bluuebunny/crossref_metadata_2025 huggingface dataset:
The Wildcat That Lives in Me: A Review on Free-Roaming Cats (Felis catus) in Brazil, Focusing on Research Priorities, Management, and Their Impacts on Cat Welfare
Authors: Gonçalves Luana S. , de Souza Machado Daiana , Caçador Maria Eduarda , Ferreira Giovanne Ambrosio , Dickman Christopher R. , Ceballos Maria Camila , Prezoto Fabio , Sant’Anna Aline Cristina
Published: January 2025

Domestic cats (Felis catus) currently occupy the 38th place in the Global Invasive Species Database. Free-roaming cats potentially have broad-ranging impacts on wildlife, occupying most terrestrial environments globally as house pets, strays, or feral animals. In Australia, for example, cats are responsible for the decline in many vertebrate populations and extinction of several native mammals. However, in Brazil, few studies have explored either direct impacts of predation on wildlife, or other indirect impacts, such as competition for resources, niche overlap, hybridization, and disease transmission. In this review, we summarize and discuss 34 original research reports, published between 2001 and 2020, on impacts of free-roaming cats in Brazil. We briefly contextualize the history of cat domestication and present that, in Brazil, more studies have focused on the potential of free-roaming cats to transmit disease than to exert impacts via predation or competition on wildlife. More studies were conducted in Brazilian mainland areas (n = 23)—notably in Atlantic Forest—than on islands (n = 11). The review highlights potential impacts of cats on wildlife. We also discuss how control management strategies can affect the welfare of domestic cats, identifying potential knowledge gaps as well as opportunities for future research. Finally, understanding risks of cat predation is necessary to inform future measures to mitigate impacts on wildlife, without neglecting cat welfare.
The Impact of the Lactation Period Gut Microbiota of Two Different Beef Cattle Breeds on Spring-Born Calves
Authors: Chen Changbo , Sha Yuzhu , Zhang Xiaoqiang , Lu Pingle , Gao Jianyuan , Jiao Ting , Zhao Shengguo
Published: January 2025

To investigate the impact of maternal microbiota during lactation in different beef cattle breeds on their own immune levels, milk quality, and the growth and development of their offspring, this study measured the immune parameters, intestinal microbiota diversity, and milk quality of Pingliang red cattle and Simmental cattle, and performed a correlation analysis with the growth and development of their offspring. Our study showed that during lactation, Pingliang red cattle had significantly higher IL-6 levels than Simmental cattle, while the latter exhibited higher levels of immune factors such as IgG, IgA, IgM, IL-1β, and TNFα. The analysis of the intestinal microbiota of lactating cows found that Pingliang red cattle were rich in Bacteroidetes and Fibrobacteres, while Simmental cattle had a higher proportion of Actinobacteria. This difference may be related to the different adaptation strategies in energy metabolism and immune regulation between the two breeds. In addition, the analysis of milk quality between different beef cattle breeds revealed significant differences in protein, acidity, milk fat, and total solids. The correlation analysis found that Alistipes_communis, Firmicutes_bacterium_CAG_110, Alistipes_communis, Paludibacter_propionicigenes, Alistipes_sp._58_9_plus, and Bacteroidales_bacterium_55_9 were associated with both milk quality and the growth of offspring calves, including body weight, body length, chest girth, and cannon circumference. In conclusion, this study provides new insights into the intestinal microbiota, immune characteristics, and their effects on offspring health in different beef cattle breeds, and has important implications for breed selection and management strategies in the livestock industry.
Bioactive Compounds from Propolis on Bone Homeostasis: A Narrative Review
Authors: Bertolucci Vanessa , Ninomiya André Felipe , Longato Giovanna Barbarini , Kaneko Luisa Oliveira , Nonose Nilson , Scariot Pedro Paulo Menezes , Messias Leonardo Henrique Dalcheco
Published: January 2025

This narrative review explores the potential effects of Propolis and its bioactive compounds on bone health. Propolis, a resinous product collected by bees, is renowned for its antimicrobial, anti-inflammatory, and antioxidant properties. Recent research emphasizes its positive role in osteogenesis, primarily through the modulation of osteoclast and osteoblast activity via molecular pathways. Key mechanisms include reducing inflammatory cytokines, protecting against oxidative stress, and upregulating growth factor essential for bone formation. While compounds such as Caffeic Acid Phenethyl Ester, Apigenin, Quercetin, and Ferulic Acid have been well-documented, emerging evidence points to the significant roles of less-studied compounds like Pinocembrin, Kaempferol, p-Coumaric acid, and Galangin. This review synthesizes the current literature, focusing on the mechanisms by which these bioactive compounds influence osteogenesis. Firstly, it explores the techniques for characterizing bioactive compounds presented in propolis, the chemogeographic variations in its composition, and the effects of both crude extracts and isolated compounds on bone tissue, offering a comprehensive analysis of recent findings across different experimental models. Further, it discusses the effects of Propolis compounds on bone health. In summary, these compounds modulate signaling pathways, including nuclear factor kappa beta, wingless-related integration site, mitogen-activated protein kinase, vascular endothelial growth factor, and reactive oxygen species. These pathways influence the receptor activator of nuclear factor kappa-β/receptor activator of nuclear factor kappa-β ligand/osteoprotegerin system, fostering bone cell differentiation. This regulation mitigates excessive osteoclast formation, stimulates osteoblast activity, and ultimately contributes to the restoration of bone homeostasis by maintaining a balanced bone remodeling process.
Nicotinamide Adenine Dinucleotide Phosphate Oxidases and Metabolic Dysfunction-Associated Steatotic Liver Disease
Authors: Cammisotto Vittoria , Valeriani Emanuele , Pignatelli Pasquale , Violi Francesco
Published: January 2025

Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by lipid accumulation in the liver due to an excess in their supplies or an impairment in their management. While some patients remain stable for years, a proportion of them progress up to steatohepatitis (MASH). MASLD links with systemic pathways being associated with metabolic and non-metabolic diseases. Although liver lipid accumulation represents the first hit for MASLD, the pathophysiology of its development and progression to MASH remains not completely understood. Oxidative stress has received particular attention in recent years, as most of the oxidative process occurs in the liver, which is also the target of oxidative stress-induced damage. Growing evidence linked the activity of nicotinamide adenine dinucleotide phosphate (NADPH) oxidases (NOX) to the increased liver production of reactive oxygen species up to liver damage and fibrosis. NOX acts both in hepatocytes and in non-parenchymal hepatic cells, contributing to hepatocyte lipotoxicity, impaired hepatic microcirculation, hepatic stellate, and mesenchymal stem cells activation and proliferation. This review aims to summarize the current knowledge on the involvement of oxidative stress in the MASLD–MASH transition, focusing on the role of NOX isoforms, and to suggest targeting NOX as a therapeutic approach in MASLD.
Berth Allocation and Quay Crane Assignment Considering the Uncertain Maintenance Requirements
Authors: Li Siwei , Song Liying
Published: January 2025

The strategic optimization of a container terminal’s quayside assets, including the berth and quay cranes, is crucial for maximizing their deployment and utilization. The interrelated and complex challenges of Berth Allocation (BAP) and Quay Crane Scheduling (QCSP) are fundamental to enhancing the resilience of container ports, as berths and quay cranes constitute essential infrastructure. Efficient berth allocation and quay crane scheduling can mitigate operational disruptions, even in the face of maintenance or failures, thereby improving both operational reliability and resilience. However, previous studies have often overlooked the uncertainty associated with quay crane maintenance when planning these operations. This paper aims to minimize vessel turnaround time by accounting for the uncertain in quay crane maintenance activities. To address this novel problem, we propose a proactive-reactive method that incorporates a reliability-based model into the Swarm Optimization with Differential Evolution (SWO-DE) algorithm. Computational results confirm the practical relevance and effectiveness of our proposed solution methods for container terminals.
Modeling of Shoulder–Elbow Movement with Exponential Parameter Identification During Walking Gaits for Healthy Subjects and Patients with Parkinson’s Disease
Authors: Pietrosanti Luca , Saggio Giovanni , Patera Martina , Suppa Antonio , Giannini Franco , Verrelli Cristiano Maria
Published: January 2025

Background: This paper aims to complement the latest contribution in the literature that provides estimates of physiological parameters of a dynamic model for the elbow time profile during walking while linking them to a neurodegenerative disorder (Parkinsons’s disease) characterized by motor symptoms. An upper limb model is here proposed in which an active contractile element is included within a model, viewing the arm as a double pendulum system and muscles as represented by a Kelvin–Voight system. All model parameters characterizing both the shoulder and the elbow of each subject are estimated via a gradient-like identifier whose exponential convergence properties are determined by a non-anticipative Lyapunov function, ensuring robustness features. Methods: Joint angle data from different walking subjects (healthy subjects and patients with Parkinson’s disease) have been recorded using an IMU sensor system and compared with the joint angles obtained by means of the proposed model, which was adapted to each subject using available anthropometric knowledge and relying on the estimated parameters. Results: Experiments show that the reconstruction of shoulder and elbow time profiles can be definitely achieved through the proposed procedure with the estimated stiffness parameters turning out to constitute objective and quantitative indices of muscle stiffness (as a pivotal symptom of the pathology), which are able to track changes due to the therapy. Conclusions: The same dynamic model is actually able to capture the main features of the upper limb movement of both (healthy and pathological) walking subjects, with its parameters, in turn, characterizing the nature and progress of the pathology.
C-SHAP: A Hybrid Method for Fast and Efficient Interpretability
Authors: Ranjbaran Golshid , Recupero Diego Reforgiato , Roy Chanchal K. , Schneider Kevin A.
Published: January 2025

