bluuebunny/crossref_metadata_2025 huggingface dataset:
Seasonal dynamics of dissolved organic matter in a small tropical estuary-coastal bay continuum: distribution, transformation, flux, and global perspectives
Authors: Liu Pengfei , Jiang Kuan , Tan Qi , Chen Fajin , Jia Renming , Wang Chao
Published: January 2025

The export and transformation of riverine dissolved organic matter (DOM) at the river-sea interface are critical to understanding carbon budgets in tropical regions, yet remain underexplored in small watersheds. This study analyzed dissolved organic carbon (DOC), chromophoric (CDOM), and fluorescent DOM (FDOM) over five cruises from summer 2021 to summer 2022 in the Suixi Estuary-Zhanjiang Bay continuum, a eutrophic tropical transition zone in the northwestern South China Sea. Seasonal variations were pronounced for DOM in the continuum and two endmembers. Freshwater DOM, dominated by terrestrial organic materials, was closely tied to soil leaching and erosion, correlating with precipitation patterns. Conversely, seawater DOM, enriched in protein-like FDOM, varied with the West-Guangdong Coastal Current and its associated primary production. Linear decreases in DOM with increasing salinity indicate that conservative mixing largely shapes DOM distributions in the continuum, especially for humic-like FDOM. Non-conservative processes, including flocculation, phytoplankton production, and microbial transformation, variably alter DOM components across seasons. The Suixi River in summer contributed considerably but disproportionately to the annual DOM flux (47-59%), due to intense soil leaching processes that mobilize refractory terrigenous DOM. The deviation observed in the Suixi River’s DOC-CDOM relationship from that of global rivers, coupled with a distinctive single-peak pattern between the carbon-specific absorption coefficient and water yield in global rivers, highlights the critical role of watershed nature in influencing river-exported DOM composition. The notably high DOC and CDOM yields for the Suixi River further emphasize the importance of small, tropical rivers in shaping the estuarine and coastal carbon budget.
Integration of ATAC-seq and RNA-seq reveals signal regulation during post-molt and inter-molt stages in muscle of Eriocheir sinensis
Authors: Wang Bin , Li Jingjing , Zhang Mingzhi , Li Anqi , Song Zhentao , He Zhen , Zhang Ruiqi , Hao Tong , Sun Jinsheng
Published: January 2025

Introduction

The molting processes are crucial for the survival and development of crustaceans. Eriocheir sinensis demonstrates representative discontinuous growth during molting, while muscle is the most obvious tissue exhibiting this property. However, the signal regulation mechanisms involved in muscle during molting remain unexplored.

Methods

In this work, a comprehensive analysis of the gene expressions in E. sinensis muscle between post-molt and inter-molt stages were performed by integrating the ATAC-seq and RNA-seq techniques.

Results

The integration analysis identified 446 up-regulated and 21 down-regulated genes in the two stages. GO enrichment analysis revealed that the up-regulated genes are largely associated with protein phosphorylation and phosphorus metabolism, while the down-regulated genes are mainly involved in DNA metabolism, transcription, cell adhesion, and G protein-coupled receptor (GPCR) signaling pathway. In all the enriched signaling pathways, GPCR signaling pathway includes the most differentially expressed genes (8 genes), which underlines its importance in the signal transduction from the post-molt stage to the inter-molt stage. Further protein structure analysis and RT-qPCR validation confirmed five GPCR genes related to molting process, in which four genes (GRM7, FMRFaR, mth2, gpr161) are active during the post-molt stage and one gene (moody) functions during the inter-molt stage.

Discussion

These findings highlight the key regulatory proteins and pathways involved in E. sinensis muscle during molting and also offer foundational data for studying the mechanisms of molting and discontinuous growth in crustaceans.
Fibroblasts in rheumatoid arthritis: novel roles in joint inflammation and beyond
Authors: Neofotistou-Themeli Elpida , Goutakoli Panagiota , Chanis Theodoros , Semitekolou Maria , Sevdali Eirini , Sidiropoulos Prodromos
Published: January 2025

High-throughput technologies in human and animal studies have revealed novel molecular and cellular pathways involved in tissue inflammation of rheumatoid arthritis (RA). Fibroblasts have been in the forefront of research for several decades. Subpopulations with specific phenotypic and functional properties have been characterized both in mouse models and human disease. Data supporting the active involvement of fibroblasts in immune responses and tissue remodeling processes, as well as their central role in promoting clinical relapses and contributing to treatment resistance, have clearly reshaped their role in disease evolution. The lung is an important non-synovial component of RA both from a clinical and an immunopathogenic aspect. Interstitial lung disease (ILD) is a significant contributor to disease burden affecting morbidity and mortality. Although our knowledge of ILD has progressed, significant gaps in both basic and clinical science remain, posing hurdles to efficient diagnosis, prediction of disease course and its effective treatment. The specific role and contribution of fibroblasts to this process has not been clearly defined. The focus of this review is on fibroblasts and their contribution to RA and RA-ILD, presenting data on genetics and immune responses associated with RA-ILD in humans and animal models.
The association between periodontal disease and adverse pregnancy outcomes: a bibliometric analysis from 2000 to 2023
Authors: Zhao Miaomiao , Chang Haoxiang , Yue Yuxu , Zeng Xinyue , Wu Shaobang , Ren Xiuyun
Published: January 2025

Background

Periodontal disease (PD) refers to a chronic inflammatory disorder affecting the supporting tissues of the teeth triggered by bacterial infection and is recognized to promote systemic inflammation, leading to dysfunction in specific organs. Adverse pregnancy outcomes (APOs), including preterm birth, small for gestational age infants, gestational diabetes and preeclampsia, are linked to pregnancy complications. Recently, the correlation between periodontal disease and adverse pregnancy outcomes has garnered global attention. However, bibliometric studies in this area remain limited. This study aimed to visualize knowledge framework and research trends concerning the relationship between periodontal disease and adverse pregnancy outcomes from 2000 to 2023 through bibliometric approaches.

