bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigating the Fatigue Response of Cathodically Charged Cold-Finished Mild Steel to Varied Hydrogen Concentrations
Authors: Sey Emmanuel , Farhat Zoheir N.
Published: September 2024

This study investigates the fatigue behavior of cold-finished mild steel subjected to electrochemical hydrogen charging under controlled conditions. Samples were subjected to hydrogen charging at constant time in a fixed electrolyte pH, after which the samples underwent fatigue testing under constant loading condition with fixed frequency. The primary objective was to assess the impact of varying hydrogen permeation levels on the number of cycles to failure. The experimental results revealed a complex relationship between hydrogen concentration and fatigue life. Initially, as hydrogen permeation increased, the number of cycles to failure substantially decreased, demonstrating the detrimental effect of diffused hydrogen on the fatigue resistance of samples. This decline in fatigue life was attributed to hydrogen embrittlement (HE) and hydrogen-enhanced decohesion (HEDE) phenomena, which collectively facilitate crack initiation and propagation. However, at high hydrogen concentrations, an unexpected increase in the number of cycles to failure was observed suggesting the existence of a threshold hydrogen concentration beyond which the fatigue mechanisms may be altered, potentially due to a saturation of hydrogen-related defects and mechanisms such as hydrogen-enhanced localized plasticity (HELP). The discovery from this research has significant implications for the material’s application in hydrogen-rich environments, such as those encountered in the energy and transportation industries.
Microstructure and Tribological Properties of WC/Ni-MoS2 Titanium-Based Composite Coating on TC4
Authors: Wang Changhao , Yan Xiaohui , Zhang Tiangang , Zhang Qiyu , Zhang Zhiqiang
Published: September 2024

To improve the mechanical properties of a TC4 surface, TC4 + Ni-MoS2 + xWC (x = 5%, 10% and 15% wt.%) composite coatings were prepared by the coaxial feeding laser cladding technique, and the effect of the WC content on the microstructure and tribological properties of the coatings were investigated using multiple characterization methods. The results indicated that increasing the WC content negatively impacted the forming quality of the coating, but did not change the coating phase which predominantly comprised Ti2Ni, Ti2S, TiC, matrix β-Ti and residual WC. With the addition of WC, TiC exhibited an increase in both quantity and particle size, accompanied by a transition in growth morphology from spherical to petal-like. MoS2 completely dissolved in all coatings and the S element provided by it effectively synthesized a strip-like phase Ti2S which presented a morphology similar to the lubricating phase TiS in the Ti-based melt pool system. The microhardness and wear-resistance of all the coatings were higher than that of TC4 and gradually improved with the addition of WC, which indicated that raising the WC content was conducive to enhancing the mechanical properties of the coatings. The friction coefficient of TC4 was lower than that of the three WC content coatings, indicating that Ti2S was not the lubricating phase. The wear mechanism of all coatings was abrasive wear.
Assessment of Warionia saharea Essential Oil as a Green Corrosion Inhibitor for Mild Steel in HCl: Experimental and Computational Studies
Authors: Ansari Abdeslam , Youssefi Youssef , Tanghourte Mohamed , Ouassou Nazih , Asoufar Nazih , Znini Mohamed , Lgaz Hassane , Mabrouk El Houssine , Azrour Mohamed , Lee Han-Seung , Hammouti Belkheir
Published: September 2024

The objective of this research work is the study of the inhibitory effect of Warionia saharea essential oil (WSEO) on the corrosion of mild steel (MS) in molar HCl solution, employing both experimental and theoretical methods. This inhibitory effect (IE) has been evaluated by using a combination of weight loss measurements (LW) and various electrochemical methods, such as open circuit potential (OCP), potentiodynamic polarization (PDP) and electrochemical impedance spectroscopy (EIS) experiments. The LW results indicated that IE increased with inhibitor concentration, reaching 83.34% at 3.00 g/L. The PDP analysis suggested that WSEO functions as a mixed inhibitor, while in the EIS results the Rct values increased with inhibitor concentration to reach 165.8 Ω cm2 at 2.00 g/L, suggesting a defensive film formation by WSEO molecules over the metallic surface. The thermodynamic study demonstrated that the WSEO molecules adsorption on the MS surface followed a Langmuir isotherm, involving mixed physical and chemical (physicochemical) adsorption on the MS surface. Theoretical methods, including density functional theory (DFT) and molecular dynamics (MD) simulations, were employed to elucidate the inhibition mechanisms of the three main components of WSEO. The quantum chemical analysis, using density functional theory (DFT) and molecular dynamics (MD) simulations, showed a low ΔEgap value of 6.30 eV and a low adsorption energy (Eads) value on an Fe (110) substrate of −258 Kcal/mol for (E)-Nerolidol, indicating the significant contribution of this molecule to the overall corrosion inhibition effect of WSEO. The scanning electron microscope (SEM) analysis verified the presence of a protective film formed by the inhibitor on the MS surface. This study highlights the potential of WSEO as a sustainable and green corrosion inhibitor in acidic environments.
A Review of the Anti-Inflammatory Skincare Potential of Epilobium angustifolium (Fireweed) Inspired by Herbal Tradition
Authors: Ailus Jaana , Saleem Imran , Ismail Fyaz M. D.
Published: September 2024

