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  Subjects -> SCIENCES: COMPREHENSIVE WORKS (Total: 374 journals)
Showing 201 - 265 of 265 Journals sorted by number of followers
Quantum Science and Technology     Hybrid Journal   (Followers: 19)
Logo STI Science, Technology and Innovation     Open Access   (Followers: 15)
Alfarama Journal of Basic & Applied Sciences     Open Access   (Followers: 12)
Patterns     Open Access   (Followers: 9)
The Innovation     Open Access   (Followers: 8)
Revista de la Sociedad Científica del Paraguay     Open Access   (Followers: 7)
Research     Open Access   (Followers: 6)
RAC: Revista Angolana de Ciências     Open Access   (Followers: 6)
Advanced Theory and Simulations     Hybrid Journal   (Followers: 5)
Frontiers in Climate     Open Access   (Followers: 5)
Discover Sustainability     Open Access   (Followers: 5)
Proceedings of the Indian National Science Academy     Full-text available via subscription   (Followers: 5)
International Journal of Culture and Modernity     Open Access   (Followers: 5)
History of Science and Technology     Open Access   (Followers: 5)
Data     Open Access   (Followers: 4)
Science & Technology Studies     Open Access   (Followers: 4)
Journal of the Indian Institute of Science     Hybrid Journal   (Followers: 4)
Journal of Big History     Open Access   (Followers: 4)
MUST : Journal of Mathematics Education, Science and Technology     Open Access   (Followers: 4)
Journal of Composites Science     Open Access   (Followers: 4)
People and Nature     Open Access   (Followers: 4)
Middle European Scientific Bulletin     Open Access   (Followers: 4)
Citizen Science : Theory and Practice     Open Access   (Followers: 3)
Research Policy : X     Open Access   (Followers: 3)
Revista Saber Digital     Open Access   (Followers: 3)
iScience     Open Access   (Followers: 2)
Applied Mathematics and Nonlinear Sciences     Open Access   (Followers: 2)
Acta Nova     Open Access   (Followers: 2)
Indonesian Journal of Science and Mathematics Education     Open Access   (Followers: 2)
Rekayasa     Open Access   (Followers: 2)
Indian Journal of History of Science     Hybrid Journal   (Followers: 2)
Jaunujų mokslininkų darbai     Open Access   (Followers: 2)
Journal of Alasmarya University     Open Access   (Followers: 2)
BJHS Themes     Open Access   (Followers: 2)
Orbis Cógnita : Revista Científica     Open Access   (Followers: 2)
Revista Científica de la Universidad Nacional del Este     Open Access   (Followers: 2)
Scientific Bulletin     Open Access   (Followers: 1)
Global Journal of Science Frontier Research     Open Access   (Followers: 1)
Impact     Open Access   (Followers: 1)
International Journal of Research in Science     Open Access   (Followers: 1)
Journal of Science and Technology     Open Access   (Followers: 1)
Uluslararası Bilimsel Araştırmalar Dergisi (IBAD)     Open Access   (Followers: 1)
Acta Scientifica Malaysia     Open Access   (Followers: 1)
Scientonomy : Journal for the Science of Science     Open Access   (Followers: 1)
Revista Vivências em Ensino de Ciências     Open Access   (Followers: 1)
PENDIPA : Journal of Science Education     Open Access   (Followers: 1)
Journal of Science and Engineering     Open Access   (Followers: 1)
International Journal of Innovative Research and Scientific Studies     Open Access   (Followers: 1)
Futures & Foresight Science     Hybrid Journal   (Followers: 1)
Journal of Scientific Research and Reports     Open Access   (Followers: 1)
AAS Open Research     Open Access   (Followers: 1)
ARPHA Conference Abstracts     Open Access   (Followers: 1)
Rihan Journal for Scientific Publishing     Open Access   (Followers: 1)
Experimental Results     Open Access   (Followers: 1)
Natural Sciences Education     Hybrid Journal   (Followers: 1)
South American Sciences     Open Access   (Followers: 1)
International Science and Technology Journal of Namibia     Open Access   (Followers: 1)
Fundamental Research     Open Access  
Research Integrity and Peer Review     Open Access  
Journal of Responsible Technology     Open Access  
Natural Sciences     Open Access  
Türk Bilim ve Mühendislik Dergisi     Open Access  
ArtefaCToS : Revista de estudios sobre la ciencia y la tecnología     Open Access  
Ethiopian Journal of Sciences and Sustainable Development     Open Access  
Vilnius University Proceedings     Open Access  
Sciential     Open Access  
ARPHA Proceedings     Open Access  
Gaudium Sciendi     Open Access  
Crea Ciencia Revista Científica     Open Access  
Rafidain Journal of Science     Open Access  
Journal of Al-Qadisiyah for Pure Science     Open Access  
Revista Tecnológica     Open Access  
Himalayan Journal of Science and Technology     Open Access  
International Journal of Academic Research in Business, Arts & Science     Open Access  
Universidad, Ciencia y Tecnología     Open Access  
Fides et Ratio : Revista de Difusión Cultural y Científica     Open Access  
Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales     Open Access  
Entre Ciencia e Ingeniería     Open Access  
Revista Politécnica     Open Access  
Reportes Científicos de la FaCEN     Open Access  
Jurnal Ilmiah Ilmu Terapan Universitas Jambi : JIITUJ     Open Access  
Revista Eletrônica Ludus Scientiae     Open Access  
Emergent Scientist     Open Access  
Asian Journal of Advanced Research and Reports     Open Access  
Archives of Current Research International     Open Access  
Advances in Research     Open Access  
International Journal of Applied Science     Open Access  
Iranian Journal of Science and Technology, Transactions A : Science     Hybrid Journal  
J : Multidisciplinary Scientific Journal     Open Access  
Revista Binacional Brasil - Argentina: Diálogo entre as ciências     Open Access  
Revista Ciencia y Tecnología     Open Access  
Journal of Institute of Science and Technology     Open Access  
Journal of Science (JSc)     Open Access  
WikiJournal of Science     Open Access  
Acta Materialia Transilvanica     Open Access  
Integrated Research Advances     Open Access  
Open Conference Proceedings Journal     Open Access  
Naturen     Full-text available via subscription  
Ekaia : EHUko Zientzia eta Teknologia aldizkaria     Open Access  
Sci     Open Access  
Maskana     Open Access  
Hoosier Science Teacher     Open Access  
Reports in Advances of Physical Sciences     Open Access  
Facets     Open Access  
Adıyaman University Journal of Science     Open Access  
Revista Brasileira de Iniciação Científica     Open Access  
Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering     Open Access  
Scientific African     Open Access  
Scientific Journal of Mehmet Akif Ersoy University     Open Access  
Black Sea Journal of Engineering and Science     Open Access  
Fırat University Turkish Journal of Science & Technology     Open Access  
Gazi University Journal of Science     Open Access  
Middle East Journal of Science     Open Access  
International Journal of Computational and Experimental Science and Engineering (IJCESEN)     Open Access  
International Journal of Engineering, Technology and Natural Sciences     Open Access  
Bulletin of the National Research Centre     Open Access  
Uni-pluriversidad     Open Access  
ConCiencia     Open Access  
Ciencia y Tecnología     Open Access  
Revista Bases de la Ciencia     Open Access  
Elkawnie : Journal of Islamic Science and Technology     Open Access  
Ciência ET Praxis     Open Access  
Arab Journal of Basic and Applied Sciences     Open Access  
International Annals of Science     Open Access  
Science Heritage Journal     Open Access  
Bilge International Journal of Science and Technology Research     Open Access  
Avrasya Terim Dergisi     Open Access  
International Scientific and Vocational Studies Journal     Open Access  
TÜBAV Bilim Dergisi     Open Access  
LOGIKA Jurnal Ilmiah Lemlit Unswagati Cirebon     Open Access  
Dalat University Journal of Science     Open Access  
Investiga : TEC     Open Access  
Investigación Joven     Open Access  
Respuestas     Open Access  
Science Diliman     Open Access  
Instruments     Open Access  
Revista Científica y Tecnológica UPSE     Open Access  
HardwareX     Open Access  
Sultan Qaboos University Journal for Science     Open Access  
Borneo Journal of Resource Science and Technology     Open Access  
Sainstek : Jurnal Sains dan Teknologi     Open Access  
Revista de Información Científica     Open Access  
Indonesian Journal of Fundamental Sciences     Open Access  
Sainteknol : Jurnal Sains dan Teknologi     Open Access  
Jurnal Natural     Open Access  
Frontiers for Young Minds     Open Access  
Revista Ciência, Tecnologia & Ambiente     Open Access  
Journal of Indian Council of Philosophical Research     Hybrid Journal  
Journal of Negative and No Positive Results     Open Access  
Revista Conhecimento Online     Open Access  
Nova     Open Access  
CienciaUAT     Open Access  
Enseñanza de las Ciencias : Revista de Investigación y Experiencias Didácticas     Open Access  
Makara Journal of Science     Open Access  
Jurnal Sains Dasar     Open Access  
Indonesian Journal of Science and Technology     Open Access  
Ethiopian Journal of Science and Technology     Open Access  
Jurnal Matematika, Sains, Dan Teknologi     Open Access  
Heidelberger Jahrbücher Online     Open Access  
ARO. The Scientific Journal of Koya University     Open Access  
International Journal of Recent Contributions from Engineering, Science & IT     Open Access  
Estação Científica (UNIFAP)     Open Access  
The Winnower     Open Access  

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Sci
Number of Followers: 0  

  This is an Open Access Journal Open Access journal
ISSN (Online) 2413-4155
Published by MDPI Homepage  [258 journals]
  • Sci, Vol. 6, Pages 5: Deep-Learning-Based Real-Time Visual Pollution
           Detection in Urban and Textile Environments

    • Authors: Md Fahim Shahoriar Titu, Abdul Aziz Chowdhury, S. M. Rezwanul Haque, Riasat Khan
      First page: 5
      Abstract: The environmental physiognomy of an area can significantly diminish its aesthetic appeal, rendering it susceptible to visual pollution, the unbeaten scourge of modern urbanization. In this study, we propose using a deep learning network and a robotic vision system integrated with Google Street View to identify streets and textile-based visual pollution in Dhaka, the megacity of Bangladesh. The issue of visual pollution extends to the global apparel and textile industry, as well as to various common urban elements such as billboards, bricks, construction materials, street litter, communication towers, and entangled electric wires. Our data collection encompasses a wide array of visual pollution elements, including images of towers, cables, construction materials, street litter, cloth dumps, dyeing materials, and bricks. We employ two open-source tools to prepare and label our dataset: LabelImg and Roboflow. We develop multiple neural network models to swiftly and accurately identify and classify visual pollutants in this work, including Faster SegFormer, YOLOv5, YOLOv7, and EfficientDet. The tuna swarm optimization technique has been used to select the applied models’ final layers and corresponding hyperparameters. In terms of hardware, our proposed system comprises a Xiaomi-CMSXJ22A web camera, a 3.5-inch touchscreen display, and a Raspberry Pi 4B microcontroller. Subsequently, we program the microcontroller with the YOLOv5 model. Rigorous testing and trials are conducted on these deep learning models to evaluate their performance against various metrics, including accuracy, recall, regularization and classification losses, mAP, precision, and more. The proposed system for detecting and categorizing visual pollution within the textile industry and urban environments has achieved notable results. Notably, the YOLOv5 and YOLOv7 models achieved 98% and 92% detection accuracies, respectively. Finally, the YOLOv5 technique has been deployed into the Raspberry Pi edge device for instantaneous visual pollution detection. The proposed visual pollutants detection device can be easily mounted on various platforms (like vehicles or drones) and deployed in different urban environments for on-site, real-time monitoring. This mobility is crucial for comprehensive street-level data collection, potentially engaging local communities, schools, and universities in understanding and participating in environmental monitoring efforts. The comprehensive dataset on visual pollution will be published in the journal following the acceptance of our manuscript.
      Citation: Sci
      PubDate: 2024-01-11
      DOI: 10.3390/sci6010005
      Issue No: Vol. 6, No. 1 (2024)
       
  • Sci, Vol. 6, Pages 6: Microbial Insights into Biofortified Common Bean
           Cultivation

