 Subjects -> SOCIOLOGY (Total: 553 journals)
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- Caffeine Consumption and Onset of Alcohol Use Among Early Adolescents
Authors: Alfgeir L. Kristjansson et al.
Abstract: Preventing or delaying the onset of alcohol use among children and youth is an important public health goal. One possible factor in alcohol use onset among early adolescents is caffeine. The aim of this study was to assess the possible contribution of caffeine to the onset of alcohol use during early adolescence. We used data from the Young Mountaineer Health Study Cohort. Survey data were collected from 1349 (response rate: 80.7%) 6th grade students (mean age at baseline 11.5 years) in 20 middle schools in West Virginia during the fall of 2020, and again approximately 6 months later in spring of 2021. We limited our analyses to students reporting never having used any form of alcohol at baseline. Logistic regression was employed in multivariable analyses and both Odds Ratios and Relative Risks reported. At follow-up, almost 14% of participants reported having consumed alcohol at least once and 57% used caffeine of 100 mg + daily. In multivariable analyses we controlled for social and behavioral variables known to impact tobacco use. Caffeine use was operationalized as a three-level factor: no use, < 100 mg per day, and 100 + mg per day, with the latter being the approximate equivalent of the minimum of a typical cup of coffee or can of energy drink. Caffeine use of 100 mg + per day was significantly related to alcohol use at 6-months follow-up (OR: 1.79, RR: 1.56, p = .037). We conclude that caffeine consumption among 11–12-year-old adolescents may be a factor in early onset of alcohol use.
PubDate: Fri, 17 Mar 2023 14:18:22 PDT
- Nursing Interventions to Manage Postoperative Delirium: An Integrative
Literature Review
Authors: Jung Daum et al.
Abstract: Postoperative delirium is prevalent and has adverse effects on patients and healthcare organizations. This literature view evaluates the effect of nursing interventions in postoperative delirium management. Findings suggest nursing interventions have a positive impact on preventing and managing postoperative delirium.
PubDate: Fri, 17 Mar 2023 13:25:28 PDT
- Principled or Partisan': The Effect of Cancel Culture Framings on
Support for Free Speech
Authors: James J. Fahey et al.
Abstract: Political scientists have long been interested in the effects that media framings have on support or tolerance for controversial speech. In recent years, the concept of cancel culture has complicated our understanding of free speech. In particular, the modern Republican Party under Donald Trump has made “fighting cancel culture” a cornerstone of its electoral strategy. We expect that when extremist groups invoke cancel culture as a reason for their alleged censorship, support for their free speech rights among Republicans should increase. We use a nationally representative survey experiment to assess whether individuals’ opposition to cancel culture is principled or contingent on the ideological identity of the speaker. We show that framing free speech restrictions as the consequence of cancel culture does not increase support for free speech among Republicans. Further, when left-wing groups utilize the cancel culture framing, Republicans become even less supportive of those groups’ free speech rights.
PubDate: Fri, 17 Mar 2023 13:17:00 PDT
- Fear or Loathing: Affect, Political Economy, and Prejudice
Authors: Stephen M. Utych et al.
Abstract: Ethnonationalist politics have been on the rise in the United States since the 2008 financial crisis, culminating with the rise of Donald Trump. We examine why two seemingly unconnected things—economic crises and prejudice—so often arise simultaneously. Combining theories of economics and emotions, we connect economic crises and prejudice through the role of emotional response to crises, namely anger and anxiety. We use two survey experiments in the United States to test various theories of how emotions might connect economic threat to negative intergroup attitudes. We find that economic concerns increase both anger and anxiety among individuals, but that these emotions have distinct effects on prejudice. Angry individuals show increased prejudice, but only towards groups one is ideologically predisposed to be prejudiced towards. In contrast, anxiety exhibits few consistent effects on prejudice.
PubDate: Fri, 17 Mar 2023 13:16:57 PDT
- Are Republicans Bad for the Environment'
Authors: Luke Fowler et al.
Abstract: Does the partisanship of officeholders affect environmental outcomes' The popular perception is that Republicans are bad for the environment, but complicating factors like federalism may limit this outcome. Using a dataset that tracks toxic releases over 20 years, we examine how partisan control of executive and legislative branches at both state and federal levels affect environmental policy. Moving beyond the passage of policies or environmental program spending allows us to fully understand the impact of Republicans on the environment. In addition, we take into account structural complications that may shape the relationship between Republican control and environmental outcomes. We find that the conventional wisdom that Republicans are bad for the environment has some validity, but it is dependent on what offices Republican elected officials occupy. More specifically, Republicans significantly affect toxic chemical releases when occupying governorships and controlling Congress. Our conclusions provide further insight into understanding how partisanship affects environmental outcomes, including how partisanship composition across the federal system matters.
PubDate: Fri, 17 Mar 2023 13:12:20 PDT
- Conditional Nature of Policy as a Stabilizing Force: Erin’s Law and
Teacher Child Abuse Reporting Practices
Authors: Luke Fowler et al.
Abstract: This article uses Erin’s Law, a law establishing consistent teacher reporting practices for child abuse, to test the multiple streams framework (MSF) implementation hypothesis in a policy area where inconsistent state-level policies have been the norm. Findings indicate that Erin’s Law has a conditional impact on teacher reporting that are dependent on problems and politics streams. While the conditional relationship between the streams in affecting implementer behavior is consistent with previous tests of the MSF implementation hypothesis, findings indicate that this conditional relationship manifests differently when the intended goals of new policies are to establish a consistent norm for administrative behavior.
PubDate: Fri, 17 Mar 2023 13:12:16 PDT
- More Human Than Human: The Consequences of Positive Dehumanization
Authors: Stephen Utych et al.
Abstract: While dehumanizing language, or comparison of humans to animals or machines, is commonplace in administrative rhetoric, there is little evidence of its consequences, particularly when used in its positive form, with intent to praise, rather than denigrate. Using a survey experiment, the authors provide respondents with an employee evaluation of a hypothetical employee that includes comments from a supervisor with treatment and experimental groups being exposed to different types of language. Results suggest that dehumanizing language can alter perceptions of employee competence, but it comes with a tradeoff related to perceptions of their personality. This raises questions about how administrative rhetoric creates images of individuals within organizations, in both positive and negative ways.
PubDate: Fri, 17 Mar 2023 13:12:11 PDT
- Is It Still a Mandate If We Don’t Enforce It': The Politics of
COVID-Related Mask Mandates in Conservative States
Authors: Jeffrey Lyons et al.
Abstract: Questions of whether to enforce COVID-related mask mandates are complex. While enforced mandates are more effective at controlling community spread, government imposed behavioral controls have met significant opposition in conservative states, where a political bloc on the right is skeptical that COVID presents a significant and immediate threat. The authors conduct a split sample survey in order to examine how inclusion of a fine provision attached to mask mandates affects support. The survey was conducted in Idaho (a Republican dominated state) at a time when a mask mandate was a central debate. Unsurprisingly, respondents were more supportive of a mask mandate if a fine was not included. Further investigation indicates this is primarily a result of shifting Republican attitudes, which highlights the complex political situation in conservative states as leaders consider best mechanisms for battling COVID.
PubDate: Fri, 17 Mar 2023 13:12:06 PDT
- Willingness to Support Environmental Actions and Policies: A Comparative
Study
Authors: Erika Allen Wolters et al.
Abstract: The urgency of climate change necessitates a transition to more sustainable practices and policies. Individuals have a significant role in reducing carbon emissions by modifying their personal behavior and/or supporting environmental policies. This research note reports the results of two surveys conducted in the Republic of Ireland (ROI)/Northern Ireland (NI) and in the U.S. (specifically in Oregon) that examined willingness to engage in sustainable lifestyle practices and policies. Results align with prior research finding that personal self-efficacy is a significant predictor of support for environmental policies and proenvironmental practices.
PubDate: Fri, 17 Mar 2023 13:12:01 PDT
- Predictors of Turnover Intention in U.S. Federal Government Workforce:
Machine Learning Evidence That Perceived Comprehensive HR Practices
Predict Turnover Intention
Authors: In Gu Kang et al.
Abstract: This study aims to identify important predictors of turnover intention and to characterize subgroups of U.S. federal employees at high risk for turnover intention. Data were drawn from the 2018 Federal Employee Viewpoint Survey (FEVS, unweighted N = 598,003), a nationally representative sample of U.S. federal employees. Machine learning Classification and Regression Tree (CART) analyses were conducted to predict turnover intention and accounted for sample weights. CART analyses identified six at-risk subgroups. Predictor importance scores showed job satisfaction was the strongest predictor of turnover intention, followed by satisfaction with organization, loyalty, accomplishment, involvement in decisions, likeness to job, satisfaction with promotion opportunities, skill development opportunities, organizational tenure, and pay satisfaction. Consequently, Human Resource (HR) departments should seek to implement comprehensive HR practices to enhance employees’ perceptions on job satisfaction, workplace environments and systems, and favorable organizational policies and supports and make tailored interventions for the at-risk subgroups.
PubDate: Fri, 17 Mar 2023 13:10:32 PDT
- The Influence of Motivational Values on Instructional Designers’
Values About Methods
Authors: Peter C. Honebein
Abstract: The focus of this research is on values about methods, a specific instructional theory framework construct that represents a person’s opinions about the usefulness of instructional methods. Previous studies have shown that values about methods have a “good guy/bad guy” structure, where instructional methods such as apprenticeship are seen by designers as being more useful than instructional methods such as lecture. This led to the question, how do human values influence values about methods' To answer this question, the researcher asked Designers (instructional design graduate students) and Non-Designers (undergraduate students in an introductory psychology class) to rate the usefulness of three higher-valued instructional methods and three lower-valued instructional methods. The researcher then asked them to rate how well those instructional methods reflect ten motivational value types. The results show that both higher-valued methods and lower-valued methods align with individualistic values as opposed to communal values, with varying intensity.
PubDate: Fri, 17 Mar 2023 13:10:29 PDT
- A Closed-Host Bi-Layer Dense/Porous Solid Electrolyte Interphase for
Enhanced Lithium-Metal Anode Stability
Authors: Corey M. Efaw et al.
Abstract: Thanks to its high specific capacity and low electrochemical potential, lithium metal is an ideal anode for next-generation high-energy batteries. However, the unstable heterogeneous surface of lithium gives rise to safety and efficiency concerns that prevent it from being utilized in practical applications. In this work, the formation of a closed-host bi-layer solid electrolyte interphase (SEI) improves the stability of lithium metal anode. This is successfully realized by forming an interconnected porous LiF-rich artificial SEI in contact with Li metal, and a dense, stable in-situ formed upper layer SEI. The porous layer increases the number of Li/LiF interfaces, which reduces local volume fluctuations and improves Li+ diffusion along these interfaces. Additionally, the tortuous porous structure guides uniform Li+ flux distribution and mechanically suppresses dendrite propagation. The dense upper layer of the SEI accomplishes a closed-host design, preventing continuous consumption of active materials. The duality of a dense top layer with porous bottom layer led to extended cycle life and improved rate performance, evidenced with symmetric cell testing, as well as full cell testing paired with sulfur and LiFePO4 (LFP) cathodes. This work is a good example of a rational design of the SEI, based on comprehensive consideration of various critical factors to improve Li-metal anode stability, and highlights a new pathway to improve cycling and rate performances of Li metal batteries.
PubDate: Fri, 17 Mar 2023 13:08:34 PDT
- Roles of Twinning and < a> Slipping in Tensile Anisotropy of Rolled
Mg–3Al–Zn Alloy
Authors: Dewen Hou et al.
Abstract: In this work, the {101̅2} tensile twinning and < a> type slipping dependence of plastic anisotropy in the rolled Mg–3Al–Zn alloy are studied by using tensile tests along two orthogonal directions, the rolling direction and normal direction. The results show that the initial basal texture of the material influences the activities of twinning and slips, leading to anisotropic deformation. During tension along the rolling direction, the deformation is dominated by basal and prismatic < a> slips. During tension along the normal direction, the deformation is accommodated through tensile twinning and basal < a> slip; prismatic < a> slip is hard to active in matrix grains, but it plays an important role in twined regions.
