Authors:Rajesh Shah, Vikram Mittal, Angelina Mae Precilla First page: 204 Abstract: Recent advances in all-solid-state battery (ASSB) research have significantly addressed key obstacles hindering their widespread adoption in electric vehicles (EVs). This review highlights major innovations, including ultrathin electrolyte membranes, nanomaterials for enhanced conductivity, and novel manufacturing techniques, all contributing to improved ASSB performance, safety, and scalability. These developments effectively tackle the limitations of traditional lithium-ion batteries, such as safety issues, limited energy density, and a reduced cycle life. Noteworthy achievements include freestanding ceramic electrolyte films like the 25 μm thick Li0.34La0.56TiO3 film, which enhance energy density and power output, and solid polymer electrolytes like the polyvinyl nitrile boroxane electrolyte, which offer improved mechanical robustness and electrochemical performance. Hybrid solid electrolytes combine the best properties of inorganic and polymer materials, providing superior ionic conductivity and mechanical flexibility. The scalable production of ultrathin composite polymer electrolytes shows promise for high-performance, cost-effective ASSBs. However, challenges remain in optimizing manufacturing processes, enhancing electrode-electrolyte interfaces, exploring sustainable materials, and standardizing testing protocols. Continued collaboration among academia, industry, and government is essential for driving innovation, accelerating commercialization, and achieving a sustainable energy future, fully realizing the transformative potential of ASSB technology for EVs and beyond. Citation: J PubDate: 2024-06-27 DOI: 10.3390/j7030012 Issue No:Vol. 7, No. 3 (2024)
Authors:Mohammed Abuhussein, Iyad Almadani, Aaron L. Robinson, Mohammed Younis First page: 218 Abstract: This research paper presents a novel approach for occlusion inpainting in thermal images to efficiently segment and enhance obscured regions within these images. The increasing reliance on thermal imaging in fields like surveillance, security, and defense necessitates the accurate detection of obscurants such as smoke and fog. Traditional methods often struggle with these complexities, leading to the need for more advanced solutions. Our proposed methodology uses a Generative Adversarial Network (GAN) to fill occluded areas in thermal images. This process begins with an obscured region segmentation, followed by a GAN-based pixel replacement in these areas. The methodology encompasses building, training, evaluating, and optimizing the model to ensure swift real-time performance. One of the key challenges in thermal imaging is identifying effective strategies to mitigate critical information loss due to atmospheric interference. Our approach addresses this by employing sophisticated deep-learning techniques. These techniques segment, classify and inpaint these obscured regions in a patch-wise manner, allowing for more precise and accurate image restoration. We propose utilizing architectures similar to Pix2Pix and UNet networks for generative and segmentation tasks. These networks are known for their effectiveness in image-to-image translation and segmentation tasks. Our method enhances the segmentation and inpainting process by leveraging their architectural similarities. To validate our approach, we provide a quantitative analysis and performance comparison. We include a quantitative comparison between (Pix2Pix and UNet) and our combined architecture. The comparison focuses on how well each model performs in terms of accuracy and speed, highlighting the advantages of our integrated approach. This research contributes to advancing thermal imaging techniques, offering a more robust solution for dealing with obscured regions. The integration of advanced deep learning models holds the potential to significantly improve image analysis in critical applications like surveillance and security. Citation: J PubDate: 2024-06-27 DOI: 10.3390/j7030013 Issue No:Vol. 7, No. 3 (2024)
Authors:Ilona Buchem, Stefano Sostak, Lewe Christiansen First page: 236 Abstract: Collaborative learning has been widely studied in higher education and beyond, suggesting that collaboration in small groups can be effective for promoting deeper learning, enhancing engagement and motivation, and improving a range of cognitive and social outcomes. The study presented in this paper compared different forms of human and robot facilitation in the game of planning poker, designed as a collaborative activity in the undergraduate course on agile project management. Planning poker is a consensus-based game for relative estimation in teams. Team members collaboratively estimate effort for a set of project tasks. In our study, student teams played the game of planning poker to estimate the effort required for project tasks by comparing task effort relative to one another. In this within- and between-subjects study, forty-nine students in eight teams