    • Authors: Alexander Machado Cardoso, Carlos Vinicius Ferreira da Silva, Vânia Lúcia de Pádua
      First page: 6
      Abstract: Microorganisms play a fundamental role in sustainable agriculture, and their importance in common bean (Phaseolus vulgaris) cultivation cannot be underestimated. This review article aims to comprehensively explore the diverse roles of microorganisms in sustainable biofortified common bean cultivation. Biofortification refers to the process of increasing the nutrient content in crops, which helps combat deficiencies in iron, zinc, and vitamins in the human body. Biofortified beans have better agronomic characteristics and offer higher micronutrient content compared to conventional crops. We examine the contribution of various microbial communities in nitrogen fixation, soil structure improvement, nutrient recycling, and disease suppression. Understanding the interaction between beneficial microorganisms and biofortified common bean plants enables us to develop ecologically sound and sustainable approaches to optimize crop productivity and improve nutrition and livelihoods for millions of people worldwide while reducing the environmental impact of agricultural practices.
      Citation: Sci
      PubDate: 2024-01-15
      DOI: 10.3390/sci6010006
      Issue No: Vol. 6, No. 1 (2024)
       
  • Sci, Vol. 6, Pages 7: The Genus Bryonia L. (Cucurbitaceae): A Systematic
           Review of Its Botany, Phytochemistry, Traditional Uses, and Biological
           Activities

    • Authors: Bachir Benarba, Khadidja Belhouala
      First page: 7
      Abstract: The Bryonia genus (Cucurbitaceae) is divided into 13 plants considered medicinal species with a significant pharmacological value fortreating as well as preventing various ailments. The current systematic review aims to present useful and updated findings published onthis genus inthe last two decades. Based on PubMed, Science Direct, JSTOR, and Google Scholar, 42 of the available previous studies on Bryonia have been selected from 2000 to 2022. Thereafter, these studies were analyzed, summarized, and separately recorded according to the topic or section, adding some comments foreach. Our review provided a botanical description of the genus, followed by itsindigenous uses. Furthermore, more than 150 reported phytochemical compounds were grouped into families such as terpenoids, alkaloids, flavonoids, glycosides, saponins, and volatile oils. Hereby, thebiological activities part of this genus wereexposed, including itsantimicrobial, antioxidant, antidiabetic, antinociceptive, and anti-inflammatory functions, along with an interesting anticancer efficiency. Overall, our findings could contribute to forthcoming investigations that may lead to determining the responsible phytoconstituents for Bryonia’s efficiency.
      Citation: Sci
      PubDate: 2024-01-18
      DOI: 10.3390/sci6010007
      Issue No: Vol. 6, No. 1 (2024)
       
  • Sci, Vol. 6, Pages 8: Sci Reloaded: Introducing the New Aims and Scope

    • Authors: Ahmad Yaman Abdin, Claus Jacob
      First page: 8
      Abstract: We are excited to share with you a crucial moment in the journey of Sci (ISSN 2413-4155) as we are announcing its new Aims and Scope [...]
      Citation: Sci
      PubDate: 2024-01-26
      DOI: 10.3390/sci6010008
      Issue No: Vol. 6, No. 1 (2024)
       
  • Sci, Vol. 6, Pages 9: Evolving Paradigms of Recombinant Protein Production
           in Pharmaceutical Industry: A Rigorous Review

    • Authors: Achuth Jayakrishnan, Wan Rosalina Wan Rosli, Ahmad Rashidi Mohd Tahir, Fashli Syafiq Abd Razak, Phei Er Kee, Hui Suan Ng, Yik-Ling Chew, Siew-Keah Lee, Mahenthiran Ramasamy, Ching Siang Tan, Kai Bin Liew
      First page: 9
      Abstract: Many beneficial proteins have limited natural availability, which often restricts their supply and thereby reduces their potential for therapeutic or industrial usage. The advent of recombinant DNA (rDNA) technology enables the utilization of different microbes as surrogate hosts to facilitate the production of these proteins. This microbial technology continues to evolve and integrate with modern innovations to develop more effective approaches for increasing the production of recombinant biopharmaceuticals. These strategies encompass fermentation technology, metabolic engineering, the deployment of strong promoters, novel vector elements such as inducers and enhancers, protein tags, secretion signals, synthetic biology, high-throughput devices for cloning, and process screening. This appraisal commences with a general overview regarding the manufacture of recombinant proteins by microbes and the production of biopharmaceuticals, their trends towards the development of biopharmaceuticals, and then discusses the approaches adopted for accomplishing this. The design of the upstream process, which also involves host selection, vector design, and promoter design, is a crucial component of production strategies. On the other hand, the downstream process focuses on extraction and purification techniques. Additionally, the review covers the most modern tools and resources, methods for overcoming low expression, the cost of producing biopharmaceuticals in microbes, and readily available recombinant protein products.
      Citation: Sci
      PubDate: 2024-01-31
      DOI: 10.3390/sci6010009
      Issue No: Vol. 6, No. 1 (2024)
       
  • Sci, Vol. 6, Pages 10: Multimodal and Multidomain Feature Fusion for
           Emotion Classification Based on Electrocardiogram and Galvanic Skin
           Response Signals

    • Authors: Amita Dessai, Hassanali Virani
      First page: 10
      Abstract: Emotion classification using physiological signals is a promising approach that is likely to become the most prevalent method. Bio-signals such as those derived from Electrocardiograms (ECGs) and the Galvanic Skin Response (GSR) are more reliable than facial and voice recognition signals because they are not influenced by the participant’s subjective perception. However, the precision of emotion classification with ECG and GSR signals is not satisfactory, and new methods need to be developed to improve it. In addition, the fusion of the time and frequency features of ECG and GSR signals should be explored to increase classification accuracy. Therefore, we propose a novel technique for emotion classification that exploits the early fusion of ECG and GSR features extracted from data in the AMIGOS database. To validate the performance of the model, we used various machine learning classifiers, such as Support Vector Machine (SVM), Decision Tree, Random Forest (RF), and K-Nearest Neighbor (KNN) classifiers. The KNN classifier gives the highest accuracy for Valence and Arousal, with 69% and 70% for ECG and 96% and 94% for GSR, respectively. The mutual information technique of feature selection and KNN for classification outperformed the performance of other classifiers. Interestingly, the classification accuracy for the GSR was higher than for the ECG, indicating that the GSR is the preferred modality for emotion detection. Moreover, the fusion of features significantly enhances the accuracy of classification in comparison to the ECG. Overall, our findings demonstrate that the proposed model based on the multiple modalities is suitable for classifying emotions.
      Citation: Sci
      PubDate: 2024-02-04
      DOI: 10.3390/sci6010010
      Issue No: Vol. 6, No. 1 (2024)
       
  • Sci, Vol. 6, Pages 11: A Review of Catalyst Modification and Process
           Factors in the Production of Light Olefins from Direct Crude Oil Catalytic
           Cracking

    • Authors: Ruth Eniyepade Emberru, Raj Patel, Iqbal Mohammed Mujtaba, Yakubu Mandafiya John
      First page: 11
      Abstract: Petrochemical feedstocks are experiencing a fast growth in demand, which will further expand their market in the coming years. This is due to an increase in the demand for petrochemical-based materials that are used in households, hospitals, transportation, electronics, and telecommunications. Consequently, petrochemical industries rely heavily on olefins, namely propylene, ethylene, and butene, as fundamental components for their manufacturing processes. Presently, there is a growing interest among refineries in prioritising their operations towards the production of fuels, specifically gasoline, diesel, and light olefins. The cost-effectiveness and availability of petrochemical primary feedstocks, such as propylene and butene, can be enhanced through the direct conversion of crude oil into light olefins using fluid catalytic cracking (FCC). To achieve this objective, the FCC technology, process optimisation, and catalyst modifications may need to be redesigned. It is helpful to know that there are several documented methods of modifying traditional FCC catalysts’ physicochemical characteristics to enhance their selectivity toward light olefins’ production, since the direct cracking of crude oil to olefins is still in its infancy. Based on a review of the existing zeolite catalysts, this work focuses on the factors that need to be optimized and the approaches to modifying FCC catalysts to maximize light olefin production from crude oil conversion via FCC. Several viewpoints have been combined as a result of this research, and recommendations have been made for future work in the areas of optimising the yield of light olefins by engineering the pore structure of zeolite catalysts, reducing deactivation by adding dopants, and conducting technoeconomic analyses of direct crude oil cracking to produce light olefins.
      Citation: Sci
      PubDate: 2024-02-04
      DOI: 10.3390/sci6010011
      Issue No: Vol. 6, No. 1 (2024)
       
  • Sci, Vol. 6, Pages 12: Alternative Evacuation Procedures and Smart
           Devices’ Impact Assessment for Large Passenger Vessels under Severe
           Weather Conditions

    • Authors: Evangelos Stefanou, Panagiotis Louvros, Fotios Stefanidis, Evangelos Boulougouris
      First page: 12
      Abstract: Within the expansive domain of maritime safety, optimizing evacuation procedures stands as a critical endeavour. After all, evacuation is literally the last and fundamental safety level afforded to mariners and passengers. Recent incidents have rekindled interest in assessing the performance of this ultimate safety barrier. However, addressing evacuability requires a holistic approach. The authors present herein the setup, simulation, and ultimately evaluation of a novel approach and its ability to rigorously assess multiple innovative risk-control options in a challenging, realistic setting. Moreover, its benchmarking against conventional regulation-dictated evacuation processes is captured distinctively along with the relative effectiveness of each proposed measure. Such measures include smart technologies and procedural changes that can result in substantial improvements to the current procedures. These will impact the ongoing discourse on maritime safety by providing insights for policymakers, vessel operators, emergency planners, etc., and emphasize the need for further research and development efforts to fortify the industry against evolving safety challenges.
      Citation: Sci
      PubDate: 2024-02-16
      DOI: 10.3390/sci6010012
      Issue No: Vol. 6, No. 1 (2024)
       
  • Sci, Vol. 6, Pages 1: Plasma-Chemical Disposal of Silicon and Germanium
           Tetrachlorides Waste by Hydrogen Reduction

    • Authors: Roman Kornev, Igor Gornushkin, Lubov Shabarova, Alena Kadomtseva, Georgy Mochalov, Nikita Rekunov, Sergey Romanov, Vitaly Medov, Darya Belousova, Nikita Maleev
      First page: 1
      Abstract: The processes of hydrogen reduction of silicon and germanium chlorides under the conditions of high-frequency (40.68 MHz) counteracted arc discharge stabilized between two rod electrodes are investigated. The main gas-phase and solid products of plasma-chemical transformations are determined. Thermodynamic analysis of SiCl4 + H2 and GeCl4 + H2 systems for optimal process parameters was carried out. Using the example of hydrogen reduction of SiCl4 by the method of numerical modeling, gas-dynamic and thermal processes for this type of discharge are investigated. The impurity composition of gas-phase and solid reaction products is investigated. The possibility of single-stage production of high-purity Si and Ge mainly in the form of compact ingots, as well as high-purity chlorosilanes and trichlorogermane, is shown.
      Citation: Sci
      PubDate: 2023-12-22
      DOI: 10.3390/sci6010001
      Issue No: Vol. 6, No. 1 (2023)
       
  • Sci, Vol. 6, Pages 2: IoT-Based Framework for COVID-19 Detection Using
           Machine Learning Techniques

    • Authors: Ahmed Salih Al-Khaleefa, Ghazwan Fouad Kadhim Al-Musawi, Tahseen Jebur Saeed
      First page: 2
      Abstract: Current advancements in the technology of the Internet of Things (IoT) have led to the proliferation of various applications in the healthcare sector that use IoT. Recently, it has been shown that voice signal data of the respiratory system (i.e., breathing, coughing, and speech) can be processed through machine learning techniques to detect different diseases of this system such as COVID-19, considered an ongoing global pandemic. Therefore, this paper presents a new IoT framework for the identification of COVID-19 based on breathing voice samples. Using IoT devices, voice samples were captured and transmitted to the cloud, where they were analyzed and processed using machine learning techniques such as the naïve Bayes (NB) algorithm. In addition, the performance of the NB algorithm was assessed based on accuracy, sensitivity, specificity, precision, F-Measure, and G-Mean. The experimental findings showed that the proposed NB algorithm achieved 82.97% accuracy, 75.86% sensitivity, 94.44% specificity, 95.65% precision, 84.61% F-Measure, and 84.64% G-Mean.
      Citation: Sci
      PubDate: 2023-12-23
      DOI: 10.3390/sci6010002
      Issue No: Vol. 6, No. 1 (2023)
       
  • Sci, Vol. 6, Pages 3: Fairness and Bias in Artificial Intelligence: A
           Brief Survey of Sources, Impacts, and Mitigation Strategies