Methods

On September 22, 2024, articles and reviews on the connection between periodontal disease and adverse pregnancy outcomes were retrieved from the Web of Science Core Collection (WOSCC). CiteSpace [6.3.R1 (64-bit) Advanced] was used to perform knowledge mapping and bibliometric studies.

Results

Over the past 23 years, 932 articles from 73 countries were collected, with the U.S. contributing over one-third (355), followed by Brazil (85) and India (59). The literature in this field has experienced multiple growth phases since 2000, with particularly rapid growth observed after 2019. The University of North Carolina (n = 34, 3.65%) is the leading institution in terms of publication output, primarily representing the U.S. Notably, the Journal of Periodontology and the American Journal of Obstetrics and Gynecology are the most frequently cited journals in the fields of periodontology and obstetrics, respectively. These publications are authored by 94 researchers, with Steven Offenbacher being both the most productive and most highly cited author, making significant contributions to the field. A visual analysis of keywords identifies “oral microbiota,” “oral health,” “adverse pregnancy outcomes,” and “global burden” as emerging research hotspots in exploring the correlation between periodontal disease and adverse pregnancy outcomes.

Conclusions

This first bibliometric and visual analysis of periodontal disease and adverse pregnancy outcomes offers a concise overview of the field and suggests future research should focus on risk factors, high-risk populations, oral microbiota, mechanisms, interventions, and international collaboration.
Case report: Primary cardiac undifferentiated sarcoma complicated by esophagus stenosis
Authors: Ge Yuxin , Lv Xiaopan , Zhang Rui , Hao Dongxiao , Si Guifei , Li Yuquan , Yuan Xuemin , Li Xiuping
Published: January 2025

In this study, we present the case of a 38-year-old woman who was diagnosed with primary cardiac undifferentiated sarcoma after hospital admission. Following postoperative treatment that included radiotherapy and immunotherapy, the patient developed esophagus stenosis.
Crisis as opportunity—manifestations of civic practice in Libyan governance and rule of law
Authors: Brinkman Anne-Marie
Published: January 2025

In Libya’s protracted conflict, authoritarian, illiberal, and democratic practises exist at local and (inter)national levels. The repeated occurrence of crises in governance and rule of law, such as sudden restrictions on civil society or deferred elections, opens a window for the emergence of civic practice. Drawing on Kaldor’s concept of war and peace logic and a development ethics viewpoint, this study will critically discuss how manifestations of civic logic depend to start with on inclusive actor selection. This paper, based on Libyan-led co-inquiries and an analysis of dialogues and actions from an EU-funded rule of law programme, will demonstrate how the involvement of a diverse group of Libyans initiates manifestations of civic practice that are used during times of crisis.
Integrating frailty interventions into existing care models: a comprehensive approach to enhancing patient outcomes in chronic disease management
Authors: Uchmanowicz Izabella , Faulkner Kenneth M. , Iovino Paolo , Kwaśny Adrian , Surma Stanisław , Magi Camilla Elena , Jakubiak Grzegorz K. , Longobucco Yari , Janczak Dawid , Rak-Pasikowska Alina , Czapla Michał , Uchmanowicz Bartosz
Published: January 2025

Frailty syndrome (FS) is a complex and multifaceted condition commonly observed in old adults patients with chronic diseases, often accompanied by cognitive impairments. This review explores the integration of frailty interventions into existing care models to improve patient outcomes, focusing on four key areas. First, it emphasizes the importance of comprehensive assessment tools to identify frailty and cognitive impairments early, facilitating targeted care planning. Second, it highlights the value of personalized interventions, such as dietary modifications, exercise programs, and cognitive training, tailored to individual patient needs and preferences. Third, the review underscores the critical role of multidisciplinary care teams in providing holistic and coordinated care, leveraging the expertise of diverse healthcare professionals. Finally, it examines the potential of technological innovations and caregiver support systems in enhancing frailty management and addressing the challenges posed by cognitive impairments. By integrating these approaches, this review presents a patient-centered framework aimed at mitigating the impact of frailty and improving long-term outcomes. The findings emphasize the need for a unified strategy that combines personalized care, interdisciplinary collaboration, and technological advancements to address the multifaceted challenges of frailty in chronic disease management.
A socioeconomic disadvantage index for informing policy, systems, and environmental change interventions for senior nutrition programs
Authors: Maleki Shadi , Johnson Cassandra M. , Méndez Mediavilla Francis A. , Shanmugam Ramalingam , Biediger-Friedman Lesli
Published: January 2025