participated in two out of four conditions. The four conditions differed in respect to the form of human and/or robot facilitation. Teams 1–4 participated in conditions C1 human online and C3 unsupervised robot, while teams 5–8 participated in conditions C2 human face to face and C4 supervised robot co-facilitation. While planning poker was facilitated by a human teacher in conditions C1 and C2, the NAO robot facilitated the game-play in conditions C3 and C4. In C4, the robot facilitation was supervised by a human teacher. The study compared these four forms of facilitation and explored the effects of the type of facilitation on the facilitator’s competence (FC), learning experience (LX), and learning outcomes (LO). The results based on the data from an online survey indicated a number of significant differences across conditions. While the facilitator’s competence and learning outcomes were rated higher in human (C1, C2) compared to robot (C3, C4) conditions, participants in the supervised robot condition (C4) experienced higher levels of focus, motivation, and relevance and a greater sense of control and sense of success, and rated their cognitive learning outcomes and the willingness to apply what was learned higher than in other conditions. These results indicate that human supervision during robot-led facilitation in collaborative learning (e.g., providing hints and situational information on demand) can be beneficial for learning experience and outcomes as it allows synergies to be created between human expertise and flexibility and the consistency of the robotic assistance. Citation: J PubDate: 2024-07-14 DOI: 10.3390/j7030014 Issue No:Vol. 7, No. 3 (2024)
Authors:Eric Martin, Matthew Ritchey, Steven Kim, Margaret Falknor, George Beckham First page: 264 Abstract: Background: The lack of knowledge about physical responses to pickleball creates a clear gap about performance in this sport. The purpose of this study was to investigate neuromuscular fatigue caused by playing doubles pickleball. Methods: Recreational pickleball players (n = 32, mean age = 60.0 years) were recruited to perform sets of four countermovement jumps (CMJs) on a force plate before and after doubles pickleball matches. Results: For players who had not played a match prior to testing, there was a significant learning effect across trials within the baseline set of jumps for five outcomes from the CMJ test, including propulsive peak force (p = 0.005); however, there was no significant learning effect for jump height. There were significant improvements in the large effect size for all except one dependent variable (propulsive phase time) between the first and second set of jumps (i.e., after one match). Neither further increases nor decreases were seen after the second set of jumps. Conclusions: Participants saw significant increases in CMJ performance across trials after one pickleball match, indicating learning and potentiation effects. After three matches of doubles pickleball, no fatigue effect was detected. Citation: J PubDate: 2024-07-31 DOI: 10.3390/j7030015 Issue No:Vol. 7, No. 3 (2024)
Authors:Shirin Kazemzadeh Pournaki, Ricardo Santos Aleman, Mehrdad Hasani-Azhdari, Jhunior Marcia, Ajitesh Yadav, Marvin Moncada First page: 281 Abstract: Due to global development and increased public awareness of food’s effects on health, demands for innovative and healthy products have risen. Biodegradable and environmentally friendly polymer usage in modern food products is a promising approach to reduce the negative health and environmental effects of synthetic chemicals. Also, desirable features such as flavor, texture, shelf-life, storage condition, water holding capacity, a decrease in water activity, and an oil absorption of fried food have been improved by many polysaccharides. One of the important polymers, which is applied in the food industry, is alginate. Alginates are a safe and widely used compound in various industries, especially the food industry, which has led to innovative methods for for the improvement of this industry. Currently, different applications of alginate in stable emulsions and nano-capsules in food applications are due to the crosslinking properties of alginate with divalent cations, such as calcium ions, which have been studied recently. The main aim of this review is to take a closer look at alginate properties and applications in the food industry. Citation: J PubDate: 2024-08-05 DOI: 10.3390/j7030016 Issue No:Vol. 7, No. 3 (2024)
