bluuebunny/crossref_metadata_2025 huggingface dataset:
Automatic Segmentation of the Left Ventricle in Apical Four-Chamber View on Transesophageal Echocardiography Based on UNeXt Deep Neural Network
Authors: Wu Lingeer , Ling Yijun , Lan Ling , He Kai , Yu Chunhua , Zhou Zhuhuang , Shen Le
Published: December 2024

Background/Objectives: The automatic left ventricle segmentation in transesophageal echocardiography (TEE) is of significant importance. In this paper, we constructed a large-scale TEE apical four-chamber view (A4CV) image dataset and proposed an automatic left ventricular segmentation method for the TEE A4CV based on the UNeXt deep neural network. Methods: UNeXt, a variant of U-Net integrating a multilayer perceptron, was employed for left ventricle segmentation in the TEE A4CV because it could yield promising segmentation performance while reducing both the number of network parameters and computational complexity. We also compared the proposed method with U-Net, TransUNet, and Attention U-Net models. Standard TEE A4CV videos were collected from 60 patients undergoing cardiac surgery, from the onset of anesthesia to the conclusion of the procedure. After preprocessing, a dataset comprising 3000 TEE images and their corresponding labels was generated. The dataset was randomly divided into training, validation, and test sets in an 8:1:1 ratio on the patient level. The training and validation sets were used to train the UNeXt, U-Net, TransUNet, and Attention U-Net models for left ventricular segmentation. The dice similarity coefficient (DSC) and Intersection over Union (IoU) were used to evaluate the segmentation performance of each model, and the Kruskal–Wallis test was employed to analyze the significance of DSC differences. Results: On the test set, the UNeXt model achieved an average DSC of 88.60%, outperforming U-Net (87.76%), TransUNet (85.75%, p < 0.05), and Attention U-Net (79.98%; p < 0.05). Additionally, the UNeXt model had a smaller number of parameters (1.47 million) and floating point operations (2.28 giga) as well as a shorter average inference time per image (141.73 ms), compared to U-Net (185.12 ms), TransUNet (209.08 ms), and Attention U-Net (201.13 ms). The average IoU of UNeXt (77.60%) was also higher than that of U-Net (76.61%), TransUNet (77.35%), and Attention U-Net (68.86%). Conclusions: This study pioneered the construction of a large-scale TEE A4CV dataset and the application of UNeXt to left ventricle segmentation in the TEE A4CV. The proposed method may be used for automatic segmentation of the left ventricle in the TEE A4CV.
Health-Enhancing Physical Activity (HEPA) and Its Barriers Among Working Women at Mansoura University, Egypt
Authors: Ramadan Wael , Abu Alim Mariam , Khamis Mohammed , El-Gilany Abdel-Hady
Published: December 2024

Background: Identifying physical activity (PA) and its barriers among middle-aged women may aid in the development of age-specific health promotion interventions. In Egypt, women, particularly those in the workforce, typically face numerous barriers that result in low levels of PA. This research seeks to assess the prevalence of health-enhancing physical activity (HEPA) among working women at Mansoura University and identify the associated barriers. Methods: This cross-sectional study employs a quantitative methodology that includes an analytic component. We studied a non-random sample of 760 Egyptian women employed at Mansoura University. Sociodemographic data were collected, and the international physical activity questionnaire (IPAQ) short form was used to assess the level of PA. Additionally, the Barriers to Being Active Quiz (BBAQ) was used to assess barriers to PA. Results: One-fourth of women engage in HEPA; 44.9% are classified as minimally active, while 30.1% are inactive. Multivariable logistic regression analysis showed the type of job is an independent predictor of HEPA, with ARR of 1.7 for manager and administrative roles. The total BBAQ score significantly predicts HEPA (ARR = 0.94). Social influences and lack of willpower scores are significant independent predictors of HEPA (ARR = 0.9 and 0.8, respectively). Most individuals encounter two to five barriers, with only 11.3% experiencing no PA barriers. The most frequently reported barrier is the lack of energy (80.4%), followed by the lack of resources, willpower, and time (74.04%, 69.6%, and 69.4%, respectively). Conclusions: The prevalence of HEPA is low among working women at Mansoura University. Policymakers can utilize findings to promote engagement with and adherence to physical activity.
Serum 25-Hydroxyvitamin D Levels and Disease Activity in Patients with Systemic Lupus Erythematosus: An Exploratory Study in Western Mexico
Authors: Deossa-Piedrahita Daniela , Vicente-Hernández Berenice , Ramírez-Ochoa Sol , Ambriz-Alarcón Mauricio Alfredo , Cervantes-Pérez Gabino , Cervantes-Guevara Gabino , González-Ojeda Alejandro , Fuentes-Orozco Clotilde , Hernández-Mora Francisco Javier , Zepeda-Gutiérrez Luis Asdruval , Michel-González Jorge Isaac , Vázquez-Beltrán Janet Cristina , Cervantes-Pérez Enrique
Published: December 2024