Model interpretability is essential in machine learning, particularly for applications in critical fields like healthcare, where understanding model decisions is paramount. While SHAP (SHapley Additive exPlanations) has proven to be a robust tool for explaining machine learning predictions, its high computational cost limits its practicality for real-time use. To address this, we introduce C-SHAP (Clustering-Boosted SHAP), a hybrid method that combines SHAP with K-means clustering to reduce execution times significantly while preserving interpretability. C-SHAP excels across various datasets and machine learning methods, matching SHAP’s accuracy in selected features while maintaining an accuracy of 0.73 for Random Forest with substantially faster performance. Notably, in the Diabetes dataset collected by the National Institute of Diabetes and Digestive and Kidney Diseases, C-SHAP reduces the execution time from nearly 2000 s to just 0.21 s, underscoring its potential for scalable, efficient interpretability in time-sensitive applications. Such advancements in interpretability and efficiency may hold value for enhancing decision-making within software-intensive systems, aligning with evolving engineering approaches.
A BIM-Enabled Workflow for the Rehabilitation of Heritage Steel Bridges
Authors: Crisan Andrei , Juravle Andreia , Bancila Radu
Published: January 2025

The rehabilitation of heritage steel bridges raises specific challenges due to their historical significance and structural complexity. These structures, often subjected to ageing, corrosion, and insufficient documentation, require specialized approaches that balance preservation with modern infrastructure demands. In this context, digitalization offers a transformative pathway, enabling more precise maintenance planning, enhanced decision-making, and better alignment with sustainability goals, with Building Information Modelling (BIM) fostering seamless information transfer and integration across project lifecycle. This paper highlights the potential of BIM in predictive maintenance, resource optimization, and strategic rehabilitation planning. It proposes a structured approach for defining and implementing information requirements (IRs), ensuring alignment between organizational objectives, asset-level needs, and project-specific deliverables. A significant contribution of this research is the development of a template for information delivery specification (IDS), providing a robust framework for data exchange and quality control throughout project phases. The IDS supports the integration of technical and historical data into a centralized digital repository, addressing both operational and heritage preservation needs. Finally, the article discusses structural assessment and strengthening strategies within the BIM workflow, emphasizing their role in achieving efficient and sustainable bridge rehabilitation.
A Polynomial-Time Algorithm for Detection of Uncovered Transitions in a Petri Net-Based Concurrent System
Authors: Wojnakowski Marcin , Maliński Maxim , Wiśniewski Remigiusz , Obuchowicz Andrzej , Li Zhiwu , Konarczak Dawid
Published: January 2025

This paper introduces a novel algorithm for the efficient verification of a Petri net-based concurrent control system. The proposed method is based on the computation of transition invariant coverage to detect possible errors in the modelled system. Transition invariants play a crucial role in ensuring the correctness and reliability of such systems; however, existing methods often struggle with high computational demand, especially in the case of large and complex systems. The proposed approach addresses this challenge by performing a fast polynomial-time analysis to identify uncovered transitions, thereby streamlining the verification process. The effectiveness and efficiency of the proposed technique is verified experimentally with a set of 386 test modules (benchmarks) and compared against two well-known established methods: the classical method proposed by Martínez–Silva (as a reference algorithm) and PIPE (Platform Independent Petri Net Editor) tool. The results of the experiments confirm high performance of the presented algorithm, which was able to compute results for all the tested cases. In contrast, both the reference algorithm as well as the PIPE tool failed to deliver results for all examined models within one hour. The proposed algorithm is especially useful in early design stages, offering system designers timely insights into potential issues.
Transient Horizontal Response of a Pipe Pile in Saturated Soil with a Flexible Support at the Pile Head
Authors: Su Ao , Zhang Min , Shang Wei , Wang Qiqi
Published: January 2025

This study examines the horizontal transient response of pipe piles in saturated soil, assuming a two-stage equivalent linear relationship between the bending moment and the rotation at the pile head. The potential function is introduced, and the three-dimensional wave equation for saturated soils is decoupled using operator decomposition and the method of separation of variables. By applying the appropriate initial and boundary conditions, the horizontal lateral forces on the pile from both the surrounding soil and the soil within the pile shaft are calculated. The pipe pile is modeled as a Timoshenko beam. Continuity conditions at the pile–-soil interface are applied, and a time-domain solution for horizontal transient vibrations is derived. This solution accounts for various pile top constraint conditions and is obtained through the inverse Laplace transform. Validation against existing results demonstrates the accuracy of the proposed model. Finally, a parametric study investigates the effects of factors such as impact load, permeability, pile diameter, and pile head constraints on pile displacement.
Elevated BP180 ELISA at Diagnosis Correlates with Disease Severity and Relapse in Oral Mucous Membrane Pemphigoid: Preliminary Results from a Retrospective Monocentric Italian Study
Authors: Gabusi Andrea , Gissi Davide B. , Rossi Roberto , Filippi Federica , Loi Camilla , Misciali Cosimo , Clarizio Giacomo , La Placa Michelangelo , Bardazzi Federico
Published: January 2025