Authors:Ramsey F. Arram, Thomas B. Morgan, John T. Nix, Yu-Lin Kao, Hsuan Chen First page: 116 Abstract: Lindera benzoin is a dioecious understory shrub native to eastern North America. Northern spicebush is a beautiful shrub with a natural round shrub shape, golden-yellow fall foliage, attractive bright red drupes, and precocious yellow flowers in early spring; however, its market value as an ornamental value has been overlooked. To improve the ornamental values of this under-cultivated nursery crop, breeding for a better compact form, larger leaves, enlarged flower clusters and fruit, and increased stress tolerances could all be beneficial. Polyploidy manipulation is a valuable method to improve such traits for many ornamental plants. This study established the genome doubling method by oryzalin-infused solid agar treatment on young northern spicebush seedlings. The seedlings of two wild populations in North Carolina were collected and used. A total of 288 seedlings were treated with solid agar containing 150 µM oryzalin for 24, 72, and 120 h. The results were sporadic in their survival ratios and tetraploid conversion ratios between different treatments; however, a total of 16 tetraploid L. benzoin plants were produced in this study. The 24-h treatment showed the optimal result, with 7.1% of total treated seedlings or 15.2% of surviving seedlings converted into tetraploids. Tetraploid plants had visible differences in leaf morphology, a statistically significant enlarged stomata size, and reduced stomatal density compared to diploid plants. This research provides ploidy manipulation information for all future breeding processes of L. benzoin and related species. Citation: J PubDate: 2024-03-22 DOI: 10.3390/j7020007 Issue No:Vol. 7, No. 2 (2024)
Authors:Paramahansa Pramanik First page: 127 Abstract: In real-world scenarios, we encounter non-exchangeable dependence structures. Our primary focus is on identifying and quantifying non-exchangeability in the tails of joint distributions. The findings and methodologies presented in this study are particularly valuable for modeling bivariate dependence, especially in fields where understanding dependence patterns in the tails is crucial, such as quantitative finance, quantitative risk management, and econometrics. To grasp the intricate relationship between the strength of dependence and various types of margins, we explore three fundamental tail behavior patterns for univariate margins. Capitalizing on the probabilistic features of tail non-exchangeability structures, we introduce graphical techniques and statistical tests designed for analyzing data that may manifest non-exchangeability in the joint tail. The effectiveness of the proposed approaches is illustrated through a simulation study and a practical example. Citation: J PubDate: 2024-04-03 DOI: 10.3390/j7020008 Issue No:Vol. 7, No. 2 (2024)
Authors:Rizos N. Krikkis First page: 153 Abstract: An electrothermal analysis for barium-titanate-based ceramics is presented, combining the Heywang–Jonker model for the electric resistivity with a heat dissipation mechanism based on natural convection and radiation in a one-dimensional model on the device level with voltage as the control parameter. Both positive-temperature-coefficient (PTC) and negative temperature coefficient (NTC) effects are accounted for through the double Schottky barriers at the grain boundaries of the material. The problem formulated in this way admits uniform and non-uniform multiple-steady-state solutions that do not depend on the external circuit. The numerical bifurcation analysis reveals that the PTC effect gives rise to several multiplicites above the Curie point, whereas the NTC effect is responsible for the thermal runaway (temperature blowup). The thermal runaway phenomenon as a potential thermal shock could be among the possible reasons for the observed thermomechanical failures (delamination fracture). The theoretical results for the NTC regime and the thermal runaway are in agreement with the experimental flash sintering results obtained for barium titanate, and 3% and 8% yttria-stabilized zirconia. Citation: J PubDate: 2024-04-26 DOI: 10.3390/j7020009 Issue No:Vol. 7, No. 2 (2024)
Authors:Luís Alves, Solange Magalhães, Cátia Esteves, Marco Sebastião, Filipe Antunes First page: 169 Abstract: In order to produce detergents with improved performance and good market acceptability, it is crucial to develop formulations with improved foamability and cleaning performance. The use of a delicate balance of surfactants and additives is an appealing strategy to obtain good results and enables a reduction in the amount of chemicals used in formulations. Mixtures of hydrophobically modified linear polymers and surfactants, as well as balanced mixtures with co-surfactants and/or hydrotropes, are the most effective parameters to control foamability and foam stability. In the present study, the effect of the addition of hydrophobically modified linear polymers, nonionic co-surfactants and hydrotropes, and their mixtures to anionic and zwitterionic surfactant aqueous solutions was evaluated. It was found that the presence of the hydrophobically modified polymer (HM-P) prevented the bubbles from bursting, resulting in better stability of the foam formed using zwitterionic surfactant solutions. Also, the surfactant packing was inferred to be relevant to obtaining foamability. Mixtures of surfactants, in the presence of a co-surfactant or hydrotrope led, tendentially, to an increase in the critical packing parameter (CPP), resulting in higher foam volumes and lower surface tension for most of the studied systems. Additionally, it was observed that the good cleaning efficiency of the developed surfactant formulations obtained a higher level of fat solubilization compared to a widely used brand of commercial dishwashing detergent. Citation: J PubDate: 2024-05-10 DOI: 10.3390/j7020010 Issue No:Vol. 7, No. 2 (2024)