Identifying socioeconomic disparities within a local area is critical for tailoring policy solutions to older adult populations. However, a comprehensive index for characterizing socioeconomic disadvantage for older adult households in the U.S. is yet to be developed. This study is the first of its kind and used secondary data from the U.S. Census to develop a new socioeconomic disadvantage index for adults older than 60 years, with a focus on food insecurity, for a large region in Central Texas. The Older Adult Socioeconomic Disadvantage Index (OASDI) includes 12 variables related to unmet needs for food, housing, healthcare access, and transportation, and others at the census tract level. For each variable, the values were ranked based on quintiles using ArcGIS Pro 3.2. An unweighted sum was used to create the OASDI, where a higher score indicated greater socioeconomic disadvantage. Choropleth maps were used to visualize the OASDI and persistent poverty for all census tracts within the study area. The OASDI was used to statistically compare two local policy regions for senior nutrition programs in the Austin and San Antonio, Texas metro areas. Results showed a greater socioeconomic disadvantage in the San Antonio region compared to the Austin region (Mann-Whitney-U = 198,303; p < 0.0001). The statistical analysis identified an area with extreme disadvantage relative to the local policy region and confirmed with member checking. Findings provided insights into local socioeconomic disparities at different levels and can be applied to advocate for policies, systems, and environmental changes for senior nutrition.
Adaptive Noise Exploration for Neural Contextual Multi-Armed Bandits
Authors: Wang Chi , Shi Lin , Luo Junru
Published: January 2025

In contextual multi-armed bandits, the relationship between contextual information and rewards is typically unknown, complicating the trade-off between exploration and exploitation. A common approach to address this challenge is the Upper Confidence Bound (UCB) method, which constructs confidence intervals to guide exploration. However, the UCB method becomes computationally expensive in environments with numerous arms and dynamic contexts. This paper presents an adaptive noise exploration framework to reduce computational complexity and introduces two novel algorithms: EAD (Exploring Adaptive Noise in Decision-Making Processes) and EAP (Exploring Adaptive Noise in Parameter Spaces). EAD injects adaptive noise into the reward signals based on arm selection frequency, while EAP adds adaptive noise to the hidden layer of the neural network for more stable exploration. Experimental results on recommendation and classification tasks show that both algorithms significantly surpass traditional linear and neural methods in computational efficiency and overall performance.
Drip Fertigation with Moderate Nitrogen Topdressing Rate Achieves High Nitrogen and Water Use Efficiencies for Irrigated Wheat
Authors: Tong Jin , Xiong Yulei , Lu Yu , Li Wen , Lin Wen , Xue Jianfu , Sun Min , Wang Yuechao , Gao Zhiqiang
Published: January 2025

Drip fertigation (DF) can improve yield, water use efficiency (WUE), and nitrogen use efficiency (NUE, grain production per unit of the sum of soil inherent mineral N and fertilizer N), as well as reduce the risk of environmental pollution compared with flood irrigation and N fertilizer broadcast (FB). Previously, we showed that DF enhanced the response of the yield to the N topdressing rate (NTR), but the underlying mechanisms associated with the soil N supply, root architecture, and N uptake remain unclear. We conducted a field experiment by testing six N treatments (no N applied, and NTRs of 0, 40, 80, 120, and 160 kg ha−1, denoted as N0, T0, T40, T80, T120, and T160, respectively) under DF and FB from 2021 to 2023. Compared with FB, the NUE and WUE were 4.8–4.9% and 10.0–10.5% higher under DF. The higher NUE was due to an improvement in N uptake efficiency (6.1–7.7%) resulting from the enhanced aboveground N uptake (AGN). The greater AGN under DF was attributed to the higher soil N availability at the soil depth of 0–40 cm. DF decreased the residual soil NO3−-N at a depth of 40–200 cm but increased the NO3−-N at a depth of 0–40 cm. In addition, DF combined with T80 achieved high root length density, surface density, and dry weight density and improved NUE and WUE. DF combined with T80 achieved high yield and efficient utilization of water and N, and the NTR threshold was 61.75–119.50 kg ha−1, in which the production conditions were similar to those of the experimental site. Our results provide a reference for high-efficiency water and N fertilizer usage for irrigated winter wheat production in North China.
Enhanced Learning Behaviors and Ability Knowledge Tracing
Authors: Ma Fanglan , Zhu Changsheng , Lei Peng , Yuan Peiwen
Published: January 2025

