bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhancing Quadruped Robot Walking on Unstructured Terrains: A Combination of Stable Blind Gait and Deep Reinforcement Learning
Authors: Marcus Shirelle Drori , Shapiro Amir , Giladi Chen
Published: February 2025

Legged robots, designed for high adaptability, are poised for deployment in hazardous tasks traditionally undertaken by humans, particularly in unstructured terrains where their wheeled counterparts cannot operate. Nevertheless, using them in unstructured settings necessitates advanced control techniques to maneuver without depending entirely on visual signals or pre-programmed instructions. To address these challenges, this research proposes a novel walking algorithm for quadruped robots that blends a stable blind gait without needing any visual cues with Deep Reinforcement Learning to enhance mobility across diverse terrains. The algorithm’s effectiveness was evaluated virtually, emphasizing the ability to regulate the robot’s leg movements and posture when reaching obstacles. Our results demonstrated a success rate of over 90% in the stair-climbing task, suggesting that the algorithm improved the robot’s mobility and stability. Although emphasizing a steady blind gait reduces reliance on visual cues, incorporating the algorithm with further sensory inputs and environmental awareness may improve the robot’s functionality and versatility in practical situations. More dynamic gaits and a wider variety of static and dynamic obstacles will be the focus of future algorithm development. Furthermore, validation in the real world will aid in detecting any shortcomings or potential areas for enhancement in the algorithm, thereby improving its adaptability and resilience in diverse settings and assignments.
Convolutional-Neural-Network-Based Fiber Optic Channel Emulator and Its Application to Fiber-Longitudinal Power Profile Estimation
Authors: Wang Daobin , Wen Kun , Bai Tiantian , Xia Ruiyang , Zhao Zanshan , Gao Guanjun
Published: February 2025

This paper proposes an accuracy enhancement method for the fiber-longitudinal power profile estimation (PPE) based on convolutional neural networks (CNN). Two types of CNNs are designed. The first one is a network that treats different polarization streams identically. This network is denoted as CNN. The second one considers the difference between the contributions of different polarization streams to the nonlinear phase shift and is denoted as enhanced CNN (ECNN). The numerical simulation results confirm the effectiveness of the method for a 64 GBaud/s DP-QPSK system with a fiber length of 320 km. The effects of finite impulse response filter (FIR) length, power into the fiber, and polarization mode dispersion on the PPE accuracy are examined. Finally, monitoring results of the proposed method in the presence of several simultaneous power attenuation anomalies in the fiber optic link are shown. It is found that the accuracy of the PPE substantially improves after using the proposed method, achieving a relative gain of up to 71%.
Tourism-Driven Rural Restructuring in Peri-Urban China: A Systems Theory Analysis of Liujiafan Community
Authors: Zhang Hexiang , Liang Jing , Zhang Xuechang , Zhang Yechen
Published: February 2025

This study investigates the impact of rural tourism on rural transformation in China, using Liujiafan in Hefei as a case study. Based on system theory, it explores the mechanisms of rural transformation and restructuration driven by tourism under the dual influence of endogenous and exogenous systems. Key findings include: (1) The tourism-driven rural transformation process exhibits distinct phased and holistic characteristics. (2) The core of this transformation is the re-creation of rural value through the interaction of "human-land-industry," supported by three major rural communities. (3) The transformation is a dynamic and cyclical process. (4) Both tourism-driven restructuring and natural evolution begin with economic restructuration but differ in trajectory and speed. This study provides actionable insights for policymakers to leverage tourism in rural revitalization strategies, emphasizing infrastructure development and community engagement.
Beneficial Microorganisms May Help Both Resistant and Susceptible Papaya Plants to Their Resistance to the Infection of Papaya Ringspot Virus
Authors: Tan Yanrong , Xie Xiang , Huang Qixing , Cao Yang , Zhou Xia , Li Chunqian , Sun Jianbo , Wang Hui , Yin Guohua , Zhao Hui , Guo Anping
Published: February 2025