The demand for naturally derived cosmetic ingredients is rising as consumers increasingly prioritize green and environmentally friendly products. Naturally derived ingredients, such as plant extracts rich in polyphenols like flavonoids and tannins, are often perceived as more sustainable and beneficial for skincare. Epilobium angustifolium (fireweed) is a circumpolar plant with traditional uses in Northern and Eastern Europe known for its skincare benefits. This review explores the chemical composition, traditional uses, and potential skincare benefits of E. angustifolium, focusing on its anti-inflammatory and antioxidant properties. Literature surveys, ethnopharmacological research, and database searches were conducted to investigate the properties of E. angustifolium. The plant contains various compounds such as flavonoids, phenolic acids, tannins, steroids, and triterpenes, each with potential skincare benefits. Pharmacological reports suggest that E. angustifolium exhibits antioxidant and antibacterial properties, making it a valuable ingredient in skincare products. The availability of E. angustifolium in the market as a raw material for cosmetics offers opportunities for formulators to create innovative products with skin-conditioning and anti-inflammatory properties. Understanding the chemical composition and bioactivity of E. angustifolium can guide the development of effective and sustainable skincare formulations.
Navigating the Dynamic Landscape of SARS-CoV-2: The Dual Role of Neutralizing Antibodies, Variability in Responses, and Strategies for Adaptive Pandemic Control
Authors: Iyer Venkatesh Anand , Mohan Aditi , Kumar Dharmender , Dahiya Praveen
Published: September 2024

The global pandemic sparked by the emergence of SARS-CoV-2 and its variants has imposed a substantial burden of morbidity and mortality. Central to the battle against these viral threats is the immune response, with a spotlight on the pivotal role played by neutralizing antibodies. This comprehensive review delves into current research, unravelling the dual functionality of neutralizing antibodies acting as formidable barriers to viral replication and crucial facilitators of adaptive immune memory. Beyond this dual purpose, the review illuminates the nuanced variability characterizing neutralizing antibody responses to SARS-CoV-2. Emphasizing the dynamic nature of these responses, the review advocates for the plausible challenges in targeted therapeutic interventions. This review also attempts to compare various vaccination approaches and their impact on SARS-CoV-2, as well as offer insights into various Omicron variations. Recognizing the ever-evolving viral landscape, this exploration underscores the necessity of flexible approaches to address the diverse challenges posed by SARS-CoV-2 and its variants, contributing valuable insights to the ongoing global efforts in pandemic mitigation and public health safeguarding.
Strict Avalanche Criterion of SHA-256 and Sub-Function-Removed Variants
Authors: Vaughn Riley , Borowczak Mike
Published: September 2024

The measure of diffusion, the property of dissipating patterns and statistical structures in cryptographic transformations, serves as a valuable heuristic for assessing the obscurity of patterns that could lead to collisions. As with many cryptographic hash functions, SHA-256 is thought to exhibit the property of diffusion. While SHA-256’s diffuse output is loosely documented, even less is known about how the diffusion rate changes across the 64 rounds in its compression function and how the algorithm’s individual sub-functions contribute to the overall diffusion. The diffusion of the unmodified compression function is initially measured using the Strict Avalanche Criterion (SAC), with the aim of understanding the alteration in diffusion across the 64 rounds of compression. The level to which sub-functions affect diffusion is subsequently measured, enabling potential prioritization of these sub-functions in future collision attacks. To accomplish this, the compression function is modified by removing sub-functions, and the diffusion of these new variants is measured. While the SAC measurements of each function eventually plateau close to the 50% target, no function, including the unmodified compression function, strictly meets the SAC, and multiple variant functions diffuse at comparatively slower rates.
Prediction of Intriguing Valley Properties in Two-Dimensional Hf2TeIX (X = I, Br) Monolayers
Authors: He Kaiyuan , Wang Peiji
Published: September 2024

The valley degree of freedom, as a new information carrier, is important for basic physical research and the development of advanced devices. Herein, using first-principle calculations, we predict that two-dimensional Hf2TeIX (X = I, Br) monolayers harbor intriguing valley properties. Without considering spin–orbit coupling (SOC), the Hf2TeI2 monolayer has a semi-metallic nature, with Dirac cones located at the high-symmetry point K, and feature, with considerable Fermi velocity. When the SOC is taken into account, a band gap opening of 271 meV can be observed at the Dirac cones. More interestingly, the Hf2TeIBr monolayer exhibits intrinsic spatial inversion symmetry breaking, which leads to the emergence of valley-contrasting physics under SOC. This is demonstrated by the presence of spin–valley splitting and opposite Berry curvature at adjacent K points. Besides, the spin–valley splitting, the band gap and magnitude of the Berry curvature of the Hf2TeIBr monolayer can be effectively tuned by strain engineering. These findings contribute significantly to the design of valleytronic devices and extend opportunities for exploring two-dimensional valley materials.
Biodiversity, Ecological Status and Ecosystem Attributes of Agricultural Ditches Based on the Analysis of Macroinvertebrate Communities
Authors: Chiorino Martina , Spreafico Cristina , Solazzo Davide , Doretto Alberto
Published: September 2024