Background and objectives: The correlation between diminished 25-hydroxyvitamin D (25-(OH)D) concentrations and heightened disease activity in systemic lupus erythematosus (SLE) patients remains contentious, as clinical studies have yielded conflicting outcomes—some propose a potential link, while others assert no relationship exists. Nonetheless, all studies report a significant prevalence of low 25-(OH)D levels among SLE patients. This study aimed to assess the frequency of low serum levels of 25-(OH)D in Mexican patients with SLE and to evaluate the correlation between 25-(OH)D deficiency or insufficiency and disease activity levels. Materials and Methods: This retrospective analysis comprised patients admitted to our hospital from November 2022 to October 2023, diagnosed with SLE, and had their serum 25-(OH)D levels tested upon admission. The frequency of low levels of 25-(OH)D was assessed, and clinical and demographic data were gathered to examine potential causes linked to 25-(OH)D deficiency or insufficiency. Results: A total of 61 patients were included, and 87% (n = 53) had low serum 25-(OH)D levels. Patients with 25-(OH)D deficiency (n = 21) were significantly younger (mean 23 vs. 39 years, p = 0.04) and had higher protein levels in 24 h urine protein (1.8 vs. 1.1 g/24 h, p = 0.006) than patients who presented only 25-(OH)D insufficiency, without significant differences in other indicators of disease activity. Conclusions: In this investigation, patients with SLE exhibited a high frequency of low serum levels of 25-(OH)D, consistent with existing literature; however, no significant correlations were identified between 25-(OH)D levels and indicators of disease activity. These findings require validation in subsequent research.
Post-COVID-19 Trends in Dental Emergencies: A Two-Year Retrospective Study from Romania
Authors: Moca Abel Emanuel , Cherecheș Jessica Olivia , Șipoș Lucian Roman , Moca Rahela Tabita , Slăvescu Dan , Iurcov Raluca
Published: December 2024

Background/Objectives: Dental emergencies significantly impact public oral health, particularly in the post-COVID-19 context. This study aimed to analyze the patterns of dental emergencies presenting to the Emergency Dental Service in Bihor, Romania, during the years 2022 and 2023, focusing on demographic characteristics and the frequency of diagnoses. Methods: A retrospective analysis of medical records from the Emergency Dental Service at Oradea County Emergency Clinical Hospital was conducted. Inclusion criteria encompassed patients presenting with dental emergencies during the specified period. Data regarding demographics, diagnoses, and living environments were collected and statistically analyzed. Results: A total of 4769 patients were analyzed, with acute pulpitis (39.2%, n = 1869) and acute apical periodontitis (37.5%, n = 1788) identified as the most common diagnoses. The study population included 52.3% males and 47.7% females, with a larger proportion residing in urban areas (58.0%) compared with rural areas (42.0%). Significant age-related patterns were evident: pulpitis was more common among patients aged 10–39 years, trauma was associated with patients aged 0–9 years, and gingival infections were prevalent in the 70–79 age group. Diagnoses also varied by dentition type, with abscesses, caries, trauma, and rhizolysis occurring more frequently in deciduous teeth, while pulpitis and post-extraction alveolitis were predominant in permanent teeth. However, no statistically significant differences were found in diagnosis frequency between genders or between rural and urban patients, indicating equitable access to emergency services across environments. Conclusions: The findings underscore the need for targeted interventions in pediatric populations to address early childhood caries, which remains a significant burden. Enhanced public health strategies and preventive education are essential to mitigate the prevalence of dental emergencies, particularly in the aftermath of the COVID-19 pandemic.
Improving Racing Drones Flight Analysis: A Data-Driven Approach Using Motion Capture Systems
Authors: Castiblanco Quintero Jose M. , Garcia-Nieto Sergio , Simarro Raul , Ignatyev Dmitry I.
Published: December 2024

The publication of the previous study, titled “Experimental Study on the Dynamic Behaviour of Drones Designed for Racing Competitions”, highlighted the increasing interest in employing scientific methods for their design and analysis. That study examined the flight data of 15 racing drones within a large flight area, using Doppler-type sensors for data collection. Building on these findings and seeking to enhance them, the current work introduces an upgraded data acquisition system utilising optical sensors, thereby improving measurement accuracy. These enhanced flight data facilitate the development of updated quality indices and conclusions, offering a more precise and definitive analysis than was previously possible.
Carnot and the Archetype of Waterfalls
Authors: Fuchs Hans , Dumont Elisabeth , Corni Federico
Published: December 2024