Soil microorganisms play an important role in regulating the responses of plants to disease, but little is known regarding the role of the microbial community in rhizosphere soil in the response to diseases in papaya. To clarify how the abundance and composition of the microbial rhizosphere community of papaya change with viral infection, papaya plants resistant and susceptible to papaya ringspot virus (PRSV) were inoculated with PRSV in the field, and differences in rhizosphere soil microbial communities between healthy and susceptible papaya were analyzed. The physiochemical properties of the soil surrounding the root system were strongly affected by microbial taxa, but this did not have a significant effect on plant health. 16S rRNA and ITS sequencing revealed that disease stress increased the microbial diversity of bacteria and decreased the diversity of fungi. The analysis of soil microbial community shows that the abundance of Nitrospirae was significantly higher in HN soil (1.35 ± 0.41) than in NC soil (0.83 ± 0.13) and YK soil (0.79 ± 0.27); the abundance of Paenibacillus was higher in HN soil (0.83 ± 0.38) than in NC (0.35 ± 0.12）and YK soil (0.58 ± 0.19); the abundance of Acremonium was higher in HN soil (0.71 ± 0.37) than in NC soil (0.21 ± 0.18) and YK soil (0.48 ± 0.43). Nitrospira, Paenibacillus, and Acremonium were all beneficial microorganisms, and they were significantly higher in healthy papaya soil than in susceptible papaya soil may help viral resistance. We show for the first time that a non-soil-borne disease may influence the microbiomes of papaya rhizosphere soil. When resistant papaya was infected with PRSV, beneficial microorganisms could be recruited in the rhizosphere soil to resist viral infection. Although these results are only preliminary insights into the potential role of beneficial microorganisms in supporting plant health under viral stress, our research provides new insights with implications for the prevention and control of papaya ringspot disease, furthermore, microorganisms that promote viral resistance could expediate the development of biopharmaceuticals or green fertilizers.
Quantitative Evaluation of PWV in Two Reanalysis Datasets Using GNSS Observations at the NSRT Site
Authors: Li Mingshuai , Zhang Hua , Li Peng , Li Xiaofei
Published: February 2025

The Global Navigation Satellite System (GNSS) provides high spatiotemporal resolution data for monitoring precipitable water vapor (PWV), a critical parameter for weather forecasting, climate research, and astronomical site selection. This study evaluates the accuracy of ERA5 and NASA reanalysis datasets by comparing them with GNSS-derived PWV data at the NSRT site. Statistical methods, including root mean square error (RMSE), mean absolute error (MAE), and mean bias error (MBE), were employed to assess their performance across seasonal and monthly scales. The results show that ERA5 and NASA datasets exhibit high consistency with GNSS-derived PWV data, effectively capturing seasonal variations. ERA5 demonstrates superior accuracy during winter with lower RMSE values (e.g., 0.56 mm in January), while NASA performs better in summer months under high water vapor conditions. Systematic biases are observed in both datasets, emphasizing the need for localized bias correction to enhance their reliability.This study highlights the complementary strengths of ERA5 and NASA datasets and underscores the importance of GNSS data in validating and improving reanalysis models. The findings provide valuable insights for water vapor monitoring, atmospheric studies, and the optimization of astronomical site selection.
Communication Strategies for Building Sustainable Supplier Relationships: A Study of Italian Dining Practices
Authors: Warwick Isabelle
Published: February 2025

This study investigates the communication strategies employed by Italian dining establishments to build sustainable supplier relationships. The importance of effective communication in fostering collaboration and ensuring mutual understanding between restaurants and suppliers is critically analyzed. The research utilizes a qualitative approach, involving in-depth interviews with key stakeholders from 26 Italian restaurants and their suppliers. The findings reveal that transparency and clarity in communication serve as foundational elements in establishing trust, allowing both parties to align their sustainability objectives effectively. Additionally, the research highlights the significance of collaboration in decision-making processes, where restaurants engage suppliers in menu planning and sustainability initiatives, promoting innovative solutions that enhance sustainability. Technological advancements also play a crucial role in streamlining communication and facilitating real-time updates, ultimately improving supplier engagement. However, challenges such as cost barriers, cultural differences, and logistical constraints present significant hurdles to achieving sustainable practices. The study emphasizes the need for tailored communication strategies to overcome these challenges and suggests that incentives can motivate suppliers to adhere to sustainability goals. Furthermore, the influence of consumer demand for sustainable products drives suppliers to adapt their practices in alignment with restaurant expectations. The findings underscore the necessity of crisis management communication strategies to navigate disruptions within the supply chain. Overall, this research contributes valuable insights into the interplay between communication and sustainability in the Italian dining sector, providing a framework for restaurants to enhance their supplier relationships and promote sustainable practices effectively.
Evaluation of Alginate Beads for Microencapsulation of Enzymes and Delivery into Hindgut of Ruminants
Authors: Almassri Nada , Trujillo Francisco J. , Bell Robert , Klieve Athol V. , Ying DanYang , Terefe Netsanet Shiferaw
Published: February 2025

