bluuebunny/crossref_metadata_2025 huggingface dataset:
Vulnerability in Children with Celiac Disease: Findings from a Scoping Review
Authors: Macedo Lúcia , Catarino Marta , Festas Constança , Alves Paulo
Published: June 2024

(1) Background: The scientific literature highlights that children diagnosed with celiac disease (CD) are at a heightened risk of experiencing physical, psychological, and social challenges, impacting their overall healthy childhood development. However, there remains a lack of a clear understanding regarding the factors that contribute to this vulnerability. The purpose of this study is to analyze and map the evidence on the sociopsychosomatic vulnerability of these children and identify gaps in this topic. (2) Methods: Following Joanna Briggs Institute’s guidelines for scoping reviews, we executed a detailed search of key electronic databases and explored the grey literature to capture a broad spectrum of studies. Our focus was on identifying research that looked into the multiple dimensions of vulnerability—physical, psychological, and social—in children with CD. We included a diverse range of study designs as well as systematic reviews, ensuring a comprehensive analysis. The selection process was stringent, utilizing clearly defined inclusion and exclusion criteria. (3) Results: We identified 61 studies that met our inclusion criteria. The review highlighted significant adverse health outcomes in children with CD and elucidated various individual and environmental determinants that influenced these vulnerabilities. It also underscored the lack of assessment tools to evaluate the risk of health problems in this population. (4) Conclusions: The findings underscore a critical need for further research to deepen our understanding of the vulnerabilities associated with CD in children. Developing targeted assessment tools will be crucial in stratifying health risks and enhancing care strategies for this vulnerable population.
Preparation of Paste Filling Body and Study on Supported Transportation Laws Using Flac3D Simulation
Authors: Wu Pengfei , Gao Zhenbo , Jin Jiaxu , Lian Fengmei , Li Yanfeng , Liu Tao
Published: June 2024

This paper proposes a new type of gangue filling body (GFB) to address the issues of the low stability, strength, poor shrinkage performance, and inadequate seepage resistance of paste filling materials in overburdened mining conditions, as well as the challenge of fully utilizing solid waste gangue. The coal gangue (CG), U-expanding agent (UEA), and amount of water added were kept constant, and the mass ratio of the various components was adjusted to the design. The standard for filling was assessed using slump tests, uniaxial compression tests, shrinkage tests, and penetration tests. A further microscopic analysis of the pastes with an optimal filling performance was conducted using SEM. The support pressure and overburden migration patterns in the GFBs were evaluated using Flac3D. The results indicate that the GFB with ratio 4 performed best, highlighting the significant role of Portland cement (OPC). The GFB with ratio 3 demonstrated the second-best performance, suggesting that GFBs with a higher early strength should be chosen to fill hollow zones for an effective filling outcome. This study introduced a new type of paste filling material and confirmed the rock transport law of this material under overburdened conditions using Flac3D, offering significant insights for the engineering field.
Research on the Skidding Resistance and Attenuation Characteristics of Asphalt Pavement Based on Image Recognition-Analysis Strategy
Authors: Zhang Ke , Xi Dianliang , Zhao Yu , Xie Wei , Zhang Wei , Gao Jiantao
Published: June 2024

To accurately evaluate the skidding resistance of asphalt pavements, a texture imaging device was developed to realize the standardized acquisition of pavement images. Based on the gray-level co-occurrence matrix and multifractal theory of texture structure, the influence of segregation degree and gradation type on the texture properties of asphalt pavement was studied. Meanwhile, a comprehensive evaluation index of skidding resistance was proposed for asphalt pavement. Furthermore, the attenuation characteristics of the anti-skidding performance for asphalt mixture were explored, and the corresponding attenuation model of asphalt pavement was established. The results show that the segregation degree and gradation type significantly affected the texture parameters and anti-skidding performance of asphalt mixture. Specially, with an increase in the segregation degree of coarse aggregate, the parameters of energy, entropy, and multifractal spectrum width gradually increased, whereas the inertial moment gradually decreased. The variation range of the multifractal spectrum difference initially increased and subsequently decreased. For the texture parameters such as energy, entropy, inertial moment, and multifractal spectrum width Δα, the values of the asphalt mixture with larger nominal maximum particle were higher than those of the mixture with smaller nominal maximum particle, whereas the multifractal spectrum difference value showed the opposite law. In addition, the texture parameters of energy, entropy, and multifractal spectrum width exhibited good linear correlation with the texture depth (TD) of asphalt mixtures with various segregation levels and gradation types. The index based on the texture parameters of energy, entropy, and multifractal spectrum width effectively evaluated the skidding resistance of asphalt pavements, which showed the same trend as the TD with the increase of the abrasion number. The achievement provides an effective solution for the evaluation of skidding resistance and attenuation characteristics of asphalt mixtures.
Exploring the In Vitro Antioxidant, Anti-Aging, and Cytotoxic Properties of Kaempferia galanga Linn. Rhizome Extracts for Cosmeceutical Formulations
Authors: Wichayapreechar Panikchar , Charoenjittichai Ranit , Prasansuklab Anchalee , Vinardell Maria Pilar , Rungseevijitprapa Wandee
Published: June 2024