Carnot treats Heat as a Force of Nature, with its typical fundamental characteristics of intensity and thermal tension (temperature and temperature difference), extension (amount of heat, i.e., caloric), and power. To suggest how the three aspects are related, he applies the imagery of waterfalls to causative thermal processes: heat powers motion in a heat engine just as falling water does when activating rotation in a water wheel. We understand Carnot’s waterfall imagery as an archetype of human reasoning—as an embodiment of how we experience and understand causative (agentive) phenomena. We project it onto the macroscopic phenomena identified in physical science and so unlock the power of analogical structure mapping between theories of fluids, electricity and magnetism, heat, substances, gravity, and linear and rotational motion. In particular, the notion of (motive) power of a waterfall lets us create imaginative explanations of the interactions of Forces of Nature and helps us construct a generalized energy principle. Two-hundred years after Carnot made us aware of it, his Waterfall Analogy is a powerful example of theory construction with roots deep in how we experience phenomena as caused by natural agents.
Infinite-Dimensional Quantum Entropy: The Unified Entropy Case
Authors: Gielerak Roman , Wiśniewska Joanna , Sawerwain Marek
Published: December 2024

Infinite-dimensional systems play an important role in the continuous-variable quantum computation model, which can compete with a more standard approach based on qubit and quantum circuit computation models. But, in many cases, the value of entropy unfortunately cannot be easily computed for states originating from an infinite-dimensional Hilbert space. Therefore, in this article, the unified quantum entropy (which extends the standard von Neumann entropy) notion is extended to the case of infinite-dimensional systems by using the Fredholm determinant theory. Some of the known (in the finite-dimensional case) basic properties of the introduced unified entropies were extended to this case study. Certain numerical examples for computing the proposed finite- and infinite-dimensional entropies are outlined as well, which allowed us to calculate the entropy values for infinite Hilbert spaces.
Causality Relationship Between Producer and Consumer Price Indexes of Selected Meat Commodities in South Africa from 1991 to 2023
Authors: Aphane Thabang R. , Muchopa Chiedza L. , Senyolo Mmapatla P.
Published: December 2024

The South African meat industry plays an important role in food provision, income generation, and economic stability. However, inflation-driven volatility in commodity markets has intensified the focus on the nexus between producer and consumer price indexes, as significant meat price changes affect both producers and consumers. Therefore, this study explored the association and the causality between consumer price index (CPI) meat and producer price index (PPI) beef, mutton, pork, and chicken from 1991 to 2023 using the Vector Error Correction Model (VECM) and Granger causality test. The findings of the study revealed a short- and a long-run relationship among the variables with an adjustment speed (ECT) of 67.67%. No causal relationship was found between PPI beef and CPI meat, while unidirectional relationships were identified between CPI meat and PPI chicken, pork, and mutton. These results suggest that consumer meat prices impact production prices for chicken, pork, and mutton, but not for beef, indicating that beef price changes are influenced by factors other than general meat price fluctuations. Thus, while price controls or subsidies may manage price changes in chicken, pork, and mutton, further research or targeted strategies are needed to address the unique factors influencing beef prices. Ultimately, understanding these dynamics will enhance price stability in the meat market, benefiting consumers, producers, and the overall stability of the South African economy.
Impact of Tourism Activity on Urban Land and Housing Market Activity: Evidence from Croatia
Authors: Barbić Tajana
Published: December 2024

This paper explores the interplay of tourism activity, local expenditures on environmental protection, and the decisions to purchase apartments, family houses, and urban land. A random effects panel model is estimated by using data from cities and municipalities from 2012 to 2021 in Croatia, a European economy heavily dependent on tourism. The findings suggest that increasing tourism intensity at a destination motivates apartment purchase decisions but does not influence family house purchases as significantly. Municipal environmental expenditures show a positive relationship with apartment and family house purchase decisions, suggesting that investments in environmental protection may enhance the attractiveness of urban living spaces, leading to increased demand for apartments. Finally, the results reveal that growth in urban land purchases for housing construction is linked to increased short-term rentals and higher municipal housing expenditures. This research contributes to understanding housing market behavior. The results provide actionable insights for policymakers in tourism-dependent economies, emphasizing the need to balance tourism growth with housing affordability and sustainable urban development.
Simulation-Based Learning as a Tool for Assessing and Fostering Awareness of Empathic Patterns in Teacher Education
Authors: Levi-Keren Michal , Landler-Pardo Gabriella , Weinberger Yehudith , Arviv Elyashiv Rinat
Published: December 2024

Simulation-Based Learning (SBL) in education has demonstrated significant potential in preparing participants to effectively address future challenges in a dynamic and ever-changing world. Empathy, as a multidimensional skill, is fundamental to successfully navigate these complex situations. This study aims to assess the effectiveness of SBL in enhancing student teachers’ awareness and understanding of empathy’s multifaceted nature. Using a quasi-experimental design, 232 students participated in courses that integrated empathy instruction with simulation workshop experiences. The students used a rubric based on the Empathetic Patterns in Interpersonal Communication (EPIC) model, developed and validated by the authors in prior studies, to identify empathic patterns in two videotaped simulations shown to them at the beginning and end of the course. The same task was completed by seven content experts in empathy and psychology, as well as six experienced simulation workshop instructors serving as clinical experts. Additionally, the students responded to open-ended questions suggesting various expressions of empathy. The results indicated that SBL workshops, when integrated into a teaching framework that addresses empathy and analyzed through a structured rubric, can serve as an effective platform for enhancing students’ ability to identify and understand empathic patterns.
An Analysis of Thermal Comfort as an Influencing Factor on the Academic Performance of University Students
Authors: Romero Pilar , Valero-Amaro Víctor , Rubio Sergio , Miranda María Teresa
Published: December 2024