Ditches are widespread and common elements of the agricultural landscape. Although they can provide habitats for aquatic biodiversity, their ecosystem integrity and processes are generally limited or even unknown due to anthropogenic pressures and the paucity of studies on this type of aquatic ecosystem. This study aimed to enhance the knowledge on the biodiversity, ecosystem attributes and ecological status of agricultural ditches by analyzing the macroinvertebrate communities of six different ditches and those of the main river in the same area. While negligible differences in taxonomic richness were observed, macroinvertebrate community composition significantly varied among sites as a function of the heterogeneous habitat conditions. These compositional differences strongly affected the relative abundance of functional feeding groups among sites and their derived ecosystem attributes. Moreover, the ecological status assessment depicted different scenarios depending on the biomonitoring indices applied. By means of a multifaceted, but still poorly adopted, analysis of the macroinvertebrate community, ranging from the taxonomic and functional diversity to ecosystem attributes and biomonitoring indices, the results obtained in this study offer useful information on the ecology of agricultural ditches with potential insights to improving their management.
Biodiversity and Possible Bio-Indicators of Mediterranean Temporary Ponds in Southern Apulia, Italy
Authors: Beccarisi Leonardo , Zuccarello Vincenzo , Accogli Rita , Belmonte Genuario
Published: September 2024

Mediterranean Temporary Ponds (MTPs) represent a priority habitat according to Directive 92/43/EEC (Natura 2000 code: 3170*). These are very shallow water habitats only seasonally flooded, with a flora mainly composed of Mediterranean therophytic and geophytic species. Its extreme seasonality and small size make this habitat highly vulnerable and hard to manage. In recent Italian monitoring campaigns, the conservation status of MTP 3170* was considered inadequate. In Apulia, where the habitat is considered as “the most vulnerable type”, 73 sites were censused, with a total coverage of about 10,000 m2. The present work refers to the monitoring for three years of a total of 16 habitat 3170* sites, with the aim of better describing faunal indicator species for this priority habitat. A total of 158 taxa of flora and 103 of fauna were identified from 54 floristic and 44 faunistic samplings in total, with a robust updating of the listed biodiversity. For the first time a group of faunal species is proposed as an indicator of the habitat MTP 3170*. The conservation status, assessed on the basis of structural and functional criteria, gave a satisfactory status for seven sites and an unsatisfactory one (variously rated as inadequate or bad) for nine.
A Comprehensive Review of the Ethnobotanical Uses, Pharmacological, and Toxicological Profiles of Piper capense L.f. (Piperaceae)
Authors: Kamsu Gabriel Tchuente , Ndebia Eugene Jamot
Published: September 2024

Commonly known as wild pepper, Piper capense (P. capense) is a culinary herb mainly used as a secret in preparation of “Nkui” and “Nah poh” in Bayangam, West Cameroon. However, it also has many interesting pharmacological properties, which is why the people of sub-Saharan Africa so highly prize it for the treatment of multiple human pathologies. This study aimed to highlight the traditional uses, phytochemical composition, biological activities, and toxicological profile of the P. capense plant, to draw the attention of pharmaceutical companies to its enormous potential for the development of future phyto- or pharmaceutical products. Documentary research was meticulously carried out in the Web of Sciences, Scopus, Pubmed/Medline, and Google Scholar databases according to PRISMA 2020 guidelines. The results show that extracts and compounds isolated from Piper capense have interesting anticancer, antibacterial, antimalarial, hypoglycemic, anti-epileptic, and antidepressant activities. Methanolic extracts and essential oils from P. capense exhibit no harmful effects when directly applied to normal human hepatocytes, umbilical cord cells, intestinal cells, and keratinocyte cell lines. Additionally, methanolic extracts administered acutely or subchronically at low doses (≤250 mg/kg body weight) in Wistar rats also demonstrate no adverse effects. In conclusion, given its interesting activities, P. capense is a viable option for developing new antimalarial, anticancer, antibacterial, hypoglycemic, anti-epileptic, and antidepressant drugs. However, many avenues still need to be explored before translation into drugs.
The Impact of Fascial Manipulation® on Posterior Shoulder Tightness in Asymptomatic Handball Players: A Randomized Controlled Trial
Authors: Barič Anja , Jesenšek Papež Breda , Bastič Majda , Kelc Robi , Brumat Peter , Stecco Antonio
Published: September 2024

