bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on the Characteristics of Scientific Research Cooperation in Carbon Neutrality Studies from the Perspective of Mode 3 of knowledge production
Authors: Tu Yifang , Huo Liping , Sun Yanli , Li Jia
Published: June 2024

This paper, from the perspective of Mode 3 of knowledge production, takes the important carrier of knowledge, scientific research papers, as the research object. The mainstream databases (SCIE and SSCI) are chosen as the data sources. Firstly, bibliometric methods are applied to analyze the cooperation status among the main bodies of paper production, including authors and their affiliated institutions, countries, and disciplines; secondly, the Analytic Hierarchy Process (AHP) is used to construct a comprehensive evaluation model for the state of research cooperation in carbon neutrality. Based on the evaluation model, the cooperation characteristics of different disciplinary fields and the relationship between paper cooperation status and high-impact research papers are comparatively analyzed. At the same time, an analysis is conducted on the support from the government, the sponsorship from enterprises, and the participation of the public in the process of paper production. Finally, some suggestions are put forward on how to build an innovative ecosystem for carbon neutrality research from the perspective of Mode 3 of knowledge production.
Selection of Relay Function Nodes for UAV Routing in Wireless Multi-Hop Network
Authors: Ohkawa Shuto , Ueda Kiyoshi , Miyoshi Takumi , Yamazaki Taku , Yamamoto Ryo
Published: June 2024

Unmanned delivery technology using unmanned aerial vehicles (UAVs) has the potential to solve issues such as traffic congestion and labor shortages. We investigated a method to construct a route between the source and destination nodes in a wireless multi-hop network by installing a radio terminal in each house. If the relay functions of all nodes in the network are in operation, the number of control messages for route construction increases, and the message relay forwarding load of each node increases. Keeping all node pairs multi-hop connectivity, we establish a method to operate the relay function with as few nodes as possible. End nodes that have not activated the relay function connect to the relay node with the closest physical distance. In this paper, we propose methods for selecting nodes to operate the relay function. Specifically, one method is based on random selection, another method is based on the number of adjacent nodes, and a third method is based on the Multipoint Relay (MPR) of the Optimized Link State Routing Protocol (OLSR). For each method, we evaluate whether the route construction is available, the number of relay nodes, the total distance of constructed routes, and the distance in population-dense regions. We clarify the characteristics of each method, and the method based on MPR is the best for constructing a network suitable for UAV navigation routes. In addition, the smaller the number of relay nodes, the more unexpected collisions on the links due to route conflicts. We clarify the minimum node density required to apply the MPR method which reduces the number of relay nodes suppressing route conflicts.
Economics Zombies in Transition: Navigating a Paradigm Shift from Tradition to Modernity
Authors: Montgomery Richard Murdoch
Published: June 2024

This article explores the pressing need for a paradigm shift in economics, challenging the dominance of classical economic theories and models that have long held sway. We delve into the limitations of traditional economic paradigms, which often rely on unrealistic assumptions and fail to capture the complexities of human behavior and the modern global economy. Drawing from insights in behavioral economics, environmental economics, and complexity theory, we argue for a more nuanced and multidisciplinary approach to economic analysis. Our discussion addresses the challenges of breaking away from deeply entrenched academic norms and the resistance to change within the economics profession. We highlight strategies for individuals and groups to advocate for the incorporation of modern economic theories in education and research. By fostering interdisciplinary collaboration, encouraging critical thinking, and engaging with policymakers and the public, we aim to catalyze a shift toward economics that is better equipped to address the intricate challenges of the 21st century. This article serves as a call to action for economists and educators alike to embrace a more dynamic and responsive approach to understanding human behavior and decision-making in the modern world.
Data-Driven Distributionally Robust Optimization for Day-Ahead Operation Planning of a Smart Transformer-based Meshed Hybrid AC/DC Microgrids Considering the Optimal Reactive Power Dispatch
Authors: Núñez-Rodríguez Rafael A. , Unsihuay-Vila Clodomiro , Posada Johnny , Pinzón-Ardila Omar
Published: June 2024

Smart Transformer (ST)-based Meshed Hybrid AC/DC Microgrids (MHM) are a feasible alternative to increase the performance of conventional microgrids (MG) and to increase the penetration of Distributed Energy Resource (DER) at the same time, active and reactive power dispatch on the system. Despite this, MHMs present challenges in managing resources under uncertainties and controlling electronic converters associated with the ST and DER, making it complex to achieve optimal system performance. In this paper, a Data-Driven Distributionally Robust Optimization (DDDRO) for Day-Ahead Operation Planning of an ST-based MHM considering the reactive power dispatch of the DER that minimizes network losses, voltage deviations, and operation cost simultaneously, considering uncertainties of Photovoltaic Generators (PVG) and demand, is proposed. The Column and Constraint Generation (C&CG) algorithm and Duality-Free Decomposition (DFD) method are adopted. Besides, the original mixed-integer non-linear planning problem is converted into a Mixed-Integer (MI) Second-Order Cone Programming (SOCP) problem through second-order cone relaxation and positive octagonal constraint method. Simulation experiments and results with a connected MHM system demonstrate the effectiveness and performance of the proposed model. Finally, we observe the effect of the meshed structure of MG and the positive impact of integrating the ST to form MHM, taking advantage of the degrees of freedom of this multi-stage converter for optimal energy management under uncertain conditions.
Characteristic of Alternative Fuels and Their Impacts on Exhaust Emissions
Authors: Pośpiech Beata
Published: June 2024