    • Authors: Emilio Ferrara
      First page: 3
      Abstract: The significant advancements in applying artificial intelligence (AI) to healthcare decision-making, medical diagnosis, and other domains have simultaneously raised concerns about the fairness and bias of AI systems. This is particularly critical in areas like healthcare, employment, criminal justice, credit scoring, and increasingly, in generative AI models (GenAI) that produce synthetic media. Such systems can lead to unfair outcomes and perpetuate existing inequalities, including generative biases that affect the representation of individuals in synthetic data. This survey study offers a succinct, comprehensive overview of fairness and bias in AI, addressing their sources, impacts, and mitigation strategies. We review sources of bias, such as data, algorithm, and human decision biases—highlighting the emergent issue of generative AI bias, where models may reproduce and amplify societal stereotypes. We assess the societal impact of biased AI systems, focusing on perpetuating inequalities and reinforcing harmful stereotypes, especially as generative AI becomes more prevalent in creating content that influences public perception. We explore various proposed mitigation strategies, discuss the ethical considerations of their implementation, and emphasize the need for interdisciplinary collaboration to ensure effectiveness. Through a systematic literature review spanning multiple academic disciplines, we present definitions of AI bias and its different types, including a detailed look at generative AI bias. We discuss the negative impacts of AI bias on individuals and society and provide an overview of current approaches to mitigate AI bias, including data pre-processing, model selection, and post-processing. We emphasize the unique challenges presented by generative AI models and the importance of strategies specifically tailored to address these. Addressing bias in AI requires a holistic approach involving diverse and representative datasets, enhanced transparency and accountability in AI systems, and the exploration of alternative AI paradigms that prioritize fairness and ethical considerations. This survey contributes to the ongoing discussion on developing fair and unbiased AI systems by providing an overview of the sources, impacts, and mitigation strategies related to AI bias, with a particular focus on the emerging field of generative AI.
      Citation: Sci
      PubDate: 2023-12-26
      DOI: 10.3390/sci6010003
      Issue No: Vol. 6, No. 1 (2023)
       
  • Sci, Vol. 6, Pages 4: Early-Wood vs. Late-Wood in Scots Pine: Finding
           Stable Relationships in Elemental Distribution

    • Authors: Vladimir L. Gavrikov, Alexey I. Fertikov, Ruslan A. Sharafutdinov, Zhonghua Tang, Eugene A. Vaganov
      First page: 4
      Abstract: This study explored whether consistent differences can be found between early-wood and late-wood in terms of elemental content of tree rings. The species to study was Pinus sylvestris L. growing within an even-aged stand planted during the early 1970s in eastern Siberia. The wood specimens were extracted from the north and south sides of trees and subsequently scanned through an X-ray fluorescent facility Itrax Multiscanner. A sequence of relatively wide tree-rings was chosen for the analysis. The scanning data on a number of elements (Al, Si, P, S, Cl, K, Ca, Ti, Mn, Fe, Cu, Zn, Sr, and Hg) were split into early-wood and late-wood data for each year of growth. The early- and late-wood data in the same ring were analyzed for basic statistics against each other as well as against available meteorological data. In the northern direction, the elements Al, Si, P, Cl, Cu, and Zn are always more abundant in the late-wood, while Ca, Fe, and Sr are always more abundant in the early-wood. What is important is how the differences for P, Ca, Fe, Cu, Zn, and Sr were always significant. The calcium content in the early-wood was the most consistently reflective regarding the meteorological data for the early summer (June). In some trees, the late-wood K content was well correlated with the Vysotskii–Ivanov climatic index. In the southern direction, Cu and Zn were always more abundant in the late-wood, while Sr was more abundant in the early-wood. The differences for all three elements were always significant. The cases of consistent relationships, though rare, help to develop a research program in the area of dendrochemistry.
      Citation: Sci
      PubDate: 2023-12-28
      DOI: 10.3390/sci6010004
      Issue No: Vol. 6, No. 1 (2023)
       
  • Sci, Vol. 5, Pages 37: T5 for Hate Speech, Augmented Data, and Ensemble

    • Authors: Tosin Adewumi, Sana Sabah Sabry, Nosheen Abid, Foteini Liwicki, Marcus Liwicki
      First page: 37
      Abstract: We conduct relatively extensive investigations of automatic hate speech (HS) detection using different State-of-The-Art (SoTA) baselines across 11 subtasks spanning six different datasets. Our motivation is to determine which of the recent SoTA models is best for automatic hate speech detection and what advantage methods, such as data augmentation and ensemble, may have on the best model, if any. We carry out six cross-task investigations. We achieve new SoTA results on two subtasks—macro F1 scores of 91.73% and 53.21% for subtasks A and B of the HASOC 2020 dataset, surpassing previous SoTA scores of 51.52% and 26.52%, respectively. We achieve near-SoTA results on two others—macro F1 scores of 81.66% for subtask A of the OLID 2019 and 82.54% for subtask A of the HASOC 2021, in comparison to SoTA results of 82.9% and 83.05%, respectively. We perform error analysis and use two eXplainable Artificial Intelligence (XAI) algorithms (Integrated Gradient (IG) and SHapley Additive exPlanations (SHAP)) to reveal how two of the models (Bi-Directional Long Short-Term Memory Network (Bi-LSTM) and Text-to-Text-Transfer Transformer (T5)) make the predictions they do by using examples. Other contributions of this work are: (1) the introduction of a simple, novel mechanism for correcting Out-of-Class (OoC) predictions in T5, (2) a detailed description of the data augmentation methods, and (3) the revelation of the poor data annotations in the HASOC 2021 dataset by using several examples and XAI (buttressing the need for better quality control). We publicly release our model checkpoints and codes to foster transparency.
      Citation: Sci
      PubDate: 2023-09-22
      DOI: 10.3390/sci5040037
      Issue No: Vol. 5, No. 4 (2023)
       
  • Sci, Vol. 5, Pages 38: Treatment of Diabetes Mellitus by Acupuncture:
           Dynamics of Blood Glucose Level and Its Mathematical Modelling

    • Authors: Marija Šimat, Mateja Janković Makek, Maja Mičetić
      First page: 38
      Abstract: The aim of this research is to present the effects of acupuncture treatment on morning blood glucose level (BGL) in type 2 diabetes mellitus (T2DM) patients, and to describe them by a predictive model. The morning BGL is measured after overnight fasting during a three-month long acupuncture treatment for two persons diagnosed with T2DM and is compared with the BGL of two persons in similar health conditions taking only metformin-based drugs. It is shown that the morning BGL is highly affected by each single acupuncture treatment and by the number of the already applied treatments. Significant lowering of BGL after each treatment is observed, as well as an overall BGL lowering effect, which is the result of the repeated acupuncture. The observed BGL reduction was found to be maintained during a follow-up performed a year after the acupuncture. The measured BGL dynamics curves are analyzed and described by a model. This model describes well all of the key features of the measured BGL dynamics and provides personal parameters that describe the BGL regulation. The model is used to simulate BGL regulation by acupuncture performed with different frequencies. It can be used generally to predict the effects of acupuncture on BGL and to optimize the time between two treatments. The results will enable a better understanding of acupuncture application in diabetes, and a prediction of its effects in diabetes treatment.
      Citation: Sci
      PubDate: 2023-09-26
      DOI: 10.3390/sci5040038
      Issue No: Vol. 5, No. 4 (2023)
       
  • Sci, Vol. 5, Pages 39: In Silico Study of Potential Small Molecule TIPE2
           Inhibitors for the Treatment of Cancer

    • Authors: Jerica Wilson, Katerina Evangelou, Youhai H. Chen, Hai-Feng Ji
      First page: 39
      Abstract: Context: Chronic inflammation has been linked to cancer since the 19th century. Tumor growth is supported by the proangiogenic factors that chronic inflammation requires. Polarized leukocytes initiate these angiogenic and tumorigenic factors. TIPE2, a transport protein, manages the cytoskeletal rearrangement that gives a polarized leukocyte its motility. Inhibition of this protein could lead to a therapeutic option for solid tumor cancers; however, no such inhibitors have been developed so far due to the large cavity size of the TIPE2 protein. Here we have examined possible small molecule inhibitors by combining structure-based and fragment-based drug design approaches. The highest binding ligands were complexed with the protein, and fragment libraries were docked with the complex with the intention of linking the hit compounds and fragments to design a more potent ligand. Three hit compounds were identified by in silico structure-based screening and a linked compound, C2–F14, of excellent binding affinity, was identified by linking fragments to the hit compounds. C2–F14 demonstrates good binding stability in molecular dynamic simulations and great predicted ADME properties. Methods: High throughput molecular docking calculations of mass libraries were performed using AutoDock Vina 1.1.2. Molecular docking of individual ligands was performed using AutoDock Vina with PyRx. Ligand libraries were prepared using OpenBabel, linked ligands were prepared using Avogadro. The protein was prepared using AutoDockTools-1.5.6. Protein-ligand complexes were visualized with PyMOL. Two- and three-dimensional representations of protein–ligand interactions were plotted with BIOVIA Discovery Studio Visualizer. In silico absorption, distribution, metabolism, and excretion (ADME) properties were calculated using SwissADME. Molecular dynamics simulations were conducted with GROMACS.
      Citation: Sci
      PubDate: 2023-10-07
      DOI: 10.3390/sci5040039
      Issue No: Vol. 5, No. 4 (2023)
       
  • Sci, Vol. 5, Pages 40: Digital Twins in Manufacturing: A RAMI 4.0
           Compliant Concept

    • Authors: Martin Lindner, Lukas Bank, Johannes Schilp, Matthias Weigold
      First page: 40
      Abstract: Digital twins are among the technologies that are considered to have high potential. At the same time, there is no uniform understanding of what this technology means. Definitions are used across disciplinary boundaries, resulting in a multitude of different interpretations. The concepts behind the terms should be clearly named to transfer knowledge and bundle developments in digitalization. In particular, the Reference Architectural Model for Industry (RAMI) 4.0, as the guiding concept of digitalization, should be in harmony with the terms to be able to establish a contradiction-free relationship. This paper therefore summarizes the most important definitions and descriptions from the scientific community. By evaluating the relevant literature, a concept is derived. The concept presented in this work concretizes the requirements and understanding of digital twins in the frame of RAMI 4.0 with a focus on manufacturing. It thus contributes to the understanding of the technology. In this way, the concept is intended to contribute to the implementation of digital twins in this context.
      Citation: Sci
      PubDate: 2023-10-10
      DOI: 10.3390/sci5040040
      Issue No: Vol. 5, No. 4 (2023)
       
  • Sci, Vol. 5, Pages 41: Privacy and Security of Blockchain in Healthcare:
           Applications, Challenges, and Future Perspectives

    • Authors: Hamed Taherdoost
      First page: 41
      Abstract: Blockchain offers a cutting-edge solution for storing medical data, carrying out medical transactions, and establishing trust for medical data integration and exchange in a decentralized open healthcare network setting. While blockchain in healthcare has garnered considerable attention, privacy and security concerns remain at the center of the debate when adopting blockchain for information exchange in healthcare. This paper presents research on the subject of blockchain’s privacy and security in healthcare from 2017 to 2022. In light of the existing literature, this critical evaluation assesses the current state of affairs, with a particular emphasis on papers that deal with practical applications and difficulties. By providing a critical evaluation, this review provides insight into prospective future study directions and advances.
      Citation: Sci
      PubDate: 2023-10-30
      DOI: 10.3390/sci5040041
      Issue No: Vol. 5, No. 4 (2023)
       
  • Sci, Vol. 5, Pages 42: Development of Tannic Acid Coated Polyvinylidene
           Fluoride Membrane for Filtration of River Water Containing High Natural
           Organic Matter

    • Authors: Rosmaya Dewi, Norazanita Shamsuddin, Muhammad Saifullah Abu Bakar, Sutarat Thongratkaew, Kajornsak Faungnawakij, Muhammad Roil Bilad
      First page: 42
      Abstract: River water can be used as a source of drinking water. However, it is vital to consider the existence of natural organic matter (NOM) and its possible influence on water quality (low turbidity, high color). The level of NOM in river water significantly impacts the ecosystem’s health and the water’s quality, and needs to be removed. A membrane-based approach is attractive for treating NOM successfully, but is still hindered by the membrane fouling problem. This study aims to develop polyvinylidene fluoride (PVDF)-based membranes customized for NOM removal from river water. The anti-fouling property was imposed by a coating of tannic acid (TA) and Fe3+ on the pre-prepared PVDF membrane. The results show that the TA–Fe coatings were effective, as demonstrated by the FTIR spectra, SEM, and EDS data. The coatings made the membrane more hydrophilic, with smaller pore size and lower clean water permeability. Such properties offer enhanced NOM rejections (up to 100%) and remarkably higher fouling recovery (up to 23%), desirable for maintaining a long-term filtration performance.
      Citation: Sci
      PubDate: 2023-11-20
      DOI: 10.3390/sci5040042
      Issue No: Vol. 5, No. 4 (2023)
       