This prospective study aimed to determine the impact of Fascial Manipulation® by Stecco (FM) on the range of motion (ROM) of internal rotation (IR) and horizontal adduction (HADD) in asymptomatic handball players, representing significant risk factors for shoulder injuries. A randomized controlled trial was conducted, with participants randomly assigned to either the investigated group (N = 29) receiving a single session of FM or the control group (N = 27) receiving no treatment. The ROM for IR and HADD were measured before, immediately after, and one month after the FM session. The investigated group experienced a statistically significant acute increase in glenohumeral IR (14 degrees, p < 0.001) and HADD (14 degrees, p < 0.001) compared to the control group (p < 0.001). The positive effects of FM persisted one month post-treatment, with increased IR ROM by 12 degrees (p < 0.001) and HADD ROM by 11 degrees (p < 0.001). Participants in the investigated group reported lower subjective tightness/stiffness immediately after (p < 0.001) and one month after treatment (p = 0.002) compared to the control group. This study demonstrates that a single application of FM effectively improves glenohumeral ROM in the dominant throwing shoulder of asymptomatic handball players. It highlights the immediate and sustained positive effects of FM on IR and HADD. These findings support the use of FM as an effective method for enhancing shoulder ROM and reducing subjective tightness/stiffness. The study was registered at ClinicalTrials.gov (NCT06009367).
Lobish: Symbolic Language for Interpreting Electroencephalogram Signals in Language Detection Using Channel-Based Transformation and Pattern
Authors: Tuncer Turker , Dogan Sengul , Tasci Irem , Baygin Mehmet , Barua Prabal Datta , Acharya U. Rajendra
Published: September 2024

Electroencephalogram (EEG) signals contain information about the brain’s state as they reflect the brain’s functioning. However, the manual interpretation of EEG signals is tedious and time-consuming. Therefore, automatic EEG translation models need to be proposed using machine learning methods. In this study, we proposed an innovative method to achieve high classification performance with explainable results. We introduce channel-based transformation, a channel pattern (ChannelPat), the t algorithm, and Lobish (a symbolic language). By using channel-based transformation, EEG signals were encoded using the index of the channels. The proposed ChannelPat feature extractor encoded the transition between two channels and served as a histogram-based feature extractor. An iterative neighborhood component analysis (INCA) feature selector was employed to select the most informative features, and the selected features were fed into a new ensemble k-nearest neighbor (tkNN) classifier. To evaluate the classification capability of the proposed channel-based EEG language detection model, a new EEG language dataset comprising Arabic and Turkish was collected. Additionally, Lobish was introduced to obtain explainable outcomes from the proposed EEG language detection model. The proposed channel-based feature engineering model was applied to the collected EEG language dataset, achieving a classification accuracy of 98.59%. Lobish extracted meaningful information from the cortex of the brain for language detection.
UAV IoT Sensing and Networking
Authors: Tropea Mauro , Lakas Abderrahmane , Sarigiannidis Panagiotis
Published: September 2024

Research on unmanned aerial vehicles, also known as drones or by the acronym UAVs, has been increasing in recent years [...]
Lattice Boltzmann Simulation of Spatial Fractional Convection–Diffusion Equation
Authors: Bi Xiaohua , Wang Huimin
Published: September 2024

The space fractional advection–diffusion equation is a crucial type of fractional partial differential equation, widely used for its ability to more accurately describe natural phenomena. Due to the complexity of analytical approaches, this paper focuses on its numerical investigation. A lattice Boltzmann model for the spatial fractional convection–diffusion equation is developed, and an error analysis is carried out. The spatial fractional convection–diffusion equation is solved for several examples. The validity of the model is confirmed by comparing its numerical solutions with those obtained from other methods The results demonstrate that the lattice Boltzmann method is an effective tool for solving the space fractional convection–diffusion equation.
South African Teachers’ Insights on Improving the Sensory Classroom Teacher Questionnaire (SCTQ) for Inclusive Education and ADHD Support
Authors: Du Preez Hannelie
Published: September 2024

The Sensory Classroom Teacher Questionnaire (SCTQ) is a psycho-educational tool designed to empower teachers in creating sensory-rich, inclusive environments that promote diversity, equity, accessibility, and inclusivity through the application of sensory ergonomics. Unlike other tools that focus on isolated strategies, the SCTQ takes a holistic approach by optimizing the overall classroom environment to meet the sensory and ergonomic needs of learners, particularly those with ADHD and sensory integration/processing challenges. This makes the SCTQ especially vital in diverse and under-resourced quintile schools, where creating sensory-optimized, inclusive environments is essential for fostering equitable learning experiences. By addressing sensory needs through thoughtful classroom design, the SCTQ not only strengthens learners’ cognitive development and socio-emotional well-being but also improves behavior regulation, physical comfort, and overall functioning. This manuscript is part of a larger exploratory mixed-methods study that validated the SCTQ using both qualitative and quantitative approaches. Here, the focus is on the qualitative aspect, utilizing thematic analysis to explore data from 23 focus group interviews with 88 Grade 1, 2, and 3 teachers from various Quintile 1–5 schools in Gauteng, South Africa. Guided by the enactivism paradigm, the study emphasizes the crucial role teachers play in creating and adapting sensory environments. Their insights were key to refining the SCTQ, ensuring it is practical, developmentally appropriate, culturally, linguistically, contextually, and socio-economically relevant. Developed through collaboration among researchers, specialists, and teachers, the SCTQ supports sensory ergonomic practices, raises awareness of ADHD and sensory integration/processing challenges, and supports both learners’ potential and teachers’ well-being, contributing to a more sustainable and positive educational experience.
Exploring the Interplay between Teacher Leadership and Self-Efficacy: A Systematic Literature Review (2013–2024)
Authors: Luo Xue , Alias Bity Salwana , Adnan Nor Hafizah
Published: September 2024