Background: Little is known about the relevance of BP180 ELISA for the clinical management of oral mucous membrane pemphigoid (OMMP). The aim of the present study was to investigate if the levels of anti-BP180 antibodies at diagnosis could be correlated with clinical severity and relapse. Methods: The present study included 44 OMMP patients with positive direct immunofluorescence (DIF). Circulating anti-BP180 IgG was measured using the same available ELISA kit (Euroimmun cut-off 20 U/mL). Clinical severity at diagnosis was measured using the oral disease severity score (ODSS). Only patients who achieved clinical remission (CR) were included in the analysis of variables related to relapse. Relapse was calculated as the interval between the date of the best type of clinical remission achieved and the date of relapse. Results: Values of BP180 > 20 U/mL significantly correlated with higher ODSSs in both univariate (p < 0.05) and multivariate analyses (p < 0.05). Among 39/44 patients who achieved CR, 17/39 relapsed. Kaplan–Meier analysis revealed that patients with BP180 > 20 U/mL displayed worse clinical behavior in terms of relapse (p < 0.05). Conclusion: BP180 ELISA at diagnosis appears to be a useful parameter to stratify OMMP patients with more severe disease and worse clinical outcomes after clinical remission.
Impact of Blade Geometric Parameters on the Specific Cutting Energy of Willow (Salix viminalis) Stems
Authors: Nowakowski Tomasz , Tucki Karol
Published: January 2025

This article presents a model to estimate the specific energy demand for cutting annual willow stems, considering variations in plant moisture content and sliding-cutting angles. The study involved laboratory tests and statistical analyses. Key parameters were measured for 50 randomly selected annual willow shoots, including total plant weight, leaf weight, stem weight, centre of gravity of the shoot, shoot length, and stem diameter at specified heights: 0, 150, 500, 750, 1000, 1250, 1500, and 2000 mm. Five levels of willow shoot moisture content were evaluated. The study established a cutting force-deformation relationship through strength tests with an accuracy of 1 N, which was subsequently used to calculate shear stress and specific cutting energy. Steel blades with an angle of 30° and sliding-cutting angles of 0°, 15°, 30°, and 45° were used in the study. Ten repetitions were performed for each combination of variable parameters: shoot moisture content and blade sliding-cutting angle. Experimental results were evaluated using analysis of variance (ANOVA), while Duncan’s test was applied to identify and classify groups with homogeneous specific energy values. The developed characterisation offers valuable information for designing shredding units and optimising their operational parameters to reduce energy consumption.
End-to-End Information Extraction from Courier Order Images Using a Neural Network Model with Feature Enhancement
Authors: Shen Wei , Li Han , Jin Youbo , Wu Chase Q.
Published: January 2025

Recently, cross-border logistics has experienced rapid development. Cross-border logistics courier orders come in various formats, featuring diverse layouts. Additionally, there is no standardized format for the writing of address and other information on these courier orders. It is challenging for current automated recognition models to handle such images. In this paper, we presented an end-to-end trainable neural network model based on feature enhancement, SwFB, capable of achieving end-to-end conversion from raw images to structured text information. We constructed our feature enhancement module, Co-G-Ma, based on a convolutional neural network (CNN), gated recurrent unit (GRU), and multi-head attention. We collected real cross-border logistics courier order images from a postal company in Zhejiang province, China, to build our dataset, COFIE, and conducted a series of experiments to explore the impact of hyperparameters on the extraction of key field text. Comparative experiments were also performed with other models on publicly available datasets CORD and SROIE. The experimental results demonstrate that our model achieves advanced performance in extracting visual text information and exhibits strong generalization.
The Real-Time Prediction of Cracks and Wrinkles in Sheet Metal Forming According to Changes in Shape and Position of Drawbeads Based on a Digital Twin
Authors: Yi Sarang , Hyun Daeil , Hong Seokmoo
Published: January 2025

In the automotive industry, extensive research has been conducted to eliminate factors negatively impacting product quality, such as wrinkles, cracks, and thickness distribution in components. The application of drawbeads often relies on the experience of field workers, leading to considerable trial and error before stabilizing the production process. Therefore, to efficiently transform these inefficiencies related to time and cost, there is a need for real-time predictive technology for forming quality based on the position of drawbeads and the bead force. This study proposes a method for predicting formability in real-time, based on a digital twin framework that considers the position of drawbeads and holder force. A digital twin was developed to predict the sheet metal forming process using Support Vector Machine, Random Forest, Gradient Boosting Machine, and Artificial Neural Networks. The machine learning models were trained using finite element analysis data corresponding to the position and bead force of drawbeads, enabling the real-time prediction of wrinkles and crack occurrences. The accuracy of the machine learning models was demonstrated, achieving 100% accuracy in determining crack occurrence, with a mean squared error (MSE) of 0.141 for wrinkle prediction and 0.038 for crack prediction, thereby ensuring the accuracy of the forming prediction model based on drawbead applications. Based on these predictive models, a user-friendly GUI has been developed, which is expected to reduce design time and costs while facilitating real-time predictions of forming quality, such as wrinkles and cracks, on-site.
An Emotion Detection GIS-Based Framework for Evaluating Exposure to Heatwave Scenarios in Urban Settlements During a Pandemic
Authors: Cardone Barbara , Di Martino Ferdinando , Mauriello Cristiano , Miraglia Vittorio
Published: January 2025