Knowledge tracing (KT) aims to understand the evolution of students’ knowledge states during learning using machine learning techniques. While KT has made significant strides with deep learning techniques, a gap remains reflecting students’ actual knowledge level—the significant effects of students’ learning behaviors and abilities are omitted, which can reflect their knowledge acquisition more deeply and ensure the reliability of the response. This paper introduces the Enhanced Learning Behaviors and Ability Knowledge Tracing model (LBAKT), addressing this gap by incorporating both learning behavior and ability into its framework. The LBAKT model is structured into four layers: embedding, learning, forgetting, and predicting. The embedding layer enriches exercise information through an exercise embedding unit (capturing knowledge skills, exercises, and difficulty) and a learning ability embedding unit (considering answer time, answers, and hint times), forming a fundamental learning embedding. The learning layer quantifies learning gain by analyzing differences between current and previous learning embedding, interval times, and relative knowledge states, employing a learning gate to assess students’ capacity to absorb knowledge. The forgetting layer models forgetting behavior with forgotten erasing and retention functions, based on previous knowledge states, current learning gains, and interval times. Experimental results demonstrate that LBAKT outperforms existing models in terms of Area Under the Curve (AUC) and Accuracy (ACC) metrics when predicting students’ knowledge states. Specifically, on the longer sequence datasets ASSIST2012 and ASSISTChall, LBAKT achieved an AUC that is 8.8% higher than that of the worst-performing model, demonstrating superior performance. However, the model’s performance on the shorter sequence Algebra0607 was less satisfactory, with an AUC 3.16% lower and an ACC 5.0% lower than that of the top-performing model. Furthermore, our model enhances interpretability by integrating learning behavior and ability, a crucial factor for a deeper understanding of how students acquire and retain knowledge over time.
Reasonable Support Parameters for Loess Tunnel Under Different Water Contents: A Case Study
Authors: Chen Hao , Luo Yanbin , Chen Jianxun , Chen Hui , Li Yanfeng , Wang Pengkun , Guo Lele
Published: January 2025

Due to the unique structural characteristics of loess, the strength of loess is significantly influenced by the water content. Therefore, different support parameters should be used for loess tunnels constructed in different water content strata. This paper takes the Fengshouling Tunnel as a case study, studying the reasonable primary support parameters under different water contents using the surrounding rock strength test, on-site monitoring, and numerical simulation software analysis. The research findings indicate that the strength of the surrounding rock is functionally related to its water content, with the cohesive force c exhibiting an exponential relationship and the angle of internal friction φ showing a linear relationship, and that the cohesive force c is more affected by changes in water content than the internal friction angle φ. The crown settlement of the loess tunnel exceeds the horizontal convergence, and the deformation behavior can be categorized into three distinct stages: rapid growth, continuous growth, and slow growth. Concurrently, the primary support structure mainly bears compressive stress. On the basis of considering structural safety and engineering economy, for tunnels with a general water content (10~17%), it is recommended to use I18 steel ribs spaced 60 cm apart and C25 shotcrete with a 24 cm thickness; for high water content (17~25%), it is recommended to use I20a steel ribs, also spaced 60 cm apart, complemented by C25 shotcrete increased to a 26 cm thickness; for situations with an extremely high water content (≥25%), it is recommended to reinforce the surrounding rock with curtain grouting and use steel ribs with the same 60 cm spacing, along with C25 shotcrete maintained at a 26 cm thickness. This paper proposes reasonable support parameters for loess tunnels applicable to different water contents. These results can provide guidance and specific reference for loess tunnels under different water content strata.
Physics-Informed Neural Networks for Modal Wave Field Predictions in 3D Room Acoustics
Authors: Schoder Stefan
Published: January 2025

The generalization of Physics-Informed Neural Networks (PINNs) used to solve the inhomogeneous Helmholtz equation in a simplified three-dimensional room is investigated. PINNs are appealing since they can efficiently integrate a partial differential equation and experimental data by minimizing a loss function. However, a previous study experienced limitations in acoustics regarding the source term. A challenging but realistic excitation case is a confined (e.g., single-point) excitation area, yielding a smooth spatial wave field periodically with the wavelength. Compared to studies using smooth (unrealistic) sound excitation, the network’s generalization capabilities regarding a realistic sound excitation are addressed. Different methods like hyperparameter optimization, adaptive refinement, Fourier feature engineering, and locally adaptive activation functions with slope recovery are tested to tailor the PINN’s accuracy to an experimentally validated finite element analysis reference solution computed with openCFS. The hyperparameter study and optimization are conducted regarding the network depth and width, the learning rate, the used activation functions, and the deep learning backends (PyTorch 2.5.1, TensorFlow 2.18.0 1, TensorFlow 2.18.0 2, JAX 0.4.39). A modified (feature-engineered) PINN architecture was designed using input feature engineering to include the dispersion relation of the wave in the neural network. For smoothly (unrealistic) distributed sources, it was shown that the standard PINNs and the feature-engineered PINN converge to the analytic solution, with a relative error of 0.28% and 2×10−4%, respectively. The locally adaptive activation functions with the slope lead to a relative error of 0.086% with a source sharpness of s=1 m. Similar relative errors were obtained for the case s=0.2 m using adaptive refinement. The feature-engineered PINN significantly outperformed the results of previous studies regarding accuracy. Furthermore, the trainable parameters were reduced to a fraction by Bayesian hyperparameter optimization (around 5%), and likewise, the training time (around 3%) was reduced compared to the standard PINN formulation. By narrowing this excitation towards a single point, the convergence rate and minimum errors obtained of all presented network architectures increased. The feature-engineered architecture yielded a one order of magnitude lower accuracy of 0.20% compared to 0.019% of the standard PINN formulation with a source sharpness of s=1 m. It outperformed the finite element analysis and the standard PINN in terms time needed to obtain the solution, needing 15 min and 30 s on an AMD Ryzen 7 Pro 8840HS CPU (AMD, Santa Clara, CA, USA) for the FEM, compared to about 20 min (standard PINN) and just under a minute of the feature-engineered PINN, both trained on a Tesla T4 GPU (NVIDIA, Santa Clara, CA, USA).
Evaluating the Performance of Smart Meters: Insights into Energy Management, Dynamic Pricing and Consumer Behavior
Authors: Koukouvinos Konstantinos G. , Koukouvinos George K. , Chalkiadakis Pavlos , Kaminaris Stavrοs D. , Orfanos Vasilios A. , Rimpas Dimitrios
Published: January 2025