  • Sci, Vol. 5, Pages 43: Changes in Anthropometric Characteristics and
           Isokinetic Muscle Strength in Elite Team Sport Players during an Annual
           Training Cycle

    • Authors: Evangelia Papaevangelou, Zacharoula Papadopoulou, Athanasios Mandroukas, Yiannis Michaildis, Pantelis T. Nikolaidis, Nikos V. Margaritelis, Thomas I. Metaxas
      First page: 43
      Abstract: The aim of the present research was to investigate the variation in the anthropometric characteristics and the isokinetic muscle strength of elite female team sport players during a season (29–36 weeks). Three groups of female athletes that consisted of soccer (n = 19; age, 23.2 ± 4.3 years), basketball (n = 26, 21.1 ± 5.4 years) and handball players (n = 26, 21.1 ± 4.2 years) underwent anthropometric and isokinetic measurements at the beginning of the preparation period, in the middle and at the end of the competitive season. Isokinetic peak torque values of the hamstrings (H) and quadriceps (Q), as well as the conventional strength ratios of H:Q, were tested on an isokinetic dynamometer at angular velocities of 60, 180 and 300°·s−1. Body weight, lean body mass and body fat of all groups decreased from the first to the third testing session (p < 0.05). Isokinetic peak torque gradually increased during the three measurements (p < 0.05). The soccer players had lower body weight and body fat compared to the basketball and handball players (p < 0.05). Isokinetic peak torque in knee flexion did not show any difference between the sports at any angular velocity or knee movement (flexion and extension), with an exception of the 180°·s−1. The improvement observed for all athletes can be attributed to the training programs that collectively characterize these team sports.
      Citation: Sci
      PubDate: 2023-11-23
      DOI: 10.3390/sci5040043
      Issue No: Vol. 5, No. 4 (2023)
       
  • Sci, Vol. 5, Pages 44: Cooperating and Competing Digital Twins for
           Industrie 4.0 in Urban Planning Contexts

    • Authors: Otthein Herzog, Matthias Jarke, Siegfried Zhiqiang Wu
      First page: 44
      Abstract: Digital twins are emerging as a prime analysis, prediction, and control concepts for enabling the Industrie 4.0 vision of cyber-physical production systems (CPPSs). Today’s growing complexity and volatility cannot be handled by monolithic digital twins but require a fundamentally decentralized paradigm of cooperating digital twins. Moreover, societal trends such as worldwide urbanization and growing emphasis on sustainability highlight competing goals that must be reflected not just in cooperating but also competing digital twins, often even interacting in “coopetition”. This paper argues for multi-agent systems (MASs) to address this challenge, using the example of embedding industrial digital twins into an urban planning context. We provide a technical discussion of suitable MAS frameworks and interaction protocols; data architecture options for efficient data supply from heterogeneous sensor streams and sovereignty in data sharing; and strategic analysis for scoping a digital twin systems design among domain experts and decision makers. To illustrate the way still in front of research and practice, the paper reviews some success stories of MASs in Industrie/Logistics 4.0 settings and sketches a comprehensive vision for digital twin-based holistic urban planning.
      Citation: Sci
      PubDate: 2023-11-28
      DOI: 10.3390/sci5040044
      Issue No: Vol. 5, No. 4 (2023)
       
  • Sci, Vol. 5, Pages 45: The Perceptions of Generation Z University Students
           about Their Futures: A Qualitative Study

    • Authors: Gül Dikeç, Simge Öztürk, Neslihan Taşbaşı, Damla Figenergül, Bilal Buğrahan Güler
      First page: 45
      Abstract: This study explored the future-oriented perceptions of Generation Z students in a foundation university. This study was conducted using qualitative research and a phenomenological design. The study sample consisted of 11 university students over the age of 18 who agreed to participate in the study. Data were collected online through individual interviews in Türkiye. Colaizzi’s phenomenological analysis method was used in the data analysis. The content analysis determined three main themes and eleven sub-themes. The first theme was the students’ knowledge acquisition about the “current situation of the country.” Under this theme were four sub-themes: economic problems, the immigrant situation, the education and justice system, and the country’s agenda. In the second theme, students shared their opinions about “being a student in the country.” This theme included economic impossibilities, their participation in limited social activities, and housing problems. In the last theme, “future anxiety,” the sub-themes of the students were found to include experiences hopelessness versus hope. Uncertainty caused anxiety, as did going abroad, finding a job, and improving themselves. It was determined that the participants were worried about the current situation in the countries they lived in during this period due to economic problems; while some were hopeful about the future, some were hopeless and would go abroad. This study might contribute to the literature on determining the future-oriented perceptions, possible stressors and hope levels of Generation Z university students in Türkiye. Additionally, intervention programs can be developed for the management these stressors to protect the mental health of Generation Z university students. On the other hand, it is necessary to protect the mental health of young people, who are the adults of the future, and to create policies for the youth of this country where social opportunities are maintained.
      Citation: Sci
      PubDate: 2023-12-08
      DOI: 10.3390/sci5040045
      Issue No: Vol. 5, No. 4 (2023)
       
  • Sci, Vol. 5, Pages 46: From Turing to Transformers: A Comprehensive Review
           and Tutorial on the Evolution and Applications of Generative Transformer
           Models

    • Authors: Emma Yann Zhang, Adrian David Cheok, Zhigeng Pan, Jun Cai, Ying Yan
      First page: 46
      Abstract: In recent years, generative transformers have become increasingly prevalent in the field of artificial intelligence, especially within the scope of natural language processing. This paper provides a comprehensive overview of these models, beginning with the foundational theories introduced by Alan Turing and extending to contemporary generative transformer architectures. The manuscript serves as a review, historical account, and tutorial, aiming to offer a thorough understanding of the models’ importance, underlying principles, and wide-ranging applications. The tutorial section includes a practical guide for constructing a basic generative transformer model. Additionally, the paper addresses the challenges, ethical implications, and future directions in the study of generative models.
      Citation: Sci
      PubDate: 2023-12-15
      DOI: 10.3390/sci5040046
      Issue No: Vol. 5, No. 4 (2023)
       
  • Sci, Vol. 5, Pages 26: Transcriptomics Analysis of Tomato Ripening
           Regulated by Carbon Dioxide

    • Authors: Jamshed Bobokalonov, Yanhong Liu, Karley K. Mahalak, Jenni A. Firrman, Shiowshuh Sheen, Siyuan Zhou, LinShu Liu
      First page: 26
      Abstract: Tomatoes are a perishable and seasonal fruit with a high economic impact. Carbon dioxide (CO2), among several other reagents, is used to extend the shelf-life and preserve the quality of tomatoes during refrigeration or packaging. To obtain insight into CO2 stress during tomato ripening, tomatoes at the late green mature stage were conditioned with one of two CO2 delivery methods: 5% CO2 for 14 days (T1) or 100% CO2 for 3 h (T2). Conventional physical and chemical characterization found that CO2 induced by either T1 or T2 delayed tomato ripening in terms of color change, firmness, and carbohydrate dissolution. However, T1 had longer-lasting effects. Furthermore, ethylene production was suppressed by CO2 in T1, and promoted in T2. These physical observations were further evaluated via RNA-Seq analysis at the whole-genome level, including genes involved in ethylene synthesis, signal transduction, and carotenoid biosynthesis. Transcriptomics analysis revealed that the introduction of CO2 via the T1 method downregulated genes related to fruit ripening; in contrast, T2 upregulated the gene encoding for ACS6, the enzyme responsible for S1 ethylene synthesis, even though there was a large amount of ethylene present, indicating that T1 and T2 regulate tomato ripening via different mechanisms. Quantitative real-time PCR assays (qRT-PCR) were used for validation, which substantiated the RNA-Seq data. The results of the present research provide insight into gene regulation by CO2 during tomato ripening at the whole-genome level.
      Citation: Sci
      PubDate: 2023-06-30
      DOI: 10.3390/sci5030026
      Issue No: Vol. 5, No. 3 (2023)
       
  • Sci, Vol. 5, Pages 27: Sensory and Cognitive Malingering: Studies and
           Tests

    • Authors: Gesualdo M. Zucco, Giuseppe Sartori
      First page: 27
      Abstract: Malingering relates to intentionally pretending or exaggerating physical or psychologic symptoms to gain an external incentive, such as avoiding work, law prosecution or military service, or seeking financial compensation from insurance companies. Accordingly, various techniques have been developed in recent years by the scientific community to address this challenge. In this review, we discuss malingering within visual, auditory and olfactory domains, as well as in cognitive disorders and psychopathology. We provide a general, critical, narrative overview on the intermodal criteria for differential diagnosis, and discuss validated psychophysical tools and electrophysiology-based tests for its detection, as well as insights for future directions.
      Citation: Sci
      PubDate: 2023-07-06
      DOI: 10.3390/sci5030027
      Issue No: Vol. 5, No. 3 (2023)
       
  • Sci, Vol. 5, Pages 28: COVID-19 as a Jump Start for Industry 4.0'
           Motivations and Core Areas of Pandemic-Related Investments in Digital
           Technologies at German Firms

    • Authors: Florian Butollo, Jana Flemming, Christine Gerber, Martin Krzywdzinski, David Wandjo, Nina Delicat, Lorena Herzog
      First page: 28
      Abstract: Academic studies prior to the pandemic rather emphasized that the progression towards Industry 4.0 happened in an incremental manner. However, the extraordinary circumstances of the pandemic have led to considerable investments that were widely interpreted as a (generalized) digitalization push. However, little is known about the character of such investments and their effects. The goal of this contribution is to provide an empirically based overview of recent investment in digital technologies in six economic sectors of the German economy: mechanical engineering, chemicals, automotives, logistics, healthcare, and financial services. Based on 36 case studies and a survey at 540 companies, we investigate the following questions: 1. How much did the COVID-19 pandemic reduce existing obstacles for investments in digitalization measures' 2. Is there a universal digitalization push due to the COVID-19 pandemic that differs from the trajectory before the pandemic' The results show that the pandemic affected investment in an unequal manner. It was driven by the immediate need to sustain business operations through the virtualization of communication among employees and with external partners. However, there was less dynamism in shop-floor-related digitalization, as it was less related to epidemiological concerns and is more long-term in nature.
      Citation: Sci
      PubDate: 2023-07-07
      DOI: 10.3390/sci5030028
      Issue No: Vol. 5, No. 3 (2023)
       
  • Sci, Vol. 5, Pages 29: Implementing Smart Services in Small- and
           Medium-Sized Manufacturing Companies: On the Progress of Servitization in
           the Era of Industry 4.0

    • Authors: Johannes Winter
      First page: 29
      Abstract: For a long time, the challenge has been to provide products and services that precisely match the preferences, habits, and needs of users [...]
      Citation: Sci
      PubDate: 2023-07-12
      DOI: 10.3390/sci5030029
      Issue No: Vol. 5, No. 3 (2023)
       
  • Sci, Vol. 5, Pages 30: Short-Term Biochemical Biomarkers of Stress in the
           Oyster Magallana angulata Exposed to Gymnodinium catenatum and Skeletonema
           marinoi

    • Authors: Rui Cereja, Joana P. C. Cruz, Joshua Heumüller, Bernardo Vicente, Ana Amorim, Frederico Carvalho, Sara Cabral, Paula Chainho, Ana C. Brito, Inês J. Ferreira, Mário Diniz
      First page: 30
      Abstract: Bivalves accumulate toxins produced by microalgae, thus becoming harmful for humans. However, little information is available about their toxicity to the bivalve itself. In the present work, the physiological stress and damage after the ingestion of toxic dinoflagellate species (Gymnodinium catenatum) and a diatom species (Skeletonema marinoi, which is non-toxic to humans but may be to grazers) in the oyster Magallana angulata are evaluated against a control treatment fed with the chlorophyte Tetraselmis sp. Oysters were exposed for two hours to a concentration of 4 × 104 cells/L of G. catenatum and 2 × 107 cells/L of S. marinoi. The biomarkers superoxide dismutase (SOD), catalase (CAT), glutathione S-Transferase, total Ubiquitin (Ubi) and Acetylcholinesterase (AchE) were assessed. The exposure of M. angulata to G. catenatum lead to a reduction in SOD and AchE activity and ubiquitin concentrations when compared to the control treatment. Moreover, it increased CAT activity in the adductor muscle, and maintained its activity in the other tissues tested. This may be related to the combination of reduced metabolism with the deployment of detoxification processes. S. marinoi also lead to a decrease in all biomarkers tested in the gills and digestive glands. Therefore, both species tested caused physiological alterations in M. angulata after two hours of exposure.
      Citation: Sci
      PubDate: 2023-07-17
      DOI: 10.3390/sci5030030
      Issue No: Vol. 5, No. 3 (2023)
       