PubDate: Fri, 17 Mar 2023 13:08:29 PDT
- Ab Initio Investigations on Metal Ion Pre-Intercalation Strategy of
Layered V2O5 Cathode for Magnesium-Ion Batteries
Authors: Dewen Hou
Abstract: Metal ions pre-intercalated layered structure materials are considered as potential high performance cathodes for Mg-ion batteries (MIBs). Herein, metal ions pre-intercalation strategy of layered cathode for MIBs by using Li, Na, Al pre-intercalated V2O5 cathode as a carrier has been investigated and proposed based on first principle calculations. The pre-intercalation process is energetically favorable and metal ion pre-intercalation improves the electronic conductivity of V2O5. The bondings of Li-V2O5, Na-V2O5 and Al-V2O5 all exhibit ionic characters, and the interaction between Al ion and V2O5 is the strongest. The interlayer distance expansion of Na pre-intercalated V2O5 is more trivial than that of Li, Al pre-intercalated V2O5. The open circuit voltage of the V2O5 cathode is dropped by pre-intercalated metal ions, and the voltage of Li and Na pre-intercalated V2O5 is higher than that of Al pre-intercalated V2O5. The diffusion barriers of Mg in the V2O5 matrix are reduced by pre-intercalation. Overall, metal ion pre-intercalation with a large atomic radius and small atomic charges holds great potentials to expand interlayer distance, enhance electronic conductivity, maintain high discharge voltage and improve diffusion ability of layered cathode. We hope our work could provide a significant guidance to the practical design of layered cathodes for MIBs.
PubDate: Fri, 17 Mar 2023 13:08:23 PDT
- Effect of Gradient Microstructure Induced by Pre-Torsion on Hydrogen
Embrittlement of Pure Iron
Authors: Xinfeng Li et al.
Abstract: Building a gradient structure can achieve overall improvement of multiple properties of metal materials. However, the investigation on hydrogen embrittlement (HE) behavior of gradient structure alloys has not been reported so far. This study investigated HE of pure iron with gradient microstructure induced by pre-torsion. The results reveal that with an increase in pre-torsion angle, the resistance to HE of alloys decreases. Fracture surface observation demonstrates that hydrogen uncharged samples present ductile cup-shape fracture, whereas hydrogen charged samples exhibit brittle spiral patterns, mainly depending on pre-torsion level. Additionally, microscopical hydrogen-assisted cracking mechanism of gradient structured pure iron has been proposed.
PubDate: Fri, 17 Mar 2023 13:08:18 PDT
- Catalyzed Oxidation of Nuclear Graphite by Simulated Fission Products Sr,
Eu, and I
Authors: Junhua Jiang et al.
Abstract: The influence of three fission products Sr, Eu, and I on the oxidation of IG-110 nuclear graphite was studied in the temperature range of 400 to 1000 °C. Sr and Eu were introduced as chlorides, and I was introduced as NaI. The temperature dependence of both CO2 and CO production during the graphite oxidation measured with mass spectroscopy and infrared spectrometry shows that the introduction of these three compounds to graphite significantly decreases the onset temperature for the oxidation of graphite. Among the three compounds, NaI is the most active towards the oxidation reaction, characterized by a significant decrease of the onset temperature from approximately 650 to 400 °C before and after its introduction to graphite. Separate measurements of CO2 and CO concentration at varying temperatures enable the calculation of the activation energy for the formation of CO2 and CO. The activation energies for the oxidation of pure and fission product-impregnated graphite samples decrease in the following order: standard IG-110 graphite, EuCl3-impregnated IG-110, SrCl2-impregnated IG-110, and NaI-impregnated IG-110. This trend indicates that the three compounds catalyze the oxidation of graphite at temperatures relevant to the operation of high-temperature gas-cooled reactors. Furthermore, it is found that the three compounds can also affect the molar ratio of reaction products CO2 and CO, and the rates of the graphite oxidation. At temperatures higher than about 850 °C, the impregnated samples exhibit lower CO2: CO ratios than the pure graphite. Different from EuCl3 and NaI, the introduction of SrCl2 decreases the graphite oxidation rates at temperatures higher than about 770 °C. Their catalytic mechanism can be understood based on a redox cycle of the intermediate active species, promoting the dissociation of molecular oxygen and transfer to the carbon.
PubDate: Fri, 17 Mar 2023 13:08:12 PDT
- Deformation-Assisted Rejuvenation of Irradiation-Induced Phase
Instabilities in Cu-Ta Heterophase Nanocomposite
Authors: Priyam V. Patki et al.
Abstract: The objective of this study is to determine the effects of coupled deformation and irradiation extremes on Ta phase evolution in Cu-10at.%Ta nanocomposite. Heterophase nanocomposites with positive heat of mixing offer exceptional mechanical properties, high temperature performance, and irradiation tolerance. Here, we consider cooperative effects of irradiation and deformation on phase stability using transmission electron microscopy phase mapping during interrupted in situ indentation. Following irradiation-induced dissolution of Ta nanoparticles, deformation-induced Ta nanoparticle nucleation and growth occur along grain boundaries. This result shows promise that irradiation and deformation may be coupled to stabilize or rejuvenate Ta nanoparticles in extreme environments.
PubDate: Fri, 17 Mar 2023 13:08:06 PDT
- Direct Ink Writing of Flexible Piezoelectric Sensors
Authors: Amanda M. White
Abstract: Piezoelectric poly(vinylidene fluoride-co-trifluoroethylene), or PVDF-trFE, builds up significant electrical charges on its surface when stressed. By correlating the mechanical force with the resulting electrical charges or voltages, researchers have developed flexible, broadband, and biocompatible force sensors. PVDF-trFE force sensors are traditionally fabricated via spin coating or solvent casting, which result in large waste production and experience difficulties in forming complex geometries. To tackle these challenges, I leveraged a commercial direct ink writing system (nScrypt microdispenser) to additively manufacture PVDF-trFE force sensors. I first synthesized an unprecedented piezoelectric ink that is compatible with a commercial ink writing system at Boise State University, specifically the nScrypt microdispenser, by dissolving PVDF-trFE powders into a cosolvent system consisting of methyl ethyl ketone and dimethyl sulfoxide. The ink composition and substrate surface properties were optimized simultaneously to ensure consistent and uniform printing. Postprocessing procedures, including air-drying, thermal curing, electrical poling and non-contact corona poling were then investigated to facilitate polymerization and beta phase transformation in the printed PVDF-trFE films. With the knowledge acquired from these investigations, I prototyped a piezoelectric force sensor consisting of printed PVDF-trFE films and printed silver electrodes. From justifying the methods for sensor fabrication, unprecedented prototypes of PVDF-trFE sensor arrays were investigated.
PubDate: Fri, 17 Mar 2023 08:00:51 PDT
- Game-Based Learning: Examining Factors That Influence K-12 Classroom Usage
Authors: Sean Ward
Abstract: Video games have become a popular and accepted part of digital culture and are becoming more accepted as an engaging instructional tool in schools. Integration of games can help develop students’ intrinsic motivation for learning and are a great way for teachers to incorporate student interests and make connections to the curriculum. Classroom usage of digital games is becoming more widespread, but prior research suggests that game-based learning is underutilized as a tool in the teacher toolbox. This study seeks to understand the factors that influence teachers’ decisions to use or not use digital games in their classroom and make suggestions for convincing reluctant teachers to increase usage of game-based learning in the future.This study uses a survey-based concurrent embedded research design. Participants in the study were 133 current K-12 educators in the United States. Quantitative data was analyzed using SPSS software and path analysis was used to determine the factors that influence a teacher’s intention to use digital games and actual reported usage of digital games in the classroom. Open-ended responses were analyzed using a word frequency and theme-based approach.Overall, the data shows that teachers are integrating digital games into their instruction, with 86% of teachers reporting usage of digital games at least once per week. Teacher perceptions, knowledge of games and teaching with games, and experiences with games were identified as factors influencing digital game usage in the classroom. Findings suggest that ongoing professional development opportunities for teachers can positively affect teacher perceptions and help resistant teachers overcome perceived barriers and increase classroom usage of GBL.
PubDate: Fri, 17 Mar 2023 08:00:50 PDT
- SOC Reconfigurable Architecture for Software-Trained Neural Networks on
FPGA
Authors: Michael Wasef
Abstract: Neural networks are extensively used in software and hardware applications. In hardware applications, it is necessary to implement a small, accelerated, and configurable hardware architecture to be easily embedded in hardware devices to implement and execute the required neural network with superior performance. Such configurable hardware architecture allows the user to implement neural networks with different structures and easily modify or change them as needed.In this dissertation, three architectures, each containing three layers, have been designed using a system-on-chip approach and implemented on a Field Programmable Gate Array (FPGA), to realize and accelerate the performance of three types of neural networks. These three neural networks are: Fully Connected Neural Networks (FCNN); Recurrent Neural Networks (RNN); and Convolution Neural Networks (CNN). The first layer of these architectures is a software Python layer, which contains a function that serves as the architecture’s user interface. The function accepts the description of the neural network structure and its training parameters as inputs and generates three binary files as outputs. These files include the network description, weights, and bias in a specific format. The second layer is an embedded software layer implemented on the on-chip ARM microcontroller. The embedded layer reads the binary files generated by the Python function and begins transferring the required parameters and configuration of each layer in the neural network to the third layer, the hardware layer. This embedded layer also monitors a status register(s) built in the third layer to determine when to send consequent layer parameters and configuration. The third layer is a hardware Intellectual Property (IP) implemented on the FPGA fabric and is configured by the second embedded layer to execute the required neural network layers consecutively. The first architecture supports implementing FCNN with up to 1024 layers, each with a 1024 maximum neurons and four distinct activation functions (Relu, Sigmoid, Tanh, and SoftMax). The design also supports implementing the Residual Neural Network (ResNet). The second architecture supports implementing RNN with three-layer types: Recurrent, Attention, and Fully Connected (FC) layers. This architecture allows the implementation of a Recurrent layer on an FPGA using a Long Short Term Memory (LSTM) model or a Gated Recurrent Unit (GRU) with up to 100 elements in each of the input and hidden vectors. It also supports executing an attention layer with up to 64 input vectors and a maximum vector length of 100 items. FC layers can be configured to support an input vector length up to a value of 256 and number of neurons up to a value of 256 in each layer. Each FC layer can use either Relu or SoftMax activation functions. Finally, the third architecture supports implementing a complete CNN, including three-layer types (Convolution, Pooling, and FC). The proposed design supports implementing the convolution layer with five different filter sizes and different stride and padding values. The CNN hardware IP also supports implementing two types of pooling (average and maximum) with various pooling window and stride sizes. This hardware architecture also supports FC layers with input and output vector lengths of up to 4096 elements and two distinct activation functions (Relu and SoftMax).