Kaempferia galanga Linn. (KG), a member of the family Zingiberaceae, is native to India, and commonly found in China, Indonesia, and Thailand. It has been used as a food condiment, folk medicine, and to relieve skin diseases due to its biological activities. However, its anti-aging effect has not yet been investigated. In this study, the rhizome of Kaempferia galanga Linn was extracted with solvents of different polarities (deionized water, absolute ethanol, ethyl acetate, and hexane). Phytochemical screening assay, total flavonoid and total phenolic contents, antioxidant activity (DPPH•, FRAP, ABTS +• assay), anti-aging activity (anti-collagenase, anti-elastase), and cell cytotoxicity on human dermal fibroblasts were investigated. The outcomes revealed that the extraction in highly polar solvents resulted in a high extract yield. Flavonoids, phenolic, and terpenoid compounds were detected in KG extracts using all extraction solvents. However, deionized water as a solvent exhibited the lowest level of flavonoids and phenolics, as compared to the other solvents. The highest total flavonoid and phenolic contents were achieved through extraction with absolute ethanol and ethyl acetate, respectively. Interestingly, the extract obtained with absolute ethanol exhibited the most potent antioxidant activities (the IC50 value of DPPH• was 0.612 mg/mL, the FRAP value was 62.79 mmol of Fe2+/g of extract, and TEAC value was 9.21 mg TE/g of extract in ABTS+• assay) and anti-aging properties (the percentages of collagenase inhibitory and elastase were 71.83%, and 66.35%, respectively). Regarding cell cytotoxicity, both KG extracts obtained with deionized water and absolute ethanol showed lower toxicity on human dermal fibroblasts compared to those obtained with ethyl acetate and hexane. Ethanol-based KG extract demonstrated a good antioxidant, anti-aging capacity and is considered safe for cosmeceutical products focused on anti-aging applications.
Data for Optimal Estimation of Under-Frequency Load Shedding Scheme Parameters by Considering Virtual Inertia Injection
Authors: Bustamante-Mesa Santiago , Gonzalez-Sanchez Jorge W. , Saldarriaga-Zuluaga Sergio D. , López-Lezama Jesús M. , Muñoz-Galeano Nicolás
Published: June 2024

The data presented in this paper are related to the paper entitled “Optimal Estimation of Under-Frequency Load Shedding Scheme Parameters by Considering Virtual Inertia Injection”, available in the Energies journal. Here, data are included to show the results of an Under-Frequency Load Shedding (UFLS) scheme that considers the injection of virtual inertia by a VSC-HVDC link. The data obtained in six cases which were considered and analyzed are shown. In this paper, each case represents a different frequency response configuration in the event of generation loss, taking into account the presence or absence of a VSC-HVDC link, traditional and optimized UFLS schemes, as well as the injection of virtual inertia by the VSC-HVDC link. Data for each example contain the state of the relay, threshold, position in every delay, load shed, and relay configuration parameters. Data were obtained through Digsilent Power Factory and Python simulations. The purpose of this dataset is so that other researchers can reproduce the results reported in our paper.
Quadcopter Unmanned Aerial Vehicle Structural Design Using an Integrated Approach of Topology Optimization and Additive Manufacturing
Authors: Al-Haddad Luttfi A. , Jaber Alaa Abdulhady , Giernacki Wojciech , Khan Zeashan Hameed , Ali Khalid Mohsin , Tawafik Mauwafak Ali , Humaidi Amjad J.
Published: June 2024

The performance of quadcopter frames, particularly in terms of weight and crash resistance, is significantly influenced by their structural design and manufacturing process. In this work, a methodology is proposed that integrates advanced principles of topology optimization (TO) and additive manufacturing (AM) techniques to optimize the frame structure for improved performance. First, an analysis is conducted to evaluate existing quadcopter frame configurations, identifying areas for improvement. Experimental evaluations of thrust and moment of motors are performed to assess the performance of the enhanced quadcopter frame, with a focus on advancing the design through computer-aided simulations of static structural analysis and impact tests. The TO technique is then employed to determine the optimal distribution of material within the frame, governed by constraints such as weight reduction and mechanical strength. The results demonstrate that the overall performance of a quadcopter frame is significantly improved by the proposed methodology, showcasing advancements in stability, weight reduction, and crashworthiness. The resulting optimized frame design is subsequently manufactured using AM methods, which offer advantages such as design flexibility and the ability to produce complex geometries. The findings of this study contribute to the field of quadcopter design and optimization by highlighting the synergies between TO and AM techniques. An avenue is offered for the development of lightweight and robust quadcopter frames, as the capabilities and performance of quadcopter systems are advanced. The insights gained from this research open up opportunities for further advancements in the design and manufacturing of UAVs.
Google Bard and ChatGPT in Orthopedics: Which Is the Better Doctor in Sports Medicine and Pediatric Orthopedics? The Role of AI in Patient Education
Authors: Giorgino Riccardo , Alessandri-Bonetti Mario , Del Re Matteo , Verdoni Fabio , Peretti Giuseppe M. , Mangiavini Laura
Published: June 2024