The study of impacts on and risks to citizens generated by climatic or environmental phenomena in urban settlements is made complex by the coexistence of events that can affect the risk assessment. In this work, a model for the assessment of impacts on and risks to the population generated by heatwaves in urban settlements in the presence of pandemic periods is proposed. The presence of epidemics is treated as a stressor that contributes to altering exposure. To assess the prevalence of this stressor, a fuzzy-based emotion detection method is utilized, which uses the FREDoC framework to categorize the subzones that comprise the urban study area according to the relevance of the pleasant and unpleasant emotions of the citizens, identified based on the examination of posts that have been published on social networks. The proposed model was tested on the urban area of study of the city of Naples in Italy, taking into consideration a heatwave scenario that occurred in the summer of 2021 during the COVID-19 pandemic and analyzing the variation in exposure in the thirty districts into which the city is partitioned. The findings demonstrate that the model can accurately represent the range of impacts and hazards associated with the heatwave brought on by the COVID-19 pandemic.
Quaternion-Based Fast SMC–PD Cross-Domain Tracking Control for Coaxial Hybrid Aerial–Underwater Vehicle Under Oceanic Disturbances
Authors: Lu Mingqing , Yang Wei , Liao Fei , Wu Shichong , Su Yumin , Wu Wenhua
Published: January 2025

In this study, nonsingular modeling and cross-domain trajectory tracking control problems for a special class of coaxial hybrid aerial–underwater vehicles (HAUVs) are investigated. Coaxial HAUVs need to effectively overcome the influence of hydrodynamic factors when moving underwater, so the attitude angle required by coaxial HAUVs is much larger than that in the air. The attitude representation based on quaternion modeling is adopted to avoid the inherent singularity of Euler angle modeling. A cascade sliding mode control and proportion differentiation (SMC-PD) controller is proposed, which is used to position trajectory and attitude quaternion tracking control, respectively. An adaptive sliding mode controller based on disturbance observer (DO) enhancement is adopted in the outer loop to carry trajectory tracking control. At the same time, the expected attitude angle is calculated by the outer loop (position) and is converted into the expected quaternion. With reference to the idea of enhanced robustness in active disturbance rejection control (ADRC), a feedforward proportion derivation (PD) controller based on DO enhancement is used to track the desired quaternion. A variable parameter adaptive algorithm based on the learning rate is introduced in the cascaded SMC-PD controller. The error convergence speed of the system is further improved by adaptively changing the controller parameters. The stability of the proposed control scheme is proved by using the Lyapunov theory. The numerical simulation results show that the controller has good robustness and effectiveness.
Improved Honey Badger Algorithm and Its Application to K-Means Clustering
Authors: Jiang Shuhao , Gao Huimin , Lu Yizi , Song Haoran , Zhang Yong , Wang Mengqian
Published: January 2025

As big data continues to evolve, cluster analysis still has a place. Among them, the K-means algorithm is the most widely used method in the field of clustering, which can cause unstable clustering results due to the random selection of the initial clustering center of mass. In this paper, an improved honey badger optimization algorithm is proposed: (1) The population is initialized using sin chaos to make the population uniformly distributed. (2) The density factor is improved to enhance the optimization accuracy of the population. (3) A nonlinear inertia weight factor is introduced to prevent honey badger individuals from relying on the behavior of past individuals during position updating. (4) To improve the diversity of solutions, random opposition learning is performed on the optimal individuals. The improved algorithm outperforms the comparison algorithm in terms of performance through experiments on 23 benchmark test functions. Finally, in this paper, the improved algorithm is applied to K-means clustering and experiments are conducted on three data sets from the UCI data set. The results show that the improved honey badger optimized K-means algorithm improves the clustering effect over the traditional K-means algorithm.
Vocal Communication Between Cobots and Humans to Enhance Productivity and Safety: Review and Discussion
Authors: Cohen Yuval , Faccio Maurizio , Rozenes Shai
Published: January 2025

This paper explores strategies for fostering efficient vocal communication and collaboration between human workers and collaborative robots (cobots) in assembly processes. Vocal communication enables the division of attention of the worker, as it frees their visual attention and the worker’s hands, dedicated to the task at hand. Speech generation and speech recognition are pre-requisites for effective vocal communication. This study focuses on cobot assistive tasks, where the human is in charge of the work and performs the main tasks while the cobot assists the worker in various peripheral jobs, such as bringing tools, parts, or materials, and returning them or disposing of them, or screwing or packaging the products. A nuanced understanding is necessary for optimizing human–robot interactions and enhancing overall productivity and safety. Through a comprehensive review of the relevant literature and an illustrative example with worked scenarios, this manuscript identifies key factors influencing successful vocal communication and proposes practical strategies for implementation.
Research on High-Speed Railway Subgrade Design Method Based on Energy Dissipation and Dynamic Stability Characteristics
Authors: Bi Zongqi , Ye Yangsheng , Cai Degou , Yan Hongye , Ouyang Mingzhe , Su Ke
Published: January 2025