PubDate: Fri, 17 Mar 2023 08:00:50 PDT
- Tibial Compression During Activities of Daily Living in Young and Older
Adults
Authors: Elijah Miles Walker
Abstract: Introduction: Stress fracture, particularly in the tibia, is a growing concern among older adults (greater than 65 years). Older adults may have inherent stress fracture risk from ageing-related changes to their musculoskeletal system. Specifically, older adults reduced ankle neuromuscular function may impair their ability to attenuate repetitive compressive forces experienced during daily locomotor tasks and increase the likelihood of suffering bone damage from decreased bone tissue elasticity. Yet, it is currently unknown if older adults exhibit greater tibial compression than their younger counterparts during locomotor tasks. Purpose: This study sought to quantify tibial compression for older and younger adults when walking and negotiating stairs and determine whether tibial compression is related to specific ankle biomechanics. Methods: 13 young (ages 18-25 years) and 13 older (greater than 65 years) adults had tibial compression, and ankle joint stiffness and biomechanics (peak joint angle and moment) quantified during an overground walk, and stair ascent and descent tasks. Statistical Analysis: Maximum and impulse of tibial compression, ankle joint stiffness, and peak of stance (0-100%) ankle flexion joint angle and moment were submitted to an independent t-test to assess the difference between young and older adults during each task. Then, correlation analysis determined the relation between tibial compression and ankle biomechanics for all participants, as well as the young and older adults. Results: Neither tibial compression (maximum and impulse), nor ankle biomechanics (joint stiffness, moment, and angle) differed between young and older adults (all: p> 0.05) during the walk and stair ascent tasks. However, older adults exhibited ~15% smaller maximum tibial compression (p = 0.004) and ~10% peak ankle joint moment (p = 0.037) compared to young adults during the stair descent. Peak ankle flexion moment exhibited a moderate to strong relation with maximum tibial compression during each task (overground walk: r = -0.69 ± 0.26; stair descent: r = -0.48 ± 0.32; stair ascent: r = -0.72 ± 0.25, respectively). Yet, older adults typically exhibited stronger relation between ankle biomechanics and tibial compression than their younger counterparts. Specifically, older adults exhibited a moderate linear relation between ankle joint stiffness and peak ankle joint moment with impulse of tibial compression during the walk (r = 0.44 ± 0.48 and r = -0.47 ± 0.47), and peak ankle joint moment with maximum tibial compression (r = -0.48 ± 0.47) during stair descent task; whereas young adults exhibited a weak relation between the same ankle biomechanical and tibial compression measures (r = 0.23, -0.20, and - 0.27, respectively) during the walk and stair descent tasks. Conclusion: Older adults exhibited a substantial, albeit statistically insignificant, 3% to 10% increase in impulse of tibial compression compared to young adults. The elevated compression impulse may place larger compressive forces on older adult’s tibia, increasing likelihood of bone microdamage accumulation and stress fracture development. Yet, despite exhibiting a stronger relation between ankle biomechanics and tibial compression than their younger counterparts, there was not a specific alteration in older adults’ ankle biomechanics that may predict the substantial change in their tibial compression
PubDate: Fri, 17 Mar 2023 08:00:49 PDT
- Atomic Layer Processing of Molybdenum Disulfide Thin Films
Authors: Jake Alan Soares
Abstract: As feature sizes in semiconductor devices continue to shrink, it is of upmost importance to synthesize materials that can accommodate the drastic degree of scaling. One such material receiving great attention is molybdenum disulfide (MoS2), which is a semiconducting two-dimensional (2D) material in its most favorable few-layer form. The distinctive electrical properties make few to single-layer MoS2 a potential candidate to replace silicon in many microelectronic devices. MoS2 research is commonly conducted on mechanically exfoliated films due to the high quality, low defect layers that can be prepared. However, exfoliation is not a scalable method due to the lack of dimensional control and poor layer reproducibility. Currently, there is a lack of suitable methods for integrating MoS2 films into manufacturing. Thus, there is a need for scalable industry-compatible processing methods to enable integration of MoS2 in modern electronics manufacturing.One processing technique that can be used for MoS2 integration is atomic layer deposition (ALD). This technique is suitable because of its self-limiting, vapor-phase surface reactions used for thin film deposition. This process offers low temperature deposition of thin and conformal films with angstrom level control. This method is commonly used in high volume manufacturing, making it a clear choice as the processing technique that can be used for MoS2 integration. One drawback, however, is the lack of in-depth knowledge of ALD MoS2 thin films. By investigating the nucleation and growth of MoS2 films, key insights can be established to allow for greater control over the deposition process and resulting material quality. This understanding of the ALD nucleation process can also help identify new processing methods, such as area-selective ALD (ASALD). ASALD can further support the efforts towards MoS2 integration. This process can help solve the issue of placement errors found in standard lithography patterning. It can additionally provide another tool for creating complex device structures. Lastly, other processing techniques such as atomic layer etching (ALE) are also critical in manufacturing. Similar to ALD, ALE is the complementary vapor phase technique for layer-by-layer etching of uniform thin films. Combined, ALD and ALE provide scalable approaches for precise atomic layer processing and advanced manufacturing. To realize these useful processing methods, efforts need to be made to better understand the film substrate interactions and subsequent film growth or removal.In this work, we present the study of the early stages of growth and nucleation of MoS2 films on common metal oxide surfaces used in semiconductor manufacturing. We show the temperature dependence of nucleation over the range of 150-250 °C. This work identifies that hydroxyl concentrations on metal oxide surfaces are directly related to the disassociation of MoF6 precursor on the substrate surface. This precursor disassociation leads to metal fluoride bonding, revealing the interface layer formation between deposited MoS2 films and the substrate. Film morphology was additionally studied, revealing the critical role that temperature has on growth mechanisms during MoS2 ALD. At increased growth temperatures, MoS2 films exhibited higher degrees of MoS2 bonding and crystalline grains oriented perpendicular to the growth surface. This study of the nucleation and growth process provides a greater understanding of 2D film-substrate interactions and offers more control over processing. Additionally, this work explores ASALD of MoS2 films on common semiconductor surfaces by exploiting inherent differences in surface chemistry between substrate materials. Selective ALD was established between various materials including alumina and thermal oxide substrates. To our knowledge, this is the first ASALD process for a 2D material that achieves selectivity without the use of inhibitors. Lastly, we established a new thermal ALE process for the removal of MoS2 films. This work identifies the removal of the MoS2 films by means of fluorination and oxidation to create volatile moly-oxyfluoride byproducts. This method was shown to etch both amorphous and crystalline ALD films, where the etch rates were highly dependent on crystallinity and temperature.This work provides insights and processing required for MoS2 integration into nanoscale electronics, as well as many other applications. By the study of both the deposition and etching of MoS2 films, we provide a greater depth of knowledge that will be required for MoS2 integration into nanoscale manufacturing.
PubDate: Fri, 17 Mar 2023 08:00:48 PDT
- Modulation of Alpha-Crystallin-Membrane Association by Phospholipid Acyl
Chain Length and Degree of Unsaturation
Authors: Geraline Trossi-Torres
Abstract: Cataract is the leading cause of blindness worldwide. The only treatment for cataracts is the surgical removal of the cataractous lens and the replacement of an intraocular lens. With less availability of treatment and low income, the visual damage caused by cataracts can go untreated. The cataract may develop again after surgery, such as posterior capsule opacification. With age and cataracts, α-crystallin, a significant protein of the mammalian eye lens, is progressively associated with the eye lens membrane. The primary association sites of α-crystallin with the membranes are phospholipids. However, it is unclear if phospholipids’ acyl chain length and degree of unsaturation influence the α-crystallin association. We used the electron paramagnetic resonance (EPR) approach to investigate the association of α-crystallin with phosphatidylcholine (PC) membranes of different acyl chain lengths and degrees of unsaturation, with and without cholesterol (Chol). The association constant (Ka) of α-crystallin follows the trends, i.e., Ka (14:0–14:0 PC)> Ka (18:0–18:1 PC)> Ka (18:1– 18:1 PC) ≈ Ka (16:0–20:4 PC) where the presence of Chol decreases Ka for all membranes. With an increase in α-crystallin concentration, the saturated and monounsaturated membranes rapidly become more immobilized near the headgroup regions than the polyunsaturated membranes. Our results directly correlate the mobility and order near the headgroup regions of the membrane with the Ka, with the less mobile and more ordered membrane having substantially higher Ka. Furthermore, our results show that the hydrophobicity near the headgroup regions of the membrane increases with the α-crystallin association, indicating that the α-crystallin-membrane association forms the hydrophobic barrier to the transport of polar and ionic molecules, supporting the barrier hypothesis in cataract development. Taken together, our findings clearly show how the changes in phospholipids’ acyl chain length and degree of unsaturation influence α-crystallin association with model membranes and provide insight for further investigations to examine how such changes in lipids in the eye lens membranes with age and cataracts modulate α-crystallin association with native membranes.
PubDate: Fri, 17 Mar 2023 08:00:48 PDT
- Hate Speech Detection Using Textual and User Features
Authors: Rohan Raut
Abstract: Social media platforms provide users with a powerful platform to share their ideas. Using one’s right to expression to incite hatred toward a particular group of people is inappropriate. However, hate speech is pervasive in our society. Spreading hate through online social networks like Facebook, Twitter, Tiktok, and Instagram is commonplace in today’s milieu. One such case is the unprecedented COVID-19 pandemic, which engendered anti-Asian hate.In current literature, there is limited study on using user features in conjunction with textual features to detect hate. This thesis aims to combine textual features with user features to improve the state-of-the-art hate speech detection technique. To test our approach, we used four different datasets available in the public domain. We have used various tools to access Twitter APIs to extract required user information, either to use directly or further compute other features using that information.We have represented the textual features in the form of BERT embeddings and linguistic features. The 97 linguistic measures computed with a Linguistic Inquiry and Word Count (LIWC) tool quantify the text’s cognitive, affective, and grammatical processes. The user feature consisted of demographic, behavioral-based, emotion-based, personality, readability, and writing style features. Our experimental evaluation over three datasets shows that the top twenty linguistic features and the top twenty user features are the best combinations for hate speech detection.Hate speech is mostly emotionally charged. We further analyzed these user and linguistic features. Among the most intuitive and prominent results was that features like anger, negative emotion, swearing, fear, and annoyance were high in hate speech, while the happiness feature was low.We compared multiple approaches along with the existing state-of-the-art. We found that the best approach with textual features was combining LIWC features with BERT embeddings. This combination gave us the F1 of 0.82 and 0.79 on Crowd-sourced (DS1) and Kaggle (DS3), respectively. Followed by this, we identified the top LIWC and user features for hate speech detection. We found that features representing negative emotions like anger, fear, sadness, and annoyance were prominently high in hate speech. Happiness is lower in hate speech. After this, we analyzed the F1 scores with standalone LIWC and user features. We also used their combinations. We found that the combination of the top twenty LIWC and top twenty user features gives the best F1 scores of 0.74, 0.90, and 0.64 on DS1, NAACL (DS2), and anti-Asian Covid hate (DS4) dataset.Finally, we used traditional machine learning algorithms combining BERT embeddings with the top twenty linguistic features and the top twenty user features. We obtained the F1 scores of 0.78, 0.92, and 0.84 on DS1, DS2, and DS4 respectively. We also compared our approach with other studies using user and textual features.
PubDate: Fri, 17 Mar 2023 08:00:47 PDT
- Using Food-Industry Byproduct to Treat Expansive Clay
Authors: Nicole L. Shaw
Abstract: Lime stabilization has proven to be a valuable method in improving the properties of expansive clays under light structures such as those in transportation projects where ground improvement methods are often necessary over a large area. Hydrous and quick lime products are also utilized in various types of food processing operations to remove impurities from agricultural products. During this purification, waste is produced consisting of precipitated calcium carbonate, organic debris, and trace amounts of soil and agricultural contaminants. This food-processing waste typically contains commercially available unspent lime products, which are still viable for construction applications. Hence, this type of waste could be viewed as a byproduct to be reused or recycled.The waste is generated in excess of 100,000 tons per year per site when produced in large-scale operations. The volume produced is too large to be sent to landfills and is not compostable due to its chemical composition. Therefore, the waste is typically stockpiled on land adjacent to food processing facilities. There is potential to save capital on construction projects as well as significantly save in land investment by food processing facilities if a more environmentally and economically sustainable solution is found to utilize, reuse, or recycle this material. This paper studies the potential to use agricultural and food industry waste in construction applications where the organic content by weight is consistently measured at lower than 5%. Using a series of geotechnical and environmental laboratory testing procedures, several engineering properties (e.g., swell potential, permeability, and strength properties) of various blends of this waste and expansive clay are measured to find the right series of tests to evaluate this potential. Preliminary testing on a series of blends with an expansive clay suggests decreased swelling potential, increased density, and potential leachate immobilization. Once more blends have been studied and procedures have been standardized, these materials may also produce a secondary revenue stream for certain food processing facilities when utilized in construction applications.
PubDate: Fri, 17 Mar 2023 08:00:47 PDT
- Understanding Students' Experience with 1:1 Computer-Supported
Collaborative Learning in a Mathematics Classroom
Authors: Oscar Antonio Perales Aguilera
Abstract: There has been a move towards integrating educational technology into K-12 mathematics classrooms. This emphasis has been partly driven by policy, increases in technology resources available, and a need to engage students in their mathematical learning. Most studies on technology integration in mathematics education are focused on teachers’ perceptions or students’ academic achievement. However, we need to learn how students perceive their learning in this type of environment. This dissertation is a basic qualitative study aimed at understanding the experiences of students with 1:1 computer-supported collaborative learning (CSCL) in an Algebraic Reasoning classroom. The study used the mathematical software, Desmos, as its CSCL system. The school in which this research took place fully implemented a 1:1 student-to-Chromebook program since 2016, and the participants of this study were students in a 1:1 Algebraic Reasoning classroom. The data used in this study were taken from participants’ responses to individual semi-structured interviews about their learning experiences with Desmos. Data was analyzed using Kumar et al.’s (2010) framework for effective CSCL systems which encompasses five criterions: (1) Open-ended and guided interactions, (2) interactions that can be stored centrally for meaningful interpretation, (3) predefined collaboration strategies, (4) underlying theories of collaboration represented in the software, and (5) providing active and passive feedback. Results suggest that students' experiences with 1:1 CSCL in Algebraic Reasoning captured all but one them. These elements can inform educational stakeholders as to how to implement an engaging, innovative, and student-centered 1:1 CSCL mathematics environment.