Energy consumption demands are rapidly increasing every year, with an 8% annual growth rate projected for the next five years. As buildings represent over 35% of this demand, a metering system is required for monitoring to accurately calculate costs. This paper explores the evolution and impact of energy management through smart meters, emphasizing their superiority over traditional electromechanical devices, in applications such as minimizing power losses and enhancing grid reliability. This study compares the performance of five distinct metering systems, including electromechanical and advanced smart meters. Real-time testing across various scenarios is incorporated, examining parameters such as real and reactive power measurement, accuracy and adaptability to smart grids. Key findings revealed that smart meters, notably the EDMI Mk10A, outperform legacy systems in precision, data transmission and energy optimization. In addition, the potential of smart meters to enable dynamic cost calculation and prevent electricity theft is evident. Despite their advantages, challenges such as data privacy, installation costs and electromagnetic radiation concerns, persist. Future investigations to address the identified limitations are required.
3D-Printed Customized Cages for Foot Arthrodesis
Authors: Botezatu Iozefina , Lăptoiu Dan , Popescu Diana , Marinescu Rodica
Published: January 2025

In recent years, the application of 3D-printed implant cages or trusses for foot arthrodesis has emerged as a personalized approach to address complex bone defects and deformities. Twenty studies involving different regions of the foot, such as the ankle and subtalar joints, were reviewed to document the 3D-printed custom solutions. The design of these implants is also discussed, including custom titanium trusses and lattice structures, which can promote osseointegration and fit the bone geometries. From a mechanical perspective, these implants proved to be stable and compatible with natural bone, aiming to reduce stress shielding while offering the mechanical strength needed for optimal outcomes. This systematic survey also addresses the additive manufacturing processes involved, namely EBM, SLM, or DMLS. Clinical cases were focused on patients with large bone loss, failed prior fusions, and deformity corrections, with the follow-up results showing high rates of fusion and functional improvement. Of the analyzed studies, three provide level III evidence, while the rest provide level IV or V, consisting of case series or reports. Since 2015, 148 patients have been reported to receive such implants. This review addresses the question, “how effective are 3D-printed titanium cage implants in foot arthrodesis in addressing large bone defects and deformities?” It is the first review to gather data on the use of such customized implants in foot arthrodesis, providing critical insights to enhance their application, including amputation avoidance. This study highlights the advantages of personalized 3D-printed implants in achieving a better anatomical fit, improving clinical outcomes, and ensuring faster recovery times, while also addressing considerations such as the cost and the need for long-term clinical data.
Stitching-Based Resolution Enhancement in Wavefront Phase Measurement of Silicon Wafer Surfaces
Authors: Ivanov-Kurtev Kiril , Trujillo-Sevilla Juan Manuel , Rodríguez-Ramos José Manuel
Published: January 2025

The increasing demand for higher resolution and faster machinery in silicon wafer inspection is driven by the rise in electronic device production and the decreasing size of microchips. This paper presents the design and implementation of a device capable of accurately measuring the surface of silicon wafers using the stitching technique. We propose an optical system design for measuring the surface profile, specifically targeting the roughness and nanotopography of a silicon wafer. The device achieves a lateral resolution of 7.56 μm and an axial resolution of 1 nm. It can measure a full 300-mm wafer in approximately 60 min, acquiring around 400 million data points. The technique utilized is a wavefront phase sensor, which reconstructs the surface shape using two images displaced a certain distance from the conjugate plane in the image space of a 4f system. The study details the calibration process and provides a method for converting local measurement coordinates to global coordinates. Quantitative phase imaging was obtained by using the wave front intensity image algorithm. The conclusive results validate the method different metrics over a wafer with bonded dies. In addition, the device demonstrates the ability to distinguish different dies that are thinned along with die-to-wafer bonding onto a carrier wafer to obtain the difference in coplanarity between the die and its surroundings as well as to detect defects during the die-to-wafer bonding. Lastly, the residual stress in the thin film deposited over the die is obtained using the Stoney model.
Simulation Research on the Effects of Air Gaps and Ambient Temperature on a 27.5 kV Power Cable
Authors: Pan Like , Luo Yunfeng , Wang Xinwei , Lei Dong , Wang Jiawei , Zhang Huan , Yang Zefeng , Wei Wenfu
Published: January 2025

A 27.5 kV cable is one of the important infrastructures of a high-speed railway traction power supply system, and the reliability of the cable directly affects the stability and safety of the high-speed railway power supply. The cable runs in the complex environment of the laying site and will inevitably face the influence of electrical stress and thermal stress, resulting in air gap and insulation deterioration, which poses a threat to the safety of a high-speed railway traction power supply system. In this paper, an electric–thermal coupling model is built and simulated under normal operating conditions and different cable damage conditions. The distributions of the electric field and thermal field under different conditions of cables are explored. The weak points of a cable with poor heat resistance and easily produced air gaps are found. The influence of various temperature differences on a damaged air gap inside the cable is studied. Finally, the damage mechanism of a further increase in the cable’s air gap caused by partial discharge of the air gap is proven. This study provides a theoretical basis for inhibiting cable degradation and prolonging cable life.
Sex-Based Kinanthropometric and Health Metric Analysis in Amateur Athletes Across Various Disciplines: A Comparative Study
Authors: Harrison Daniel Jonathan Navas , Pico Ana María Pérez , Rodríguez Julia Villar , Ripado Olga López , Acevedo Raquel Mayordomo
Published: January 2025