Academic performance is the level of achievement that students reach in their educational activities. It is influenced by several factors that should be analysed and prioritised, especially in engineering courses, characterised by their difficulty and low success rates compared to other careers. This paper analyses the impact of these factors on academic performance during exams in a technical college in southwestern Spain, with a particular focus on environmental conditions, identified as a relevant and independent variable. The results show a significant connection between thermal comfort and academic performance. Temperatures within the comfort range (23–26 °C) improved students’ satisfaction with exams. In contrast, those who experienced thermal discomfort pointed to environmental conditions as the main obstacle to their performance, overcoming factors such as prior preparation and coincidence of exams. These findings underline the importance of optimising the classroom’s thermal environment through strategies that promote a more favourable learning space, improving both students’ well-being and their academic performance.
Evaluating the Impact of an Educational Intervention Using Project-Based Learning on Postpandemic Recovery in Rural Colombia
Authors: Arrieta-Cohen Mercedes Carmen , Torres-Arizal Luz Angela , Gómez-Yepes Ricardo León
Published: December 2024

This study evaluates the impact of a Project-Based Learning (PBL) intervention on postpandemic educational recovery in rural Colombia, focusing on student competencies in mathematics, language, science, and 21st-century skills. Conducted in rural schools, the intervention aimed to address significant learning gaps exacerbated by the COVID-19 pandemic by providing teacher training and direct student support. A pretest–posttest single-group design was used to assess the effectiveness of the intervention, with standardized tests measuring academic competencies and an analytical rubric evaluating 21st-century skills. The results indicate significant improvements in math, language, and science test scores, with notable gains in problem-solving, collaborative work, communication, and critical thinking. However, a decline in creativity scores highlights the need for a stronger emphasis on fostering creativity within the PBL framework. Gender differences were observed, with female students generally outperforming males, suggesting the need for tailored instructional approaches. This study’s limitations, including the absence of a control group, nonrandom sampling, and the use of subjective assessment methods, are acknowledged, with recommendations for future research to address these issues. Despite these limitations, the findings underscore the potential of PBL to enhance student learning outcomes in rural settings, offering valuable insights for educators and policymakers aiming to support educational recovery and development in similar contexts. Further research is recommended to explore the long-term effects of PBL and to refine the intervention for broader implementation.
Exploring the Interplay Between Teaching Strategies and Digital Competencies Beliefs Among Pre-Service Teachers: A Longitudinal Study
Authors: Hirsch Anne-Kathrin , Rubach Charlott
Published: December 2024

One goal of teacher education is to create learning environments where pre-service teachers can explore and enhance their digital competencies. We aim to contribute knowledge on how these learning environments should be designed. First, our study focuses on examining the changes in pre-service teachers’ Technological Pedagogical Knowledge (TPK) and Technological Pedagogical Content Knowledge (TPACK) over one semester. Secondly, we evaluate the impact of various teaching strategies aimed at fostering these professional digital competencies, as conceptualized by the Synthesis of Qualitative Evidence (SQD) model. Our sample comprised 308 pre-service teachers (30% male students; x¯age = 23.29) from one German University attending different seminars (N = 40). Utilizing latent-change score models and bi-factor exploratory structural equation models, we indicated no significant overall change in TPK and TPACK across seminars. Taking into account the SQD teaching strategies and students’ satisfaction with these, not single teaching strategies but the orchestration of these strategies significantly positively impacted the development of pre-service teachers’ TPK and TPACK across seminars within a semester. These findings highlight the importance of employing various teaching strategies in pre-service teacher education to enhance pre-service teachers’ TPK and TPACK.
Engaging Preservice Secondary Science Teachers in TeachLivETM to Support English Learners in Developing and Communicating Science Ideas: An Innovation Guided by a Trifocal Approach
Authors: Beeghly Kelsey , Gao Su , Zygouris-Coe Vassiliki , Nutta Joyce
Published: December 2024

To meet the needs of English learners (ELs) and the call of the Next Generation Science Standards to engage all students in communicating science ideas, a collaboration between science, second language acquisition, and disciplinary literacy teacher educators resulted in a trifocal approach within a reformed science teacher education program. The purpose of this study is to explore how TeachLivETM, a mixed-reality simulation technology, was used to prepare preservice teachers (PSTs) to support ELs in communicating science ideas through questioning. Findings from transcribed lessons, coaching sessions, and PST self-reports show that TeachLivETM provided opportunities to practice questioning and reflect on challenges, and was a collaborative learning context. The significance for secondary science teacher education and inservice teacher professional development is presented.
The Past, Present, and Future of Clickers: A Review
Authors: Henderson J. Bryan , Chambers Elijah L.
Published: December 2024