The subgrade structure of high-speed railways is an important foundation for the safe and smooth operation of high-speed trains, and the scientific design of the subgrade structure provides a fundamental guarantee of its durability and technical economy. As, in the development of high-speed railways in China, higher speeds are being pursued, more requirements have been put forward for the dynamic stability of subgrade structures. To address this issue, this article focuses on the control requirements for the long-term stability of subgrade deformation, and various design methods for high-speed railway subgrade structures are presented. Considering the energy dissipation and dynamic stability characteristics of subgrade filling materials, the dynamic performance of coarse-grained soil filling materials in the bottom layer and graded crushed stones in the surface layer are revealed. The methods for determining the values of dynamic parameters such as the dynamic modulus and damping ratio are provided. Based on the dynamic shakedown theory, the stress–strain hysteresis characteristics of fillers and the variation law of dissipated energy are revealed. The correlation between unit volume dissipated energy and shakedown state under cyclic loading conditions is identified. A criterion for determining the critical shakedown state of high-speed railway subgrade structures based on equivalent unit volume dissipated energy is proposed, and a method for determining the design threshold of dynamic stress and dynamic strain is also proposed. The results show that the shakedown design critical values of equivalent unit volume dissipated energy in the bottom and surface layers of the foundation were between 0.0103~0.0133 kJ/m3 and 0.0121~0.0149 kJ/m3, respectively. The critical dynamic strain range was 0.8 × 10−3~1.3 × 10−3. On this basis, a high-speed railway subgrade design method based on energy dissipation and dynamic shakedown characteristics was developed. The results can provide theoretical support for the design of high-speed railway subgrade structures with different filling material alternatives and control standards.
LHB-YOLOv8: An Optimized YOLOv8 Network for Complex Background Drop Stone Detection
Authors: Yu Anjun , Fan Hongrui , Xiong Yonghua , Wei Longsheng , She Jinhua
Published: January 2025

Real-time detection of rockfall on slopes is an essential part of a smart worksite. As a result, target detection techniques for rockfall detection have been rapidly developed. However, the complex geologic environment of slopes, special climatic conditions, and human factors pose significant challenges to this research. In this paper, we propose an enhanced high-speed slope rockfall detection method based on YOLOv8n. First, the LSKAttention mechanism is added to the backbone part to improve the model’s ability to balance the processing of global and local information, which enhances the model’s accuracy and generalization ability. Second, in order to ensuredetection accuracy for smaller targets, an enhanced detection head is added, and other detection heads of different sizes are combined to form a multi-scale feature fusion to improve the overall detection performance. Finally, a bidirectional feature pyramid network (BiFPN) is introduced in the neck to effectively reduce the parameters and computational complexity and improve the overall performance of rockfall detection. In addition we compare the LSKAttention mechanism with other attention mechanisms to verify the effectiveness of the improvements. Compared with the baseline model, our method improves the average accuracy mAP@0.5 by 4.8%. Moreover, the amount of parameters is reduced by 20.2%. Among the different evaluation criteria, the LHB-YOLOv8 method shows obvious advantages, making it suitable for engineering applications and the practical deployment of slope rockfall detection systems.
Identification of Inequities in Green Visibility and Ways to Increase Greenery in Neighborhoods: A Case Study of Wuhan, China
Authors: Guo Xiaohua , Liu Chang , Bi Shibo , Tang Yuling
Published: January 2025

The rapid increase in urban population density driven by urban development has intensified inequity in urban green space distribution. Identifying the causes of changes in green equity and developing strategies to improve urban greening are crucial for optimizing resource allocation and alleviating social inequalities. However, the long-term spatio-temporal evolution of green visibility and equity remains underexplored. This study utilized the “Time Machine” feature to capture street view images from 2014, 2017, and 2021, analyzing changes in green visibility and its equity across residential communities in Wuhan. Deep learning techniques and statistical methods, including the Gini coefficient and location quotient (LQ), were employed to assess the distribution and spatial equity of street-level greenery. The results showed that overall green visibility in Wuhan increased by 4.18% between 2014 and 2021. However, this improvement did not translate into better spatial equity, as the Gini coefficient consistently ranged between 0.4 and 0.5. Among the seven municipal districts, only the Jiang’an District demonstrated relatively equitable green visibility in 2017 and 2021. Despite a gradual reduction in disparities in green visibility, a spatial mismatch persisted between UGS growth and population distribution, leading to uneven patterns in UGS equity. This study explores the factors driving inequities in green visibility and proposes strategies to enhance urban greening. Key recommendations include integrating the green visibility equity evaluation framework into urban planning to guide fair green space allocation, prioritizing greenery in low-income neighborhoods, and reducing hardscapes to support the planting and maintenance of tall canopy trees. These measures aim to enhance accessible and visible green resources and promote equitable access across communities.
A Stakeholder-Centric Approach to Advancing the Circular Economy in the Building Sector
Authors: Kaya Fuat Emre
Published: January 2025

Since the Industrial Revolution, climate change has intensified due to rising greenhouse gas emissions, leading to severe environmental impacts. Given the building sector’s significant contribution to climate change, the circular economy has emerged as a key mitigation strategy. Despite political support and some advancements, significant barriers persist in the building sector’s transition to the circular economy. This article explores the pivotal role of stakeholders as essential agents of change, highlighting the necessity of a concentrated effort on stakeholder engagement in the building sector’s circular economy transition. Using an online questionnaire, this article evaluated the current status of the building sector, as well as stakeholders’ awareness, roles, and perspectives on the transition. The results revealed that while stakeholders are aware of their environmental impacts, knowledge gaps persist, particularly in waste management and circular economy practices. The stakeholders recognize that the transition is happening, but there is a sense of uncertainty about its effectiveness due to substantial barriers. Despite these barriers, there is an increasing commitment toward the practices of the circular economy, underscoring the need for policy development, infrastructure provision, and training programs to support the transition. This article contributes to the literature by providing insights into key stakeholders’ perspectives and offering actionable strategies to enhance engagement for a more effective transition to the circular economy in the building sector.
Paradigm Shift in Typhoon Forecasting for the Korean Peninsula: A Case Study on the Applicability of the Typhoon-Ready System
Authors: Na Hana , Jung Woo-Sik
Published: January 2025