This systematic review rigorously explores the reciprocal relationship between teacher leadership and self-efficacy across a range of educational and cultural settings. Drawing on eleven peer-reviewed studies from 2013 to 2024 and guided by the PRISMA framework, the analysis substantiates a robust, bidirectional link: teacher leadership significantly bolsters self-efficacy, which, in turn, profoundly impacts educational practices and outcomes. The dynamics of this relationship exhibit considerable variation across cultural divides, with collectivist settings predominantly favoring a collaborative approach that enhances collective efficacy and teamwork, whereas individualistic contexts tend to prioritize personal achievement and empowerment. The findings highlight the imperative for culturally tailored professional development programs and affirm the critical influence of teacher self-efficacy in driving educational innovation and reform. Despite the richness of the insights presented, the studies’ limited sample sizes and the specificity of their educational contexts may temper the broader applicability of the conclusions. This review recommends that future research adopt longitudinal and mixed-methods approaches to deepen the understanding of these interactions across diverse cultural landscapes, thereby enriching the theoretical and practical implications for global educational advancement.
Half-Wave Phase Shift Modulation for Hybrid Modular Multilevel Converter with Wide-Range Operation
Authors: Ma Junchao , Peng Yan , Su Zimeng , Gu Yilei , Ni Qiulong , Yang Ying , Wang Yi , Liu Jianing
Published: September 2024

Hybrid modular multilevel converters (MMCs), which combine submodule chain links and device series switches, offer advantages such as lower costs and smaller volumes compared with MMCs. However, the hybrid MMCs only operate at a fixed modulation ratio, potentially compromising system adjustment ability. This paper presents a half-wave phase shift modulation (HPSM) strategy aimed at extending the operation range of a hybrid MMC. First, the commutation angle is introduced as a control variable to change the fixed voltage modulation ratio. The energy balance of the converter is completed by adjusting the commutation angle. Then, the operation performance for the half-wave alternating multilevel converter (HAMC) with the proposed HPSM strategy is analyzed. Finally, the full-scale simulations are carried out to verify the theoretical analysis and the feasibility of the proposed control strategy. Compared to the third-order harmonic current injection (THCI) strategy, HPSM reduces operating losses by 50% and demonstrates superior control performance.
A Unified Model of a Virtual Synchronous Generator for Transient Stability Analysis
Authors: Li Ming , Wei Chengzhi , Zhao Ruifeng , Lu Jiangang , Chen Yizhe , Yang Wanli
Published: September 2024

A virtual synchronous generator (VSG) is prone to transient instability under a grid fault, which leads to the loss of synchronization between the new energy converter and grid, and threatens the operation safety of high-proportion new energy grids. There are a variety of control models in the existing VSG control, including active and reactive power models, which lead to their different transient stabilities. However, the evolution characteristics, correlation between different models of VSG, and the internal mechanism affecting transient stability have not been fully studied. To this effect, this paper analyzes their evolution characteristics based on the existing mainstream VSG control models and establishes a unified VSG model and its equivalent correspondence with other models. Then, the phase plane method is used to comprehensively analyze and compare the transient stability of the VSG unified model with other models. It is pointed out that the key factors affecting the transient stability of different models are three links of primary frequency regulation, reactive power regulation and reactive power tracking. Finally, the correctness of the established VSG unified model and the conclusion of transient stability analysis is verified by experiments.
Leveraging Generative AI in Short Document Indexing
Authors: Bouzid Sara , Piron Loïs
Published: September 2024

The efficiency of information retrieval systems primarily depends on the effective representation of documents during query processing. This representation is mainly constructed from relevant document terms identified and selected during their indexing, which are then used for retrieval. However, when documents contain only a few features, such as in short documents, the resulting representation may be information-poor due to a lack of index terms and their lack of relevance. Although document representation can be enriched using techniques like word embeddings, these techniques require large pre-trained datasets, which are often unavailable in the context of domain-specific short documents. This study investigates a new approach to enrich document representation during indexing using generative AI. In the proposed approach, relevant terms extracted from documents and preprocessed for indexing are enriched with a list of key terms suggested by a large language model (LLM). After conducting a small benchmark of several renowned LLM models for key term suggestions from a set of short texts, the GPT-4o model was chosen to experiment with the proposed indexing approach. The findings of this study yielded notable results, demonstrating that generative AI can efficiently fill the knowledge gap in document representation, regardless of the retrieval technique used.
Research on Rail Surface Defect Detection Based on Improved CenterNet
Authors: Mao Yizhou , Zheng Shubin , Li Liming , Shi Renjie , An Xiaoxue
Published: September 2024