Classroom response technologies commonly called “clickers” have been a popular tool for teaching in many disciplines, even required by some courses. Despite this excitement and corresponding investment in clicker technology, scholars disagree on the value of clickers. To help support teachers who utilize or are interested in using clickers, we explore the past, present, and future of clickers in education. This manuscript provides a literature review of how clickers are used, the benefits and challenges, and suggestions on the implementation of clicker technologies. Utilizing five research databases and a wide range of search terms, two general trends for clicker use became apparent: traditional classrooms that use clickers to enhance them and classrooms integrating clickers with more novel pedagogical approaches. After separating the papers into groups based on the trend they follow, the benefits and challenges were identified and recorded. In turn, we summarize what research has to say regarding both teachers and students for each of these primary outcomes. Building off clicker research both past and present, this review then looks toward the future by providing suggestions for overcoming the challenges faced by students and teachers when using clickers. Furthermore, we recommend important directions to consider for future research on clickers, including the need for more empirical studies of how different uses of clickers can benefit different learners in increasingly equitable ways.
Efficient User Pairing and Resource Optimization for NOMA-OMA Switching Enabled Dynamic Urban Vehicular Networks
Authors: Balaraman Aravindh , Shioda Shigeo , Kim Yonggang , Kim Yohan , Kim Taewoon
Published: December 2024

Vehicular communication is revolutionizing transportation by enhancing passenger experience and improving safety through seamless message exchanges with nearby vehicles and roadside units (RSUs). To accommodate the growing number of vehicles in dense urban traffic with limited channel availability, non-orthogonal multiple access (NOMA) is a promising solution due to its ability to improve spectral efficiency by sharing channels among multiple users. However, to completely leverage NOMA on mobile vehicular networks, a chain of operations and resources must be optimized, including vehicle user (VU) and RSU association, channel assignment, and optimal power control. In contrast, traditional orthogonal multiple access (OMA) allocates separate channels to users, simplifying management but falling short in high-density environments. Additionally, enabling NOMA-OMA switching can further enhance the system performance while significantly increasing the complexity of the optimization task. In this study, we propose an optimized framework to jointly utilize the power domain NOMA in a vehicular network, where dynamic NOMA-OMA switching is enabled, by integrating the optimization of vehicle-to-RSU association, channel assignment, NOMA-OMA switching, and transmit power allocation into a single solution. To handle the complexity of these operations, we also propose simplified formulations that make the solution practical for real-time applications. The proposed framework reduces total power consumption by up to 27% compared to Util&LB/opt, improves fairness in user association by 18%, and operates efficiently with minimal computational overhead. These findings highlight the potential of the proposed framework to enhance communication performance in dynamic, densely populated urban environments.
GDE-Pose: A Real-Time Adaptive Compression and Multi-Scale Dynamic Feature Fusion Approach for Pose Estimation
Authors: Kuok Kaiian , Liu Xuan , Ye Jinwei , Wang Yaokang , Liu Wenjian
Published: December 2024

This paper introduces a novel lightweight pose estimation model, GDE-pose, which addresses the current trade-off between accuracy and computational efficiency in existing models. GDE-pose builds upon the baseline YOLO-pose model by incorporating Ghost Bottleneck, a Dynamic Feature Fusion Module (DFFM), and ECA Attention to achieve more effective feature representation and selection. The Ghost Bottleneck reduces computational complexity, DFFM enhances multi-scale feature fusion, and ECA Attention optimizes the selection of key features. GDE-pose improves pose estimation accuracy while preserving real-time performance. Experimental results demonstrate that GDE-pose achieves higher accuracy on the COCO dataset, with a substantial reduction in parameters, over 80% fewer FLOPs, and an increased inference speed of 31 FPS, underscoring its exceptional lightweight and real-time capabilities. Ablation studies confirm the independent contribution of each module to the model’s overall performance. GDE-pose’s design highlights its broad applicability in real-time pose estimation tasks.
Enhancing Software Effort Estimation with Pre-Trained Word Embeddings: A Small-Dataset Solution for Accurate Story Point Prediction
Authors: Atoum Issa , Otoom Ahmed Ali
Published: December 2024

Traditional software effort estimation methods, such as term frequency–inverse document frequency (TF-IDF), are widely used due to their simplicity and interpretability. However, they struggle with limited datasets, fail to capture intricate semantics, and suffer from dimensionality, sparsity, and computational inefficiency. This study used pre-trained word embeddings, including FastText and GPT-2, to improve estimation accuracy in such cases. Seven pre-trained models were evaluated for their ability to effectively represent textual data, addressing the fundamental limitations of TF-IDF through contextualized embeddings. The results show that combining FastText embeddings with support vector machines (SVMs) consistently outperforms traditional approaches, reducing the mean absolute error (MAE) by 5–18% while achieving accuracy comparable to deep learning models like GPT-2. This approach demonstrated the adaptability of pre-trained embeddings for small datasets, balancing semantic richness with computational efficiency. The proposed method optimized project planning and resource allocation while enhancing software development through accurate story point prediction while safeguarding privacy and security through data anonymization. Future research will explore task-specific embeddings tailored to software engineering domains and investigate how dataset characteristics, such as cultural variations, influence model performance, ensuring the development of adaptable, robust, and secure machine learning models for diverse contexts.
Apple Defect Detection in Complex Environments
Authors: Shan Wei , Yue Yurong
Published: December 2024