PubDate: Fri, 17 Mar 2023 08:00:46 PDT
- Tinkering Towards Theories: The Role of Tinkering in Building Scientific
Models
Authors: ShaKayla Moran
Abstract: Tinkering and modeling have increasingly gained traction within science education. For this study, I adopt the construct of tinkering, which is usually applied to the development of tangible artifacts and consider how this activity might apply to the development of novel models and theoretical objects in science. Data was collected from student artifacts and coding of transcripts was performed to identify how students design models in science, with a focus on how students engage in tinkering when doing so. Using a multiple case study approach, I examined two cases of undergraduate pre-service science teachers’ development of models of light and color. The data shows that students can invent theoretical objects to productively model complex abstract scientific ideas. Examining these models revealed that students use many of the same tinkering processes-iteration, improvisation, playfulness, and shifting of emergent goals- as seen in tinkering in engineering, but students use theoretical objects (ideas) instead of tangible objects. Coding of student discussion further showed that students can tinker with theoretical objects in an iterative, playful, improvisational manner with shifting goals to refine and improve their models. Overall, including tinkering and modeling in the science classrooms creates a space where students can richly develop scientific ideas and novel models of scientific phenomena.
PubDate: Fri, 17 Mar 2023 08:00:45 PDT
- Structure, Function, and Immunogenic Applications of AB5-type
ADP-Ribosylating Bacterial Toxins
Authors: Elise Marie Overgaard
Abstract: Bacterial mono-ADP-ribosyltransferases (ARTs) catalyze the singular transfer of an ADP-ribose moiety from an NAD+ molecule onto a target molecule. ARTs contain an ancient and highly conserved tertiary structure and have a wide variety of intracellular targets and effects. Some, but not all, bacterial ARTs have an AB5-type multimeric structure consisting of an enzymatically active subunit non-covalently situated atop of a non-toxic pentamer. The active, or A, subunit of AB5-type toxins has a catalytic action that contributes to bacterial pathogenicity, and it is sometimes, but not always, an ART. ArtAB is an ART with AB5-type structure from the virulent and highly antibiotic resistant Salmonella Typhimurium DT104. In the studies described here, we tested the hypothesis that the active subunit of ArtAB is structurally and enzymatically homologous to that of the well-characterized AB5-type ART pertussis toxin. ArtAB was purified from E. coli and was used to characterize ArtAB’s cellular effects, predicted structure, and biophysical properties. In addition, a set of single-residue mutants was constructed and purified to probe ArtAB’s active site. AB5-type toxins have long been studied for their immunogenic properties, and some of these bacterial munitions have been harnessed and repurposed as vaccines or vaccine adjuvants to prevent infectious disease. Their receptor-binding pentamer, abbreviated as B5, binds to, and facilitates entry into, host cells. In additional work presented here, we tested the hypothesis that the B5 subunit of cholera toxin (CTB) from Vibrio cholerae could be used to construct a safe and effective mucosal vaccine against Staphylococcus aureus-caused mastitis. We constructed a bovine vaccine by conjugating Staphylococcus aureus antigens to the CTB-based adjuvant platform, and the immunogenicity of the vaccine was characterized in a bovine clinical trial. Finally, clinical isolates of caprine S. aureus were screened for the presence of surface antigens that could be use in a caprine version of the vaccine against mastitis. The work on bacterial AB5-type ARTs presented here contributes to a growing global understanding of the bacterial ART family, lays a foundation for the potential incorporation of ArtAB in a vaccine against Salmonella, and advances the development of bovine and caprine vaccines against S. aureus-caused mastitis.
PubDate: Fri, 17 Mar 2023 08:00:45 PDT
- Literate Change Agents Working in Oral Communities: Navigating Paradigm
Shifts
Authors: Regina Marie Manley
Abstract: This research documents the experience of 12 local leaders implementing an oral curriculum over 13 months in Karnataka, India. These leaders were Change Agents interested in influencing a community with new information. They created audio materials referred to as “content” in their group’s mother tongue: In a Kannada-Telegu mix for the Madiga group (a Scheduled Caste); in Vaagri Booli for the Hakkipikki group (a Scheduled Tribe); and in Kannada for the Kannadiga group. The first two languages are unwritten. The Kannada language is the official language of Karnataka state. The oral curriculum followed the Spoken Worldwide® model. Each team of local leaders designed their content by combining a topic, a local proverb, and an informative resource in story form. Next, the individual leaders facilitated discussion groups in their community centered on the content. Eighteen men were interviewed; this included six community discussion group members.The Connected Learning Framework was the conceptual lens for this research. It consists of four constructs—relationship, relevance, oral modes of communication, and mutual respect. Relationships played a primary role because the learners preferred to work with individuals they knew, or with individuals who were approved by the community’s leaders. Content that centered on what was relevant to community members was well-received by the listeners. The leaders used modes of communication that were familiar to community members by presenting content in the mother tongue and including local proverbs. By facilitating discussion after presenting the content, the leaders demonstrated mutual respect ensuring a multidirectional flow of information. This informed how the leaders created subsequent content.This research found that introducing new ideas, specifically Christian Scripture as a source of wisdom, was received positively by almost all audiences. In addition, the Team Leaders who had more experience using oral modes of communication, specifically telling Bible stories, and facilitating discussion were more consistent in implementing the Spoken process and principles and modeled the process during the content creation sessions with their Local Leaders or in presenting the content in their Leader’s gatherings. These leaders who had more experience with Connect Learning strategies were able to navigate further in the oral learning paradigm.
PubDate: Fri, 17 Mar 2023 08:00:44 PDT
- The U.S. Endangered Species Act and Agency Discretion: The Role of Public
Commenting During the Rulemaking Process
Authors: Krista Helmstadter Lyons
Abstract: The most recent International Union for Conservation of Nature (IUCN) Red List classifies 40,084 out of the 142,577 evaluated species as threatened with extinction, with 1,962 of those species identified in the United States. The U.S. Endangered Species Act (ESA) was enacted in 1973 to protect and recover threatened and endangered species from extinction. The ESA federal listing process can be lengthy and arduous, taking years for a species to be proposed for listing. During the process the U.S. Fish and Wildlife Service (FWS) seeks comments from the public and peer reviewers on the proposed rule. Previous research debates the effectiveness of these public comments on the final rule. This dissertation examines the commenting influence on the FWS decision-making during the Director Dan Ashes tenure to examine the FWS’s use of agency discretion during listing determinations. The qualitative study coded 1,053 narrative comments and the FWS response 11 listing rulemakings. Results showed that 50% of the commenting was science-related, with 34% directed at the underlying science of the proposed listing and 16% providing new or additional species information. The FWS was found to be more responsive to new and additional species information commenting than underlying science commenting. Although ESA statute forbids consideration of economics during a listing determination, almost 23% of the issues raised by commenters were economic related. Critical habitat, however, was only viewed as an issue in 2% of the comments. These findings can inform species conservation efforts and assist natural resource managers.
PubDate: Fri, 17 Mar 2023 08:00:43 PDT
- A Phenomenological Study of Digital Business Simulation Games and
Implementation for Corporate Learning
Authors: Jeremy Morgan Manjorin
Abstract: This qualitative phenomenological study investigated the experiences of a purposive sample of eight Learning and Development executives to understand the circumstances leading to, as well as the experiences implementing Digital Business Simulation Games (DBSG) in a corporate learning environment, specifically related to the financial service industry. Their perception of the organizational needs, decision-making process of those involved, as well as the experience in design, development, and implementation may contribute to a better understanding of the circumstances within an organization where a DBSG would be an effective solution to achieve the development goals of learners within that organization. This study will also investigate the impact the implementation of the DBSG had on the organization, as well as provide further insight into best practices and critical success factors for future implementations. The research technique employed was a modified van Kaam method as described by Moustakas (1994) based upon transcribed interviews using semi-structured questions to capture the organizational needs, decision-making, and implementation experiences as well as perceptions of the participants. Five significant themes with two subthemes that emerged are prevalent from within the collected data from the participants: 1) needs intake and leadership support, 2) safe space to practice, 3) innovation on current curricula, 4) higher degrees of engagement, and 5) positive measurement results. The resulting analysis also led to considerable collection of best practices and critical success factors in deciding to undertake a DBSG program, and the design, development and implementation of a DBSG
PubDate: Fri, 17 Mar 2023 08:00:43 PDT
- Accessible and Inclusive Online Course Design in Higher Education
Authors: Amy Lomellini
Abstract: The growth of online learning has expanded the reach of higher education to more diverse students than ever before; however, students often face barriers to equitable access to online instructional materials, course activities, and assessments. The challenge of meeting the needs of diverse learners was both highlighted and exacerbated during the COVID-19 pandemic and the rapid shift to remote teaching and learning at many institutions. Disabled students were one group that was particularly affected. Research has explored faculty and students’ (with and without disabilities) perceptions of online learning; however, less is known about instructional designers’ and their team leaders’ roles and perceptions of inclusive online course design. We posit that instructional designers are well-positioned to lead the charge in designing accessible and inclusive online courses that will better serve disabled students. Thus, this article-based dissertation presents three studies focused on accessible and inclusive online learning. Chapter one will introduce the research space and elaborate on the issues of accessible and inclusive online course design in higher education and the role that instructional designers and their team leaders play. Chapter two will present a literature review on accessible and inclusive online course design in higher education. The themes and gaps that emerged from the literature review led to the proposal of two qualitative studies. Chapter three is a qualitative exploration of online learning leaders’ (i.e., those who lead teams of instructional designers) perceptions of accessible and inclusive online learning. Leaders provided insight into the institutional and systemic barriers impacting instructional designers’ ability to collaborate in the creation of accessible and inclusive online learning experiences. Chapter four is a qualitative study focusing on instructional designers’ experiences, perceptions, and knowledge and skills related to accessible and inclusive online course design. These studies, when taken together, are intended to fill the gap in the literature about instructional design teams’ current and potential role in ensuring that diverse learners can effectively access, participate, and feel a sense of belonging in online higher education. Chapter five provides a synthesis of the findings from the three studies, explores the scholarly significance, and presents areas for future research.
PubDate: Fri, 17 Mar 2023 08:00:42 PDT
- The Effects of Mental Training on Acute Psychophysiological Stress
Responses in Endurance Athletes
Authors: Shelanda Antonia Maria Kujala
Abstract: Introduction: In sports, pre-competition stress responses can influence performance. Mental skills training is a strategy used to successfully mitigate stress responses and positively impact performance. Psychological (e.g., anxiety) and physiological (e.g., cortisol) stress responses are not often measured in a single study, providing an incomplete picture of athlete experiences. When researchers have measured these constructs together, studies have excluded endurance athletes and ways to effectively buffer stress responses. Purpose: The current study had two aims. 1. How will athlete’s perceptions of stress and physiological markers of stress be related to each other' 2. How will athlete’s perceptions of stress and physiological markers of stress be impacted by a mental skills training program' Hypothesis: H1: It was hypothesized that perceptions of stress will be positively correlated to physiological markers of stress. H2: It was hypothesized that athletes who participate in the three mental training sessions would have lower levels of acute pre-competition psychological (anxiety) and physiological (salivary cortisol levels) stress responses prior to races. Methods: Twenty-one endurance athletes were recruited from two local high school cross country running teams. Cortisol and anxiety testing occurred on three occasions (Baseline, Time 1, and Time 2). Participants completed three mental training sessions between Time 1 and Time 2. Mental skills training included relaxation and breathing, imagery, and self-talk. Anxiety was quantified using the Competitive State Anxiety Inventory (CSAI-2R). Salivary cortisol levels were analyzed at the Salimetrics lab. Statistical Analysis: A one- way repeated measures ANOVA (Time) assessed anxiety, and cortisol levels. Bivariate correlations were conducted to assess the relationships between the study variables. One-way ANOVAs also assessed the association between reported stress the week prior to testing, school, gender and cortisol, self-confidence, and anxiety Results: The ANOVA results showed no statistically significant changes between variables of cortisol, anxiety and self-confidence at different times. Statistically significant positive correlations were found between self-confidence at B, T1 and T2 testing, and significant a negative correlation was found between anxiety and self-confidence at Baseline testing. The relationship between reported high levels of stress the week prior to T2 and high levels of cortisol at T2 testing was statistically significant as was the relationship between cortisol and school at Baseline testing. Discussion: A small sample size likely contributed to the low number of statistically significant results. The relationship between stress the week prior to T2 and cortisol points to the importance of focusing on mental skills training through an entire season versus just the few days prior to competition. The significance between cortisol and school at B testing was a result of cold weather during testing conditions and points to the need to consider time of day and other conditions when interpreting cortisol results. Future studies should include more participants in a longer study design.