  • Sci, Vol. 5, Pages 31: Artificial Neural Networks in Membrane Bioreactors:
           A Comprehensive Review—Overcoming Challenges and Future Perspectives
           

    • Authors: Zacharias Frontistis, Grigoris Lykogiannis, Anastasios Sarmpanis
      First page: 31
      Abstract: Among different biological methods used for advanced wastewater treatment, membrane bioreactors have demonstrated superior efficiency due to their hybrid nature, combining biological and physical processes. However, their efficient operation and control remain challenging due to their complexity. This comprehensive review summarizes the potential of artificial neural networks (ANNs) to monitor, simulate, optimize, and control these systems. ANNs show a unique ability to reveal and simulate complex relationships of dynamic systems such as MBRs, allowing for process optimization and fault detection. This early warning system leads to increased reliability and performance. Integrating ANNs with advanced algorithms and implementing Internet of Things (IoT) devices and new-generation sensors has the potential to transform the advanced wastewater treatment landscape towards the development of smart, self-adaptive systems. Nevertheless, several challenges must be addressed, including the need for high-quality and large-quantity data, human resource training, and integration into existing control system facilities. Since the demand for advanced water treatment and water reuse will continue to expand, proper implementation of ANNs, combined with other AI tools, is an exciting strategy toward the development of integrated and efficient advanced water treatment schemes.
      Citation: Sci
      PubDate: 2023-08-15
      DOI: 10.3390/sci5030031
      Issue No: Vol. 5, No. 3 (2023)
       
  • Sci, Vol. 5, Pages 32: An Analysis of the Convergence Problem of a
           Function in Functional Norms by Applying the Generalized
           Nörlund-Matrix Product Operator

    • Authors: Hari M. Srivastava, Hare K. Nigam, Swagata Nandy
      First page: 32
      Abstract: In this paper, we analyze the convergence problems of function g of Fourier series in Besov and generalized Zygmund norms using generalized Nörlund-Matrix (Np,qA) means of Fourier series. Convergence results are also compared by means of applications.
      Citation: Sci
      PubDate: 2023-08-22
      DOI: 10.3390/sci5030032
      Issue No: Vol. 5, No. 3 (2023)
       
  • Sci, Vol. 5, Pages 33: Development of a Semi-Empirical Model for
           Estimating the Efficiency of Thermodynamic Power Cycles

    • Authors: Evangelos Bellos
      First page: 33
      Abstract: Power plants constitute the main sources of electricity production, and the calculation of their efficiency is a critical factor that is needed in energy studies. The efficiency improvement of power plants through the optimization of the cycle is a critical means of reducing fuel consumption and leading to more sustainable designs. The goal of the present work is the development of semi-empirical models for estimating the thermodynamic efficiency of power cycles. The developed model uses only the lower and the high operating temperature levels, which makes it flexible and easily applicable. The final expression is found by using the literature data for different power cycles, named as: organic Rankine cycles, water-steam Rankine cycles, gas turbines, combined cycles and Stirling engines. According to the results, the real operation of the different cases was found to be a bit lower compared to the respective endoreversible cycle. Specifically, the present global model indicates that the thermodynamic efficiency is a function of the temperature ratio (low cycle temperature to high cycle temperature). The suggested equation can be exploited as a quick and accurate tool for calculating the thermodynamic efficiency of power plants by using the operating temperature levels. Moreover, separate equations are provided for all of the examined thermodynamic cycles.
      Citation: Sci
      PubDate: 2023-08-24
      DOI: 10.3390/sci5030033
      Issue No: Vol. 5, No. 3 (2023)
       
  • Sci, Vol. 5, Pages 34: The Additional Diagnostic Value of
           Electrocardiogram and Strain Patterns in Transplanted Patients

    • Authors: Laura Stefani, Goffredo Orlandi, Marco Corsi, Edoardo Falconi, Roberto Palazzo, Alessio Pellegrino, Pietro Amedeo Modesti
      First page: 34
      Abstract: Background: Transplanted patients are frail individuals who may be affected by diastolic dysfunction, leading to a decrease in exercise tolerance. Previous studies have reported that certain ECG and echocardiographic parameters (such as the P-wave interval, PQ interval, P-wave dispersion, Tend-P interval, QTc interval, and strain) can support the diagnosis of diastolic dysfunction when the ejection fraction is preserved. This study aimed to examine the potential diagnostic contribution of specific ECG and deformation parameters in transplanted recipients, who are at a high risk of heart failure. Materials and Methods: A group of 33 transplanted subjects (17 renal and 16 liver) were categorized using two scores for heart failure with preserved ejection fraction (HFpEF). Additionally, they underwent evaluation based on ECG parameters (P-wave interval, PQ interval, Pwave dispersion, and Tend-P QTc) and echocardiographic deformation parameters (strain and twist). The Student’s t-test was used for statistical analysis. Results: The two scores identified different numbers of excludable and not excludable subjects potentially affected by HFpEF. The not excludable group presented ECG parameters with significantly higher values (P-wave, PQ interval, posterior wall diastole, and Tend-P, all with p ≤ 0.05) and significantly lower 4D strain and twist values (p < 0.05) Conclusions: There is evidence for a significant diagnostic contribution of additional ECG and echo strain parameters in an early phase of diastolic dysfunction in subjects potentially affected by HFpEF.
      Citation: Sci
      PubDate: 2023-08-25
      DOI: 10.3390/sci5030034
      Issue No: Vol. 5, No. 3 (2023)
       
  • Sci, Vol. 5, Pages 35: On Hens, Eggs, Temperatures and CO2: Causal Links
           in Earth’s Atmosphere

    • Authors: Demetris Koutsoyiannis, Christian Onof, Zbigniew W. Kundzewicz, Antonis Christofides
      First page: 35
      Abstract: The scientific and wider interest in the relationship between atmospheric temperature (T) and concentration of carbon dioxide ([CO2]) has been enormous. According to the commonly assumed causality link, increased [CO2] causes a rise in T. However, recent developments cast doubts on this assumption by showing that this relationship is of the hen-or-egg type, or even unidirectional but opposite in direction to the commonly assumed one. These developments include an advanced theoretical framework for testing causality based on the stochastic evaluation of a potentially causal link between two processes via the notion of the impulse response function. Using, on the one hand, this framework and further expanding it and, on the other hand, the longest available modern time series of globally averaged T and [CO2], we shed light on the potential causality between these two processes. All evidence resulting from the analyses suggests a unidirectional, potentially causal link with T as the cause and [CO2] as the effect. That link is not represented in climate models, whose outputs are also examined using the same framework, resulting in a link opposite the one found when the real measurements are used.
      Citation: Sci
      PubDate: 2023-09-13
      DOI: 10.3390/sci5030035
      Issue No: Vol. 5, No. 3 (2023)
       
  • Sci, Vol. 5, Pages 36: A Sensitive Strain Sensor Based on Multi-Walled
           Carbon Nanotubes/Polyaniline/Silicone Rubber Nanocomposite for Human
           Motion Detection

    • Authors: Seyedmajid Hosseini, Mohsen Norouzi, Jian Xu
      First page: 36
      Abstract: Strain sensors play a pivotal role in quantifying stress and strain across diverse domains, encompassing engineering, industry, and medicine. Their applicability has recently extended into the realm of wearable electronics, enabling real-time monitoring of body movements. However, conventional strain sensors, while extensively employed, grapple with limitations such as diminished sensitivity, suboptimal tensile strength, and susceptibility to environmental factors. In contrast, polymer-based composite strain sensors have gained prominence for their capability to surmount these challenges. The integration of carbon nanotubes (CNTs) as reinforcing agents within the polymer matrix ushers in a transformative era, bolstering mechanical strength, electrical conductivity, and thermal stability. This study comprises three primary components: simulation, synthesis of nanocomposites for strain sensor fabrication, and preparation of a comprehensive measurement set for testing purposes. The fabricated strain sensors, incorporating a robust polymer matrix of polyaniline known for its exceptional conductivity and reinforced with carbon nanotubes as strengthening agents, demonstrate good characteristics, including a high gauge factor, stability, and low hysteresis. Moreover, they exhibit high strain sensitivity and show linearity in resistance changes concerning applied strain. Comparative analysis reveals that the resulting gauge factors for composite strain sensors consisting of carbon nanotubes/polyaniline and carbon nanotubes/polyaniline/silicone rubber are 144.5 and 167.94, respectively.
      Citation: Sci
      PubDate: 2023-09-20
      DOI: 10.3390/sci5030036
      Issue No: Vol. 5, No. 3 (2023)
       
  • Sci, Vol. 5, Pages 14: Clustering Analysis on Sustainable Development Goal
           Indicators for Forty-Five Asian Countries

    • Authors: Anuradha Mathrani, Jian Wang, Ding Li, Xuanzhen Zhang
      First page: 14
      Abstract: This paper draws upon the United Nations 2022 data report on the achievement of Sustainable Development Goals (SDGs) across the following four dimensions: economic, social, environmental and institutional. Ward’s method was applied to obtain clustering results for forty-five Asian countries to understand their level of progress and overall trends in achieving SDGs. We identified varying degrees of correlation between the four dimensions. The results show that East Asian countries performed poorly in the economic dimension, while some countries in Southeast Asia and Central and West Asia performed relatively well. Regarding social and institutional dimensions, the results indicate that East and Central Asian countries performed relatively better than others. Finally, in the environmental dimension, West and South Asian countries showed better performance than other Asian countries. The insights gathered from this study can inform policymakers of these countries about their own country’s position in achieving SDGs in relation to other Asian countries, as they work towards establishing strategies for improving their sustainable development targets.
      Citation: Sci
      PubDate: 2023-03-28
      DOI: 10.3390/sci5020014
      Issue No: Vol. 5, No. 2 (2023)
       
  • Sci, Vol. 5, Pages 15: A One-Dimensional Blocking Index Becomes
           Two-Dimensional Using GIS Technology

    • Authors: Eli D. Ethridge, Bahtiyar Efe, Anthony R. Lupo
      First page: 15
      Abstract: Many previous studies of the occurrence of blocking anticyclones, their characteristics, and dynamics have defined the onset longitude using the one-dimensional zonal index type criterion proposed by Lejenas and Okland. In addition to examining the blocking event itself, the onset longitude was determined to start at the nearest five degrees longitude using the National Centers for Environmental Prediction/National Center for Atmospheric Research Reanalyses that were used to identify the events. In this study, each blocking event in the University of Missouri Blocking Archive was re-examined to identify an onset latitude, and this information was added to the archive. The events were then plotted and displayed on a map of the Northern or Southern Hemisphere using Geographic Information System (GIS) software housed at the University of Missouri as different colored and sized dots according to block intensity and duration, respectively. This allowed for a comparison of blocking events in the archive above to studies that used a two-dimensional index. Then the common onset regions were divided by phase of the El Nino and Southern Oscillation (ENSO), and the typical onset of intense and persistent blocking events could be examined. The results found a favorable comparison between the onset regions identified here and those found in previous studies that used a two-dimensional blocking index. Additionally, there was variability identified in the onset regions of blocking in both hemispheres by ENSO phase, including the location of more intense and persistent events.
      Citation: Sci
      PubDate: 2023-04-03
      DOI: 10.3390/sci5020015
      Issue No: Vol. 5, No. 2 (2023)
       
  • Sci, Vol. 5, Pages 16: Two-Dimensional Model for Consolidation-Induced
           Solute Transport in an Unsaturated Porous Medium