Authors:Mohammad Al-Shaar, Pierre-Charles Gerard, Ghaleb Faour, Walid Al-Shaar, Jocelyne Adjizian-Gérard First page: 183 Abstract: Rockfalls are incidents of nature that take place when rocks or boulders break from a steep slope and fall to the ground. They can pose considerable threats to buildings placed in high-risk zones. Despite the fact that the impact of a rockfall on a building can cause structural and non-structural damage, few studies have been undertaken to investigate the danger associated with this event. Most of these studies indicated that the risk resulting from rockfall hazards is hard to forecast and assess. A comprehensive quantitative risk assessment approach for rockfalls on buildings is developed and described in this paper and applied for the Mtein village in Mount Lebanon. This method employs a 3D model to simulate the rockfall trajectories using a combination of digital elevation data, field surveys, and orthorectified aerial photographs. The spatial and temporal probability of rockfalls were evaluated using the analysis of historical data in two triggering-factor scenarios: earthquake and precipitation. The findings show that, during the period of 1472 years between the years 551 (the first observed large earthquake in Lebanon) and the current year of the study (2023), the temporal probability will potentially be equal to 0.002 and 0.105 in the cases of earthquake- and rainfall-triggered rockfalls, respectively, while the maximal damage values are expected to be 232 USD and 10,511 USD per year, respectively. The end result is a final map presenting the risk values assigned to each building that could be damaged by rockfalls. Citation: J PubDate: 2024-05-30 DOI: 10.3390/j7020011 Issue No:Vol. 7, No. 2 (2024)
Authors:Georgios Lampropoulos First page: 19 Abstract: To achieve sustainability and fulfill sustainable development goals, the digitalization of the power sector is vital. This study aims to examine how blockchain can be integrated into and enrich smart grids. In total, 10 research questions are explored. Scopus and Web of Science (WoS) were used to identify documents related to the topic. The study involves the analysis of 1041 scientific documents over the period 2015–2022. The related studies are analyzed from different dimensions including descriptive statistics, identification of the most common keywords and most widely used outlets, examination of the annual scientific production, the analysis of the most impactful and productive authors, countries, and affiliations. The advancement of the research focus and the most popular topics are also examined. Additionally, the results are analyzed, the main findings are discussed, open issues and challenges are presented, and suggestions for new research directions are provided. Based on the results, it was evident that blockchain plays a vital role in securing smart grids and realizing power sector digitalization, as well as in achieving sustainability and successfully meeting sustainable development goals. Citation: J PubDate: 2024-01-06 DOI: 10.3390/j7010002 Issue No:Vol. 7, No. 1 (2024)
Authors:Maria Vasiliki Sanida, Theodora Sanida, Argyrios Sideris, Minas Dasygenis First page: 48 Abstract: Chest X-ray imaging plays a vital and indispensable role in the diagnosis of lungs, enabling healthcare professionals to swiftly and accurately identify lung abnormalities. Deep learning (DL) approaches have attained popularity in recent years and have shown promising results in automated medical image analysis, particularly in the field of chest radiology. This paper presents a novel DL framework specifically designed for the multi-class diagnosis of lung diseases, including fibrosis, opacity, tuberculosis, normal, viral pneumonia, and COVID-19 pneumonia, using chest X-ray images, aiming to address the need for efficient and accessible diagnostic tools. The framework employs a convolutional neural network (CNN) architecture with custom blocks to enhance the feature maps designed to learn discriminative features from chest X-ray images. The proposed DL framework is evaluated on a large-scale dataset, demonstrating superior performance in the multi-class diagnosis of the lung. In order to evaluate the effectiveness of the presented approach, thorough experiments are conducted against pre-existing state-of-the-art methods, revealing significant accuracy, sensitivity, and specificity improvements. The findings of the study showcased remarkable accuracy, achieving 98.88%. The performance metrics for precision, recall, F1-score, and Area Under the Curve (AUC) averaged 0.9870, 0.9904, 0.9887, and 0.9939 across the six-class categorization system. This research contributes to the field of medical imaging and provides a foundation for future advancements in DL-based diagnostic systems for lung diseases. Citation: J PubDate: 2024-01-22 DOI: 10.3390/j7010003 Issue No:Vol. 7, No. 1 (2024)