Aiming at the problem of high false detection and missed detection rate of apple surface defects in complex environments, a new apple surface defect detection network: space-to-depth convolution-Multi-scale Empty Attention-Context Guided Feature Pyramid Network-You Only Look Once version 8 nano (SMC-YOLOv8n) is designed. Firstly, space-to-depth convolution (SPD-Conv) is introduced before each Faster Implementation of CSP Bottleneck with 2 convolutions (C2f) in the backbone network as a preprocessing step to improve the quality of input data. Secondly, the Bottleneck in C2f is removed in the neck, and Multi-scale Empty Attention (MSDA) is introduced to enhance the feature extraction ability. Finally, the Context Guided Feature Pyramid Network (CGFPN) is used to replace the Concat method of the neck for feature fusion, thereby improving the expression ability of the features. Compared with the YOLOv8n baseline network, mean Average Precision (mAP) 50 increased by 2.7% and 1.1%, respectively, and mAP50-95 increased by 4.1% and 2.7%, respectively, on the visible light apple surface defect data set and public data set in the self-made complex environments.The experimental results show that SMC-YOLOv8n shows higher efficiency in apple defect detection, which lays a solid foundation for intelligent picking and grading of apples.
Analysis of the Influence of Time Harmonics on the Leakage Coefficient of Canned Permanent Magnet Synchronous Motors
Authors: Li Ming , Wang Rong , Chi Lei , Lun Shuxian
Published: December 2024

At present, the influence of time-harmonic currents on the leakage flux coefficient of canned permanent magnet synchronous motors (CPMSMs) remains unclear. Therefore, this paper investigates and summarizes the effects of inverter time-harmonic currents on the leakage flux coefficient of the CPMSM. A 1.5 kW, 9000 RPM (Revolutions Per Minute) CPMSM is used as the research subject. Based on a finite element model, the leakage flux coefficients under sinusoidal and non-sinusoidal supply conditions are calculated using the magnetic flux density integration method. Additionally, the study examines changes in the leakage flux coefficient under different harmonic orders and amplitudes. The results indicate that the introduction of fifth and seventh time-harmonic currents by the inverter reduces the leakage flux coefficient, which helps to improve the utilization of the permanent magnets. This research significantly contributes to enriching the theory of inverter-fed permanent magnet motors.
Design and Performance Analysis of a Parallel Pipeline Robot
Authors: Shen Zhonghua , Xie Menglin , Song Zhendong , Bao Danyang
Published: December 2024

A parallel four-legged pipeline robot is designed to mitigate the issue of uneven motor loading on the single-leg linkage responsible for movement along the pipe diameter. This issue occurs because the drive motor located closer to the robot body requires higher torque when the serial robot operates along the inner wall of a circular polyethylene gas pipe in an urban environment. The forward and inverse kinematic equations for a single-leg linkage are derived to establish the relationship between joint angles and foot trajectories. Building on this analysis, the forward and inverse kinematic solutions for all four legs are also derived. An optimized diagonal trotting gait is selected as the robot’s walking pattern to ensure a balance between stability and movement efficiency, considering the robot’s structural configuration. Motion simulations for both the serial and parallel robots are performed using simulation software, with a detailed analysis of the displacement of the robot’s center of mass and the leg centers during movement. The driving torque of the leg motors in both configurations is controlled and examined. Simulation results indicate that the designed parallel four-legged pipeline robot achieves lower motion error and smoother leg movements within the pipe. Compared to the serial robot, the maximum torque required to drive the leg motors is reduced by approximately 33%, demonstrating the effectiveness and validity of the overall structural design.
Mixed Label Assignment Realizes End-to-End Object Detection
Authors: Chen Jiaquan , Shao Changbin , Su Zhen
Published: December 2024

Currently, detectors have made significant progress in inference speed and accuracy. However, these detectors require Non-Maximum Suppression (NMS) during the post-processing stage to eliminate redundant boxes, which limits the optimization of model inference speed. We first analyzed the reason for the dependence on NMS in the post-processing stage. The result showed that a score loss in a one-to-many label assignment leads to the presence of high-quality redundant boxes, making them difficult to remove. To realize end-to-end object detection and simplify the detection pipeline, we propose herein a mixed label assignment (MLA) training method, which uses one-to-many label assignment to provide rich supervision signals, alleviating the performance degradation, and we eliminate the need for NMS in the post-processing stage by using one-to-one label assignment. Additionally, a window feature propagation block (WFPB) is introduced, utilizing the inductive bias of images to enable feature sharing in local regions. Through these methods, we conducted experiments on the VOC and DUO datasets; our end-to-end detector MA-YOLOX achieved 66.0 mAP and 52.6 mAP, respectively, outperforming the YOLOX by 1.7 and 1.6. Additionally, our model performed faster than other real-time detectors without NMS.
Market Risk of Lithium Industry Chain—Evidence from Listed Companies
Authors: Kong Weicheng , Cheng Jinhua , Xiao Jianzhong
Published: December 2024