    • Authors: Sheng Wu, Dong-Sheng Jeng
      First page: 16
      Abstract: Solute transport through porous media is usually described by well-established conventional transport models with the ability to account for advection, dispersion, and sorption. In this study, we further extend our previous one-dimensional model for solute transport in an unsaturated porous medium to two dimensions. The present model is based on a small-strain approach. The proposed model is validated with previous work. Both homogeneous landfill and pointed landfill conditions are considered. A detailed parametric study shows the differences between the present model and previous one-dimensional model.
      Citation: Sci
      PubDate: 2023-04-04
      DOI: 10.3390/sci5020016
      Issue No: Vol. 5, No. 2 (2023)
       
  • Sci, Vol. 5, Pages 17: A Modular Structure for Immediate and Transitory
           Interventions to Guarantee Access to Basic Healthcare in Italy

    • Authors: Silvia Brunoro, Lisa Mensi
      First page: 17
      Abstract: The access to basic healthcare for people who are not registered in the national health system is nowadays a very urgent problem, both in Italy and in the rest of the world. Immigration and poverty are only some of the factors that make one of the primary rights of humanity—healthcare—not a right for everyone. The main problems, which have grown exponentially in the last decade, are at operational level, due to the lack of personnel (mostly volunteers) and the lack of spaces. This paper illustrates procedures and techniques for the design of a small emergency structure that can be moved and positioned in urban contexts. The first part consists of a deep analysis of the problem and of the state of the art of existing typologies. The second part is dedicated to the conceptual framework (requirements, conceptual model) and to the definition of the preliminary design for the new approach to basic non-conventional sanitary spaces. Finally, a virtual case study (project application) in Italy is presented.
      Citation: Sci
      PubDate: 2023-04-11
      DOI: 10.3390/sci5020017
      Issue No: Vol. 5, No. 2 (2023)
       
  • Sci, Vol. 5, Pages 18: Analysis of Gun Crimes in New York City

    • Authors: Antonio Sarasa-Cabezuelo
      First page: 18
      Abstract: Violence involving firearms in the USA is a very important problem. As a consequence, a large number of crimes of this type are recorded every year. However, the solutions proposed have not managed to reduce the number of this type of crime. One of the cities with a large number of violent crimes is New York City. The number of crimes is not homogeneous and depends on the district where they occur. This paper proposes to study the information about the crimes in which firearms are involved with the aim of characterizing the factors on which the occurrence of this type of crime depends, such as the levels of poverty and culture. Since the districts are not homogeneous, the information has been analyzed at the district level. For this, data from the open data portal of the city of New York have been used and machine-learning techniques have been used. The results have shown that the variables on which they depend are different in each district.
      Citation: Sci
      PubDate: 2023-04-20
      DOI: 10.3390/sci5020018
      Issue No: Vol. 5, No. 2 (2023)
       
  • Sci, Vol. 5, Pages 19: Depth Analysis of Anesthesia Using EEG Signals via
           Time Series Feature Extraction and Machine Learning

    • Authors: Raghav V. Anand, Maysam F. Abbod, Shou-Zen Fan, Jiann-Shing Shieh
      First page: 19
      Abstract: The term “anesthetic depth” refers to the extent to which a general anesthetic agent sedates the central nervous system with specific strength concentration at which it is delivered. The depth level of anesthesia plays a crucial role in determining surgical complications, and it is imperative to keep the depth levels of anesthesia under control to perform a successful surgery. This study used electroencephalography (EEG) signals to predict the depth levels of anesthesia. Traditional preprocessing methods such as signal decomposition and model building using deep learning were used to classify anesthetic depth levels. This paper proposed a novel approach to classify the anesthesia levels based on the concept of time series feature extraction, by finding out the relation between EEG signals and the bi-spectral Index over a period of time. Time series feature extraction on basis of scalable hypothesis tests were performed to extract features by analyzing the relation between the EEG signals and Bi-Spectral Index, and machine learning models such as support vector classifier, XG boost classifier, gradient boost classifier, decision trees and random forest classifier are used to train the features and predict the depth level of anesthesia. The best-trained model was random forest, which gives an accuracy of 83%. This provides a platform to further research and dig into time series-based feature extraction in this area.
      Citation: Sci
      PubDate: 2023-05-05
      DOI: 10.3390/sci5020019
      Issue No: Vol. 5, No. 2 (2023)
       
  • Sci, Vol. 5, Pages 20: Incidence and Predictors of Soft Tissue Injuries
           during Basic Combat Training

    • Authors: Pantelis T. Nikolaidis, Konstantinos Havenetidis
      First page: 20
      Abstract: Strenuous exercise, such as military training, is known to demand a high degree of physical performance and to cause injuries. The present study aimed to (a) monitor the incidence of soft tissue injuries (blisters, contusions, and lacerations) among cadets during Basic Combat Training (BCT), and (b) identify possible risk factors for these injuries. Participants were 315 first-grade cadets (women, n = 28; men, n = 287), recruited from the Hellenic Army Academy. Seven weeks of BCT resulted in an overall cadet injury rate of 24.1% (n = 76) with 13.7% being injured one time, whereas 10.4% of participants were injured 2–6 times. The incidence of injuries was 2.9 soft tissue injuries per 1000 training hours. The logistic regression model using sex, being an athlete, nationality, weight, height, body mass index, and percentage of body fat (BF) to predict soft tissue injury was not statistically significant (χ2(7) = 5.315, p = 0.622). The results of this study showed that BCT caused a large number of soft tissue injuries similar to the number reported for musculoskeletal injuries. In conclusion, following BCT, soft tissue injury characteristics (occurrence, severity, treatment) are similar to those applied in musculoskeletal injuries for Army cadets. However, risk factors such as sex, nationality, and BF have not been related to soft tissue injury prediction as previously shown for musculoskeletal injuries for the same sample group.
      Citation: Sci
      PubDate: 2023-05-06
      DOI: 10.3390/sci5020020
      Issue No: Vol. 5, No. 2 (2023)
       
  • Sci, Vol. 5, Pages 21: Hoarding Disorder: A Sociological Perspective

    • Authors: Giovanna Ricci, Filippo Gibelli, Paolo Bailo, Anna Maria Caraffa, Maria Angela Casamassima, Ascanio Sirignano
      First page: 21
      Abstract: Hoarding disorder (HD) is a recently recognized psychiatric condition, now classified under the category of obsessive-compulsive and related disorders in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). It leads to an unwarranted attachment to material possessions, such that the individual is unable to separate themselves from them. There is still a lack of awareness of the critical sociological implications of this disorder, which is too often considered a purely health-related issue. This article endeavors to frame hoarding disorder from a unique socio-criminological and legal perspective, proposing an alternative approach to HD that considers it not only as a mental disorder, but also as a genuine societal issue. We also explore potential avenues for protection, considering both the well-being of individuals with this mental disorder and the communities in which individuals suffering from HD reside. This paper presents a fresh perspective on HD, aiming to delineate its impact and significance as an affliction affecting both individuals and society at large.
      Citation: Sci
      PubDate: 2023-05-11
      DOI: 10.3390/sci5020021
      Issue No: Vol. 5, No. 2 (2023)
       
  • Sci, Vol. 5, Pages 22: Digital Factory Transformation from a Servitization
           Perspective: Fields of Action for Developing Internal Smart Services

    • Authors: Jens Neuhüttler, Maximilian Feike, Janika Kutz, Christian Blümel, Bernd Bienzeisler
      First page: 22
      Abstract: In recent years, a complex set of dynamic developments driven by both the economy and the emergence of digital technologies has put pressure on manufacturing companies to adapt. The concept of servitization, i.e., the shift from a product-centric to a service-centric value creation logic, can help manufacturing companies stabilize their business in such volatile times. Existing academic literature investigates the potential and challenges of servitization and the associated development of data-based services, so-called smart services, with a view to external market performance. However, with the increasing use of digital technologies in manufacturing and the development of internal smart services based on them, we argue that the existing insights on external servitization are also of interest for internal transformation. In this paper, we identify key findings from service literature, apply them to digital factory transformation, and structure them into six fields of action along the dimensions of people, technology, and organization. As a result, recommendations for designing digital factory transformation in manufacturing companies are derived from the perspective of servitization and developing internal smart services.
      Citation: Sci
      PubDate: 2023-05-16
      DOI: 10.3390/sci5020022
      Issue No: Vol. 5, No. 2 (2023)
       
  • Sci, Vol. 5, Pages 23: A Survey on EEG Data Analysis Software

    • Authors: Rupak Kumar Das, Anna Martin, Tom Zurales, Dale Dowling, Arshia Khan
      First page: 23
      Abstract: Electroencephalography (EEG) is a mechanism to understand the brain’s functioning by analyzing brain electrical signals. More recently, it has been more commonly used in studies that are focused on the causation and effect of dementia. More tools are now available to gather EEG data. This brings about the challenge of understanding brain signals, which involves signal processing. Professionals with an electrical engineering background are very comfortable analyzing EEG data. Still, scientists in computer science and related fields need a source that can identify all the tools available and the process of analyzing the data. This paper deals specifically with the existing EEG data analysis tools and the processes involved in analyzing the EEG data using these tools. Furthermore, the paper goes in-depth into identifying the tools and the mechanisms of data processing techniques. In addition, it lists a set of definitions required for a better understanding of EEG data analysis, which can be challenging. The purpose of this paper is to serve as a reference for not only scientists that are new to EEG data analysis but also seasoned scientists that are looking for a specific data component in EEG and can go straight to the section of the paper that deals with the tool that they are using.
      Citation: Sci
      PubDate: 2023-06-01
      DOI: 10.3390/sci5020023
      Issue No: Vol. 5, No. 2 (2023)
       
  • Sci, Vol. 5, Pages 24: Assessment of Spatial Variations in Pesticide,
           Heavy Metal, and Selenium Residues in Honey Bee (Apis mellifera L.)
           Products

    • Authors: Mai M. Awad, Randall B. Boone
      First page: 24
      Abstract: Apis mellifera L. is considered one of the most important pollinators in nature. Unfortunately, in addition to other insect species, honey bee populations are decreasing at an alarming rate, urging researchers to investigate the causes and stressors that precipitated this decline. This study focuses on chemical stressors that are found to affect bee populations. We used pollen and honey samples to examine the variations in pesticides, selenium, and heavy metals in two different landscapes: urban and agricultural areas of northeastern Colorado, USA. Subsequently, we extrapolated the risks of these toxins’ residues to Apis spp. Based on the current literature, we found no spatial variations in metal and selenium concentrations in the pollen and honey samples collected from urban and agricultural areas. Moreover, we observed no spatial variations in pesticide concentrations in pollen and honey samples. Based on the previous literature and a comparison of the residues of heavy metals, selenium, and pesticides in our pollen and honey samples, we found that the heavy metal and selenium residues in some honey and pollen likely pose a severe health risk to honey bees. Although the levels of pesticide residues were below the documented thresholds of risk, we consider the possibility of synergistic chemical impacts. Our findings support future efforts to investigate the health risks associated with multiple-factor combinations.
      Citation: Sci
      PubDate: 2023-06-06
      DOI: 10.3390/sci5020024
      Issue No: Vol. 5, No. 2 (2023)
       
  • Sci, Vol. 5, Pages 25: Conventional Platinum Metal Implants Provoke
           Restenosis Responses in Atherogenic but Not Healthy Arteries

    • Authors: Lea M. Morath, Roger J. Guillory, Alexander A. Oliver, Shu Q. Liu, Martin L. Bocks, Galit Katarivas Levy, Jaroslaw W. Drelich, Jeremy Goldman
      First page: 25
      Abstract: Platinum-containing stents are commonly used in humans with hypercholesterolemia, whereas preclinical stent evaluation has commonly been performed in healthy animal models, providing inadequate information about stent performance under hypercholesterolemic conditions. In this investigation, we used an ApoE−/− mouse model to test the impact of hypercholesterolemia on neointima formation on platinum-containing implants. We implanted 125 μm diameter platinum wires into the abdominal aortas of ApoE−/− and ApoE+/+ mice for 6 months, followed by histological and immunofluorescence examination of neointimal size and composition. It was found that ApoE−/− mice developed neointimas with four times larger area and ten times greater thickness than ApoE+/+ counterparts. Neointimas developed in the ApoE−/− mice also contained higher amounts of lipids quantified as having 370 times more coverage compared to ApoE+/+, a 3-fold increase in SMCs, and a 22-fold increase in macrophages. A confluent endothelium had regenerated in both mouse strains. The ApoE−/− mice experienced luminal reductions more closely resembling clinically relevant restenosis in humans. Overall, the response to platinum arterial implants was highly dependent upon the atherogenic environment.
      Citation: Sci
      PubDate: 2023-06-19
      DOI: 10.3390/sci5020025
      Issue No: Vol. 5, No. 2 (2023)
       