The use of alternative fuels and electric vehicles is an opportunity to reducing exhaust emissions. We observe that the regulations on exhaust emissions from mobile sources are becoming gradually stricter on the all the world. As is widely known, using alternative fuels instead of conventional fuels helps lower vehicle emissions. The most popular alternative fuels are hydrogen, propane, biobutanol, methanol, dimethyl ether, etc. It is very important that more than a dozen alternative fuels are under development. The article contains a comparison of the operating costs of electric cars and cars with an internal combustion engine. This work shows also the characteristic of new alternative fuels and their impacts on exhaust emissions.
Friction and Wear Behaviour of Double-Walled Carbon Nanotube-Yttria-Stabilized ZrO2 Nanonanocomposites Prepared by Spark Plasma Sintering
Authors: Kasperski Anne , Alkattan Dalya , Turq Viviane , Estournes Claude , Laurent Christophe , Weibel Alicia
Published: June 2024

Double-walled carbon nanotube-yttria-stabilized ZrO2 nanocomposites are prepared by a mixing route followed by Spark Plasma Sintering. Incorporation of carbon at contents higher than 2 wt.% results in significantly lower friction coefficients, both against alumina and steel balls. Double-walled carbon nanotubes improve wear resistance and reduce friction without severe damage, contrary to multi-walled carbon nanotubes.
A Complex Background SAR Ship Target Detection Method Based on Fusion Tensor and Cross-Domain Adversarial Learning
Authors: Chan Haopeng , Qiu Xiaolan , Lu Dongdong , Gao Xin
Published: June 2024

Synthetic Aperture Radar (SAR) ship target detection has been extensively researched. However, most methods use the same dataset division for both training and validation. In practical applications, it is often necessary to quickly adapt to new loads, new modes, and new data to detect targets effectively. This presents a cross-domain detection problem that requires further study. This paper proposes a method for detecting SAR ships in complex backgrounds using fusion tensor and cross-domain adversarial learning. The method is designed to address the cross-domain detection problem of SAR ships with large differences between the training and test sets. Specifically, it can be used for the cross-domain detection task from the fully-polarised medium-resolution ship dataset (source domain) to the high-resolution single-polarised dataset (target domain). This method proposes a Channel Fusion Module (CFM) based on the YOLOV5s model. The CFM utilises the correlation between polarised channel images during training to enrich the feature information of single-polarised images extracted by the model during inference. The article proposes a module called Cross-Domain Adversarial Learning Module (CALM) to reduce overfitting and achieve adaptation between domains. Additionally, the paper introduces the Anti-Interference Head (AIH) which decouples the detection head to reduce the conflict of classification and localization problems. This improves the anti-interference and generalization ability in complex backgrounds. This paper conducts cross-domain experiments using the constructed medium-resolution SAR full polarization dataset (SFPD) as the source domain and the high-resolution single-polarised ship detection dataset (HRSID) as the target domain. Compared to the best-performing YOLOV8s model among typical mainstream models, this model improves Precision by 4.9%, Recall by 3.3%, AP by 2.4%, and F1 by 3.9%. This verifies the effectiveness of the method and provides a useful reference for improving cross-domain learning and model generalization capability in the field of target detection.
Applying and Improving Pyranometric Method to Estimate Sunshine Duration for a Tropical Site
Authors: Fanjirindratovo Tovondahiniriko , Calogine Didier , Chau Oanh , Ramiarinjanahary Olga
Published: June 2024

The aim of this paper is to apply all the existing pyranometric method, to estimate the sunshine duration from the global solar irradiation, in order to find in their original form the most suitable method for a tropical site. Then, in a second step, one of these methods will be optimized to well fit tropical sites. Five methods in the literature (Step Algorithm, Carpentras Algorithm, Slob & Monna Algorithm, Slob & Monna 2 Algorithm, and Linear Algorithm) were applied with eleven years of global and diffuse solar radiation data. As a result, in their original form, the Step Algorithm is on the first rank. But in the second step, after improving its main coefficients, the Carpentras Algorithm was found to be the best algorithm for tropical site in the southern hemisphere.
Effective Living Donor Evaluation in a Western Liver Transplantation Program
Authors: Rohland Oliver
Published: June 2024