Rail surface defect detection is vital for railway safety. Traditional methods falter with varying defect sizes and complex backgrounds, while two-stage deep learning models, though accurate, lack real-time capabilities. To overcome these challenges, we propose an enhanced one-stage detection model based on CenterNet. We replace ResNet with ResNeXt and implement a multi-branch structure for better low-level feature extraction. Additionally, we integrate SKNet attention mechanism with the C2f structure from YOLOv8, improving the model’s focus on critical image regions and enhancing the detection of minor defects. We also introduce an elliptical Gaussian kernel for size regression loss, better representing the aspect ratio of rail defects. This approach enhances detection accuracy and speeds up training. Our model achieves a mean accuracy (mAP) of 0.952 on the rail defects dataset, outperforming other models with a 6.6% improvement over the original and a 35.5% increase in training speed. These results demonstrate the efficiency and reliability of our method for rail defect detection.
Smart Transfer Planer with Multiple Antenna Arrays to Enhance Low Earth Orbit Satellite Communication Ground Links
Authors: Chang Mon-Li , Lin Ding-Bing , Rao Hui-Tzu , Lin Hsuan-Yu , Chou Hsi-Tseng
Published: September 2024

In this study, we propose a smart transfer planer equipped with multiple antenna arrays to improve ground links for low Earth orbit (LEO) satellite communication. The STP features a symmetrical structure and is strategically placed on both ends of a window, serving both indoor and outdoor environments. Using the window glass as a medium, energy transmission occurs through a coupling mechanism between the planers. The design focuses on large array antenna design, beamforming networks, and coupler design on both sides of the glass. Beamforming networks enable the indoor and outdoor antenna arrays to switch beams in various directions, optimizing high-gain antennas with narrow beamwidths. Through electromagnetic induction and filter couplers, a robust signal transmission channel is established between indoor and outdoor environments. This setup significantly enhances communication efficiency, particularly in non-line-of-sight environments.
Identification and Evaluation of Vulnerable Links in a Distribution Network with Renewable Energy Source Based on Minimum Discriminant Information
Authors: Shi Kejian , Wang Ting , Dai Zikuo , Tian Ye , Yang Pu , Li Haifeng
Published: September 2024

With the increase in the proportion of photovoltaic and wind power access, the scale and form of distribution networks are becoming more and more complex. The traditional single distribution network vulnerability assessment method is difficult to use to identify the vulnerable links in the distribution network. Therefore, this paper proposes a method for identifying and evaluating vulnerable links in distribution networks based on minimum discriminant information. First, considering the influence of distributed grid connection, an improved probabilistic power flow calculation method is proposed, which improves the calculation efficiency and accuracy. Second, considering the correlation degree, transmission capacity, and voltage stability of branches in the distribution network, the identification index of vulnerable lines is defined. Based on power quality and operating state, the identification index of vulnerable nodes in a distribution network is defined. Finally, based on the indicators of vulnerable nodes and vulnerable lines, the vulnerable links in the distribution network are comprehensively evaluated based on the principle of minimum discriminant information, and the vulnerable links of the entire distribution network are evaluated according to different degrees of vulnerability. The rationality and effectiveness of the proposed method are verified via an example analysis of actual power grid data.
The Impact of Oil Price on Carbon Dioxide Emissions in the Transport Sector: The Threshold Effect of Environmental Policy Stringency
Authors: Ding Xingong , Wang Mengzhen
Published: September 2024

Carbon dioxide emissions from the transport sector make a significant contribution to global greenhouse gases, and understanding the factors that influence these emissions is beneficial for devising effective emission reduction policies. Oil prices are an important influencing factor since the fuel used in the transport sector is primarily based on oil, and fluctuations in oil prices directly impact the sector’s CO2 emissions. Additionally, environmental policies, as a key means of controlling CO2 emissions, can affect the relationship between oil prices and CO2 emissions in the transport sector. Therefore, this study aims to examine the impact of oil prices on CO2 emissions in the transport sector and explore the nonlinear role of environmental policy stringency in this relationship. Based on data from 27 OECD member countries and 6 non-member countries from 1990 to 2019, we used the environmental policy stringency index as a threshold variable to construct a panel threshold regression model. The analysis results indicate a double-threshold effect: when the environmental policy stringency index is low, the impact of oil prices on CO2 emissions in the transport sector is not significant. However, when the index reaches the first threshold, the impact of oil prices significantly increases; upon reaching the second threshold, the effect is further intensified. This paper also analyzes the three subindicators—market-based policies, non-market-based policies, and technology support policies—to clarify the distinct impact mechanisms of different types of environmental policies. Finally, based on the research findings, we propose policy recommendations to achieve carbon dioxide emission reduction targets in the transport sector.
Effect of Interface Defects on the Electric–Thermal–Stress Coupling Field Distribution of Cable Accessory Insulation
Authors: Lu Xu , Hu Ran , Guo Kongying , Lan Rui , Tian Jie , Wei Yanhui , Li Guochang
Published: September 2024