Background: This study evaluates the potential of ChatGPT and Google Bard as educational tools for patients in orthopedics, focusing on sports medicine and pediatric orthopedics. The aim is to compare the quality of responses provided by these natural language processing (NLP) models, addressing concerns about the potential dissemination of incorrect medical information. Methods: Ten ACL- and flat foot-related questions from a Google search were presented to ChatGPT-3.5 and Google Bard. Expert orthopedic surgeons rated the responses using the Global Quality Score (GQS). The study minimized bias by clearing chat history before each question, maintaining respondent anonymity and employing statistical analysis to compare response quality. Results: ChatGPT-3.5 and Google Bard yielded good-quality responses, with average scores of 4.1 ± 0.7 and 4 ± 0.78, respectively, for sports medicine. For pediatric orthopedics, Google Bard scored 3.5 ± 1, while the average score for responses generated by ChatGPT was 3.8 ± 0.83. In both cases, no statistically significant difference was found between the platforms (p = 0.6787, p = 0.3092). Despite ChatGPT’s responses being considered more readable, both platforms showed promise for AI-driven patient education, with no reported misinformation. Conclusions: ChatGPT and Google Bard demonstrate significant potential as supplementary patient education resources in orthopedics. However, improvements are needed for increased reliability. The study underscores the evolving role of AI in orthopedics and calls for continued research to ensure a conscientious integration of AI in healthcare education.
Homonymous Hemiatrophy of Macular Ganglion Cell Layer as a Marker of Retrograde Neurodegeneration in Multiple Sclerosis—A Narrative Review
Authors: Cujbă Larisa , Banc Ana , Drugan Tudor , Coadă Camelia Alexandra , Cristea Andreea-Petra , Stan Cristina , Nicula Cristina
Published: June 2024

Retrograde axonal neurodegeneration along the visual pathway—either direct or trans-synaptic—has already been demonstrated in multiple sclerosis (MS), as well as in compressive, vascular, or posttraumatic lesions of the visual pathway. Optical coherence tomography (OCT) can noninvasively track macular and optic nerve changes occurring as a result of this phenomenon. Our paper aimed to review the existing literature regarding hemimacular atrophic changes in the ganglion cell layer identified using OCT examination in MS patients without prior history of optic neuritis. Homonymous hemimacular atrophy has been described in post-chiasmal MS lesions, even in patients with normal visual field results. Temporal and nasal macular OCT evaluation should be performed separately in all MS patients, in addition to an optic nerve OCT evaluation and a visual field exam.
The Role of Vascular Cell Adhesion Molecule-1 (VCAM-1) in Predicting Complicated Appendicitis in Children
Authors: Lin Wen-Ya , Lee En-Pei , Chen Chun-Yu , Guo Bei-Cyuan , Lin Mao-Jen , Wu Han-Ping
Published: June 2024

Background: Acute appendicitis is a common abdominal emergency observed in emergency departments (ED). Distinguishing between uncomplicated and complicated appendicitis is important in determining a treatment strategy. Serum soluble vascular cell adhesion molecule-1 (VCAM-1) is an inflammatory biomarker. We aimed to determine the role of VCAM-1 in predicting complicated appendicitis in children. Methods: Pediatric patients with suspected appendicitis admitted to the ED were enrolled in this prospective study. Pre-surgical serum VCAM-1 was tested in children with acute appendicitis within 72 h of symptoms (from day 1 to day 3). Serum VCAM-1 levels were further analyzed and compared between patients with and without complicated appendicitis. Results: Among the 226 pediatric appendicitis patients, 70 had uncomplicated appendicitis, 138 had complicated appendicitis, and 18 had normal appendices. The mean serum VCAM-1 levels in patients with perforated appendicitis were higher than in those with simple appendicitis (p < 0.001). On day 1 to day 3, the mean VCAM-1 levels in patients with complicated appendicitis were all significantly higher than in those with uncomplicated appendicitis (all p < 0.001). Conclusion: Serum VCAM-1 levels may be helpful in differentiating uncomplicated and complicated appendicitis in children and could predict appendiceal perforation.
GETNet: Group Normalization Shuffle and Enhanced Channel Self-Attention Network Based on VT-UNet for Brain Tumor Segmentation
Authors: Guo Bin , Cao Ning , Zhang Ruihao , Yang Peng
Published: June 2024

Currently, brain tumors are extremely harmful and prevalent. Deep learning technologies, including CNNs, UNet, and Transformer, have been applied in brain tumor segmentation for many years and have achieved some success. However, traditional CNNs and UNet capture insufficient global information, and Transformer cannot provide sufficient local information. Fusing the global information from Transformer with the local information of convolutions is an important step toward improving brain tumor segmentation. We propose the Group Normalization Shuffle and Enhanced Channel Self-Attention Network (GETNet), a network combining the pure Transformer structure with convolution operations based on VT-UNet, which considers both global and local information. The network includes the proposed group normalization shuffle block (GNS) and enhanced channel self-attention block (ECSA). The GNS is used after the VT Encoder Block and before the downsampling block to improve information extraction. An ECSA module is added to the bottleneck layer to utilize the characteristics of the detailed features in the bottom layer effectively. We also conducted experiments on the BraTS2021 dataset to demonstrate the performance of our network. The Dice coefficient (Dice) score results show that the values for the regions of the whole tumor (WT), tumor core (TC), and enhancing tumor (ET) were 91.77, 86.03, and 83.64, respectively. The results show that the proposed model achieves state-of-the-art performance compared with more than eleven benchmarks.
Hypothyroidism and Heart Rate Variability: Implications for Cardiac Autonomic Regulation
Authors: Bogdan Carina , Ivan Viviana Mihaela , Apostol Adrian , Sandu Oana Elena , Maralescu Felix-Mihai , Lighezan Daniel Florin
Published: June 2024