BackgroundLiving donor liver transplantation offers comparable long-term results to cadaveric donor transplantation. This study analyzes the selection process of living liver donors at a Western transplant center that utilizes both donation forms. MethodsThis retrospective analysis examined potential living donors, collecting medical data and reasons for refusal, and divided patients by indication and urgency for transplantation. ResultsFrom January 2013 to December 2023, 594 potential living donors were assessed at Jena University Hospital. Of these, 124 living donor transplants were performed. During outpatient evaluation, 357 potential donors were excluded. Subsequently, 238 individuals underwent inpatient assessment, with 100 more being excluded. Main reasons for donor refusal included medical or psychological issues (n=160), disease progression in recipients (n=90), and recipient refusal or donor withdrawal (n=54). The evaluation process showed a trend towards considering more distant relatives and acquaintances as donor candidates with increasing severity of the recipient's disease.
Bayesian Modelling of Travel Times on the Example of Food Delivery: Part 2 - Model Creation and Handling Uncertainty
Authors: Pomykacz Jan , Gibas Justyna , Baranowski Jerzy
Published: June 2024

The e-commerce sector is in a constant state of growth and evolution, particularly within its subdomain of online food delivery. As such, ensuring customer satisfaction is critical for companies working in this field. One way to achieve this is by providing accurate delivery time estimation. While companies can track couriers via GPS, they often lack real-time data on traffic and road conditions, complicating delivery time predictions. To address this, a range of statistical and machine learning techniques are being employed, including neural networks and specialized expert systems, with different degree of success. One issue with neural networks and machine learning models is their heavy dependence on vast, high quality data. To mitigate this issue we propose two Bayesian generalized linear models to predict time of the delivery. Utilizing a linear combination of predictor variables, we generate practical range of outputs with Hamiltonian Monte Carlo sampling method. These models offer a balance of generality and adaptability, allowing for tuning with expert knowledge. They were compared with PSIS-LOO and WAIC criteria. Results show that both models accurately estimated delivery times from the dataset, while maintaining numerical stability. Model with more predictor variables proved to be more accurate.
Brand Communication and Supply Chain Management: A Qualitative Study on Co-Creation of Value in B2B Markets
Authors: Holloway Samuel
Published: June 2024

Brand communication and supply chain management are critical components of value co-creation in B2B markets, yet their interplay and implications remain underexplored in current literature. This qualitative study investigates how these elements synergistically contribute to mutual value creation among businesses. Through semi-structured interviews with senior executives and managers from diverse industries, key insights were gleaned regarding the strategic alignment of brand communication strategies with supply chain practices. Findings underscore the importance of authenticity, transparency, and consistency in brand messaging to build credibility and foster stakeholder trust. Supply chain management emerged as pivotal in supporting effective brand communication, facilitated by advancements in AI, blockchain, IoT, and cloud computing, enhancing operational efficiency and responsiveness across global networks. Entrepreneurship and emotional intelligence were identified as crucial drivers of innovation and collaboration within B2B contexts, augmenting organizational agility and resilience. Furthermore, the integration of sustainable practices within supply chain operations was found to enhance brand reputation and mitigate risks associated with environmental and ethical considerations. The study highlights actionable insights for practitioners, emphasizing the strategic integration of brand communication and SCM capabilities to navigate complexities, capitalize on emerging opportunities, and foster sustainable growth. This research contributes to a deeper understanding of the multifaceted dynamics shaping B2B interactions and provides a foundation for future research endeavors. By aligning brand communication strategies with SCM practices and leveraging technological advancements, businesses can enhance competitive advantage, cultivate enduring relationships with stakeholders, and achieve sustainable success in a dynamic global marketplace.
Novel Intelligent Traffic Light Controller Design
Authors: Zahwa Firas , Cheng Chi-Tsun , Simic Milan
Published: June 2024

Efficient traffic flow management at intersections is vital for optimizing urban transportation networks. This paper presents a comprehensive approach to refining traffic flow by analyzing the capacity of roads and integrating fuzzy logic-based traffic light control systems. We were examining the capacity of roads connecting intersections, considering factors such as road vehicle capacity, vehicle speed, and traffic flow volume, through detailed mathematical modelling and analysis. Control is determined by the maximum capacity of each road segment, providing valuable insights into traffic flow dynamics. Building upon this capacity and flow analysis, the research introduces a novel Intelligent Traffic Light Controller (ITLC) system based on fuzzy logic principles. By incorporating real-time traffic data and lever-aging fuzzy logic algorithms, our ITLC system dynamically adjusts traffic light timings to optimize vehicle flow at two intersections. The paper discusses the de-sign and implementation of the ITLC system, highlighting its adaptive capabilities in response to changing traffic conditions. Simulation results are presented, demonstrating effectiveness of the ITLC system in improving traffic flow and re-ducing congestion at intersections. Furthermore, this research provides an analysis of the mathematical models used to calculate road capacity, offering insights into the underlying principles of traffic flow optimization. Through the simulation, we have validated accuracy and reliability of our controller.
Reverberating Action Potentials and the Emergence of Short Circuit Propagation in Gliosis
Authors: Montgomery Richard
Published: June 2024