PubDate: Fri, 17 Mar 2023 08:00:41 PDT
- The Book of Ela or Apokalypsis in Five Acts
Authors: Noah Leventhal
Abstract: The Book of Ela or Apokalypsis in Five acts seeks first and foremost to investigate the layers of mental abstraction in which the human mind engages when thinking, and by extension, when writing. Writing and thinking do not end at the boundaries of genre. As such, I felt the styles therein should not stop at those boundaries either. Making use of influences such as Samuel Beckett, Virginia Woolf, Renee Gladman and Rosemarie Waldrop, I have endeavored to use narrative as a to form more fully and poetically explore the contours of language, and by extension, the contours of the mind. The project began with the investigation of character appearing in the text, known as the cartographer. The cartographer is strictly atemporal, and thus supersedes human consciousness. And yet, the cartographer’s existence presented itself as an ideal jumping off point from which to explore the many layers of consciousness that one immersed in such a continuum could never survey in full. Around the same time I was working on this character, I came across an article that reimagined Schrodinger’s famous thought experiment of the cat and the box with an additional layer. Now it was not only the cat, the box and the person opening the box that combined to collapse the wave function. This new configuration required a second observer watching from outside the room, observing not only cat and box, but observer. The question was: when in this scenario does the wave function collapse' This was endlessly fascinating to me, and I found myself thinking that since we are so many selves, this sort of dynamic unfolds within the bounds of consciousness in every decision we make.
PubDate: Fri, 17 Mar 2023 08:00:41 PDT
- Sexually Selected Preferences for Human Altruism Across Sexual
Orientation, Gender, Age, and Reproductive Status
Authors: Katherine Valinske Kappelman
Abstract: Prior studies have attempted to establish how human altruism has evolved, including theories of kin selection, reciprocal altruism, and costly signaling. Recent investigations have explored the evolution of altruism as the result of sexual selection, where individuals may exhibit altruistic behavior because it is preferred by potential mates. In this study, I examine how altruistic behavior toward different people (family, friends, strangers, or general altruistic acts) is preferred when considering potential short-term and long-term mates. While previous research has examined this question using college-aged heterosexual participants, this study uses a more diverse sample, including individuals who identify as LGBTQ, those of varying ages, and those who identify as childfree. Seven hypotheses were tested to understand how preferences for altruistic behavior vary based on individual characteristics. An on-line survey was conducted and over 500 participants responded. Results show that women prefer potential mates who behave altruistically toward strangers more so than men; when examining long-term relationships, people prefer potential mates who behave altruistically toward family; and that an individual’s self-reported altruistic behavior is positively correlated with an individual’s preference for altruistic behavior in a mate. Surprisingly, some hypotheses were not confirmed. For instance, there is no difference between preferences for altruistic behavior in potential mates based on sexual orientation. When examining women’s preferences for altruistic behavior in potential mates based on reproductive status, I found that post-reproductive women have a greater preference for altruistic behavior that is directed toward strangers or general altruistic behavior as compared to reproductive aged women. The results of this thesis provide insights into the evolution of human altruism.
PubDate: Fri, 17 Mar 2023 08:00:40 PDT
- DNA Origami Scaffold Development for Digital Nucleic Acid Memory
Authors: Sarah Elizabeth Kobernat
Abstract: Recently, DNA nanotechnology has emerged as a promising and rapidly expanding method to utilize nucleic acids as a nanoscale building material. DNA origami is a major structural application of DNA nanotechnology, using DNA to construct two- and three-dimensional shapes. These structures have been employed for a variety of uses including DNA data storage. DNA is a promising material to address the impending shortage of silicon-based storage as data demands increase. There are many sequence-based methods of data storage, but digit Nucleic Acid Memory (dNAM) uses DNA origami as a breadboard and is read by super-resolution microscopy instead. dNAM uses DNA origami to spatially position DNA probe sequences in a matrix arrangement that can be read by DNA-PAINT. The prototype used 15 different origami structures to successfully encode and read “Data is in our DNA!\n”.The dNAM prototype showed the feasibility of using DNA origami as a breadboard, however, the origami’s size limits data capacity and reading efficiency. In chapter 2, we engineered a larger DNA origami rectangle for dNAM. First, we designed a larger node, with an 8x10 matrix of potential data points, a 67% increase from the dNAM prototype. To construct this larger structure, we designed, cloned, produced, and tested a large, custom ssDNA scaffold. With this scaffold, we successfully folded larger origami as confirmed by AFM, and showed the correct positioning of DNA data point probes by DNA-PAINT. This larger structure enabled a 67% increase in the number of data points per origami, which allows for an 80% increase in the number of bits/node when encoding data. This larger node supports the scaling of dNAM, and will allow for more efficient production and reading.To take advantage of recent advances in array-based oligonucleotide synthesis, in chapter three we explore the use of pooled staples for dNAM. First, we tested the performance of pooled staples compared to individually synthesized staples using the original dNAM node with the M13mp18 scaffold. We showed that both sets of staples performed equally well in terms of folding origami, and arranging the matrix of data points. Next, we tested the formation of multiple origami structures using orthogonal scaffolds in the context of mixed pools of oligos. We compared the ability of two different scaffolds to fold into the appropriate origami with individual and mixed sets of staple strands. We showed that origami could be folded successfully with either one scaffold and both sets of staples (“random access”) or both scaffolds and both sets of staples (“one-pot synthesis”). Finally, we designed multiple scaffolds that use orthogonal sets of staple strands and analyzed their orthogonality. Together, these results move dNAM towards taking advantage of pooled oligos, which will enhance scalability and efficiency. All moving dNAM towards real world applications.
PubDate: Fri, 17 Mar 2023 08:00:40 PDT
- Meshfree Methods for PDEs on Surfaces
Authors: Andrew Michael Jones
Abstract: This dissertation focuses on meshfree methods for solving surface partial differential equations (PDEs). These PDEs arise in many areas of science and engineering where they are used to model phenomena ranging from atmospheric dynamics on earth to chemical signaling on cell membranes. Meshfree methods have been shown to be effective for solving surface PDEs and are attractive alternatives to mesh-based methods such as finite differences/elements since they do not require a mesh and can be used for surfaces represented only by a point cloud. The dissertation is subdivided into two papers and software.In the first paper, we examine the performance and accuracy of two popular meshfree methods for surface PDEs:generalized moving least squares (GMLS) and radial basis function-finite differences (RBF-FD). While these methods are computationally efficient and can give high orders of accuracy for smooth problems, there are no published works that have systematically compared their benefits and shortcomings. We perform such a comparison by examining their convergence rates for approximating the surface gradient, divergence, and Laplacian on the sphere and a torus as the resolution of the discretization increases. We investigate these convergence rates also as the various parameters of the methods are changed. We also compare the overall efficiencies of the methods in terms of accuracy per computation cost.The second paper is focused on developing a novel meshfree geometric multilevel (MGM) method for solving linear systems associated with meshfree discretizations of elliptic PDEs on surfaces represented by point clouds. Multilevel (or multigrid) methods are efficient iterative methods for solving linear systems that arise in numerical PDEs. The key components for multilevel methods: \grid" coarsening, restriction/ interpolation operators coarsening, and smoothing. The first three components present challenges for meshfree methods since there are no grids or mesh structures, only point clouds. To overcome these challenges, we develop a geometric point cloud coarsening method based on Poisson disk sampling, interpolation/ restriction operators based on RBF-FD, and apply Galerkin projections to coarsen the operator. We test MGM as a standalone solver and preconditioner for Krylov subspace methods on various test problems using RBF-FD and GMLS discretizations, and numerically analyze convergence rates, scaling, and efficiency with increasing point cloud resolution. We finish with several application problems.We conclude the dissertation with a description of two new software packages. The first one is our MGM framework for solving elliptic surface PDEs. This package is built in Python and utilizes NumPy and SciPy for the data structures (arrays and sparse matrices), solvers (Krylov subspace methods, Sparse LU), and C++ for the smoothers and point cloud coarsening. The other package is the RBFToolkit which has a Python version and a C++ version. The latter uses the performance library Kokkos, which allows for the abstraction of parallelism and data management for shared memory computing architectures. The code utilizes OpenMP for CPU parallelism and can be extended to GPU architectures.
PubDate: Fri, 17 Mar 2023 08:00:39 PDT
- The Effect of the 2018 Tariffs on European Wine
Authors: Henry Johnson
Abstract: This paper estimates a vector autoregression model for average wine prices across U.S. cities to assess the impact of tariff changes on the U.K., France, Germany, and Spain after they were enacted in October 2019. It uses impulse response functions to gauge how a one-unit impulse in the per-liter duty rate may effect the average wine price in the U.S. and the quantity of wine from various exporters to the U.S. It finds that a one-unit impulse in the duty rate levied against the bloc of countries impacted by the tariff results in a fall in the quantity of wine imported from those countries and that wine from the bloc of countries is substituted with wine from the top three exporters not included in the bloc.
PubDate: Fri, 17 Mar 2023 08:00:38 PDT
- Lived Experiences of Women in Collegiate Esports Leadership
Authors: Kim S. Johnson
Abstract: A leadership gender gap exists in politics, business, and higher education, and there appears to be one in collegiate esports. Researchers have conducted studies on some aspects of esports; however, we know little about women’s experiences leading collegiate esports programs. The purpose of this qualitative study - a descriptive (transcendental) phenomenology – was to explore and describe the essence of women’s lived experiences in leading collegiate varsity esports programs at higher education institutions. In-depth interviews were the research method. Seven women employed as collegiate varsity esports coaches or directors described their historical context, present experiences in the profession, and how this experience is meaningful. NVivo qualitative software was used for organizing, analyzing, and coding data for themes and commonalities. This preliminary work led to the development of textural and structural descriptions and, finally, the essence of women’s experiences as collegiate esports coaches and directors. Ultimately, the essence of the lived experiences of a woman in collegiate esports leadership funneled down to meaningful managing with excellence using skills developed through previous life experiences. Meaningful managing with excellence is that “condition or quality without” which being a woman in collegiate esports leadership “would not be what it is.”
PubDate: Fri, 17 Mar 2023 08:00:38 PDT
- The Influence of Visitors, Habitat, and Methodology on Mexican Spotted Owl
(Strik occidentalis lucida) Occupancy and Detection in a Remote Canyon
Environment
Authors: Kirsten Fuller
Abstract: National Parks across America play an important role in protecting natural resources and providing access to recreation for visitors. However, these goals may come into conflict as visitation rates rise. Grand Canyon National Park in Northern Arizona is one of the most highly visited parks in the United States, with over 6 million visitors a year. Backcountry hiking and camping are popular activities in the park, and many highly visited hiking trails and campgrounds overlap with known breeding areas of a threatened species, Mexican Spotted Owl. In this thesis, I explore the intersection of recreation and wildlife conservation at this popular park through the lens of long-term occupancy of a threatened species. My aims are to (1) assess the potential impact of visitor use on long-term occupancy (2001 to 2021) of Mexican Spotted Owls at the Grand Canyon, and (2) evaluate the potential for autonomous recording units (ARUs) to complement current survey protocols. To assess long-term occupancy, I ran a multi-season occupancy model using 20-years of call-back survey data conducted in protected activity centers (PACs), along with measures of visitor use and habitat characteristics. To assess the use of ARUs, I ran a single-season occupancy model using three years of data, which was collected using autonomous recording units in PACs from 2019 to 2021. I found that visitor use in the Grand Canyon had no effect on owl occupancy, which remained stable across PACs over the 20-year study period. Owl occupancy remained high across the 20-year survey period and was strongly informed by habitat characteristics. Specifically, Mexican Spotted Owls occupied PACs with higher proportions of mixed shrubland habitat and Supai formation. Conversely, owl occupancy decreased in PACs with more pinyon-juniper woodland habitat and Redwall Limestone. Assessing the use of ARUs as a complement to current protocol, ARUs were found to be a useful tool for supplementing traditional call-back surveys, particularly at PACs with extremely limited access. In particular, ARUs detected Mexican Spotted Owls with high probability early in the breeding season prior to the official call-back survey period, which allows managers to extend their monitoring period. In highly remote PACs, ARUs were more suitable than call-backs because they could collect more data with less effort. Incorporating this method into Spotted Owl survey protocol may be essential for improving monitoring of under-sampled locations, which is a critical component for assessing long-term trends for this species across its range.