Thyroid hormones have a pivotal role in controlling metabolic processes, cardiovascular function, and autonomic nervous system activity. Hypothyroidism, a prevalent endocrine illness marked by inadequate production of thyroid hormone, has been linked to different cardiovascular abnormalities, including alterations in heart rate variability (HRV). The study included 110 patients with hypothyroid disorder. Participants underwent clinical assessments, including thyroid function tests and HRV analysis. HRV, a measure of the variation in time intervals between heartbeats, serves as an indicator of autonomic nervous system activity and cardiovascular health. The HRV values were acquired using continuous 24-h electrocardiogram (ECG) monitoring in individuals with hypothyroidism, as well as after a treatment period of 3 months. All patients exhibited cardiovascular symptoms like palpitations or fatigue but showed no discernible cardiac pathology or other conditions associated with cardiac disease. The findings of our study demonstrate associations between hypothyroidism and alterations in heart rate variability (HRV) parameters. These results illustrate the possible influence of thyroid dysfunction on the regulation of cardiac autonomic function.
A Performance Assessment on Rotor Noise-Informed Active Multidrone Sound Source Tracking Methods
Authors: Yen Benjamin , Yamada Taiki , Itoyama Katsutoshi , Nakadai Kazuhiro
Published: June 2024

This study evaluates and assesses the performance of recent developments in sound source tracking using microphone arrays from multiple drones. Stemming from a baseline study, which triangulates the spatial spectrum calculated from the MUltiple SIgnal Classification (MUSIC) for each drone, otherwise known as Particle Filtering with MUSIC (PAFIM), recent studies extended the method by introducing methods to improve the method’s effectiveness. This includes a method to optimise the placement of the drone while tracking the sound source and methods to reduce the influence of high levels of drone rotor noise in the audio recordings. This study evaluates each of the recently proposed methods under a detailed set of simulation settings that are more challenging and realistic than those from previous studies and progressively evaluates each component of the extensions. Results show that applying the rotor noise reduction method and array placement planning algorithm improves tracking accuracy significantly. However, under more realistic input conditions and representations of the problem setting, these methods struggle to achieve decent performance due to factors not considered in their respective studies. As such, based on the performance assessment results, this study summarises a list of recommendations to resolve these shortcomings, with the prospect of further developments or modifications to PAFIM for improved robustness against more realistic settings.
Spatial Aspect of Global Value Chain in East Asia: How Ports and Airports Shape Industrial Clusters in East Asia
Authors: Kumagai Satoru
Published: June 2024

This paper examines how geography matters for the location of industries in East Asia, employing regression analyses on a novel and comprehensive regional GDP dataset. This study examines how geography affects industrial location patterns, particularly the role of infrastructure, such as ports and airports. This paper analyzes the current economic geography of East Asia using the novel dataset. The regression analyses utilize location quotients as the dependent variable and incorporate explanatory variables, such as domestic/foreign market access, per capita income, population density, and distance-based dummies for ports and airports. The findings reveal that the determinants of industrial location differ significantly across industries. The relative importance of domestic versus foreign market access and proximity to ports and airports varies across sectors. The results imply that countries/regions cannot easily host industries of their choice, as different industries require distinct locational characteristics.
Coding Decoded: Exploring Course Achievement and Gender Disparities in an Online Flipped Classroom Programming Course
Authors: Malkoc Smirna , Steinmaurer Alexander , Gütl Christian , Luttenberger Silke , Paechter Manuela
Published: June 2024

In introductory programming courses (IPCs), students encounter various difficulties that are related to low achievement and high dropout and failure rates. Technology-rich approaches that promote self-directed learning while facilitating competency development and knowledge construction through social collaboration may offer advantages in this context. The current study assesses such an instructional approach by (1) identifying antecedents and process variables related to course achievement in an online flipped classroom IPC and (2) testing for gender differences regarding antecedents, process variables, and course achievement. In the winter semester of 2020/21, a sample of 144 Austrian university students participated in a survey with measurements at different points in time. Multiple linear regression was carried out to explore factors related to course achievement. The results indicate that gender, achievement-avoidance goals, academic self-concept, engagement in asynchronous learning, and course satisfaction were positively related to achievement. In contrast, work avoidance was identified as a barrier to achievement. Additionally, multivariate analysis of variance (MANOVA) was employed to test gender differences. MANOVA revealed significant gender differences regarding learning goals, mathematical self-concept, work avoidance, and engagement in synchronous learning. There were no gender differences regarding course satisfaction or achievement. The study has implications for designing innovative programming courses that could foster course satisfaction and achievement and thus reduce dropout and failure rates.
Virtual Reality in Preservice Teacher Education: Core Features, Advantages and Effects
Authors: Van der Want Anna C. , Visscher Adrie J.
Published: June 2024