This study explores the intriguing phenomenon of action potentials reverberating and propagating in high-resistance tissues, such as gliosis, leading to the emergence of short circuits within the brain. Gliosis, characterized by increased tissue resistance, presents a unique environment for electrical signals. My research investigates the possible mechanisms behind these reverberations and their role in the creation of self-empowering short circuits that can potentially affect the entire brain's functionality. Understanding these processes may have significant implications for the treatment and management of neurological disorders associated with gliosis and abnormal electrical activity in the brain.
Perceptions of Supply Chain Sustainability and Its Influence on Consumer Buying Decisions
Authors: Holloway Samuel
Published: June 2024

This qualitative study explores consumer perceptions of supply chain sustainability and its impact on buying decisions. Through in-depth interviews and focus groups, the research investigates the multifaceted factors influencing consumer behaviors towards sustainable products. Findings reveal that environmental impact, social responsibility, transparency, economic considerations, and cultural influences are pivotal in shaping consumer attitudes. While consumers express strong motivations to support sustainability, practical barriers such as higher costs and limited availability often hinder consistent adoption of sustainable practices. Effective communication strategies, including transparency reports and sustainability certifications, emerge as crucial in bridging the gap between consumer intentions and actions. The study underscores the importance of aligning corporate sustainability initiatives with consumer expectations to build trust and foster sustainable consumption patterns. Insights suggest a need for targeted interventions and policy measures to address barriers and promote broader adoption of sustainable behaviors. By understanding and responding to consumer concerns, businesses can enhance their sustainability strategies and contribute to a more environmentally and socially responsible marketplace.
Enhanced Performance of a Hydrokinetic Turbine Through a Biomimetic Design
Authors: Galdo María Isabel Lamas , Rodríguez Juan de Dios , Couce-Casanova Antonio , Damota Javier Blanco , Caccia Claudio Giovanni , Lorenzo Jose Manuel Rebollido , Telmo Miranda Javier
Published: June 2024

Hydrokinetic energy constitutes a significant promise as a renewable energy source, yet many regions experience flow velocities insufficient to support conventional turbine installations. According to this, the present work proposes a vertical axis hydrokinetic turbine aimed to environments where conven-tional turbines may not be feasible due to insufficient water velocity. This turbine is based on a biologi-cally inspired design which improves the traditional Savonius turbine. This innovative configuration is inspired by the Fibonacci spiral. The turbine's performance was analyzed through Computational Fluid Dynamics. A notable improvement was found in comparison with the traditional Savonius turbine, providing a 15.1% increment in the power coefficient.
Portable Sensors for Dynamic Exposure Assessments in Urban Environments: State of the Science
Authors: Hofman Jelle , Lazarov Boris , Stroobants Christophe , Elst Evelyne , Smets Inge , Van Poppel Martine
Published: June 2024

This study presents a fit-for-purpose evaluation of commercially available portable sensor systems, measuring PM, NO2 and/or BC, through extensive lab- and field benchmarking. The main aim of the study is to identify sensor systems that can be used for mobile monitoring by citizens to assess dynamic exposure in ambient air. After an initial literature study and market search resulting in 39 sensor systems, 10 sensor systems were ultimately purchased and benchmarked in laboratory and real-word conditions. We evaluated comparability to reference analyzers, sensor precision and sensitivity to temperature, humidity and O3. Moreover, we evaluated if accuracy can be improved by the lab and field calibration. Because the targeted application of the sensor systems under evaluation is mobile monitoring, we conducted a mobile field test in an urban environment to evaluate the GPS accuracy and potential impacts from vibrations on the resulting sensor signals. Results of the considered sensor systems indicate that out-of-the-box performance is relatively good for PM and BC, but maturity of the tested NO2 sensors is still low and additional efforts are needed in terms of signal noise and calibration. The horizontal accuracy of the build-in GPS was generally good achieving a <10m horizontal accuracy for all sensor systems. More accurate and dynamic exposure assessments in contemporary urban environments are crucial to study real-world exposure of individuals and exposome impacts on potential health endpoints. A greater availability of mobile monitoring systems capable of quantifying urban pollutant gradients will further boost this line of research.
How Supply Chain Disruptions Affect Brand Loyalty: A Qualitative Analysis of Consumer Experiences During Crises
Authors: Holloway Samuel
Published: June 2024

This qualitative study investigates how supply chain disruptions affect brand loyalty by analyzing consumer experiences during crises. Through in-depth interviews with diverse participants, the research explores the nuanced factors shaping consumer perceptions and behaviors when supply chains face challenges. Findings reveal that trust is pivotal, with transparent communication and consistent updates fostering consumer confidence and loyalty. Brand reputation emerges as crucial, influencing perceptions of reliability and ethical conduct during disruptions. Effective crisis management strategies, including agility and proactive communication, mitigate negative impacts on brand loyalty. Consumer decision-making is influenced by the availability of substitutes and perceptions of disruption severity, highlighting the importance of brand resilience and continuity. Emotional responses, such as frustration and anxiety, significantly influence consumer loyalty, underscoring the role of empathetic engagement and support from brands. Aligning with consumer expectations and delivering on promises are essential for sustaining loyalty and reducing the risk of consumer defection. The study concludes that navigating supply chain disruptions requires brands to prioritize trust, reputation, crisis management, consumer-centric strategies, emotional intelligence, and alignment with consumer expectations. These insights contribute to a deeper understanding of consumer behavior in crisis contexts and provide strategic implications for brands seeking to enhance resilience and maintain loyalty in dynamic market environments.
Transversal STEM Education for Improving Science learning in Secondary Students
Authors: Sardiña Eduardo , Hijón-Neira Raquel
Published: June 2024