PubDate: Fri, 17 Mar 2023 08:00:37 PDT
- Deep Learning of Microstructures
Authors: Amir Abbas Kazemzadeh Farizhandi
Abstract: The internal structure of materials also called the microstructure plays a critical role in the properties and performance of materials. The chemical element composition is one of the most critical factors in changing the structure of materials. However, the chemical composition alone is not the determining factor, and a change in the production process can also significantly alter the materials' structure. Therefore, many efforts have been made to discover and improve production methods to optimize the functional properties of materials. The most critical challenge in finding materials with enhanced properties is to understand and define the salient features of the structure of materials that have the most significant impact on the desired property. In other words, by process, structure, and property (PSP) linkages, the effect of changing process variables on material structure and, consequently, the property can be examined and used as a powerful tool in material design with desirable characteristics. In particular, forward PSP linkages construction has received considerable attention thanks to the sophisticated physics-based models. Recently, machine learning (ML), and data science have also been used as powerful tools to find PSP linkages in materials science. One key advantage of the ML-based models is their ability to construct both forward and inverse PSP linkages. Early ML models in materials science were primarily focused on process-property linkages construction. Recently, more microstructures are included in the materials design ML models. However, the inverse design of microstructures, i.e., the prediction of vii process and chemistry from a microstructure morphology image have received limited attention. This is a critical knowledge gap to address specifically for the problems that the ideal microstructure or morphology with the specific chemistry associated with the morphological domains are known, but the chemistry and processing which would lead to that ideal morphology are unknown.In this study, first, we propose a framework based on a deep learning approach that enables us to predict the chemistry and processing history just by reading the morphological distribution of one element. As a case study, we used a dataset from spinodal decomposition simulation of Fe-Cr-Co alloy created by the phase-field method. The mixed dataset, which includes both images, i.e., the morphology of Fe distribution, and continuous data, i.e., the Fe minimum and maximum concentration in the microstructures, are used as input data, and the spinodal temperature and initial chemical composition are utilized as the output data to train the proposed deep neural network. The proposed convolutional layers were compared with pretrained EfficientNet convolutional layers as transfer learning in microstructure feature extraction. The results show that the trained shallow network is effective for chemistry prediction. However, accurate prediction of processing temperature requires more complex feature extraction from the morphology of the microstructure. We benchmarked the model predictive accuracy for real alloy systems with a Fe-Cr-Co transmission electron microscopy micrograph. The predicted chemistry and heat treatment temperature were in good agreement with the ground truth. The treatment time was considered to be constant in the first study.In the second work, we propose a fused-data deep learning framework that can predict the heat treatment time as well as temperature and initial chemical compositions by reading the morphology of Fe distribution and its concentration. The results show that the trained deep neural network has the highest accuracy for chemistry and then time and temperature. We identified two scenarios for inaccurate predictions; 1) There are several paths for an identical microstructure, and 2) Microstructures reach steady-state morphologies after a long time of aging. The error analysis shows that most of the wrong predictions are not wrong, but the other right answers. We validated the model successfully with an experimental Fe-Cr-Co transmission electron microscopy micrograph.Finally, since the data generation by simulation is computationally expensive, we propose a quick and accurate Predictive Recurrent Neural Network (PredRNN) model for the microstructure evolution prediction. Essentially, microstructure evolution prediction is a spatiotemporal sequence prediction problem, where the prediction of material microstructure is difficult due to different process histories and chemistry. As a case study, we used a dataset from spinodal decomposition simulation of Fe-Cr-Co alloy created by the phase-field method for training and predicting future microstructures by previous observations. The results show that the trained network is capable of efficient prediction of microstructure evolution.
PubDate: Fri, 17 Mar 2023 08:00:36 PDT
- Anticipating the impacts of the Social, Political, and Biophysical
Landscape on Long-Term Connectivity for Reintroduced Plains Bison
Authors: Jamie Ann Faselt
Abstract: Intense anthropogenic pressures on the natural environment have created the need for implementing strategies that promote or restore habitat connectivity. The ability for animals to move between habitat patches allows animals to find mates, access resources, and shift their range in response to the changing climate and ensures that ecological and evolutionary processes persist. Connectivity conservation typically focuses on biophysical barriers to animal movement, but for many species reintroductions, establishing and maintaining connectivity often requires overcoming both ecological and socio-political barriers. Despite the need to navigate complex socio-political landscapes to implement connectivity conservation plans, datasets depicting those conditions are rarely used in the connectivity models that underlie connectivity conservation plans. In this research, I demonstrate an approach for leveraging social, political, institutional, and ecological datasets to model long-term connectivity for reintroduced Plains bison (Bison bison) in part of the Northern Great Plains, where no habitat connectivity currently exists.Efforts to reintroduce bison, both for cultural and ecological reasons, have been ongoing since their near extirpation in the late 1800s due to colonial forces. There are currently more than 20 international, federal, non-profit, and Tribally-led efforts to reintroduce bison to parts of Plains bison expansive historic range. These reintroduction efforts have occasionally been met with intense socio-political backlash highlighting the need for conservation interventions that address important socio-political obstacles in order to achieve long-term connectivity. Some of the socio-political barriers that practitioners seeking to restore bison face are a lack of social acceptance, political opposition from the Republican party and cattle ranching industry, and the need to navigate complex jurisdictional boundaries across a large landscape.I analyzed the impacts of these specific barriers by using responses from an international wildlife governance preference survey, republican voting trends, cattle sales, and parcel density as a measure of jurisdictional complexity. I integrated these datasets with spatial surfaces depicting bison habitat suitability and human modification to develop a suite of resistance surfaces that depict both the challenges of a bison moving through the landscape and the challenges of conserving important movement pathways for the species. I used these resistance surfaces to compare the costs and probabilities for implementing a variety of connectivity conservation plans. My results highlight where social-ecological mismatches and fit occur throughout the landscape. The analysis shows that the most ecologically ideal pathway is also socio-politically costly, and that choosing a slightly less ecologically valuable pathway may cost less in terms of socio-political resistance.I also analyzed the potential spatial footprints of three commonly used interventions for promoting conservation outcomes by manipulating the socio-political resistance to reflect three hypothetical conservation interventions using the wildlife governance preference survey. I explored the interventions of creating public land tolerance zones (e.g., shift in jurisdictional complexity), economic incentives aimed at promoting social acceptance, and a Tribal and First Nations governance intervention given the cultural importance of bison to Indigenous people in North America. I found that the economic incentive did little to shift the probability of implementing a connectivity plan for bison when compared to the public land tolerance zone and Tribal and First Nations governance scenario, suggesting that those strategies may have a greater impact on bison’s long-term connectivity in the region. This approach can help conservation managers make more informed decisions regarding where to implement bison connectivity plans, as well as what levers may lead more successful conservation outcomes. My approach could be applied in research for other wide-ranging, reintroduced, or otherwise controversial species to characterize the potential trade-offs involved with different conservation interventions and ultimately lead to conservation plans that have a higher probability of successful implementation.
PubDate: Fri, 17 Mar 2023 08:00:36 PDT
- Use of Harsh-Braking Data from Connected Vehicles as a Surrogate Safety
Measure
Authors: Nathaniel Patrick Edelmann
Abstract: Traffic safety may be analyzed with the use of surrogate safety measures, measures of safety that do not incorporate collision data but rather rely on the concept of traffic conflicts. Use of these measures provides several benefits over use of more traditional analysis methods with historical crash data. Surrogate measures eliminate the need to wait for crashes to occur to conduct a safety analysis. The amount of time required for enough crash data to accumulate can be significant, delaying safety analyses. Similarly, these measures allow for safety analysis to be conducted prior to crashes occurring, potentially calling attention to hazardous areas which may be altered to prevent crashes. In addition to these benefits, traffic conflicts occur much more frequently than collisions, generating many more data points which in turn make statistical methods of analysis more effective.Evaluating surrogate safety measures for a particular transportation network is most effectively done with the use of traffic microsimulation or with connected vehicle data. Traffic microsimulation (such as the use of PTV VISSIM) will generate kinematic data that may then be used for computation of surrogate safety measures. A significant amount of research has been done on this topic, resulting in the establishment of algorithms for calculation of several different surrogate measures and validation of these measures.Kinematic data from connected vehicles has also been used for the calculation of surrogate safety measures. One data point collected by connected vehicles is harsh braking events which could serve as a surrogate safety measure. Because drivers usually brake more gently if given the opportunity to do so, harsh braking events indicate that a traffic conflict has occurred or is about to occur. Such events take away the driver’s opportunity to brake gently. This research establishes statistical models which relate harsh braking events to crashes on intersections and segments in Salt Lake City, Utah. The findings indicate that harsh braking events have the effect of reducing expected crashes because they represent traffic conflicts which were remedied through the use of harsh braking as an evasive action. The presence of schools and the presence of left turn lanes were also found to be statistically significant crash predictors. In addition to this research work a paper outlining the existing state of safety analysis with surrogate safety measures and evaluating the usefulness and practicality of various existing measures is presented.
PubDate: Fri, 17 Mar 2023 08:00:35 PDT
- Communicating Multiplicative Reasoning Through Semiotic Resources
Authors: Emilie N. Eisenberger
Abstract: The importance of fostering in students the requisite language to understand what is being communicated and how to communicate their understanding requires educators to conceptualize themselves as teachers of language and content. It is possible to engage in activities of the mathematics classroom and through that participation engage in language practices and mathematical practices simultaneously. The purpose of this study was to explore the use of semiotic resources, and modality, with a student-generated tool on students’ communication of multiplicative reasoning.The study design was a qualitative case study that included a single third-grade class with an in-depth look at six students of varying knowledge levels. Two students, one male and one female, were randomly selected from Beyond, On, and Approaching levels. Discourse analysis served dual purposes for the data collected: first, it explored a socially constructed multi-modal tool utilized as an activity to enhance language use individually and interactively during mathematical discourse; second, it supported investigating the language used by participants during the studied activities and how they relate to Communication About and Communication In multiplication.The findings support the utilization of semiotic resources, inclusive of visual representations, signs, symbolic notations, and receptive and expressive language elements as fundamental to the learning and communication we are asking of our students. Through the interplay of semiotic resources, a multimodal student-generated tool can support students in summarizing their learning, individually and interactively, enhancing their means of communicating discursively in mathematics.