The need for effective enzyme delivery systems in ruminant nutrition is underscored by the challenge of protecting enzymes in the harsh rumen environment. This study focused on enhancing the encapsulation efficiency (EE) of β-glucosidase in alginate beads to improve its stability and protection within rumen-like conditions. The objective was to develop a microencapsulation system capable of sustaining enzyme activity post-ingestion, using β-glucosidase as a model enzyme. Various formulations were tested to optimize EE and stability. Data were collected by systematically incorporating different stabilizers and crosslinking agents into the alginate matrix. The addition of 0.1% chitosan into the gelling solution significantly improved EE to 49% by reducing the matrix’s porosity. Further improvements were achieved with stabilizers: 4% sucrose (AOS) increased EE to 95.5%, while the combination of 4% sucrose and 2% maltodextrin (AOMS) reached the highest EE at 100 ± 2.16%. In contrast, the addition of 4% pectin (APB) reduced EE to 40.5%, likely due to interference with alginate crosslinking and higher water content, weakening bead structure.In vitro rumen fermentation tests showed degradation rates of 42–54%, highlighting the need for further development of more robust microcapsules. These findings suggest that additional coating strategies are essential to improve bead stability in rumen environments. Future research should focus on creating bead formulations with enhanced protective layers to increase enzyme retention and recovery during delivery.
Enhanced Tribological and Electrical Performance of Graphene-Coated Polyetheretherketone Nanocomposites
Authors: Lee Pyoung-Chan , Hong Seo-Hwa , Kim Jung Hoon , Seo Jae Young , Ko Youn Ki , Ha Jin Uk , Jeoung Sun Kyoung , Kim Myeong-Gi , Cho Beom-Gon
Published: February 2025

Polyetheretherketone (PEEK) is widely used across various industries because of its high thermal stability, chemical resistance, and superior mechanical properties. This paper introduces an optimized method for dispersing functionalized graphene to improve the frictional and electrical resistance properties of PEEK. The influence of graphene, recognized as an effective additive, on the melt behavior, thermal stability, and tribological and electrical properties of PEEK–graphene nanocomposites was assessed for different filler contents. Results show that graphene acts as a nucleating agent, enhancing crystallinity in PEEK–graphene nanocomposites. A nanocomposite containing 1.0 wt.% graphene exhibited optimal frictional performance and surface resistance. Additionally, the study reveals that the integration of hybrid additives with varied shapes fosters the formation of three-dimensional particle networks more effectively than graphene additives alone.
Improving Road Safety with AI: Automated Detection of Signs and Surface Damage
Authors: Merolla Davide , Latorre Vittorio , Salis Antonio , Boanelli Gianluca
Published: February 2025

Public transportation plays a crucial role in our lives, and the road network is a vital component in the implementation of smart cities. Recent advancements in AI have enabled the development of advanced monitoring systems capable of detecting anomalies in road surfaces and road signs, which can lead to serious accidents. This paper presents an innovative approach to enhance road safety through the detection and classification of traffic signs and road surface damage using advanced deep learning techniques (CNN). This integrated approach supports proactive maintenance strategies, improving road safety and resource allocation for the Molise region and the city of Campobasso. The resulting system, developed as part of the CTE Molise research project funded by the Italian Minister of Economic Growth (MIMIT), leverages cutting-edge technologies such as Cloud computing and High Performance Computing with GPU utilization. It serves as a valuable tool for municipalities, for the quick detection of anomalies and the prompt organization of maintenance operations.
Impact of Climate Change on Water Quality and Sustainability in Baluchistan: Pakistan’s Challenges in Meeting United Nations Sustainable Development Goals (UNSDGs)
Authors: Ishaque Waseem , ur Rehman Muhammad Zia , Ellahi Haroon
Published: February 2025