The text examines the assessment of learning in science and the use of technologies like Scratch to enhance this process. Assessment is crucial for measuring progress and guiding teaching, especially in science where it fosters scientific skills and understanding. The study focuses on third-year secondary education students, evaluating the impact of Scratch on their learning compared to a gamification approach. Scratch, developed by MIT, is effective in interactive teaching and improves academic performance and student motivation. The research used an experimental design with a control group (gamification) and an experimental group (Scratch), measuring acquired knowledge through pretests and posttests. Results show that both groups significantly improved their knowledge, although the control group had a higher baseline initially. Students valued collaboration and playful learning. However, they faced technical challenges and highlighted the importance of teamwork. The study concludes that Scratch has great educational potential, suggesting improvements such as redesigning activities and increasing work sessions to maximize its effectiveness in learning and student motivation.
Cultura material do bejú e a proposição de currículo na Educação Infantil na Amazônia Bragantina, Estado do Pará, Brasil
Authors: Maciel Rogerio Andrade , Magalhães Franciele de Almeida , Nery Vitor Sousa Cunha
Published: June 2024

Este artigo teve como objetivo compreender a cultura material do Bejú e a tessitura do currículo da Educação Infantil. Metodologicamente, foi utilizada a Abordagem da Nova História Cultural e a análise dos dados foi operada pelos modos de fazer em Certeau (2014). Os resultados evidenciam a cultura material do bejú pelos seguintes objetos: a macaxeira; o terçado; o facão; o carro de mão; os baldes; a canoa; o catitu; o ralo; o tacho; o tipiti; o Sari; a Peneira; o forno; o rodo; a basqueta; e as folhas de sororoca. Assim, a partir dos resultados, é fato que a proposição do currículo da Educação Infantil é mediada por práticas docentes de contação de histórias; rodas de conversas; pinturas; jogos; desenhos e estimula o imaginário da criança na Amazônia Bragantina, Estado do Pará, Brasil.
A relação entre o público e o privado na educação básica pública como modalidade neoliberal de privatização: o caso do ensino médio integral de Sergipe
Authors: Teles Thadeu Vinícius Souza , Teles Gildete Cecilia Neri Santos
Published: June 2024

Este artigo objetiva investigar a relação público e privado na educação básica funcionando como modalidade neoliberal (Laval, 2019) de privatização sob o contexto do modelo de gestão do Ensino Médio Integral (EMI) em Sergipe (Teles, 2023). Desse modo, foram necessários aportes teóricos que excedem a Linguística Aplicada (Zacchi, 2016) para fundamentar sociopoliticamente questões levantadas durante o texto, como o ensino integral e o neoliberalismo pedagógico (Freitas, 2018). O estudo se dá por meio de uma pesquisa qualitativa, que utiliza os documentos de implantação e manutenção do EMI em Sergipe (Sergipe, 2016a; 2016b) para análise e triangulação de dados. Assim, buscamos reconhecer a presença do setor privado na máquina pública de modo a transpor o modo de funcionamento desta nas engrenagens daquela. Tal ação resultou no reconhecimento dos riscos destas parcerias que atacam a escola pública de gestão pública e contribuem para uma crise democrática na educação que põe em funcionamento uma agenda oculta por trás do discurso de busca por qualidade total, justificando a relevância desse estudo.
Influence of permanent magnet parameters on the performances of claw pole machines used in hybrid vehicles
Authors: Kimouche A. , Mekideche M. R. , Chebout M. , Allag H.
Published: June 2024

Introduction. Claw pole machines (CPM) are commonly used in the automotive industry. Recently, importance has focused on the use and introduction of permanent magnets (PM) in this type of machine to increase the power density. This paper studies the performance of permanent magnet claw pole machines (PM-CPM) used in hybrid electric vehicle applications. The structure considers that the PMs are placed between the claws of the rotor. Purpose. The influence of the PM magnetization effect on the performance of synchronous PM-CPM is analyzed. Radial and tangential magnetizations are applied to obtain the best possible sinusoidal shape of the electromotive force and an acceptable cogging torque. Then, the electromagnetic performance of the PM-CPM is analyzed and evaluated. Furthermore, due to the complexity of the rotor armature, it seems difficult to give a direct relationship between the PM parameters and the machine torque. This led us to study the effects of magnets geometrical dimensions variations on the torque and its ripple. Method. 3D nonlinear model of the machine is analyzed using the finite element method and comparisons between some electromagnetic performances are processed. Results. It was found that the tangential magnetization of PMs makes it possible to obtain a better distribution of the flux density and a minimum of cogging torque mainly responsible for vibrations and acoustic noise. Also, we observed a non-linear variation between the torque and its ripples depending on the dimensions of the PM. In fact, electromagnetic torque increases linearly with PM size but this is not the case for torque ripples. References 22, tables 2, figures 16.
Development of methods for adapting the parameters of spatial end winding sections in 2D circuit-field models of induction-synchronous electric machines
Authors: Kotsur M. I.
Published: June 2024