PubDate: Fri, 17 Mar 2023 08:00:35 PDT
- Heteroepitaxy of GaSb on GaAs (111)A for Electron Transport Studies
Authors: Madison Drake
Abstract: III-V semiconductors grown by molecular beam epitaxy (MBE) on (111) surfaces have some interesting electronic properties. For certain materials with a (111)-orientation, the Γ- and L-valleys are reasonably close in energy. This means that it may be possible to take advantage of electron conduction in the L- and Γ-valleys at the same time, allowing us to overcome the so-called “density-of-states bottleneck,” and enable transistors with large drive currents.1 We have investigated this phenomenon in GaSb- and InAs-based 2D electron gases for which the electron effective masses are low.However, growth of materials with a (111) orientation is typically more challenging than on traditional (001) surfaces. The MBE conditions needed to grow high quality material are often poorly understood.2 We began by exploring InAs/GaSb quantum well (QW) structures,3 grown directly on GaSb(111)A substrates. This work shows that low growth rates under very high group V overpressures produce good GaSb homoepitaxy and InAs heteroepitaxy, as characterized by XRD and AFM. However, although we have been able to identify MBE conditions that lead to the growth of smooth, high-quality material, GaSb(111)A substrates are extremely expensive, as well as being intrinsically n-type, which complicates the carrier transport measurements in which we are interested. If we could instead grow our GaSb-based QW structures on cheaper, non-conductive GaAs(111)A substrates, we could overcome these issues. The challenge is the large lattice mismatch between GaSb and GaAs, which typically results in strain-driven crystallographic disorder at the heterointerface and poor material quality.One technique that has shown promise in circumventing these problems on (001) surfaces is the use of interfacial misfit arrays (IMFs). Under specific molecular beam epitaxy (MBE) conditions it is possible to produce an array of 90° dislocations that lie in the GaSb/GaAs(001) heterointerface. These dislocations efficiently relieve the strain between the two materials without generating the high density of threading dislocations that one would ordinarily expect. As a result, it is possible to grow high quality materials and active device structures above these IMF-based heterointerfaces.This thesis describes our work to extend a modified version of this IMF technique to (111) surfaces in order to grow our InAs/GaSb QW structures on GaAs(111)A substrates. So far, this work has produced GaSb grown on GaAs (111)A with a fullwidth- half-maximum (FWHM) XRD peak value of 124’’. For GaSb/GaAs(001) grown via an IMF approach, other groups have reported FWHM values of 240’’.4 This work shows how various MBE parameters such as growth temperature, Sb overpressure, GaSb growth initiation and GaSb growth rate affect IMF formation. This thesis also reports initial electron transport measurements from InAs/GaSb QWs grown on GaAs(001) and (111) substrates via this IMF technique.
PubDate: Fri, 17 Mar 2023 08:00:34 PDT
- Associations Between the School Physical Environment and Climate in Rural
Schools
Authors: Tate Castleton
Abstract: According to the National Center for Education Statistics (2021), more than half of all public-school districts and nearly one-third of all public-school students attend rural schools in the U.S. This study identifies characteristics of the physical environment of rural schools, considers how the physical environment of rural schools compares to urban and suburban schools, and describes the associations of a school’s physical environment with perceptions of school climate among students, staff, and parents.Using the School Assessment for Environmental Typology (SAfETy; Bradshaw et al., 2015), this study objectively assessed the physical environment of 40 rural schools in Idaho. Those characteristics were compared with data collected in prior research (Bottiani et al., 2020). This study found rural and non-rural schools, and the make-up of their physical environments, are not that different. The physical environment of rural schools had low frequencies of instances of disorder, such as trash, graffiti, drugs, paraphernalia, and evidence of building decline, such as broken windows and neglected landscaping. Rural schools also produced moderate scores related to appearance, with characteristics including illumination, visibility, and ownership. Most schools in this study were found to have interior and exterior surveillance cameras in place and employed school resource officers.Rural secondary schools in this study had a higher presence of surveillance measures than non-rural high schools, whereas non-rural high schools had higher frequencies of disorder. And, although a comparison to non-rural elementary schools is not available, the rural elementary schools score in the current study show similar physical environmental characteristics as did urban secondary schools in all three factors of the SAfETy.In addition, the current work also examined aspects of the social environment, through evaluating school climate. The Maryland Safe and Supportive (MDS3) School Climate Survey Suite was administered to students, parents, and staff in all 40 schools participating in this study. Multi-variable regression analysis was used to examine the associations between the SAfETy and school climate. Several associations were found among students, with fewer associations among staff and parents.This research study concludes that a variety of important, urgent, and malleable associations exist between a rural school’s physical environment and perceptions of school climate among students, staff, and parents. This research, and future research that builds upon this work, will assist schools as they strive to transform, strengthen, and sustain positive school environments for all stakeholders.
PubDate: Fri, 17 Mar 2023 08:00:33 PDT
- Understanding and Mitigating the Effects of Artificial Light on Bats and
Nocturnal Arthropods in Grand Teton National Park
Authors: Hunter Cole
Abstract: Bat and insect populations are at risk globally, and identifying factors that may influence bat and insect populations alongside mitigation techniques for anthropogenic factors that may negatively influence these taxa will be crucial for their conservation. To identify landscape characteristics that influence bats throughout Grand Teton National Park, we placed passive acoustic monitors throughout the park in areas with different microhabitat characteristics to identify factors that influence activity. Additionally, we developed a R package, `EcoCountHelper`, to assist wildlife managers in analyzing ecological count data similar to our bat monitoring data. As a demonstration of the package, we conducted a GLMM-based analysis of this landscape-scale bat monitoring data. Following our broad-scale assessment of bat activity in Grand Teton National Park, we also installed experimental street lights capable of emitting both red and white light throughout Grand Teton National Park’s Colter Bay area, and monitored bat and insect activity while altering the color of light illuminating a focal parking lot to assess red light’s ability to mitigate the impacts of artificial light on bats and insects.Through our park-wide acoustic monitoring, we found that bat habitat use varied for the seven species we fit candidate models for, with distance to water, the number of buildings suitable for roosting, and forest cover all influencing activity levels for different species of bats throughout the park. As a result of our fine-spatial-scale research surrounding light pollution mitigation, we also found that red light does not seem to be an effective method of promoting bat activity in artificially illuminated areas that is similar to that of unlit areas, but insects did exhibit more similar sample counts to unlit areas during red light treatment periods than white light treatment periods. Our findings both provide valuable information for land and wildlife managers in Grand Teton National Park to conserve bat and insect populations, and highlight the need for additional research surrounding bat-human interactions. Additionally, we hope our development of a streamlined R package for GLMM analysis using count data will facilitate and promote robust and reproducible analyses for wildlife managers and researchers alike.
PubDate: Fri, 17 Mar 2023 08:00:33 PDT
- Improved Computational Prediction of Function and Structural
Representation of Self-Cleaving Ribozymes with Enhanced Parameter
Selection and Library Design
Authors: James D. Beck
Abstract: Biomolecules could be engineered to solve many societal challenges, including disease diagnosis and treatment, environmental sustainability, and food security. However, our limited understanding of how mutational variants alter molecular structures and functional performance has constrained the potential of important technological advances, such as high-throughput sequencing and gene editing. Ribonuleic Acid (RNA) sequences are thought to play a central role within many of these challenges. Their continual discovery throughout all domains of life is evidence of their significant biological importance (Weinreb et al., 2016). The self-cleaving ribozyme is a class of noncoding Ribonuleic Acid (ncRNA) that has been useful for relating sequence variants to structural features and their associated catalytic activities. Self-cleaving ribozymes possess tractable sequence spaces, perform easily identifiable catalytic functions, and have well documented structures. The determination of a self-cleaving ribozyme’s structure and catalytic activity within the laboratory is typically a slow and expensive process. Most current explorations of structure and function come from these empirical processes. Computational approaches to the prediction of catalytic activity and structure are fast and inexpensive, but have failed both to achieve atomic accuracy or to correctly identify all base-pair interactions (Watkins et al., 2018). One prominent impediment to computational approaches is the lack of existing structural and functional data typically required by predictive models (Jumper et al., 2021). Using data from deep-mutational scanning experiments and high-throughput sequencing technology, it is possible to computationally map mutational variants to their observed catalytic activity for a range of self-cleaving ribozymes. The resulting map reveals important base-pairing relationships that, in turn, facilitate accurate predictions of higher-order variants. Using sequence data from three experimental replicates of five model self-cleaving ribozymes, I will identify and map all single and double mutation variants to their observed cleavage activity. These mappings will be used to identify structural features within each ribozyme. Next, I will show within a training tool how observed cleavage for multiple reaction times can be used to identify the catalytic rates of our model ribozymes. Finally, I will predict the functional activity for model ribozyme variants of various mutational orders using machine learning models trained only on functionally labeled sequence variants. Together, these three dissertation chapters represent the kind of analysis needed to further the implementation of more accurate structural and functional prediction algorithms.
PubDate: Fri, 17 Mar 2023 08:00:32 PDT
- Nutrient Recovery from Wastewater by a Consortium of Algae Species for
Biofuel Production
Authors: Edgardo Ayala
Abstract: Current energy sources are predominantly petroleum-based and their use increases greenhouse gas (GHG) emissions. As the global population grows, and along with it the demand for energy, there is a need to further develop renewable energy sources to avoid the effects of increasing atmospheric CO2 concentrations on the climate. Biofuels, a renewable energy source, have gained significant interest as a replacement for petroleum-based fuels due to their environmental benefits and carbon neutrality. Biofuels are expected to make up 9.0% of the total fuel consumption in the U.S. by 2040, up from 7.3% in 2019 [1]. Currently, terrestrial crop-based biofuels are the most widely used. However, their production competes for land, fertilizer, and water resources with food production. Cultivation of microalgae-based biofuels can avoid this competition through higher productivity that leads to lower land requirements and their ability to use wastewater as a water and nutrient source for cultivation. We designed and tested a large-scale and semi-continuous operating algal polyculture cultivation system to determine the utility of using undiluted agricultural wastewater as the sole nutrient and water source for algal production. Algal biomass was evaluated for both biofuel production and water treatment (i.e., nutrient sequestration). Algal biomass was converted to a bio-oil by hydrothermal liquefaction (HTL). We also asked if algal production could be maximized by recycling nutrients recovered from HTL processing into a secondary bench-scale algal cultivation system (i.e., in a closed nutrient-loop system). Semi-continuous operations resulted in increased biomass yields, with projections estimated at 4,000 kg biomass/year in polyhydroxyalkanoate effluent (PHAE). Recycling HTL(aq) did not present additional benefits in sustaining or increasing algal productivity. Based on our estimations, the highest economic return will result from coupling nitrogen (N) water quality trading (WQT) with biomass conversion to bio-crude.
PubDate: Fri, 17 Mar 2023 08:00:31 PDT
- Investigations on the interactions of Streptolysin O and Lysenin with
Natural and Artificial Lipid Membranes
Authors: Marcelo Ayllon
Abstract: The investigations described in this work are focused on better understanding the interactions between pore-forming toxins (PFTs) and lipid membranes. The necessity of these investigations is justified by the important role of PFTs in infectivity and their potential impact on the development of alternative strategies for mitigating the global burden presented by infectious diseases and the onset of antimicrobial resistance. To achieve our scientific goals, we employed Red Blood Cells (RBCs) as a model for assessing the lytic action of two PFTs, Streptolysin O (SLO), and lysenin. To address the interactions between PFTs and specific membrane moieties as mediators of binding, oligomerization, and lysis, we employed spectrophotometrical assessments of hemolysis in conjunction with affinity measurements by the Kinetics Exclusion Assay (KinExA). The observation that SLO-induced hemolysis was gradually diminished upon cholesterol depletion even when the affinity of SLO for target membranes increased led to the conclusion that a slight reduction in the cholesterol content promotes binding but affects oligomerization into functional pores. Sphingomyelin depletion also led to a reduced hemolytic activity of lysenin but significantly diminished the barrier function of RBC membranes. Prompted by these results, we investigated the use of liposomes as target decoys for SLO and lysenin, capable of diminishing hemolysis in a concentration-dependent manner, which may constitute a complementary or alternative therapeutic approach for infectious diseases in which PFTs act as virulence factors. A direct comparison between the inhibitory effectiveness of monoclonal antibodies and liposomes for SLO clearance indicates the tremendous potential therapeutic applications presented by custom-designed liposomes for aiding in the world-wide fight against bacterial infections.