Kinanthropometry is the study of body dimensions and composition measurements, which are influenced by factors such as age and nutritional status, establishing a relationship between static measurements and dynamic performance. This study aimed to evaluate the kinanthropometric differences among 403 individuals (aged 18–42), categorized by biological sex and the recreational sport they practiced. The main objective of this study was to clarify whether or not there were statistically significant differences between these groups. All of the measurements and indices were obtained following the International Society for the Advancement of Kinanthropometry (ISAK) protocol. Significant differences were found in most variables among the different sports. In general, the men showed higher values in terms of weight, height, body circumference, body mass index (BMI), relative index of the lower limbs (RILLs), percentage of muscle mass (%M), and percentage of residual mass (%R). The women exhibited higher values in terms of skinfold thicknesses, Cormic index (CI), body density index (BDI), percentage of fat mass (%F), and percentage of bone mass (%B). These findings can guide individuals in selecting sports based on their morphotype, optimizing their physical performance in recreational activities and improving their health and quality of life.
A Combined Calibration Method for Workpiece Positioning in Robotic Machining Systems and a Hybrid Optimization Algorithm for Improving Tool Center Point Calibration Accuracy
Authors: Hao Daxian , Zhang Gang , Zhao Huan , Ding Han
Published: January 2025

This paper addresses the machining requirements for large aerospace structural components using robotic systems and proposes a method for rapid workpiece positioning that combines the simplicity of vision-based positioning with the precision of contact-based methods. To enhance the accuracy of robot calibration, a novel approach utilizing a ruby probe for sphere-to-sphere contact calibration of the Tool Center Point (TCP) is introduced. A robot contact calibration model is formulated, transforming the calibration process into a nonlinear least squares (NLS) optimization problem. To tackle the challenges of NLS optimization, a hybrid LM-D algorithm is developed, integrating the Levenberg–Marquardt (L-M) and DIviding RECTangle (DIRECT) algorithms in an iterative process to achieve the global optimum. This algorithm ensures computational efficiency while maximizing the likelihood of finding a globally optimal solution. An iterative convergence termination criterion for TCP calibration is established to determine global convergence, further enhancing the algorithm’s efficiency. Experimental validation was performed on industrial robots, demonstrating the proposed algorithm’s superior performance in global convergence and iteration efficiency compared to traditional methods. This research provides an effective and practical solution for TCP calibration in industrial robotic applications.
Three-Dimensionally Printed Self-Expanding Polylactic Acid Stent for Assisting Arteriovenous Fistula Maturation
Authors: Chang Fuh-Yu , Liang Te-Hsien , Huang Ke-Jie
Published: January 2025

This study presents the development of a novel biodegradable, self-expanding stent designed to facilitate arteriovenous fistula (AVF) maturation. The stent, made of polylactic acid (PLA), is engineered to be crimped into a standard 6 Fr (2 mm) catheter for delivery and to self-expand, increasing the vein diameter beyond 4.2 mm with the aid of pre-strained elastic lines, thereby enhancing maturation rates. A validated finite element model was utilized to design the stent, ensuring it meets functional requirements with less than 3% strain in both crimped and fully expanded states. The stent prototype was fabricated using a modified fused deposition modeling (FDM) 3D printer, and the Taguchi method was employed to optimize manufacturing parameters, achieving strut width and thickness variations of less than 5%. Experimental validation demonstrated that the PLA stent could be crimped to 2 mm, self-expand to 6.4 mm, and deliver a radial force of 0.08 N/mm, meeting the performance requirements of AVF stents. Additionally, the stent exhibits excellent elasticity post-implantation, minimizing the risk of damage from external forces, and fully degrades after AVF maturation, reducing the risk of long-term vascular obstruction and related complications. This novel stent design offers a promising biodegradable solution for enhancing AVF maturation and improving patient outcomes.
Ceramic-Rich Composite Separators for High-Voltage Solid-State Batteries
Authors: Vattappara Kevin , Finsterbusch Martin , Fattakhova-Rohlfing Dina , Urdampilleta Idoia , Kvasha Andriy
Published: January 2025