Introduction. Recently, the theory of a special class of cascade slow-speed non-contact induction-synchronous electrical machines (ISEM) has been developed. This allowed to obtain a combination of positive properties from conventional induction and synchronous electric machines. Problem. The lack of circuit and field models of ISEM imposes restrictions on further research of electromagnetic, mechanical and energy processes, in transient and quasi-steady modes of its operation. Goal. Development of 3D and adapted 2D circuit-field models of ISEM, decomposition methods, and dynamic synthesis with adaptation of electromagnetic parameter coupling conditions at the boundaries of calculated subdomains of ISEM. Methodology. Spatial elements of ISEM design are represented by separate spatial calculation subareas. The conditions of compliance with electromagnetic processes, which are formed by a complete calculation area and separate spatial calculation subareas of ISEM, are accepted. The influence of end effects and the parameters of the frontal parts of ISEM windings are determined by the inequality of the magnetic field energy of separate calculation subareas. These parameters, including end effects, are displayed as circuit elements in the 2D circuit-field model. Results. The obtained combination of 3D area decomposition methods and dynamic synthesis with adaptation of electromagnetic parameters coupling conditions at the boundaries of its calculated ISEM’s subdomains. The proposed technique for determining the resistance and inductive resistances of the frontal parts of the ISEM windings, taking into account edge effects. The accuracy and effectiveness of the proposed methods is confirmed by the results of an experimental study. Originality. An adapted dynamic 2D circuit-field model of transient processes of ISEM has been developed, which allows taking into account parameters of the frontal parts of its windings. Practical value. The proposed methods can be used for various types of electrical machines. References 27, tables 3, figures 12.
The method for design of electromagnetic hybrid active-passive shielding by overhead power lines magnetic field
Authors: Kuznetsov B. I. , Nikitina T. B. , Bovdui I. V. , Chunikhin K. V. , Kolomiets V. V. , Kobylianskyi B. B.
Published: June 2024

Aim. Development of the method for designing electromagnetic hybrid active-passive shield, consisting from active and multy-circuit passive parts, which is characterized by increased effectiveness of reducing the industrial frequency magnetic field created by two-circuit overhead power lines in residential buildings. Methodology. The designing problem of electromagnetic hybrid active-passive shield including robust system of active shielding and multy-circuit passive shield of initial magnetic field comes down to a solution of the multy-criteria two-player zero-sum antagonistic game. The game payoff vector calculated based on the finite element calculations system COMSOL Muliphysics. The game solution calculated based on the particles multyswarm optimization algorithms. Results. During the design of the electromagnetic hybrid active-passive shield the coordinates of the spatial arrangement of 11 circuits passive shield and the coordinates of the spatial location of one compensation winding, as well as the current and phase in this winding of the active shielding system are calculated. The results of theoretical and experimental studies of hybrid active and multy-circuit passive shield by magnetic field in residential building from two-circuit power transmission line with a «Barrel» type arrangement of wires presented. Originality. For the first time the method for designing hybrid active and multy-circuit passive shield, consisting from active and multy-circuit passive parts, which is characterized by increased effectiveness of reducing the magnetic field of industrial frequency created by two-circuit overhead power lines in residential buildings is developed. Practical value. Based on results of calculated study the shielding efficiency of the initial magnetic field what is confirmed by experimental studies determined that shielding factors whith only multy-circuit passive shield is more 1.2 units, whith only active shield is more 4 units and with electromagnetic hybrid active-passive shield is more 6.2 units. It is shown the possibility to reduce the level of magnetic field induction in residential building from two-circuit power transmission line with a «Barrel» type arrangement of wires by means of electromagnetic hybrid active shielding with single compensating winding and multy-circuit passive shielding with 11 circuit passive shield to 0.5 μT level safe for the population. References 51, figures 17.
Enhancing grid stability and low voltage ride through capability using type 2 fuzzy controlled dynamic voltage restorer
Authors: Sajan Ch. , Satish Kumar P. , Virtic P.
Published: June 2024