Authors:Amirfarhang Nikkhoo, Ali Esmaeili, Shayan Rabizade, Majid Zamiri First page: 72 Abstract: This study presents a novel numerical methodology that is designed for the dynamic adjustment of three-dimensional high-rise building configurations in response to aerodynamic forces. The approach combines two core components: a numerical simulation of fluid flow and the adjoint method. Through a comprehensive sensitivity analysis, the influence of individual variables on aerodynamic loads, including lift and drag coefficients, is assessed. The findings underscore that the architectural design, specifically the building’s construction pattern, exerts the most substantial impact on these forces, accounting for a substantial proportion (76%). Consequently, the study extends its evaluation to the sensitivity of fluid flow across various sections of the tower by solving the adjoint equation throughout the entire fluid domain. As a result, the derived sensitivity vector indicates a remarkable reduction of approximately 31% in the applied loads on the tower. This notable improvement has significant implications for the construction of tall buildings, as it effectively mitigates aerodynamic forces, ultimately enhancing the overall comfort and structural stability of these architectural marvels. Citation: J PubDate: 2024-02-05 DOI: 10.3390/j7010004 Issue No:Vol. 7, No. 1 (2024)
Authors:Jakob Merkač, Mateja Sirše First page: 94 Abstract: In patients with reccurent lateral and medial patellar instability, isolated medial patellofemoral ligament (MPFL) reconstruction may be insufficient due to poor lateral retinacular tissue quality. In this report, we describe a case of a patient that underwent simultaneous MPFL and lateral patellofemoral ligament (LPFL) reconstruction on the left knee due to chronic bidirectional patellar instability. A 29-year-old female patient presented with first-time lateral patellar dislocation five years ago due to acute strain. She underwent a tibial tuberosity transposition in another hospital. After the surgery, she suffered from recurrent medial and lateral patellar dislocation and presented to our center. MPFL and concomitant LPFL reconstruction on the left knee was simultaneously performed due to bilateral patellar dislocation. The patella was stable postoperatively, and the patient underwent physiotherapy with successful results to date. Single-time patellar dislocation should be treated conservatively. Surgical treatment after the first episode of dislocation can magnitude the risk of postoperative complications. The simultaneous reconstructing of the LPFL yields patellar fixation indistinguishable from the native LPFL. These grafts provide separate tensioning depending on body anatomy, allowing for individualized stability. Anatomical MPFL reconstruction is supported by well-established high-quality research. Reconstructing the LPFL anatomically yields patellar fixation indistinguishable from the native LPFL. Citation: J PubDate: 2024-02-24 DOI: 10.3390/j7010005 Issue No:Vol. 7, No. 1 (2024)
Authors:Yunus Emre Koc, Murat Aycan, Toshiaki Mitsui First page: 103 Abstract: The increasing global population and climate change threaten food security, with the need for sustenance expected to rise by 85% by 2050. Rice, a crucial staple food for over 50% of the global population, is a major source of calories in underdeveloped and developing countries. However, by the end of the century, over 30% of rice fields will become saline due to soil salinity caused by earthquakes, tsunamis, and rising sea levels. Plants have developed strategies to deal with salt stress, such as ion homeostasis, antioxidant defense mechanisms, and morphological adaptations. Proline, an endogenous osmolyte, is the predominant endogenous osmolyte that accumulates in response to salinity, and its overexpression in rice plants has been observed to increase plant salinity tolerance. Exogenously applied proline has been shown to improve plant salt tolerance by reducing the destructive effect of salinity. Recent research has focused on ionic toxicity, nitrogen fixation, and gene expression related to salt tolerance. Exogenous proline has been shown to improve water potential and leaf content, restoring water usage efficiency. It can also ease growth inhibition in salt-sensitive plants. Exogenously applied proline increases antioxidant activities and enhances plant salinity tolerance. This review examines the role and processes of proline in rice plants under salt stress and its relationship with other tolerance mechanisms. Citation: J PubDate: 2024-03-11 DOI: 10.3390/j7010006 Issue No:Vol. 7, No. 1 (2024)
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