This article presents a review of the research into the use of virtual reality (VR) for preservice teacher education. In addition to generating a description of the nature of VR, the analysis of the 24 included studies showed that the use of VR in preservice teacher education can have several benefits for student teachers and their educators, such as practicing professional competence in safe and diverse VR environments, the possibility of monitoring student development with VR, the use of learning environments that would not be accessible, and distance education for student teachers when schools for internships are located too far away from a teacher training institute. Although research into the effects of the use of VR in preservice teacher education is still limited, the results thus far indicate positive effects on student teachers’ motivation, self-efficacy, and various classes of teacher skills. We reflect on the challenges with respect to designing VR environments for preservice teacher education and on studying VR effects on teaching quality and student learning outcomes.
“Active Mathematics”—A Classroom-Based Physical Active Learning Intervention in an Elementary School: An Experimental Pilot Study
Authors: Ramos Liliana , Simões Vera , Franco Susana
Published: June 2024

This experimental pilot study aimed to compare the amount of physical activity (PA) of children in a second-year class of an elementary school that had a mathematics class while performing PA, based on playful math games, with children that had a mathematics class seated in a traditional room, for 12 weeks 1 day/week 45 min/class; furthermore, the other two mathematics regular seated classes were attended equally by both groups, and whether both groups showed similar results concerning mathematics grading was assessed. Children (n = 22) were randomly divided into a control group (CG) and an experimental group (EG). In both groups, the number of steps (PA) was measured with a pedometer, before and during all sessions of the intervention program, and an initial diagnostic and a final assessment mathematics test were carried out. EG significantly improved the amount of PA levels in the intervention program, when compared to CG and to the initial baseline (before the program started), with no significant differences between groups in the results of mathematics grading. The introduction of active classes based on playful maths games increases the amount of PA levels in children, and having one math class per week using PA, instead of seating in a traditional room, does not negatively affect the results in terms of mathematics grading. These positive results can contribute to more approaches, at schools, that combine PA and mathematics content.
Content and Sentiment Analysis of Autobiographical Narratives of Experienced and Well-Evaluated Teachers in Spain
Authors: Barbosa Mayara Lustosa de Oliveira , Marín-Suelves Diana
Published: June 2024

Analysing the content and feelings of teachers’ autobiographical narratives provides relevant information about teaching processes, challenges in professional development, performance, and identity. In this work, we analysed the narratives of five well-evaluated Spanish teachers with more than 10 years of experience. We used Iramuteq, RStudio, and TextRazor to describe the main themes, analyse the emotions, and check whether evidence-based teaching practices were mentioned. The results showed that emotional aspects were central, with positive feelings dominating. In the content analysis, themes such as mental health, inclusion, immigration, war, empathy, critical pedagogy, and autonomous and emancipatory education stand out. The analyses are relevant for teacher educators, policy makers, researchers, and teachers in training or in active service.
ChatGPT in Teaching and Learning: A Systematic Review
Authors: Ali Duha , Fatemi Yasin , Boskabadi Elahe , Nikfar Mohsen , Ugwuoke Jude , Ali Haneen
Published: June 2024

The increasing use of artificial intelligence (AI) in education has raised questions about the implications of ChatGPT for teaching and learning. A systematic literature review was conducted to answer these questions, analyzing 112 scholarly articles to identify the potential benefits and challenges related to ChatGPT use in educational settings. The selection process was thorough to ensure a comprehensive analysis of the current academic discourse on AI tools in education. Our research sheds light on the significant impact of ChatGPT on improving student engagement and accessibility and the critical issues that need to be considered, including concerns about the quality and bias of generated responses, the risk of plagiarism, and the authenticity of educational content. The study aims to summarize the utilizations of ChatGPT in teaching and learning by addressing the identified benefits and challenges through targeted strategies. The authors outlined some recommendations that will ensure that the integration of ChatGPT into educational frameworks enhances learning outcomes while safeguarding academic standards.
An Efficient Masked White-Box Implementation of SM4
Authors: Zhao Dongyan , Wang Yubo , Li Yan , Hu Xiaobo , Yu Yanyan , Chen Shi , Zheng Shihui
Published: June 2024

Differential computation analysis (DCA) is a powerful method for extracting secret information from carefully designed white-box schemes without reverse engineering. Consequently, white-box solutions typically require substantial storage and computing resources to withstand DCAs, as demonstrated by the schemes proposed by Zhang et al. and Yuan et al. for the ISO/IEC standard algorithm SM4. Our approach employs Boolean masking to obscure the correlation between the key and intermediate states. Additionally, we introduce nonlinear permutations to reuse random mask values, thereby reducing space consumption. Experimental results indicate that DCAs against both the simplified version and the algebraic enhancement version of our scheme fail to retrieve the correct keys. Moreover, the former version can be implemented with approximately 1.62 MB of memory and the latter with 7.8 MB, which is much less than 24.3 MB (Zhang et al.) and 34.5 MB (Yuan et al.). Consequently, our design can thwart first-order DCA with lower overhead.
The Level of Physical Activity, E-Game-Specific Reaction Time, and Self-Evaluated Health and Injuries’ Occurrence in Non-Professional Esports Players
Authors: Cyma-Wejchenig Magdalena , Maciaszek Janusz , Ciążyńska Julia , Stemplewski Rafał
Published: June 2024