Climate change has significantly increased multi-hazard disasters caused by typhoons, exposing the limitations of conventional forecasting systems that often neglect regional socio-economic vulnerabilities. This study develops and validates the Typhoon-Ready System (TRS) as an effective disaster-management framework for the Korean Peninsula. The TRS integrates hazard data with socio-economic and environmental vulnerability factors to produce region-specific risk indices. The analysis of four representative typhoons—Lingling (2019), Rusa (2002), Maemi (2003), and Mitak (2019)—demonstrates TRS’s applicability in identifying high-risk zones and supporting disaster preparedness strategies. The TRS framework incorporates indices, such as the Strong Wind Index (SWI), Heavy Rainfall Index (HRI), Storm Surge Index (SSI), and Air Quality Index (AQI), effectively combining meteorological modeling with vulnerability analysis. Results demonstrate that the TRS outperforms traditional systems by accurately identifying high-risk zones and correlating them with observed damage patterns. For example, the TRS successfully pinpointed high wind risks in Seoul and Incheon during Typhoon Lingling and forecasted severe flooding in Gangneung and Samcheok during Typhoon Rusa. By integrating vulnerability factors, including population density, infrastructure aging, and urbanization levels, the TRS provides a more holistic and accurate risk assessment. This research highlights the necessity of a multi-dimensional forecasting approach for enhancing disaster preparedness and resilience against climate change-induced typhoon impacts.
Dynamics of a Fractional-Order Eco-Epidemiological Model with Two Disease Strains in a Predator Population Incorporating Harvesting
Authors: El-Shahed Moustafa , Moustafa Mahmoud
Published: January 2025

In this paper, a fractional-order eco-epidemiological model with two disease strains in the predator population incorporating harvesting is formulated and analyzed. The model assumes that the population is divided into a prey population, a susceptible predator population, a predator population infected by the first disease, and a predator population infected by the second disease. A mathematical analysis and numerical simulations are performed to explain the dynamics and properties of the proposed fractional-order eco-epidemiological model. The positivity, boundedness, existence, and uniqueness of the solutions are examined. The basic reproduction number and some sufficient conditions for the existence of four equilibrium points are obtained. In addition, some sufficient conditions are proposed to ensure the local and global asymptotic stability of the equilibrium points. Theoretical results are illustrated through numerical simulations, which also highlight the effect of the fractional order.
Exploring RNA-Seq Data Analysis Through Visualization Techniques and Tools: A Systematic Review of Opportunities and Limitations for Clinical Applications
Authors: Manzoor Farhana , Tsurgeon Cyruss A. , Gupta Vibhuti
Published: January 2025

RNA sequencing (RNA-seq) has emerged as a prominent resource for transcriptomic analysis due to its ability to measure gene expression in a highly sensitive and accurate manner. With the increasing availability of RNA-seq data analysis from clinical studies and patient samples, the development of effective visualization tools for RNA-seq analysis has become increasingly important to help clinicians and biomedical researchers better understand the complex patterns of gene expression associated with health and disease. This review aims to outline the current state-of-the-art data visualization techniques and tools commonly used to frame clinical inferences from RNA-seq data and point out their benefits, applications, and limitations. A systematic review of English articles using PubMed, Scopus, Web of Science, and IEEE Xplore databases was performed. Search terms included “RNA-seq”, “visualization”, “plots”, and “clinical”. Only full-text studies reported between 2017 and 2024 were included for analysis. Following PRISMA guidelines, a total of 126 studies were identified, of which 33 studies met the inclusion criteria. We found that 18% of studies have visualization techniques and tools for circular RNA-seq data, 56% for single-cell RNA-seq data, 23% for bulk RNA-seq data, and 3% for long non-coding RNA-seq data. Overall, this review provides a comprehensive overview of the common visualization tools and their potential applications, which is a useful resource for researchers and clinicians interested in using RNA-seq data for various clinical purposes (e.g., diagnosis or prognosis).
Broussonetia papyrifera Extract Can Be Used as a Raw Material Source for a Sterility Agent for Microtus fortis
Authors: Wang Shuangye , Lan Tian , Zhao Yunlin , Liu Wanfu , Huang Tian , Zhang Meiwen , Hu Zhiyuan , Xu Zhenggang
Published: January 2025