The combined insulation interface of a high-voltage cable and accessories is the weakest part of a cable system. In this paper, the parameters of the dielectric constant, thermal conductivity, and elastic modulus of cross-linked polyethylene (XLPE) and silicone rubber (SIR) are obtained experimentally. On this basis, the model of a specific type of 110 kV cable and prefabricated insulation joint is established. A simulation of the electric–thermal–stress coupling field in the presence of typical defects in the main insulation–inner semi-conductive (SEMI) shielding layer (XLPE/SEMI interface) and the main insulation–silicone rubber insulation layer (XLPE/SIR interface) is studied. The simulation results show that at the XLPE/SIR interface, the electric field distortion caused by bubble defects reached 20.17 kV/mm, and the temperature rose to 56.15 °C. The effect of air-gap defects on the interface is similar to that of bubble defects. In addition, the semi-conductive impurity defects induced an increase in temperature to 56.82 °C and an increase in stress to 0.32 MPa. At the XLPE/SEMI interface, the electric field distortion induced by bubble defects was 19.98 kV/mm, and the temperature rose to 61.72 °C. The electric field distortion caused by metallic and semi-conductive defects was 8.44 kV/mm and 8.64 kV/mm, respectively. This study serves as a reference for the fault analysis and the operation and maintenance of cable accessories.
Towards Energy Equity: Understanding and Addressing Multifaceted Energy Inequality
Authors: Volodzkiene Lina , Streimikiene Dalia
Published: September 2024

Given the pressing necessity to mitigate the consequences of climate change, it is of the utmost importance to establish a carbon-neutral society. Nevertheless, sustainability is significantly impeded by energy inequality. It is the term used to describe the unequal distribution, access, and utilization of energy resources among demographic groups, which has been further exacerbated by the pandemic and geopolitical tensions. This research aims to conceptualize and quantify energy inequality in Lithuania and compare it with EU data in order to bolster the ambitious objective of a climate-neutral Europe by 2050. This article elucidates the intricacy of energy inequality by utilizing a Lithuanian population survey and a literature review, which are supplemented by an EU macroeconomic analysis. The findings underline the necessity of locally tailored solutions and underscore the significant disparities in energy access between Lithuanian regions and demographic groups. Targeted policy measures are necessary to overcome economic, technological, and socio-political obstacles that impede progress toward a climate-neutral society. The necessity of a multidimensional approach and global cooperation is underscored by a comparative analysis of EU statistics, which reveals variable progress in addressing energy inequality. Theis research is a pertinent contribution to the discourse on sustainability and social justice, and it offers policy-makers, practitioners, and stakeholders guidance for a more inclusive and sustainable energy future.
A Nonlinear Wind Turbine Wake Expansion Model Considering Atmospheric Stability and Ground Effects
Authors: Han Xingxing , Wang Tongguang , Ma Xiandong , Xu Chang , Fu Shifeng , Zhang Jinmeng , Xue Feifei , Cheng Zhe
Published: September 2024

This study investigates the influence of atmospheric stability and ground effects on wind turbine wake recovery, challenging the conventional linear relationship between turbulence intensity and wake expansion coefficient. Through comprehensive field measurements and numerical simulations, we demonstrate that the linear wake expansion assumption is invalid at far-wake locations under high turbulence conditions, primarily due to ground effects. We propose a novel nonlinear wake expansion model that incorporates both atmospheric stability and ground effects by introducing a logarithmic relationship between the wake expansion coefficient and turbulence intensity. Validation results reveal the superior prediction accuracy of the proposed model compared to typical engineering wake models, with root mean square errors of wake wind speed predictions ranging from 0.04 to 0.063. The proposed model offers significant potential for optimizing wind farm layouts and enhancing overall wind energy production efficiency.
Electric Vehicle Charging Load Demand Forecasting in Different Functional Areas of Cities with Weighted Measurement Fusion UKF Algorithm
Authors: Tang Minan , Guo Xi , Qiu Jiandong , Li Jinping , An Bo
Published: September 2024

The forecasting of charging demand for electric vehicles (EVs) plays a vital role in maintaining grid stability and optimizing energy distribution. Therefore, an innovative method for the prediction of EV charging load demand is proposed in this study to address the downside of the existing techniques in capturing the spatial–temporal heterogeneity of electric vehicle (EV) charging loads and predicting the charging demand of electric vehicles. Additionally, an innovative method of electric vehicle charging load demand forecasting is proposed, which is based on the weighted measurement fusion unscented Kalman filter (UKF) algorithm, to improve the accuracy and efficiency of forecasting. First, the data collected from OpenStreetMap and Amap are used to analyze the distribution of urban point-of-interest (POI), to accurately classify the functional areas of the city, and to determine the distribution of the urban road network, laying a foundation for modeling. Second, the travel chain theory was applied to thoroughly analyze the travel characteristics of EV users. The Improved Floyd (IFloyd) algorithm is used to determine the optimal route. Also, a Monte Carlo simulation is performed to estimate the charging load for electric vehicle users in a specific region. Then, a weighted measurement fusion UKF (WMF–UKF) state estimator is introduced to enhance the accuracy of prediction, which effectively integrates multi-source data and enables a more detailed prediction of the spatial–temporal distribution of load demand. Finally, the proposed method is validated comparatively against traffic survey data and the existing methods by conducting a simulation experiment in an urban area. The results show that the method proposed in this paper is applicable to predict the peak hours more accurately compared to the reference method, with the accuracy of first peak prediction improved by 53.53% and that of second peak prediction improved by 23.23%. The results not only demonstrate the high performance of the WMF–UKF prediction model in forecasting peak periods but also underscore its potential in supporting grid operations and management, which provides a new solution to improving the accuracy of EV load demand forecasting.
Additives Improving the Efficiency of Biogas Production as an Alternative Energy Source—A Review
Authors: Pilarska Agnieszka A. , Pilarski Krzysztof , Kulupa Tomasz , Kubiak Adrianna , Wolna-Maruwka Agnieszka , Niewiadomska Alicja , Dach Jacek
Published: September 2024