This study aims to compare physical activity levels, esports-specific reaction times, self-evaluated health, and injuries between non-professional esports players (EPs) and non-players (NPs). Participants were healthy, with an average age of 22.7 ± 2.49 years and BMI of 25.5 ± 4.95 kg/m2. Physical activity was quantified using the Baecke Questionnaire, while reaction times were measured with computer games. The analysis reveals that EPs exhibit significantly lower levels of physical activity compared to NPs (p < 0.05), underscoring the sedentary nature of esports. Despite this, EPs demonstrate superior reaction times (p < 0.001), suggesting cognitive enhancements associated with esports participation. EPs report increased incidences of gameplay-related discomfort (p = 0.025), highlighting health drawbacks of prolonged gaming. However, no significant differences were observed in overall self-evaluated health statuses and specific pain complaints between the groups, indicating a complex relationship between esports involvement and perceived health outcomes. These findings suggest that esports can offer cognitive benefits through improved reaction times but are also associated with reduced physical activity and increased reporting of discomfort. This dichotomy underscores the need for strategies that capitalize on the cognitive advantages of esports while mitigating its physical health risks, encouraging a more balanced engagement with the activity.
A Novel Self-Adaptation Approach for Multi-Domain Communication Considering Heterogenerous Power Service in Data Centers
Authors: Bu Xian-De , Liu Shi-Dong , Hou Meng , Liu Chuan , Zhang Xi
Published: June 2024

With the rapid development of cloud computing, artificial intelligence, etc., data centers have become a flexible load due to their adjustable capabilities and are able to take on power service. However, the existing communication architecture is monolithic and poorly adapted between services and communications, which poses a challenge for data centers to participate in power service. Firstly, this article constructs a multi-domain communication architecture for data center management systems that includes local and remote communication, and analyzes the key technologies supporting this architecture. Secondly, based on differentiated service types and communication requirements, an evaluation system for the adaptability between service and communication technology was constructed, and a communication mode adaptation method based on fuzzy analytic hierarchy process (FAHP)-improved CRITIC combined weighting model and grey Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) was proposed to achieve the analysis of the adaptability between differentiated service and multi-domain communication technology. According to the analysis of examples, the architecture and adaptation algorithm proposed in this article provide an effective theoretical basis and solution for the selection of multi-domain communication technologies for data center management system service.
Ice Cover Prediction for Transmission Lines Based on Feature Extraction and an Improved Transformer Scheme
Authors: Ke Hongchang , Sun Hongbin , Zhao Huiling , Wu Tong
Published: June 2024

Frequent and severe icing on transmission lines poses a serious threat to the stability and safe operation of the power system. Meteorological data, inherently stochastic and uncertain, requires effective preprocessing and feature extraction to ensure accurate and efficient prediction of transmission line icing thickness. We address this challenge by leveraging the meteorological features of icing phenomena and propose a novel feature preprocessing method that integrates Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) and spectral clustering. This method effectively preprocesses raw time series data, extracts key features, and constructs a similarity matrix and feature vector. The resulting feature vector serves as a new data representation, facilitating cluster analysis to isolate meteorological and icing-related features specific to transmission lines. Subsequently, we introduce an enhanced Transformer model for predicting transmission line icing thickness. The proposed model leverages the extracted meteorological and icing features by independently embedding variable tokens for each input feature. This approach improves the model’s prediction accuracy under multiple feature inputs, leading to more effective learning. The experimental results demonstrate that the performance of the proposed prediction algorithm is better than the three baseline algorithms (hybrid CEEMDAN and LSTM (CEEMDAN-LSTM), hybrid CEEMDAN, spectral clustering, and LSTM (CEEMDAN-SP-LSTM), and hybrid CEEMDAN, spectral clustering, and Transformer (CEEMDAN-SP-Transformer)) under multiple feature inputs and different parameter settings.
Path Planning of a Mobile Robot Based on the Improved Rapidly Exploring Random Trees Star Algorithm
Authors: Wang Jiqiang , Zheng Enhui
Published: June 2024