Lithium, a crucial raw material for new energy vehicles, is experiencing significant market price fluctuations due to escalating geopolitical conflicts, periodic mismatches in supply and demand, and increased attention to lithium resources from countries around the world. These factors may adversely affect the development of the new energy vehicle industry. This paper adopts the TVP-VAR-DY model, which measures dynamic spillover effects by allowing for variance changes through the estimation of a stochastic Kalman filter, thereby measuring risk spillover among upstream and downstream firms in the lithium industry chain. We selected 16 listed companies and six regional financial markets as the research sample, with the sample period from 4 July 2018, to 30 June 2023. The main conclusions are as follows: Between 2018 and 2020, the overall risk spillover in the lithium industry chain demonstrated a declining trend, though it experienced a sudden surge in 2020 as a result of the COVID-19 pandemic. This increase was followed by a gradual decline as the global economy improved and market stability was restored, leading to a reduction in risk aversion. Regarding the reception of risk spillovers, upstream firms exhibited a generally consistent level of directional risk spillovers, whereas downstream firms experienced more significant fluctuations. Chinese firms exhibited a higher level of received risk spillovers compared to their international counterparts, with less variation in these spillovers. From the perspective of risk spillover effects, significant variations were observed between firms in both the upstream and downstream markets. Chinese firms exhibited a higher level of risk inflow than international firms, with more pronounced changes in risk spillovers. Upstream enterprises should enhance their market competitiveness to mitigate the adverse effects of economic uncertainty. Downstream enterprises can alleviate the rise in raw material costs resulting from market price fluctuations through strategic cooperation. Additionally, the government should increase the market supply of resources, which will contribute to the establishment of a more robust lithium industry chain system.
Energy Utilization of Rapeseed Biomass in Europe: A Review of Current and Innovative Applications
Authors: Suchocki Tomasz
Published: December 2024

Rapeseed (Brassica napus L.) biomass holds significant potential as a renewable energy resource in Europe due to its adaptability, high oil content, and role in biodiesel production. This review explores the energy applications of rapeseed biomass, examining its agronomic characteristics and environmental benefits. A detailed analysis of extraction processes—pressing, solvent extraction, and refining—highlights methods to optimize oil yield and quality. Additionally, the review addresses the use of rapeseed oil in various biofuel applications, including its direct use and in blends with fuels like alcohols and hydrogen, analyzing performance and emissions outcomes. Rapeseed cake, a valuable by-product, is discussed for its dual role as animal feed and as a moderate biofuel alternative. Emissions data and combustion efficiency metrics provide insights into the feasibility of rapeseed oil as a fuel substitute. Overall, this review aims to underscore the contributions of rapeseed biomass to sustainable energy and to identify gaps in current research that can guide future innovations in biofuel production and agricultural sustainability in Europe. Research in rapeseed biomass focuses on optimizing extraction methods, improving combustion efficiency and emission control, exploring advanced uses for rapeseed cake, developing higher-yielding and resilient varieties, conducting lifecycle sustainability assessments, and investigating new biofuel blends and applications.
A Novel Approach of −80 °C Cascade Refrigeration System Using Non-Flammable Quaternary Refrigerants for Semiconductor Process Applications
Authors: Lee Su-Been , Son Chang-Hyo , Lee Joon-Hyuk
Published: December 2024

Ultra-low temperature chillers have seen increasing demand with the advancement of semiconductor technology. Mixed refrigerant (MR) cascade refrigeration systems (CRSs) are widely utilized for their stability and high cooling performance at low temperatures. Extensive research has been conducted on optimizing MR, which has a significant impact on CRS performance. However, most previous studies have either fixed the system pressure or used the refrigeration effect as the sole performance indicator. This did not account for the potential of achieving higher performance with an optimal MR composition at the same target temperature. In this study, a detailed parametric analysis was performed to investigate how the mass fractions of high-, mid-, and low boiling point refrigerants affect the coefficient of performance (COP) and exergy in ultra-low temperature CRSs without fixing the suction pressure. The analysis revealed that at the point of maximum COP, the refrigeration effect was relatively low, highlighting the limitations of using the refrigeration effect alone as a performance indicator. Additionally, COP was found to inversely correlate with total exergy destruction. As cascade temperature increases, COP tends to decrease, emphasizing the need for appropriate cascade temperature selection for MR CRS performance. This study introduces a novel approach to optimizing MR composition under various operating conditions, contributing to the advancement of ultra-low temperature CRSs.
Fluid Dynamic and Thermal Performance of a V-Shape Slotted Cylinder
Authors: Alhashem Abdulwahab , Alshareef Sultan , Alharbi Ali Y. , Alrahmani Mosab A.
Published: December 2024