Introduction. The integration of Renewable Energy Sources (RESs), particularly Wind Energy Conversion Systems (WECS), is vital for reducing reliance on fossil fuels and addressing climate change. However, this transition poses challenges, including ensuring grid stability in the face of intermittent RESs. Compliance with grid codes is crucial, with a focus on Low Voltage Ride Through (LVRT) capability. Problem. The intermittent nature of RESs, specifically in Permanent Magnet Synchronous Generator (PMSG) based WECS, presents challenges to grid stability during voltage dips. Goal. To enhance voltage stability and LVRT capability in PMSG-based WECS by integrating a Dynamic Voltage Restorer (DVR) with an energy storage device. This involves regulating the input DC voltage to the DVR using a type 2 fuzzy controller, adapting intelligently to changing conditions. Methodology. DVR, powered by an energy storage device, is strategically integrated with WECS. A type 2 fuzzy controller regulates the DC voltage to DVR. The rectified WECS output undergoes processing through an isolated flyback converter. A 31-level Cascaded H-Bridge Multilevel Inverter (CHBMLI) with PI control ensures high-quality AC output. Results. The validation of developed system is executed using MATLAB/Simulink revealing a reduced Total Harmonic Distortion (THD) value of 1.8 %, ensuring significance in LVRT capability. Originality. The strategic integration of DVR with PMSG-based WECS, addresses the LVRT challenges. The use of type 2 fuzzy controller for intelligent voltage regulation and a sophisticated multilevel inverter contributes to the uniqueness of proposed solution. Practical value. The developed system provides benefits by ensuring reliable LVRT capability in PMSG-based WECS with reduced THD of 1.8 % indicating improved grid compatibility. References 26, tables 5, figures 20.
Contribution of using a photovoltaic unified power quality conditioner in power quality improvement
Authors: Bousnoubra C. , Djeghader Y. , Belila H.
Published: June 2024

Introduction. With the increasing complexity of power systems and the integration of diverse energy sources, issues such as voltage sags, swells, and signal distortions have emerged as critical challenges. These power quality problems can result in equipment malfunction, production downtime, and financial losses for industries, as well as inconvenience and potential damage to electrical appliances in households. There is an urgent need for enhanced system efficiency. Methods. This objective is effectively achieved through the utilization of the newly proposed power theory, which is rooted in solar photovoltaic (PV) control, in conjunction with the Unified Power Quality Conditioner (UPQC). Purpose. The proposed method incorporates a modified synchronous reference frame scheme, coupled with a phase-locked loop mechanism. This control strategy enables the UPQC to effectively mitigate power quality issues. Novelty. PV-UPQC is utilized to uphold power integrity in the presence of diverse current and voltage distortions. This device, known as a multi-objective power conditioning apparatus, serves the purpose of maintaining power quality. PV-UPQC incorporates both a shunt and series voltage source converter, which are interconnected through a shared DC-link. Additionally, the PV system is interconnected at the DC-link of the UPQC in order to supply power to the load. Results. In this study, a novel approach is presented for controlling the UPQC, aiming to address power quality concerns such as unbalanced grid voltage and harmonic distortions and enabling us to control active and reactive power. References 16, tables 2, figures 15.
Statistical approach for insulation coordination of high voltage substation exposed to lightning strikes
Authors: Bedoui S. , Bayadi A.
Published: June 2024

Introduction. Insulation coordination requires accurate prediction of overvoltages at various points within a substation. Computer simulations of electromagnetic transients in real structures of substations become more precise due to the improvements of used models. Goal. This paper discusses in a first step the use of the modified ZnO arrester dynamic model alongside other substation equipment models, considering electrical phenomena like the corona model for reproducing the stresses that lightning can cause in an air-insulated substation and (method) then conducting a statistical approach based on the Monte Carlo method. The implemented MATLAB/ATP procedure estimates not only the substation Mean Time between Failures (MTBF), but also is used to select surge arresters or substation basic insulation levels (BILs). In this procedure ATP transients program is used to calculate lightning overvoltages and multicore environment for the calculations. Results. The obtained MTBF curves offer guidance for selecting appropriate insulation levels based on specific system requirements and conditions. The obtained results comply well with existing international insulation standards. This valuable approach significantly contributes to the field of lightning protection. References 31, tables 3, figures 10.
Observations of Beach Change and Runup, and the Performance of Empirical Runup Parameterizations during Large Storm Events
Authors: Kim Lauren Nicole , Brodie Katherine , Cohn Nicholas , Giddings Sarah , Merrifield Mark
Published: June 2024

Timeseries observations of beach elevation change and wave runup from a tower-mounted stationary lidar assess the skill of 2% runup exceedance (𝑅𝑅2%) estimates during four storm events at Duck, NC. The runup parameterization requires the foreshore beach slope, which generally unknown during high energy events. Pre-storm estimates are often used as a proxy. 𝑅𝑅2% hindcasts use the observed time-varying beach slope and a static pre-storm beach profile, yielding an 𝑅𝑅2% skill of 0.57. The skill drops to −1.0 using seasonal mean beach slopes and reduces after the peak of two storms with the appearance of beach cusps in the swash zone morphology. One storm’s runup is underpredicted by up to 1.0 m at high tides following the storm peak when cusps are present Additional pre- and post-storm mobile lidar surveys for one storm confirm ubiquitous small-scale beach cusps along 8 km of the local shoreline. The results suggest skillful runup estimates are often attainable given the availability of beach information before a storm. The parameterization errors increase when beach cusps develop, highlighting the need to extend standard one-dimensional runup parameterizations to account for two-dimensional effects.
Iron oxidation–reduction processes in warming permafrost soils and surface waters expose a seasonally rusting Arctic watershed
Authors: Barker Amanda , Sullivan Taylor , Baxter W. , Barbato Robyn , Gallaher Shawn , Patton Grace , Smith Joseph , Douglas Thomas
Published: June 2024