  • Sci, Vol. 5, Pages 1: Financial Feasibility of Harvesting Rainwater from
           Permeable Pavements: A Case Study in a City Square

    • Authors: Caio Wolf Klein, Jéssica Kuntz Maykot, Enedir Ghisi, Liseane Padilha Thives
      First page: 1
      Abstract: The objective of this study was to carry out the financial feasibility analysis of harvesting rainwater from permeable pavements in a city square. A case study was carried out in a square close to the beach in the city of Florianópolis, Brazil. Questionnaires were applied to pedestrians who circulate within the area. The square is to be implemented to promote sustainability and improve the user’s quality of life. From the rainfall data and the average daily water demand for irrigation of the square vegetation, the volume of rainwater to be harvested from the permeable pavement was calculated. The rainwater demand was estimated as 662 L/day. The implementation and operation costs of the pavement and irrigation systems were evaluated. The potential for potable water savings was 89.8%. The payback period was estimated as 347 months. This study showed that rainwater collected from permeable pavements is financially feasible and represents a promising technique.
      Citation: Sci
      PubDate: 2023-01-03
      DOI: 10.3390/sci5010001
      Issue No: Vol. 5, No. 1 (2023)
       
  • Sci, Vol. 5, Pages 2: Yield and Composition Variations of the Milk from
           Different Camel Breeds in Saudi Arabia

    • Authors: Amr A. El-Hanafy, Yasser M. Saad, Saleh A. Alkarim, Hussein A. Almehdar, Fuad M. Alzahrani, Mohammed A. Almatry, Vladimir N. Uversky, Elrashdy M. Redwan
      First page: 2
      Abstract: With the increasing interest in the identification of differences between camel breeds over the last decade, this study was conducted to estimate the variability of milk production and composition of four Saudi camel breeds during different seasons. Milk records were taken two days per week from females of Majahem, Safra, Wadha, and Hamra breeds distributed over Saudi Arabia. The milk yield during winter indicated that the weekly average of the Wadha breed was significantly lower (27.13 kg/week) than Majahem and Hamra breeds. The Safra breed had the lowest milk yield (30.7 kg/week) during summer. During winter, the Hamra breed had a lower content of all analyzed milk components except proteins and was characterized by a lower pH than the milk of the other breeds. However, the Hamra breed had significantly higher contents of milk fat and lactose than the other breeds during summer, with the corresponding values of 3.87 and 4.86%, respectively. Milk collected during winter from Majahem, Safra, and Wadha breeds was characterized by a significant increase in all milk components and milk pH. Finally, the isoelectric focusing analysis revealed noticeable variability of casein purified from camel milk within the different Saudi breeds, with the highest significant value of 2.29 g per 100 mL recorded for the Wadha breed.
      Citation: Sci
      PubDate: 2023-01-06
      DOI: 10.3390/sci5010002
      Issue No: Vol. 5, No. 1 (2023)
       
  • Sci, Vol. 5, Pages 3: The Impact of Trap-Assisted Tunneling and
           Poole–Frenkel Emission on Synaptic Potentiation in an
           α-Fe2O3/p-Si Memristive Device

    • Authors: Punya Mainali, Phadindra Wagle, Chasen McPherson, David. N. McIlroy
      First page: 3
      Abstract: A signature of synaptic potentiation conductance has been observed in an α-Fe2O3/p-Si device fabricated using spin coating. The conductance of the device in dark conditions and illumination with a white light source was characterized as a function of the application of a periodic bias (voltage) with a triangular profile. The conductance of the device increases with the number of voltage cycles applied and plateaus to its maximum value of 0.70 μS under dark conditions and 12.00 μS under illumination, and this mimics the analog synaptic weight change with the action potential of a neuron. In the range of applied voltage from 0 V to 0.7 V, the conduction mechanism corresponds to trap-assisted tunneling (TAT) and in the range of 0.7–5 V it corresponds to the Poole–Frenkel emission (PFE). The conductance as a function of electrical pulses was fitted with a Hill function, which is a measure of cooperation in biological systems. In this case, it allows one to determine the turn-on threshold (K) of the device in terms of the number of voltage pulses, which are found to be 3 and 166 under dark and illumination conditions, respectively. The gradual conductance change and activation after a certain number of pulses perfectly mimics the synaptic potentiation of neurons. In addition, the threshold parameter extracted from the Hill equation fit, acting as the number of pulses for synaptic activation, is found to have programmability with the intensity of the light illumination.
      Citation: Sci
      PubDate: 2023-01-12
      DOI: 10.3390/sci5010003
      Issue No: Vol. 5, No. 1 (2023)
       
  • Sci, Vol. 5, Pages 4: Acknowledgment to the Reviewers of Sci in 2022

    • Authors: Sci Editorial Office Sci Editorial Office
      First page: 4
      Abstract: High-quality academic publishing is built on rigorous peer review [...]
      Citation: Sci
      PubDate: 2023-01-18
      DOI: 10.3390/sci5010004
      Issue No: Vol. 5, No. 1 (2023)
       
  • Sci, Vol. 5, Pages 5: Socioconnectomics: Connectomics Should Be Extended
           to Societies to Better Understand Evolutionary Processes

    • Authors: Cédric Sueur
      First page: 5
      Abstract: Connectomics, which is the network study of connectomes or maps of the nervous system of an organism, should be applied and expanded to human and animal societies, resulting in the birth of the domain of socioconnectomics compared to neuroconnectomics. This new network study framework would open up new perspectives in evolutionary biology and add new elements to theories, such as the social and cultural brain hypotheses. Answering questions about network topology, specialization, and their connections with functionality at one level (i.e., neural or societal) may help in understanding the evolutionary trajectories of these patterns at the other level. Expanding connectomics to societies should be done in comparison and combination with multilevel network studies and the possibility of multiorganization selection processes. The study of neuroconnectomes and socioconnectomes in animals, from simpler to more advanced ones, could lead to a better understanding of social network evolution and the feedback between social complexity and brain complexity.
      Citation: Sci
      PubDate: 2023-01-30
      DOI: 10.3390/sci5010005
      Issue No: Vol. 5, No. 1 (2023)
       
  • Sci, Vol. 5, Pages 6: Explaining Personal and Public Pro-Environmental
           Behaviors

    • Authors: Philip Q. Yang, Michaela LaNay Wilson
      First page: 6
      Abstract: A global crisis generated by human-made climate change has added urgency to the need to fully understand human pro-environmental behaviors (PEBs) that may help slow down the crisis. Factors influencing personal and public PEBs may or may not be the same. Only a few studies have empirically investigated the determinants of personal and public PEBs simultaneously, but they contain major limitations with mixed results. This study develops a conceptual model for explaining both personal and public PEBs that incorporate demographic, socioeconomic, political, and attitudinal variables, and their direct and indirect effects. Using the latest available data from the 2010 General Social Survey and structural equation modeling (SEM), we tested the determinants of both personal and public PEBs in the United States. The results reveal that environmental concerns, education, and political orientation demonstrate similar significant impacts on both personal and public PEBs, but income, gender, race, urban/rural residency, region, and party affiliation have differential effects on these behaviors. Age, cohort, and religion have no significant effect on both types of behaviors. Our results confirm some existing findings; however, they challenge the findings of much of the literature.
      Citation: Sci
      PubDate: 2023-02-07
      DOI: 10.3390/sci5010006
      Issue No: Vol. 5, No. 1 (2023)
       
  • Sci, Vol. 5, Pages 7: Make a Stand(ard) for Science

    • Authors: Ahmad Yaman Abdin, Claus Jacob
      First page: 7
      Abstract: During the global Corona pandemic, the validity of science has been challenged by sections of the public, often for political gains [...]
      Citation: Sci
      PubDate: 2023-02-09
      DOI: 10.3390/sci5010007
      Issue No: Vol. 5, No. 1 (2023)
       
  • Sci, Vol. 5, Pages 8: Multi-Lexicon Classification and Valence-Based
           Sentiment Analysis as Features for Deep Neural Stock Price Prediction

    • Authors: Shubashini Rathina Velu, Vinayakumar Ravi, Kayalvily Tabianan
      First page: 8
      Abstract: The goal of the work is to enhance existing financial market forecasting frameworks by including an additional factor–in this example, a collection of carefully chosen tweets—into a long-short repetitive neural channel. In order to produce attributes for such a forecast, this research used a unique attitude analysis approach that combined psychological labelling and a valence rating that represented the strength of the sentiment. Both lexicons produced extra properties such 2-level polarization, 3-level polarization, gross reactivity, as well as total valence. The emotional polarity explicitly marked into the database contrasted well with outcomes of the innovative lexicon approach. Plotting the outcomes of each of these concepts against actual market rates of the equities examined has been the concluding step in this analysis. Root Mean Square Error (RMSE), preciseness, as well as Mean Absolute Percentage Error (MAPE) were used to evaluate the results. Across most instances of market forecasting, attaching an additional factor has been proven to reduce the RMSE and increase the precision of forecasts over lengthy sequences.
      Citation: Sci
      PubDate: 2023-02-15
      DOI: 10.3390/sci5010008
      Issue No: Vol. 5, No. 1 (2023)
       
  • Sci, Vol. 5, Pages 9: Industry 4.0: Options for Human-Oriented Work Design

    • Authors: Hartmut Hirsch-Kreinsen
      First page: 9
      Abstract: This contribution deals with the diffusion of Industry 4.0 technologies and their consequences for work. Additionally, design options for work in Industry 4.0 are discussed. The following are outlined: First, since there are as yet no concrete future prospects for digital work, different development perspectives can be envisioned. Second, the development of Industry 4.0, therefore, has to be regarded as a design project. One theoretical basis for this is the “sociotechnical systems” approach. Third, this approach enables criteria for the design and implementation of human-oriented forms of digitized work to be systematically developed. The empirical basis of this contribution derives from research findings on the implementation of Industry 4.0 technologies and the development of digitized work in German industry. The research results are based on qualitative research methods such as company case studies and expert interviews.
      Citation: Sci
      PubDate: 2023-02-15
      DOI: 10.3390/sci5010009
      Issue No: Vol. 5, No. 1 (2023)
       
  • Sci, Vol. 5, Pages 10: A Dual Multimodal Biometric Authentication System
           Based on WOA-ANN and SSA-DBN Techniques

    • Authors: Sandeep Pratap Singh, Shamik Tiwari
      First page: 10
      Abstract: Identity management describes a problem by providing the authorized owners with safe and simple access to information and solutions for specific identification processes. The shortcomings of the unimodal systems have been addressed by the introduction of multimodal biometric systems. The use of multimodal systems has increased the biometric system’s overall recognition rate. A new degree of fusion, known as an intelligent Dual Multimodal Biometric Authentication Scheme, is established in this study. In the proposed work, two multimodal biometric systems are developed by combining three unimodal biometric systems. ECG, sclera, and fingerprint are the unimodal systems selected for this work. The sequential model biometric system is developed using a decision-level fusion based on WOA-ANN. The parallel model biometric system is developed using a score-level fusion based on SSA-DBN. The biometric authentication performs preprocessing, feature extraction, matching, and scoring for each unimodal system. On each biometric attribute, matching scores and individual accuracy are cyphered independently. A matcher performance-based fusion procedure is demonstrated for the three biometric qualities because the matchers on these three traits produce varying values. The two-level fusion technique (score and feature) is implemented separately, and their results with the current scheme are compared to exhibit the optimum model. The suggested plan makes use of the highest TPR, FPR, and accuracy rates.
      Citation: Sci
      PubDate: 2023-03-01
      DOI: 10.3390/sci5010010
      Issue No: Vol. 5, No. 1 (2023)
       
  • Sci, Vol. 5, Pages 11: The Digital Calibration Certificate (DCC) for an
           End-to-End Digital Quality Infrastructure for Industry 4.0