With the increasing utilization of sampling-based path planning methods in the field of mobile robots, the RRT* algorithm faces challenges in complex indoor scenes, including high sampling randomness and slow convergence speed. To tackle these issues, this paper presents an improved RRT* path-planning algorithm based on the generalized Voronoi diagram with an adaptive bias strategy. Firstly, the algorithm leverages the properties of the generalized Voronoi diagram (GVD) to obtain heuristic paths, and a sampling region with target bias is constructed, increasing the purposefulness of the sampling process. Secondly, the node expansion process incorporates an adaptive bias strategy, dynamically adjusting the step size and expanding direction. This strategy allows the algorithm to adapt to the local environment leading to improved convergence speed. To ensure the generation of smooth paths, the paper employs the cubic spline curve interpolation algorithm for trajectory optimization to ensure that the mobile robotic can obtain the best trajectory. Finally, the proposed algorithm is experimentally compared with existing algorithms, including the RRT* and Informed-RRT* algorithms, to verify the feasibility and stability.
RFP-MSR Hybrid Reactor Model for Tritium Breeding and Actinides Transmutation †
Authors: Murgo Stefano , Bustreo Chiara , Ciotti Marco , Lomonaco Guglielmo , Orsitto Francesco Paolo , Piovan Roberto , Pompeo Nicola , Ricco Giovanni , Ripani Marco , Panza Fabio
Published: June 2024

The studies on the development of fusion–fission hybrid reactors (FFHR) have gained consensus in recent years as an intermediate step before fusion energy. This work proposes a possible approach to FFHRs based on the coupling of a Reversed Field Pinch fusion machine and a Molten Salt Subcritical fission test bed. The proposed test bed is characterized by the coexistence of a fast-neutron fission core and a dedicated thermal-neutron zone, allowing the performing of tritium breeding and actinides transmutation studies. The neutronic design solutions and the results obtained by the irradiation of FLiBe salt (inside the thermal-neutron zone) and of an actinide target (inside the core) are shown. The outcomes of the analysis reveal the potential of FFHR systems as breeding/burner systems. In particular, the results regarding tritium breeding are very encouraging as the system is demonstrated to be able to reach a very high Tritium Breeding Ratio.
The Impact of the Location of a Passive Frame House on Its Energy Demand for the Purpose of Heating—A Case Study
Authors: Wąs Krzysztof
Published: June 2024

The reduction of energy demand in buildings is one of the key challenges in contemporary construction. To this end, the application of structural and material partitioning solutions that provide a high level of thermal insulation and the employment of technical installations with high energy performance have become widespread. However, there are a number of other factors that can reduce energy demand. These include the optimal use of heat gains from solar radiation. An aspect that is often discussed in the literature is the overheating of buildings due to excessive heat gains from solar radiation. This article is a case study showing the impact of the orientation of a single-family passive house on its heating energy demand. The building under consideration is located in Central Europe. External climate parameters measured directly at the site during experimental examinations were used for the calculations. This paper adopts six calculation options, considering the different orientations of the glazed façade. As the simulations showed, the effect of solar radiation on the energy demand between two extreme options of glazing orientation, that is south and north-facing orientation, reached 4.7% of the annual energy demand for heating, while for the option corresponding to the actual location of the building and the option involving south-facing windows, the difference was 0.3%, respectively.
Topographic Variation in Ecosystem Multifunctionality in an Old-Growth Subtropical Forest
Authors: Wang Jiaming , Xu Han , Yang Qingsong , Li Yuying , Ji Mingfei , Li Yepu , Chang Zhongbing , Qin Yangyi , Yu Qiushi , Wang Xihua
Published: June 2024

Exploring the relationship between topography and forest multifunctionality enhances understanding of the mechanisms maintaining forest multifunctionality and proves beneficial for managing overall forest functions across different landscapes. Leveraging census data from a 20 ha subtropical forest plot, we investigated the topographic variations in individual functions, multifunctionality, and their interrelationships. Our results revealed that relative to lower elevations, higher elevations had higher woody productivity, sapling growth, and recruitment that drove higher average forest multifunctionality (FMA). However, forest multifunctionality at the 50% threshold level (FMt50) had no significant difference between high and low elevations. Compared with the valley and slope, higher woody productivity, higher sapling recruitment, and higher soil organic carbon stock drove higher forest multifunctionality (FMA and FMt50) in the ridge. These results indicate the ridge serves as a forest multifunctionality “hotspot” within the Tiantong 20 hm2 plot. Additionally, relative to the low elevation, the degree of synergy among functions at the high elevation was significantly lower, indicating difficulties in attaining high forest multifunctionality at the high elevation. Our work underscores the importance of topography in regulating subtropical forest multifunctionality and relationships between forest functions at a local scale, suggesting that future forest management strategies (such as regulating synergistic or trade-off relationships between functions) should give particular attention to topographic conditions.
Oxidative Status of the Pyloric Caeca and Proximal Intestine in Gilthead Sea Bream Fed Diets Including Different Vegetable Oil Blends from Palm, Rapeseed and Linseed
Authors: García-Meilán Irene , Fontanillas Ramon , Gutiérrez Joaquim , Capilla Encarnación , Navarro Isabel , Gallardo Ángeles
Published: June 2024