Composite solid electrolytes are gaining interest regarding their use in Li-metal solid-state batteries. Although high ceramic content improves the electrochemical stability of ceramic-rich composite separators (C-SCE), the polymeric matrix also plays a vital role. In the first generation of C-SCE separators with a PEO-based matrix, the addition of 90–95 wt% of Li6.45Al0.05La3Zr1.6Ta0.4O12 (LLZO) does not make C-SCE stable for cell cycling with high-voltage (HV) cathodes. For the next iteration, the objective was to find an HV-stable polymeric matrix for C-SCEs. Herein, we report results on optimizing C-SCE separators with different ceramics and polymers which can craft the system towards better stability with NMC622-based composite cathodes. Both LLZO and Li1.3Al0.3Ti1.7(PO4)3 (LATP) were utilized as ceramic components in C-SCE separators. Poly(diallyldimethylammonium) bis(trifluoromethanesulfonyl)imide (PDDA-TFSI) and poly (vinylidene fluoride-co-hexafluoropropylene) (PVDF-HFP) were used as polymers in the “polymer/LiTFSI/plasticizer”-based matrix. The initial phase of the selection criteria for the separator matrix involved assessing mechanical stability and ionic conductivity. Two optimized separator formulations were then tested for their electrochemical stability with both Li metal and HV composite cathodes. The results showed that Li/NMC622 cells with LP70_PVDF_HFP and LZ70_PDDA-TFSI separators exhibited more stable cycling performance compared to those with LZ90_PEO300k-based separators.
Precision Imaging for Early Detection of Esophageal Cancer
Authors: Yang Po-Chun , Huang Chien-Wei , Karmakar Riya , Mukundan Arvind , Chen Tsung-Hsien , Chou Chu-Kuang , Yang Kai-Yao , Wang Hsiang-Chen
Published: January 2025

Early detection of early-stage esophageal cancer (ECA) is crucial for timely intervention and improved treatment outcomes. Hyperspectral imaging (HSI) and artificial intelligence (AI) technologies offer promising avenues for enhancing diagnostic accuracy in this context. This study utilized a dataset comprising 3984 white light images (WLIs) and 3666 narrow-band images (NBIs). We employed the Yolov5 model, a state-of-the-art object detection algorithm, to predict early ECA based on the provided images. The dataset was divided into two subsets: RGB-WLIs and NBIs, and four distinct models were trained using these datasets. The experimental results revealed that the prediction performance of the training model was notably enhanced when using HSI compared to general NBI training. The HSI training model demonstrated an 8% improvement in accuracy, along with a 5–8% enhancement in precision and recall measures. Notably, the model trained with WLIs exhibited the most significant improvement. Integration of HSI with AI technologies improves the prediction performance for early ECA detection. This study underscores the potential of deep learning identification models to aid in medical detection research. Integrating these models with endoscopic diagnostic systems in healthcare settings could offer faster and more accurate results, thereby improving overall detection performance.
Effects of Lysophospholipids on the Antioxidant Capacity, Digestive Performance, and Intestinal Microbiota of Litopenaeus vannamei
Authors: Yan Hailiang , Wang Yun , Liang Hong , Duan Yafei , Wang Jun , Zhou Chuanpeng , Huang Zhong
Published: January 2025

This study seeks to assess the impact of varying concentrations of lysophospholipids on the antioxidant capacity, digestive performance, and intestinal microbiota of L. vannamei. A total of 840 shrimp, with an average initial weight of 2.22 ± 0.11 g, were randomly distributed across 28 aquaculture tanks (30 shrimp per tank), organized into 7 distinct treatment groups, each comprising 4 replicates. The control group (DL2) was administered a basal diet formula supplemented with 2% soy lecithin, whereas the experimental groups received lysophospholipids at varying concentrations of 0% (RL0), 0.1% (RL0.1), 0.5% (RL0.5), 1% (RL1), 1.5% (RL1.5), and 2% (RL2). The results revealed that the total antioxidant capacity (T-AOC) level in the RL0.1 group was significantly elevated compared to the DL2 and RL2 groups (p < 0.05). Furthermore, glutathione peroxidase (GSH-Px) and catalase (CAT) activities were markedly higher in the RL1 and RL1.5 groups relative to other groups (p < 0.05). Superoxide dismutase (SOD) activity exhibited a significant increase across all lysophospholipid-supplemented groups when compared to the DL2 group (p < 0.05). Malondialdehyde (MDA) levels were notably elevated in the RL0.5, RL1.5, and RL2 groups relative to the other groups (p < 0.05). Regarding antioxidant-related genes in the hemocytes, the relative expression levels of Nrf1, Nrf2, GPx, SOD, CAT, and Hippo were significantly higher in the RL0.5 and RL1 groups compared to the DL2 group (p < 0.05). Additionally, the relative expression levels of GPx and SOD were significantly elevated in the RL2 group compared to the DL2 group (p < 0.05). In the intestinal tract, the activities of trypsin and α-amylase (AMS) were significantly elevated in the RL0.1, RL0.5, and RL1 groups compared to the DL2 group (p < 0.05). Additionally, the RL0.1 group demonstrated significantly higher lipase (LPS) activity than the other groups supplemented with lysophospholipids (p < 0.05). Furthermore, the relative expression levels of the trypsin and α-amylase genes were significantly increased in the RL1 and RL1.5 groups in comparison to the DL2 group (p < 0.05). Sequencing analysis of the intestinal microbiota indicated that the incorporation of lysophospholipids resulted in an enhancement of the composition and structure of the intestinal microbiota. The functional abundance of the intestinal microbiome was primarily enriched in metabolic pathways. Overall, the incorporation of lysophospholipids into the diet exerted a beneficial effect on the antioxidant capacity, digestive performance, and intestinal microbiota of L. vannamei, especially with the supplementation of 0.1% lysophospholipids.
Deletion of Murine APP Aggravates Tau and Amyloid Pathologies in the 5xFADXTg30 Alzheimer’s Disease Model
Authors: Ando Kunie , Kosa Andreea-Claudia , Mehadji Yasmina , Lasri Hinde , Lopez-Gutierrez Lidia , Quintanilla-Sánchez Carolina , Aydin Emmanuel , Doeraene Emilie , Wathelet-Depauw Alain , Nagaraj Siranjeevi , Brion Jean-Pierre , Leroy Karelle
Published: January 2025