Pakistan's water quality and water management are at a crucial juncture, especially in the underdeveloped province of Baluchistan. The 5th most populous country which ranks 5th in global climate vulnerability index confronts evolving water security challenges, which is complicating its national security matrix. Water shortages are escalating swiftly due to increasing demand across all industries that utilize water. Burgeoning population, increasing from 175 million in 2010 to an estimated 247 million in 2024 and adverse impacts of climate change are seriously affecting water quality and availability across different sectors, which is exacerbated by persistent political instability and internal security issues, disincentivizing the potential investors in water sector at-least in short to medium term in Pakistan. The quality of drinking water is rapidly deteriorating due to water scarcity and contamination from various sources. Despite the government’s promises of providing clean drinking water to inhabitants of Baluchistan and employing smart technology for irrigation purposes, the implementation of these policies remains a formidable task. The study argues that surface and ground water in Baluchistan is contaminated, posing health risks and evolving human security challenges. The study examines drinking water quality using laboratory testing by collecting samples from designated urban and rural areas and comparing them with the minimum safe standards established by international and national clean drinking water guidelines. Laboratory testing has shown a significant decay in the quality of drinking water in Baluchistan, warranting immediate redressal. The persistent decline in water quality and water availability poses serious challenges in the attainment of the water related United Nations Sustainable Development Goals (UNSDGs) number six by 2030. The study provides incisive analysis and recommendations to facilitate the government and relevant ministries in mitigating the vulnerabilities of climate change, provide clean drinking water to inhabitants of Baluchistan and address critical issues of water security on sustainable basis.
Ecological Structures, Conditions, and the Enhancement of Food Web and Ecosystem Stability
Authors: Montgomery Richard Murdoch
Published: February 2025

Abstract Ecological dynamics are inherently complex, involving nonlinear interactions across multiple scales and life stages. Despite extensive research on population dynamics and food web stability, the phenomenon of “lag interference”—where delays inherent in stage‐structured interactions combine in nontrivial ways to influence overall system dynamics—remains underexplored. In this article, we develop a conceptual framework to examine how ecological structures and conditions foster lag interference, potentially enhancing stability in stage‐structured populations, food webs, and entire ecosystems. Drawing on delay differential equation theory, structured matrix models, and food web network analyses, we review the conditions under which demographic delays (e.g., maturation times, reproduction lags) interact to dampen oscillations and mitigate destabilizing feedback loops. We also highlight how spatial heterogeneity, network topology, and the strength of coupling between life stages modulate lag interference. Finally, we discuss future research directions that integrate empirical and theoretical approaches to test these ideas and refine our understanding of ecosystem resilience.
Predictive Analysis Research for Workplace Job Risks and Burnout of Public Health and Safety Inspectors Amid the Global Climate Crisis
Authors: Adamopoulos Ioannis , Valamontes Antonios , Dounias George
Published: February 2025

The increasing severity of climate-related workplace hazards poses a significant challenge to occupational health and safety. Public Health and Safety Inspectors are particularly vulnerable to extreme temperatures, air pollution, and high-risk environments, which contribute to immediate physical threats and long-term burnout. This study employs secondary data analysis AI-driven predictive analytics to assess workplace hazards and forecast burnout risks, integrating machine learning models and tools such as eXtreme Gradient Boosting (XGBoost), Random Forest, Autoencoders, and Long Short-Term Memory (LSTMs), adapted for modeling and data processing. The results indicate that predictive models achieved 85–90% accuracy in predicting workplace hazards, with early warning systems reducing workplace incidents by 35% over six months. Burnout risk analysis identified key predictors, including physical hazard exposure (β = 0.76, p < 0.01), extended work hours (>10h/day, +40% risk). Inadequate training (β = 0.68, p < 0.05), adaptive workload scheduling, fatigue monitoring, successfully lowered burnout prevalence by 28%. The models improved hazard detection by incorporating real-time environmental data, while Natural Language Processing (NLP)-based text mining identified stress-related indicators in worker reports. The evidence indicates the effectiveness of the driven predictions in workplace safety, demonstrating its ability to predict, classify, and mitigate occupational risks before escalation. The findings underscore the necessity of reinforcement learning-based adaptive monitoring to optimize workforce well-being. Expanding predictive-driven occupational health frameworks to broader industries could enhance safety protocols and ensure proactive, data-driven risk mitigation strategies for a sustainable workforce and future applications for integrating biometric wearables and real-time physiological monitoring to improve predictive accuracy.
Advanced TiO2 Based Photocatalytic Systems for Water Splitting: A Comprehensive Review from Fundamentals to Manufacturing
Authors: Ahasan Tarek , Edirisooriya E.M.N. Thiloka , Senanayake Punhasa S. , Xu Pei , Wang Huiyao
Published: February 2025