Nowadays, including vegetable ingredients in fish diets without growth effects is common; however, their intestinal oxidative status under these conditions is less known. Five isonitrogenous and isolipidic diets with 75% vegetable oil (VO) inclusion were formulated for juvenile gilthead sea bream (Sparus aurata). As VO, one diet contained palm oil (diet P), another rapeseed oil (diet R), and the other three included linseed oil (L) combined with the above-mentioned VOs (named PL, RL and RPL diets). After 18 weeks, pyloric caeca (PC) and proximal intestine (PI) were analyzed for oxidative stress biomarkers, lipid peroxidation (LPO), and gene expression. Dietary linseed oil diminished the superoxide dismutase activity in both intestinal regions, catalase in PC and glutathione reductase in PI; rapeseed oil reduced the glutathione peroxidase (GPx) and glutathione-S-transferase activities in PC, and palm oil upregulated GPx activity in PI. The PL diet triggered LPO levels in the PI, and RPL-fed fish showed the highest levels of LPO in the PC due to lower antioxidant activities, while RL-fed fish presented the best oxidative status. The results suggest that the dietary amount of n-6 and the unsaturated/saturated fatty acids ratio are factors to be considered in aquafeed formulation, including VOs, to improve the intestinal oxidative status in fish.
Interrupter Technique Revisited: Building an Experimental Mechanical Ventilator to Assess Respiratory Mechanics in Large Animals
Authors: Zilianti Camilla , Bashar Erfan , Kyriakoudi Anna , Pecchiari Matteo
Published: June 2024

Large animals are increasingly used as experimental models of respiratory diseases. Precise characterization of respiratory mechanics requires dedicated equipment with specific characteristics which are difficult to find together in the same commercial device. In this work, we describe building and validation of a computer-controlled ventilator able to perform rapid airways occlusions during constant flow inflations followed by a prolonged inspiratory hold. A constant airflow is provided by a high pressure source (5 atm) connected to the breathing circuit by three proportional valves. The combined action of three 2-way valves produces the phases of the breath. During non-inspiratory breath phases, airflow is diverted to a flowmeter for precise feedback regulation of the proportional valves. A computer interface enables the user to change the breathing pattern, trigger test breaths or run predetermined breaths sequences. A respiratory system model was used to test the ability of the ventilator to correctly estimate interrupter resistance. The ventilator was able to produce a wide range of constant flows (0.1–1.6 L/s) with the selected timing. Errors in the measurement of interrupter resistance were small (1 ± 5% of the reference value). The device described reliably estimated interrupter resistance and can be useful as a measuring tool in large animal research.
Three-Dimensional Long-Wave Instability of an Evaporation/Condensation Film
Authors: Jiang Weiyang , Huang Ruiqi , Yang Qiang , Ding Zijing
Published: June 2024

This paper explores the stability and dynamics of a three-dimensional evaporating/condensing film while falling down a heated/cooled incline. Instead of using the Hertz–Knudsen–Langmuir relation, a more comprehensive phase-change boundary condition is employed. A nonlinear differential equation is derived based on the Benny-type equation, which takes into account gravity, energy transport, vapor recoil, effective pressure, and evaporation. The impact of effective pressure and vapor recoil on instability is studied using a linear stability analysis. The results show that spanwise perturbations can amplify the destabilizing effects of vapor recoil, leading to instability. Energy transport along the interface has almost no effect on the stability of the system, but it does influence the linear wave speed. Nonlinear evolution demonstrates that, in contrast to the vapor recoil effect, effective pressure can improve stability and delay film rupture. The self-similar solution demonstrates that the minimal film thickness decreases as (tr−t)1/2 and (tr−t)1/3 under the dominance of evaporation and vapor recoil, respectively.
Molecular Regulatory Mechanisms Affecting Fruit Aroma
Authors: Lu Haifei , Zhao Hongfei , Zhong Tailin , Chen Danwei , Wu Yaqiong , Xie Zhengwan
Published: June 2024

Aroma, an important quality characteristic of plant fruits, is produced by volatile organic compounds (VOCs), mainly terpenes, aldehydes, alcohols, esters, ketones, and other secondary metabolites, in plant cells. There are significant differences in the VOC profile of various fruits. The main pathways involved in the synthesis of VOCs are the terpenoid, phenylalanine, and fatty acid biosynthesis pathways, which involve several key enzyme-encoding genes, transcription factors (TFs), and epigenetic factors. This paper reviews the main synthetic pathways of the main volatile components in fruit, summarizes studies on the regulation of aroma formation by key genes and TFs, summarizes the factors affecting the fruit aroma formation, describes relevant studies on the improvement of fruit flavor quality, and finally proposes potential challenges and prospects for future research directions. This study provides a theoretical basis for the further precise control of fruit aroma quality and variety improvement.
Fractional Operators and Fractionally Integrated Random Fields on Zν
Authors: Pilipauskaitė Vytautė , Surgailis Donatas
Published: June 2024

We consider fractional integral operators (I−T)d,d∈(−1,1) acting on functions g:Zν→R,ν≥1, where T is the transition operator of a random walk on Zν. We obtain the sufficient and necessary conditions for the existence, invertibility, and square summability of kernels τ(s;d),s∈Zν of (I−T)d. The asymptotic behavior of τ(s;d) as |s|→∞ is identified following the local limit theorem for random walks. A class of fractionally integrated random fields X on Zν solving the difference equation (I−T)dX=ε with white noise on the right-hand side is discussed and their scaling limits. Several examples, including fractional lattice Laplace and heat operators, are studied in detail.