Additives for anaerobic digestion (AD) can play a significant role in optimizing the process by increasing biogas production, stabilizing the system, and improving digestate quality. The role of additives largely boils down to, among others, enhancing direct interspecies electron transfer (DIET) between microbial communities, resulting in improved syntrophic interactions, adsorption of toxic substances that may inhibit microbial activity, improving microbial activity, and increasing process stability and accelerating the decomposition of complex organic materials, thereby increasing the rate of hydrolysis. Through the aforementioned action, additives can significantly affect AD performance. The function of these materials varies, from enhancing microbial activity to maintaining optimal conditions and protecting the system from inhibitors. The choice of additives should be carefully tailored to the specific needs and conditions of the digester to maximize benefits and ensure sustainability. In light of these considerations, this paper characterizes the most commonly used additives and their combinations based on a comprehensive review of recent scientific publications, including a report on the results of conducted studies. The publication features chapters that describe carbon-based conductive materials, metal oxide nanomaterials, trace metal, and biological additives, including enzymes and microorganisms. It concludes with the chapters summarising reports on various additives and discussing their functional properties, as well as advantages and disadvantages. The presented review is a substantive and concise analysis of the latest knowledge on additives for the AD process. The application of additives in AD is characterized by great potential; hence, the subject matter is very current and future-oriented.
Efficiency Optimization of LCL-Resonant Wireless Power Transfer Systems via Bidirectional Electromagnetic–Thermal Coupling Field Dynamics
Authors: Yuan Yao , La Yuan , Shen Sicheng , Zhao Yihui , Li Jianchao , Yin Fanghui
Published: September 2024

This paper delved into the thermal dynamics and stability of Wireless Power Transfer (WPT) systems, with a focus on the temperature effects on the coil structure. Using the Finite Element Method (FEM), this study investigated both unidirectional and bidirectional coupling field simulations, assessing their impacts on the transmission efficiency of LCL-resonant WPT systems. The boundary conditions and processes of the electromagnetic–thermal coupling field related to coil loss were analyzed, as well as the dynamic thermal balance in the bidirectional coupling field model. It was found that there is a significant temperature variation across the coil, with the highest temperatures at the central position and the lowest at the edges. This temperature rise notably changed the electrical parameters of the system, leading to variations in its operating state and a reduction in transmission efficiency. A constant coil voltage control strategy was more effective in mitigating the temperature rise compared to a constant coil current strategy, providing valuable insight for enhancing the efficiency and stability of WPT systems.
LightGBM-, SHAP-, and Correlation-Matrix-Heatmap-Based Approaches for Analyzing Household Energy Data: Towards Electricity Self-Sufficient Houses
Authors: Singh Nitin Kumar , Nagahara Masaaki
Published: September 2024

The rapidly growing global energy demand, environmental concerns, and the urgent need to reduce carbon footprints have made sustainable household energy consumption a critical priority. This study aims to analyze household energy data to predict the electricity self-sufficiency rate of households and extract meaningful insights that can enhance it. For this purpose, we use LightGBM (Light Gradient Boosting Machine)-, SHAP (SHapley Additive exPlanations)-, and correlation-heatmap-based approaches to analyze 12 months of energy and questionnaire survey data collected from over 200 smart houses in Kitakyushu, Japan. First, we use LightGBM to predict the ESSR of households and identify the key features that impact the prediction model. By using LightGBM, we demonstrated that the key features are the housing type, average monthly electricity bill, presence of floor heating system, average monthly gas bill, electricity tariff plan, electrical capacity, number of TVs, cooking equipment used, number of washing and drying machines, and the frequency of viewing home energy management systems (HEMSs). Furthermore, we adopted the LightGBM classifier with ℓ1 regularization to extract the most significant features and established a statistical correlation between these features and the electricity self-sufficiency rate. This LightGBM-based model can also predict the electricity self-sufficiency rate of households that did not participate in the questionnaire survey. The LightGBM-based model offers a global view of feature importance but lacks detailed explanations for individual predictions. For this purpose, we used SHAP analysis to identify the impact-wise order of key features that influence the electricity self-sufficiency rate (ESSR) and evaluated the contribution of each feature to the model’s predictions. A heatmap is also used to analyze the correlation among household variables and the ESSR. To evaluate the performance of the classification model, we used a confusion matrix showing a good F1 score (Weighted Avg) of 0.90. The findings discussed in this article offer valuable insights for energy policymakers to achieve the objective of developing energy-self-sufficient houses.