Alzheimer’s disease is characterized by two key neuropathological lesions: amyloid plaques composed of amyloid β and neurofibrillary tangles formed by hyperphosphorylated tau. Amyloid β is produced through successive cleavages of amyloid precursor protein (APP) via the amyloidogenic pathway. While increasing evidence suggests that APP plays critical roles in neuronal function and that its proteolytic derivative, sAPPα, has neurotrophic effects, the impact of APP deletion on both amyloid and tau pathologies remains poorly understood. Here, we introduce a novel transgenic mouse model, 5xFAD×Tg30XAPP-/-, in which murine APP is deleted in the presence of both amyloid and tau pathologies. Using this innovative model, we demonstrate for the first time that deletion of APP exacerbates tau aggregation, amyloid deposition, and gliosis compared to control 5xFAD×Tg30 mice. This study provides the first in vivo evidence that APP deletion has profound and detrimental effects on both amyloid and tau pathologies in a transgenic model of Alzheimer’s disease, highlighting the previously unappreciated role of APP in the regulation of these neurodegenerative processes.
The Neural Development of Chinese Lexical Tone Perception: A Mismatch Negativity Study Across Childhood, Adolescence, and Adulthood
Authors: Wu Han , Zhang Yixiao , Liu Yiru , Zhang Shijun , Zhang Linjun , Shu Hua , Zhang Yang
Published: January 2025

Background/Objectives: In a tonal language like Chinese, phonologically contrasting tones signify word meanings at the syllable level. Although the development of lexical tone perception ability has been examined in many behavioral studies, its developmental trajectory from childhood to adulthood at the neural level remains unclear. This cross-sectional study aimed to examine the issue by measuring the mismatch negativity (MMN) response to a Chinese lexical tonal contrast in three groups. Methods: The MMN response to a flat-falling tonal contrast (Tone1 versus Tone4) were recorded from children (25 participants aged 6–8), adolescents (26 participants aged 12–14), and young adults (20 participants aged 18–24). Nonsense speech stimuli were also used by superimposing Tone1 and Tone4 on an English syllable. Results: All three groups demonstrated typical early MMN responses in both the meaningful and nonsense syllable conditions. However, the MMN amplitudes varied significantly across groups, with the child group showing smaller responses compared to the adolescent and adult groups, while the latter two groups had similar MMN amplitudes. Conclusions: Neural sensitivity to tonal contrasts is not fully mature in children and reaches a more adult-like level during adolescence, with no significant difference in sensitivity to meaningful versus nonsense syllables. These results provide new insights into the neural development of lexical tone perception in a tonal language, highlighting its maturation during adolescence in this process.
Decision-Making Styles, Prosociality, and Behavioral Difficulties in Adolescent Offenders: The Mediating Role of Life Satisfaction and Emotional Experiences
Authors: Cardona-Isaza Arcadio de Jesús , Montoya-Castilla Inmaculada , Trujillo Angela
Published: January 2025

Research on adolescents suggests that decision-making styles, emotional experiences, and life satisfaction play a crucial role in emotional and behavioral difficulties and the development of prosocial behaviors. This study analyzed the relationship between decision-making styles, prosociality, and difficulties among adolescent offenders, as well as the mediating role of life satisfaction and emotional experiences in this relationship. A total of 457 adolescents aged from 14 to 19 years (M = 16.23; S.D. = 1.31; 32.2% female) participated in this study. The variables of interest were assessed using self-reports and descriptive, reliability, correlational, predictive, and mediation analyses were performed. A significant association was found between the study variables. Non-rational decision-making styles and negative emotional experiences influenced difficulties, whereas rational decision-making, life satisfaction, and positive emotional experiences influenced prosocial behavior. Furthermore, the results show that the relationship between rational decision-making and prosocial behavior is mediated by life satisfaction, emotional balance, and positive emotional experiences. Similarly, negative emotional experiences mediated the relationship between a hypervigilance decision-making style and emotional and behavioral difficulties. The results of this study indicate the importance of intervening in decision-making styles, emotional management, and life satisfaction in offending adolescents to decrease behavioral and emotional difficulties and favor prosocial behavior.
Risk Perception and Key Beliefs on Business Adaptation Behavior of Family Farmers: Empirical Evidence from Sichuan Province, China
Authors: Mou Yu , Li Xiaofeng
Published: January 2025

Family farmers face various business risks, including natural disasters, policies, technology adoption, and market uncertainties. This paper develops a conceptual framework for the formation mechanism of family farmers’ business adaptation behaviors by linking “risk perception, key beliefs, and adaptation behavior”. Using microdata from 363 family farmers in Sichuan Province, China, and applying ordered logit model regression analysis, we find that both risk perception and key beliefs positively influence family farmers’ business adaptation behavior. Key beliefs partially mediate this relationship, while risk preference negatively moderates the effect of risk perception on business adaptation behavior. Additionally, family farmers with higher farm profit levels and larger social networks are more likely to engage in business adaptation behavior. Family farmers who have higher education, are older, operate larger-scale farms, and are male exhibit stronger risk perceptions.