    • Authors: Siegfried Hackel, Shanna Schönhals, Lutz Doering, Thomas Engel, Reinhard Baumfalk
      First page: 11
      Abstract: This article depicts the role of the Digital Calibration Certificate (DCC) for an end-to-end digital quality infrastructure and as the basis for developments that are designated by the keyword “Industry 4.0”. Furthermore, it describes the impact the DCC has on increasing productivity in the manufacturing of products and in global trade. The DCC project is international in its scope. Calibration certificates document the measurement capability of a measurement system. They do this independently and by providing traceability to measurement standards. Therefore, they do not only play an important role in the world of metrology, but they also make it possible for manufacturing and commercial enterprises to exchange measurement values reliably and correctly at the national and at the international level. Thus, a DCC concept is urgently needed for the end-to-end digitalization of industry for the era of Industry 4.0 and for Medicine 4.0. A DCC brings about important advantages for issuers and for users. The DCC leads to the stringent, end-to-end, traceable and process-oriented organization of manufacturing and trading. Digitalization is thus a key factor in the field of calibration as it enables significant improvements in product and process quality. The reason for this is that the transmission of errors will be prevented, and consequently, costs will be saved as the time needed for distributing and disseminating the DCCs and the respective calibration objects will be reduced. Furthermore, it will no longer be necessary for the test equipment administration staff to update the data manually, which is a time-consuming, tedious and error-prone process.
      Citation: Sci
      PubDate: 2023-03-06
      DOI: 10.3390/sci5010011
      Issue No: Vol. 5, No. 1 (2023)
       
  • Sci, Vol. 5, Pages 12: Exercise Testing and Motivation

    • Authors: Pantelis T. Nikolaidis
      First page: 12
      Abstract: Exercise testing has important applications for sport, exercise and clinical settings, providing valuable information for exercise prescription and diagnostics for health purposes. Often, exercise testing includes the participant’s maximal effort, and the testing score partially depends on whether the maximal effort has been exerted. In this context, motivation in exercise testing, including verbal encouragement and video presentation, plays a vital role in assessing participants. Professionals involved in exercise testing, such as exercise physiologists and sport scientists, should be aware of motivation’s role in performance during laboratory or field testing, especially using verbal encouragement. Motivation during exercise testing should be standardized and fully described in testing protocols. In this way, exercise testing would provide valid and reliable results for exercise prescription or other purposes (e.g., sport talent identification, athletes’ selection, education, research and rehabilitation).
      Citation: Sci
      PubDate: 2023-03-07
      DOI: 10.3390/sci5010012
      Issue No: Vol. 5, No. 1 (2023)
       
  • Sci, Vol. 5, Pages 13: Review on Alzheimer Disease Detection Methods:
           Automatic Pipelines and Machine Learning Techniques

    • Authors: Amar Shukla, Rajeev Tiwari, Shamik Tiwari
      First page: 13
      Abstract: Alzheimer’s Disease (AD) is becoming increasingly prevalent across the globe, and various diagnostic and detection methods have been developed in recent years. Several techniques are available, including Automatic Pipeline Methods and Machine Learning Methods that utilize Biomarker Methods, Fusion, and Registration for multimodality, to pre-process medical scans. The use of automated pipelines and machine learning systems has proven beneficial in accurately identifying AD and its stages, with a success rate of over 95% for single and binary class classifications. However, there are still challenges in multi-class classification, such as distinguishing between AD and MCI, as well as sub-stages of MCI. The research also emphasizes the significance of using multi-modality approaches for effective validation in detecting AD and its stages.
      Citation: Sci
      PubDate: 2023-03-21
      DOI: 10.3390/sci5010013
      Issue No: Vol. 5, No. 1 (2023)
       
 
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  Subjects -> SCIENCES: COMPREHENSIVE WORKS (Total: 374 journals)
Showing 201 - 265 of 265 Journals sorted by number of followers
Quantum Science and Technology     Hybrid Journal   (Followers: 19)
Logo STI Science, Technology and Innovation     Open Access   (Followers: 15)
Alfarama Journal of Basic & Applied Sciences     Open Access   (Followers: 12)
Patterns     Open Access   (Followers: 9)
The Innovation     Open Access   (Followers: 8)
Revista de la Sociedad Científica del Paraguay     Open Access   (Followers: 7)
Research     Open Access   (Followers: 6)
RAC: Revista Angolana de Ciências     Open Access   (Followers: 6)
Advanced Theory and Simulations     Hybrid Journal   (Followers: 5)
Frontiers in Climate     Open Access   (Followers: 5)
Discover Sustainability     Open Access   (Followers: 5)
Proceedings of the Indian National Science Academy     Full-text available via subscription   (Followers: 5)
International Journal of Culture and Modernity     Open Access   (Followers: 5)
History of Science and Technology     Open Access   (Followers: 5)
Data     Open Access   (Followers: 4)
Science & Technology Studies     Open Access   (Followers: 4)
Journal of the Indian Institute of Science     Hybrid Journal   (Followers: 4)
Journal of Big History     Open Access   (Followers: 4)
MUST : Journal of Mathematics Education, Science and Technology     Open Access   (Followers: 4)
Journal of Composites Science     Open Access   (Followers: 4)
People and Nature     Open Access   (Followers: 4)
Middle European Scientific Bulletin     Open Access   (Followers: 4)
Citizen Science : Theory and Practice     Open Access   (Followers: 3)
Research Policy : X     Open Access   (Followers: 3)
Revista Saber Digital     Open Access   (Followers: 3)
iScience     Open Access   (Followers: 2)
Applied Mathematics and Nonlinear Sciences     Open Access   (Followers: 2)
Acta Nova     Open Access   (Followers: 2)
Indonesian Journal of Science and Mathematics Education     Open Access   (Followers: 2)
Rekayasa     Open Access   (Followers: 2)
Indian Journal of History of Science     Hybrid Journal   (Followers: 2)
Jaunujų mokslininkų darbai     Open Access   (Followers: 2)
Journal of Alasmarya University     Open Access   (Followers: 2)
BJHS Themes     Open Access   (Followers: 2)
Orbis Cógnita : Revista Científica     Open Access   (Followers: 2)
Revista Científica de la Universidad Nacional del Este     Open Access   (Followers: 2)
Scientific Bulletin     Open Access   (Followers: 1)
Global Journal of Science Frontier Research     Open Access   (Followers: 1)
Impact     Open Access   (Followers: 1)
International Journal of Research in Science     Open Access   (Followers: 1)
Journal of Science and Technology     Open Access   (Followers: 1)
Uluslararası Bilimsel Araştırmalar Dergisi (IBAD)     Open Access   (Followers: 1)
Acta Scientifica Malaysia     Open Access   (Followers: 1)
Scientonomy : Journal for the Science of Science     Open Access   (Followers: 1)
Revista Vivências em Ensino de Ciências     Open Access   (Followers: 1)
PENDIPA : Journal of Science Education     Open Access   (Followers: 1)
Journal of Science and Engineering     Open Access   (Followers: 1)
International Journal of Innovative Research and Scientific Studies     Open Access   (Followers: 1)
Futures & Foresight Science     Hybrid Journal   (Followers: 1)
Journal of Scientific Research and Reports     Open Access   (Followers: 1)
AAS Open Research     Open Access   (Followers: 1)
ARPHA Conference Abstracts     Open Access   (Followers: 1)
Rihan Journal for Scientific Publishing     Open Access   (Followers: 1)
Experimental Results     Open Access   (Followers: 1)
Natural Sciences Education     Hybrid Journal   (Followers: 1)
South American Sciences     Open Access   (Followers: 1)
International Science and Technology Journal of Namibia     Open Access   (Followers: 1)
Fundamental Research     Open Access  
Research Integrity and Peer Review     Open Access  
Journal of Responsible Technology     Open Access  
Natural Sciences     Open Access  
Türk Bilim ve Mühendislik Dergisi     Open Access  
ArtefaCToS : Revista de estudios sobre la ciencia y la tecnología     Open Access  
Ethiopian Journal of Sciences and Sustainable Development     Open Access  
Vilnius University Proceedings     Open Access  
Sciential     Open Access  
ARPHA Proceedings     Open Access  
Gaudium Sciendi     Open Access  
Crea Ciencia Revista Científica     Open Access  
Rafidain Journal of Science     Open Access  
Journal of Al-Qadisiyah for Pure Science     Open Access  
Revista Tecnológica     Open Access  
Himalayan Journal of Science and Technology     Open Access  
International Journal of Academic Research in Business, Arts & Science     Open Access  
Universidad, Ciencia y Tecnología     Open Access  
Fides et Ratio : Revista de Difusión Cultural y Científica     Open Access  
Revista de la Academia Colombiana de Ciencias Exactas, Físicas y Naturales     Open Access  
Entre Ciencia e Ingeniería     Open Access  
Revista Politécnica     Open Access  
Reportes Científicos de la FaCEN     Open Access  
Jurnal Ilmiah Ilmu Terapan Universitas Jambi : JIITUJ     Open Access  
Revista Eletrônica Ludus Scientiae     Open Access  
Emergent Scientist     Open Access  
Asian Journal of Advanced Research and Reports     Open Access  
Archives of Current Research International     Open Access  
Advances in Research     Open Access  
International Journal of Applied Science     Open Access  
Iranian Journal of Science and Technology, Transactions A : Science     Hybrid Journal  
J : Multidisciplinary Scientific Journal     Open Access  
Revista Binacional Brasil - Argentina: Diálogo entre as ciências     Open Access  
Revista Ciencia y Tecnología     Open Access  
Journal of Institute of Science and Technology     Open Access  
Journal of Science (JSc)     Open Access  
WikiJournal of Science     Open Access  
Acta Materialia Transilvanica     Open Access  
Integrated Research Advances     Open Access  
Open Conference Proceedings Journal     Open Access  
Naturen     Full-text available via subscription  
Ekaia : EHUko Zientzia eta Teknologia aldizkaria     Open Access  
Sci     Open Access  
Maskana     Open Access  
Hoosier Science Teacher     Open Access  
Reports in Advances of Physical Sciences     Open Access  
Facets     Open Access  
Adıyaman University Journal of Science     Open Access  
Revista Brasileira de Iniciação Científica     Open Access  
Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering     Open Access  
Scientific African     Open Access  
Scientific Journal of Mehmet Akif Ersoy University     Open Access  
Black Sea Journal of Engineering and Science     Open Access  
Fırat University Turkish Journal of Science & Technology     Open Access  
Gazi University Journal of Science     Open Access  
Middle East Journal of Science     Open Access  
International Journal of Computational and Experimental Science and Engineering (IJCESEN)     Open Access  
International Journal of Engineering, Technology and Natural Sciences     Open Access  
Bulletin of the National Research Centre     Open Access  
Uni-pluriversidad     Open Access  
ConCiencia     Open Access  
Ciencia y Tecnología     Open Access  
Revista Bases de la Ciencia     Open Access  
Elkawnie : Journal of Islamic Science and Technology     Open Access  
Ciência ET Praxis     Open Access  
Arab Journal of Basic and Applied Sciences     Open Access  
International Annals of Science     Open Access  
Science Heritage Journal     Open Access  
Bilge International Journal of Science and Technology Research     Open Access  
Avrasya Terim Dergisi     Open Access  
International Scientific and Vocational Studies Journal     Open Access  
TÜBAV Bilim Dergisi     Open Access  
LOGIKA Jurnal Ilmiah Lemlit Unswagati Cirebon     Open Access  
Dalat University Journal of Science     Open Access  
Investiga : TEC     Open Access  
Investigación Joven     Open Access  
Respuestas     Open Access  
Science Diliman     Open Access  
Instruments     Open Access  
Revista Científica y Tecnológica UPSE     Open Access  
HardwareX     Open Access  
Sultan Qaboos University Journal for Science     Open Access  
Borneo Journal of Resource Science and Technology     Open Access  
Sainstek : Jurnal Sains dan Teknologi     Open Access  
Revista de Información Científica     Open Access  
Indonesian Journal of Fundamental Sciences     Open Access  
Sainteknol : Jurnal Sains dan Teknologi     Open Access  
Jurnal Natural     Open Access  
Frontiers for Young Minds     Open Access  
Revista Ciência, Tecnologia & Ambiente     Open Access  
Journal of Indian Council of Philosophical Research     Hybrid Journal  
Journal of Negative and No Positive Results     Open Access  
Revista Conhecimento Online     Open Access  
Nova     Open Access  
CienciaUAT     Open Access  
Enseñanza de las Ciencias : Revista de Investigación y Experiencias Didácticas     Open Access  
Makara Journal of Science     Open Access  
Jurnal Sains Dasar     Open Access  
Indonesian Journal of Science and Technology     Open Access  
Ethiopian Journal of Science and Technology     Open Access  
Jurnal Matematika, Sains, Dan Teknologi     Open Access  
Heidelberger Jahrbücher Online     Open Access  
ARO. The Scientific Journal of Koya University     Open Access  
International Journal of Recent Contributions from Engineering, Science & IT     Open Access  
Estação Científica (UNIFAP)     Open Access  
The Winnower     Open Access  

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