Landscape-scale changes from climate change in the Arctic affect the soil thermal regime and impact the depth to permafrost in vulnerable tundra watersheds. When top-down thaw of permafrost occurs, oxygen and porewaters infiltrate deeper in the soil column exposing fresh, previously frozen material and altering redox conditions. A gap remains in understanding how redox stratifications in thawing permafrost impact the geochemistry of watersheds in response to climate change and how investigations into redox may be scaled by coupling extensive geophysical mapping techniques. In this study, we collected soils and soil porewaters from three soil pits and surface water samples from an Arctic watershed on the North Slope of Alaska and analyzed for trace metals iron (Fe) and manganese (Mn) and Fe oxidation state using bulk and microscale techniques. We also used geophysical mapping and soil thermistors to measure active layer depths across the watershed to relate accelerating permafrost thaw to watershed geochemistry. Overall, evidence showed that Fe and Mn could be useful as geochemical indicators of permafrost thaw and release of Fe(II) from thawing permafrost and further oxidation to Fe(III) could translate to a higher degree of seasonal rusting coinciding with the warming and thawing of near surface-permafrost.
WITHDRAWN: Prognostic Impact of the Metabolic Syndrome and Its Components in Acute Type A Aortic Dissection After Surgery: A 3-Year Follow-Up
Authors: Liu Peng , Zhang Feng , Wang Zibin , Zhang Miao , Niu Xupeng , Han Yaru
Published: June 2024

The full text of this preprint has been withdrawn by the authors while they make corrections to the work. Therefore, the authors do not wish this work to be cited as a reference. Questions should be directed to the corresponding author.
Virtual melting and cyclic transformations between amorphous Si, Si I, and Si IV in a shear band
Authors: Levitas Valery , Chen Hao
Published: June 2024

Virtual melting (VM) as alternative deformation and stress relaxation mechanisms under extreme load is directly validated by molecular dynamics (MD) simulations of the simple shear of single crystal Si I at a temperature 1,383 K below the melting temperature. The shear band consisting of liquid Si is formed immediately after the shear instability while stress drops to zero. A thermodynamic criterion for VM, which depends on the ratio of the sample to shear band widths, is derived analytically and confirmed by MD simulations. With further shear, the VM immediately transforms to a mixture of lowdensity amorphous a-Si, Si I, and IV, which undergo cyclic transformations a-Si to and from Si I, a-Si to and from Si IV, and Si I to and from Si IV with volume fraction of phases mostly between 0.2 and 0.4 and non-repeatable nanostructure evolution. Such cyclic transformations produce additional important carriers for plastic deformation through transformation strain and transformation-induced plasticity due to volume change, which may occur in shear bands in various material systems but missed in experiments and simulations.
Tear proteomics reveals expressed proteins and potential pathways associated with diabetic keratopathy
Authors: Lu Xiaohe , Chen Zixiang , Li Jiali , Li Yingli , Liang Lifang , Zhong Yanyan
Published: June 2024

Background
Patients with diabetes are at risk of developing diabetic keratopathy (DK). The pathophysiological mechanisms of DK and associated biomarkers remain unclear. However, tear analysis provides crucial insights into DK. Thus, we conducted a quantitative proteomic analysis of tears from DK patients to identify differentially expressed proteins and potential pathways associated with DK.
Methods
This prospective case-controlled study included patients admitted to Zhujiang Hospital between October 2022 and February 2023. We examined 22 eyes with DK and 11 control eyes without DK. General characteristics and dry eye-related features were recorded, including those observed using ocular surface analysis, conjunctival impression cytology, and tear ferning tests. Tear fluid was collected using Schirmer strips after ensuring group similarity in confounders. Proteins were analysed through four-dimensional label-free mass spectrometry. Differential proteins were subjected to analyses of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. A protein–protein interaction network map was constructed.
Results
Of the 2733 proteins identified, 313 (156 upregulated and 157 downregulated) differentially expressed proteins were screened. Gene Ontology analysis revealed that these differentially expressed proteins mainly participated in mRNA decay, nuclear transcription, and receptor-mediated endocytosis. Kyoto Encyclopedia of Genes and Genomes analysis showed that these differentially expressed proteins could be involved in pathways, such as arginine biosynthesis, extracellular matrix-receptor interactions, and lysosome-related processes.
Conclusions
Arginine biosynthesis and extracellular matrix-receptor interactions may be involved in DK pathogenesis. These findings may enhance the understanding of DK among ophthalmologists.