PubDate: Fri, 17 Mar 2023 08:00:31 PDT
- Associations Between Stakeholder Perceptions of School Climate and
Fidelity of Implementation of Key Features of the Positive Behavioral
Interventions and Supports Framework in Rural Schools
Authors: Nathan Florin Anderson
Abstract: School climate can be complex to measure and to change, but it is clear that it is a critical component of an effective school. One practice that has been shown to positively influence school climate is Positive Behavioral Interventions and Supports (PBIS). PBIS is a framework of evidence-based practices and its power for initiating change has been shown to come from fidelity of implementation of its key components. Although there is a lot of research on PBIS implementation, not a lot is known about implementation in rural schools and the unique challenges that setting provides. This study measures baseline levels of PBIS components, assesses the perceptions of school climate, and analyzes how those two domains are associated in rural schools prior to formal PBIS training and implementation.In this quantitative study, the baseline data for a Randomized Controlled Trial with 40 rural schools across one state is utilized as the sample data. The Schoolwide Evaluation Tool (SET) is used to measure fidelity of PBIS implementation at each school and the Maryland Safe and Supportive Schools (MDS3) Climate Survey provides the perspectives of students, parents, and staff on school climate. Information on the relationship between these variables in the rural setting will contribute important information to researchers and implementers in rural schools.The analysis found that although there is generally a positive perspective on school climate in these rural schools, a lack of fidelity in PBIS implementation is evident, and is associated with climate perceptions. The only PBIS component implemented to fidelity across the schools was a strong discipline system, yet was associated with lower order and discipline. These results suggest that the punishment-heavy approaches that schools are utilizing are not producing the desired outcomes without the foundational practices of teaching and acknowledging expected behavior. In fact, clearly teaching expectations was significantly associated with improved climate perspectives of staff and parents, and having a system for acknowledging those expectations was significantly associated with improved climate perspectives of students.I recommend that future researchers and implementers build on these findings and conclusions to better understand how to implement PBIS in rural schools. Additional research that applies similar methodologies to other demographic groups and more urban settings is needed for further comparison. Additional time points and longitudinal data will also provide more insights to the causes and impacts of PBIS on school climate in small and remote schools.
PubDate: Fri, 17 Mar 2023 08:00:30 PDT
- Home Field Advantage: Roots, Reelection, and Representation in the Modern
Congress
Authors: Charles Hunt
Abstract: Although partisan polarization gets much of the attention in political science scholarship about Congress, members of Congress represent diverse communities around the country. Home Field Advantage demonstrates the importance of this understudied element of American congressional elections and representation in the modern era: the local, place-based roots that members of Congress have in their home districts. Charles Hunt argues that legislators’ local roots in their district have a significant and independent impact on their campaigns, election outcomes, and more broadly on the relationship between members of the U.S. House of Representatives and their constituents. Drawing on original data, his research reveals that there is considerable variation in election outcomes, performance relative to presidential candidates, campaign spending, and constituent communication styles that are not fully explained by partisanship, incumbency, or other well-established theories of American political representation. Rather, many of these differences are the result of the depth of a legislator’s local roots in their district that predate their time in Congress. Hunt lays out a detailed “Theory of Local Roots” and their influence in congressional representation, demonstrating this influence empirically using multiple original measures of local roots over a full cross- section of legislators and a significant period of time.
PubDate: Thu, 16 Mar 2023 10:01:02 PDT
- Effectiveness of Novel Ankle Prophylactic Compared with Lace-Up Brace or
Tape
Authors: Wyatt D. Ihmels et al.
Abstract: Context: Conventional ankle prophylactics restrict harmful ankle inversion motions that lead to injury. But these existing prophylactics also limit other ankle motions, potentially leading to detriments in functional joint capacity. The ankle roll guard (ARG) may alleviate the prevailing issues of existing ankle prophylactics and prevent harmful ankle inversion, while allowing other joint motions. Objective: This technical report sought to compare the ARG’s ability to prevent ankle inversion, but not restrict other ankle motions with existing prophylactics. Design: Repeated-measures study. Setting: Motion capture laboratory. Participants: Thirty participants. Intervention: Each participant had dominant limb ankle kinematics recorded during 5 successful trials of a sudden inversion event and 30-cm drop landing task with each of 4 conditions (ARG, ASO ankle stabilizer [brace], closed-basket weave athletic tape [tape], and unbraced [control]). Main Outcome Measures: Peak ankle inversion angle, range of inversion motion (ROM), and time to peak inversion during the sudden inversion event, and ankle plantar- and dorsiflexion ROM during the drop landing were submitted to a 1-way repeated-measures analysis of variance to test the main effect of prophylaxis. Results: Participants exhibited greater inversion ROM with control compared with tape (P = .001), and greater plantar- and dorsiflexion ROM with ARG and control compared with brace (P = .02, P = .001) and tape (P = .02, P 41°), but is less restrictive than existing prophylactics. The less restrictive ARG may make its use ideal during rehabilitation as it allows ankle plantar- and dorsiflexion motions, while preventing inversion related to injury.
PubDate: Wed, 15 Mar 2023 10:01:18 PDT
- Leveraging Free-Form Comments to Assess and Improve Patient Satisfaction
Authors: Regis Terpend et al.
Abstract: This study employed a text-analysis methodology to identify themes within patient comments and measure the relationship of those themes to patient satisfaction. Using these findings, a spreadsheet tool was created to allow a large sample of comments to be readily analyzed. The tool was validated using patient comment data provided by the Family Medicine Residency of Idaho. The tool gives clinicians the ability to easily analyze patient comments and identify actionable measures of patient satisfaction. Additionally, this tool will allow researchers to reduce vast sets of comment text into numerical data suited for quantitative analyses.
PubDate: Wed, 15 Mar 2023 10:00:35 PDT
- Human Population Growth and Accessibility from Cities Shape Rangeland
Condition in the American West
Authors: Juan M. Requena-Mullor et al.
Abstract: Drylands cover 40 % of the global land surface and more than 3 billion people worldwide are dependent on the ecosystem services (ES) that they provide (Hoover et al., 2020). Dryland ecosystems are subject to multiple forces of change, including climate change, invasive plants, and increasing wildfires (Maestre et al., 2016). For example, human pressure and land use intensification can quickly induce changes in healthy drylands that lead to degradation, thus reducing their capacity to recover from extreme climate events (Gunderson, 2000, Sun et al., 2021). We define degradation as a transition from a functional native ecosystem to an undesired state that may include lower biodiversity and provide fewer ecosystem services (Maestre et al., 2016). For many drylands ecosystems, reversing degradation is challenging, due to hysteresis (Scheffer et al., 2001, Suding et al., 2004). Potential cascading feedbacks between multiple drivers of change emphasize an urgent need for research on socio-ecological dynamics in drylands to inform sustainable land management (Nkonya, Winslow, Reed, Mortimore, & Mirzabaev, 2011).
PubDate: Wed, 15 Mar 2023 09:55:34 PDT
- Not Whodunit But Whydunit: Story Characters’ Motivations Influence
Audience Interest in Services
Authors: Anne Hamby et al.
Abstract: Service providers and consumer well-being advocates often share stories to promote audience interest in relevant behavior. This research examines how characters’ motivations for engaging in service-related behavior in such stories influence consumers’ interest in services. Across five studies, we show that audiences are more interested in services after reading about a character who acts for intrinsically (vs. extrinsically) motivated reasons. We show that this occurs because the audience identifies more with intrinsically motivated characters. We also examine how consequences of characters’ actions (both for others and for themselves when they make miscalibrated decisions) shape an audience’s service interest in targeted ways, specifically encouraging interest in services that help people while avoiding unintended negative consequences. The results of this work suggest that stories can be an effective way to encourage consumers’ interest in services that enhance personal and societal well-being and identify critical story elements that influence their success in doing so.
PubDate: Wed, 15 Mar 2023 09:54:08 PDT
- Above the Scam: Moral Elevation Reduces Gullibility
Authors: Anne Hamby et al.
Abstract: Consumers are increasingly exposed to scams and questionable marketing practices. The current work examines how consumers’ emotional states influence their gullibility (a belief or compliance with a request that most people would consider naïve). Across four studies, we show that the emotional experience of moral elevation reduces susceptibility to believe dubious claims or comply with suspicious requests. While past research showed that moral elevation enhances nurturance behavior (and support of a requester), the current work suggests that elevation may also play a protective function (that is, reduce gullibility). We show that decreased trust in a persuasion agent mediates the influence of elevation on gullibility, and demonstrate this effect in the context of health and financial domains.
PubDate: Wed, 15 Mar 2023 09:54:04 PDT
- The Effect of Affect: An Appraisal Theory Perspective on Emotional
Engagement in Narrative Persuasion
Authors: Anne Hamby et al.
Abstract: Most recent research examining the influence of story-based advertisements on persuasion leverages theories of narrative and character involvement. These theories emphasize emotional engagement as key to stories’ persuasive influence. Researchers who build on these theories tend to assume that an audience will experience the emotions depicted by a focal character and examine emotional engagement with respect to intensity (i.e., amount of emotion experienced). The current work integrates insights from the appraisal theory of emotion to develop a framework of audience emotional engagement in stories. We expand the current conceptualization of emotional engagement in narratives to include the discrete emotion experienced while involved in the story as well as the event appraisals that elicit the emotions. We highlight antecedents of an audience’s emotional response to a story and ways in which the appraisal theme associated with the discrete emotion experienced while emotionally engaged in a narrative ad explains variance in outcomes of importance to advertisers.
PubDate: Wed, 15 Mar 2023 09:53:58 PDT
- How Does Ambivalence Affect Young Consumers’ Response to Risky
Products'
Authors: Anne Hamby et al.
Abstract: Although ambivalence (the coexistence of positive and negative components of an attitudinal target) is common in consumers’ lives, prior research is mixed in terms of when and how it influences consumers’ behavior. We theorize that ambivalence-evoked arousal causes people to focus on the immediate consequences of a consumption choice. Thus, ambivalence enhances approach behavior when immediate outcomes associated with consuming the focal product are positive, as is often the case with risky products. In six studies across multiple product categories, we show that adolescents’ and young adults’ (from the U.S. and France) ambivalence toward a risky product enhances willingness to pay for, intention to use, and interest in positive information about risky products. We also show that the heuristic cue of information about salient social norms moderates the relationship between ambivalence and approach behavior toward a risky product: the effect of ambivalence on approach behavior is enhanced when descriptive norms are higher and attenuated when lower.
PubDate: Wed, 15 Mar 2023 09:53:54 PDT
- Empathy as a Panacea to the Great Resignation: Is Our Business Landscape
and Its Leaders Capable to Accommodate for Real Empathy'
Authors: Ria Roy
Abstract: This back-page article questions the recent call for empathy among organizations to manage what is being heralded as the Great Resignation as a result of the pandemic. The author questions how the call for empathy among business leaders addresses the deep systemic issues that have gone unnoticed, unaddressed, and perhaps even been fostered, and thus have become legacies within organizations.
PubDate: Tue, 14 Mar 2023 14:48:45 PDT
- Digital Compliance and Risk Assessment: Did the Field of Performance
Improvement Miss the Plot'
Authors: Ria Roy
Abstract: Sophisticated and nuanced discussions are moot when the fundamentals of an organization are lacking. How does an organization plan for competitive advantage, garner investment, hire and retain highly skilled professionals, expand, and so on in the absence of a culture of integrity, ethics, trust, responsibility, and honesty' As the demands of a globalized economy has made compliance incredibly complex and time consuming, the current article makes an initial foray into digital compliance, examines the digital solution employed by Honeywell, and questions the lack of engagement by proponents of performance improvement.
PubDate: Tue, 14 Mar 2023 14:48:42 PDT
- Dataset for Sex, Body Size, and Winter Weather Explain Migration
Strategies in a Partial Migrant Population of American Kestrels (Falco
sparverius)
Authors: Sadie C. Ranck et al.
Abstract: Given increasing evidence that climate change affects the annual cycles of birds, it is important to understand the mechanisms underlying individual migration strategies and population-level patterns in partial migrants. In this study, we found that thermoregulation (body size and winter temperatures) was a key driver of American Kestrel (Falco sparverius) migration decisions. The annual proportion of migrants in the population, however, was not explained by winter weather and may be the result of differential survival. We used measured stable hydrogen isotope values (δD) of talon tissues to distinguish migrant from resident kestrels in a partially migratory population of American Kestrels in southwestern Idaho during the 2013 – 2021 breeding seasons. We then evaluated drivers of migration decisions by assessing potential correlates of migration strategies, whether individuals switched migration strategies between years, and whether the proportion of migrants in the population changed over time or was correlated with winter weather. Male kestrels were 1.6 times more likely to migrate than females, and in colder than average winters, smaller birds of both sexes were more likely to migrate than larger birds. A small proportion of birds (n = 7) showed evidence of switching their migration strategies on an annual basis. There was no temporal trend in the proportion of migrants in the population, but proportions varied between years. Interestingly, there was no association between winter minimum temperature anomalies and annual migrant proportions in the population, suggesting that differential over-winter survival, or other stochastic processes, may play an important role in population composition. As winters continue to warm, fewer kestrels may migrate and more may remain resident on breeding grounds. However, it is unclear how changes in migration strategies might affect population-level patterns and resilience to climate change.
PubDate: Mon, 13 Mar 2023 09:11:31 PDT
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