The flow characteristics and thermal performance of circular cylinders with V-shape slots are investigated numerically. The simulation is a two-dimensional incompressible flow that employs the semi-implicit finite volume multi-material algorithm MPM-ICE, which is a module of the Uintah framework. The normalized slot width s2/D ranges from 0.1 to 0.2, and the corresponding increases in total surface area are from ~99% to ~70%, respectively. Compared to the solid cylinder, the slotted cylinder has the largest total drag reduction of ~67% at s2/D of 0.2. Meanwhile, although the heat transfer is proportional with the surface area, the thermal performance of the V-shape slot first improves with the slot width, and then declines. The heat transfer improvement has an optimum value of ~192% at s2/D of 0.15. The overall slot performance, defined by the ratio of the heat transfer to the drag force, is best at 0.175.
Vanadium-Doped Bi2S3@Co1−xS Heterojunction Nanofibers as High-Capacity and Long-Cycle-Life Anodes
Authors: Yang Haomiao , Liu Lehao , Wu Zhuoheng , Zhang Jinkui , Song Chenhui , Li Yingfeng
Published: December 2024

Lithium-ion batteries (LIBs) are considered one of the most important solutions for energy storage; however, conventional graphite anodes possess limited specific capacity and rate capability. Bismuth sulfide (Bi2S3) and cobalt sulfide (Co1−xS) with higher theoretical capacities have emerged as promising alternatives, but they face challenges such as significant volume expansion during electrochemical cycling and poor electrical conductivity. To tackle these problems, vanadium was doped into Bi2S3 to improve its electronic conductivity; subsequently, a vanadium-doped Bi2S3 (V-Bi2S3)@Co1−xS heterojunction structure was synthesized via a facile hydrothermal method to mitigate volume expansion by the closely bonded heterojunction interface. Moreover, the built-in electric field (BEF) created at the heterointerfaces can significantly enhance charge transport and facilitate reaction kinetics. Additionally, the nanofiber morphology of the V-Bi2S3@Co1−xS heterojunction structure further contributed to improved electrochemical performance. As a result, the V-Bi2S3 electrode exhibited better electrochemical performance than the pure Bi2S3 electrode, and the V-Bi2S3@Co1−xS electrode showed a significantly enhanced performance compared to the V-Bi2S3 electrode. The V-Bi2S3@Co1−xS heterojunction electrode displayed a high capacity of 412.5 mAh g−1 after 2000 cycles at 1.0 A g−1 with high coulombic efficiencies of ~100%, indicating a remarkable long-term cycling stability.
Innovative Approaches to Bridging Energy Supply and Demand Gaps Through Thermal Energy Storage: A Case Study
Authors: Gorás Michal , Domanický Ján , Káposztásová Daniela , Vranay František , Vranayová Zuzana
Published: December 2024

This study investigates innovative solutions for balancing energy supply and demand using long-term thermal energy storage (TES) systems, with a focus on tank thermal energy storage (TTES) for European buildings, which account for approximately 40% of energy consumption in the European Union. Research conducted at the Technical University of Košice explores the potential of TTES systems for efficient and long-term energy storage. The accumulation is carried out in three existing underground tanks of different volumes. Among various outputs, we present the cooling process resulting from covering the water surface and the effect of tank size on cooling. The findings indicate that covering the water surface in the tanks can effectively double the energy retention time, thereby extending the cooling period. A tank with a larger volume cools slower and better ensures the formation of temperature layers. Temperature layering allows for better utilization of the tanks’ potential in terms of energy. The overall result is a significant reduction in heat losses and CO₂ emissions. These results demonstrate the critical role of TTES in stabilizing renewable energy sources, especially solar energy, to support sustainable energy solutions in buildings by providing reliable and long-term energy storage.
Thermal-Management Performance of Phase-Change Material on PV Modules in Different Climate Zones
Authors: Tang Liang , Luo Yong , Yin Linlin , Li Jinwei , Cao Xiaoling
Published: December 2024

Phase-change material (PCM) can enhance the efficiency of photovoltaic (PV) modules by reducing their temperature and is widely studied for thermal management. However, their performance varies due to differences in local solar radiation and climate conditions. Previous studies have mainly focused on the thermal properties of PCM, but practical evaluation should consider specific local conditions. To investigate the thermal-management performance of PCMs in different zones and obtain optimal design parameters, this study investigated the temperature-control effect of PCMs on PV systems across different regions through experiments. The results revealed that the temperature-control performance of PCM was limited in cold regions. Furthermore, the study developed a PCM-PV model and employed response surface methodology along with an NSGA-II to analyze the temperature-control effectiveness of the PCM-PV system in nine regions of China. Pareto solutions were obtained for nine regions in China, balancing annual power generation and system costs. PCM effectiveness is limited in colder regions like Naqu, where it increases power generation by only 0.5%, while in other regions, it improves annual power generation by 1.4% to 3%, especially in areas with high temperatures and abundant solar resources. However, when considering life-cycle gains and initial investment, PCM technology may not always be economically efficient, highlighting the need for region-specific evaluations.