Plant sterilants are used to control rodent populations due to their minimal environmental risk and other ethical considerations. However, their practical utilization is unsatisfactory due to high costs and processing difficulties. Broussonetia papyrifera is a plant material that has shown the potential to inhibit the reproduction of Microtus fortis, a species that causes serious damage to crops in the Dongting Lake region in China. M. fortis was treated with different doses of B. papyrifera leaf methanol extracts. The results show that the growth of sex organs was inhibited, and the males’ testosterone levels and sperm quality were reduced. Though there were some positive effects on females, the reproductive parameters of coupled voles were inferior; the most treated couple exhibited an increased reproductive time, fetal counts, and reduced weight. It was also found that M. fortis responded negatively to the extract after a single treatment or long-term repeated treatment compared to a short-term repeated treatment. B. papyrifera leaves showed a higher application potential as a sterilant for male rodents. These findings enrich the study of plant sterilants and provide insights into the utilization of B. papyrifera and the management of rodents. Owing to the effectiveness and accessibility of the leaves, the derived sterilant may be more economical for controlling rodent pests.
Endometrial Receptivity–Lessons from “Omics”
Authors: Ye Louie , Dimitriadis Evdokia
Published: January 2025

The window of implantation (WOI) is a critical phase of the menstrual cycle during which the endometrial lining becomes receptive and facilitates embryo implantation. Drawing on findings from various branches of “omics”, including genomics, epigenomics, transcriptomics, proteomics, lipidomics, metabolomics, and microbiomics, this narrative review aims to (1) discuss mechanistic insights on endometrial receptivity and its implication in infertility; (2) highlight advances in investigations for endometrial receptivity; and (3) discuss novel diagnostic and therapeutic strategies that may improve reproductive outcomes.
Visual and High-Efficiency Secretion of SARS-CoV-2 Nanobodies with Escherichia coli
Authors: Zhao Shuai , Zeng Wanting , Yu Fang , Xu Pingping , Chen Chin-Yu , Chen Wanping , Dong Yanming , Wang Fei , Ma Lixin
Published: January 2025

Nanobodies have gained attention as potential therapeutic and diagnostic agents for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) due to their ability to bind and neutralize the virus. However, rapid, scalable, and robust production of nanobodies for SARS-CoV-2 remains a crucial challenge. In this study, we developed a visual and high-efficiency biomanufacturing method for nanobodies with Escherichia coli by fusing the super-folder green fluorescent protein (sfGFP) to the N-terminus or C-terminus of the nanobody. Several receptor-binding domain (RBD)-specific nanobodies of the SARS-CoV-2 spike protein (S) were secreted onto the surface of E. coli cells and even into the culture medium, including Fu2, ANTE, mNb6, MR3-MR3, and n3113.1. The nanobodies secreted by E. coli retained equal activity as prior research, regardless of whether sfGFP was removed. Since some of the nanobodies bound to different regions of the RBD, we combined two nanobodies to improve the affinity. Fu2-sfGFP-ANTE was constructed to be bispecific for the RBD, and the bispecific nanobody exhibited significantly higher affinity than Fu2 (35.0-fold), ANTE (7.3-fold), and the combination of the two nanobodies (3.3-fold). Notably, Fu2-sfGFP-ANTE can be normally secreted into the culture medium and outer membrane. The novel nanobody production system enhances the efficiency of nanobody expression and streamlines the downstream purification process, enabling large-scale, cost-effective nanobody production. In addition, E. coli cells secreting the nanobodies on their surface facilitates screening and characterization of antigen-binding clones.
Biological Behavior of Bioactive Glasses SinGlass (45S5) and SinGlass High (F18) in the Repair of Critical Bone Defects
Authors: Nogueira Dayane Maria Braz , Rosso Marcelie Priscila de Oliveira , Santos Paulo Sérgio da Silva , Sousa-Neto Manoel Damião , Silva-Sousa Alice Corrêa , Soares Cleverson Teixeira , Reis Carlos Henrique Bertoni , Rossi Jéssica de Oliveira , Bueno Cleuber Rodrigo de Souza , Buchaim Daniela Vieira , Buchaim Rogério Leone , Zangrando Mariana Schutzer Ragghianti
Published: January 2025

This study evaluated the osteogenic potential of the bioactive glasses SinGlass (45S5) and SinGlass High (F18) in regenerating critical bone defects in rat calvaria. Both biomaterials promoted new bone formation around the particles, with the SinGlass High (F18) group exhibiting a higher rate of bone maturation. Histomorphological and birefringence analyses revealed better organization of the newly formed bone in the biomaterial-treated groups, and immunohistochemistry indicated the expression of osteogenic markers such as osteocalcin, immunostaining for bone morphogenetic protein 2 (BMP 2), and immunostaining for bone morphogenetic protein 4 (BMP 4). Microtomography computadorized (Micro-CT) revealed centripetal bone formation in both groups, with greater integration of the particles into the surrounding bone tissue. The superior performance of SinGlass High (F18) was attributed to its higher potassium and magnesium content, which enhance osteoconductivity. After 42 days, the SinGlass High (F18) group showed the highest percentage of new bone formation, in line with previous studies. Although our results are promising, the limited follow-up period and use of a single animal model highlight the need for further research to validate clinical applicability. SinGlass High (F18) appears to be a viable alternative to autografts in bone repair, with potential to improve tissue integration and accelerate recovery.