The global imperative for clean energy solutions has positioned photocatalytic water splitting as a promising pathway for sustainable hydrogen production. This review comprehensively analyzes recent advances in TiO2-based photocatalytic systems, focusing on materials engineering, water source effects, and scale-up strategies. We recognize the advancement in nanoscale architectural design, engineered heterojunction of the catalyst, and cocatalyst integration that have significantly enhanced photocatalytic efficiency. Particular emphasis is placed on the crucial role of water chemistry in photocatalytic system performance, analyzing how different water sources—from wastewater to seawater—impact hydrogen evolution rates and system stability. Additionally, the review addresses key challenges in scaling up these systems, including optimization of reactor design, light distribution, and mass transfer. Recent developments in artificial intelligence-driven materials discovery and process optimization are discussed, along with emerging opportunities in bio-hybrid systems and CO2 reduction coupling. Through critical analysis, we identify fundamental challenges and propose strategic research directions for advancing TiO2-based photocatalytic technology toward practical implementation. This work will provide a comprehensive framework for researchers to explore advanced TiO2-based composite materials to develop efficient and scalable photocatalytic systems for multifunctional simultaneous hydrogen production.
Comparative Evaluation of Shear Bond Strength of Aesthetic Orthodontic Brackets Bonded to Aged Composite Restorative Resin Materials
Authors: Sayed Mohammed E.
Published: February 2025

Background: Patients demand for aesthetic orthodontic brackets (OBs) has increased since orthodontic treatments are of long duration. Clinicians encounter old composite restorations frequently, against which OBs need to be bonded. Aims and objectives: This study aims to determine the shear bond strength (SBS) of two aesthetic OBs (ceramic and resin) against aged composite resins (flowable and packable) after standard surface treatment. Materials and methods: 96 disc-shaped specimens of two aged (A) composite resins [flowable (F) and packable (P)] were divided into 8 groups, using ceramic (C) and plastic (P) brackets, out of which four subgroups served as control [non-aged (N)FC, NPC, NFR, NPR] and four as experimental [AFC, APC, AFR, APR]. Surface treatment included mechanical [air abrasion] and chemical [Assure Plus and Transbond XT]. After 24 h of storage, the specimens were tested for SBS and observed for failure mode using adhesive remnant index (ARI) scores. Mean values of SBS in each subgroup were analysed statistically using a one-way analysis of variance (ANOVA) test and Tukey (HSD) post hoc test. All probability ‘p’ differences were significant at a value of 0.05 and less. Results: All aged composite resin subgroups had decreased bond strength than controls, with all subgroups bonded with plastic brackets having the least bond strengths that were clinically nonacceptable [≤7 to 10 MPa]. Flowable composites when bonded with either ceramic or plastic brackets had higher strength than packable composites. Ceramic brackets had higher SBS than plastic brackets for both flowable and packable composites. Significant differences in bond strength were observed among subgroups of plastic brackets. Ceramic brackets were associated with higher residue of adhesives on the composite surface. Conclusion: Aged composite resins exhibit significantly lower SBS than fresh composites, with ceramic brackets and flowable composites producing better bond strength values than plastic brackets and packable composites.
Effectiveness of Total-Body Screening Examination in Diagnosing Melanoma at Earlier Stages: A Cohort Study
Authors: Caraviello Camila , Nazzaro Gianluca , Alberti-Violetti Silvia , Passoni Emanuela , Benzecry Mancin Valentina , Bortoluzzi Paolo , Murgia Giulia , Marzano Angelo Valerio
Published: February 2025

Background/ Objectives: Melanoma is the most severe form of skin cancer, with incidence increasing worldwide. However, there is still a lack of strong evidence to support melanoma screening, and screening strategies vary among healthcare systems. This study aims to compare the effectiveness of two strategies, total-body screening (TBS) examination and lesion-directed examination (LDE) of a suspicious lesion, in detecting melanoma at earlier stages (thickness<0.8mm). Methods: Data was collected from all patients who came for dermatology visits, whose appointment reason was either a TBS visit or a LDE of a suspicious melanoma lesion. All visits were performed at Ospedale Maggiore Policlinico, Milan, Italy, between October and December 2023. Results: 1116 patients were included in the cohort (866 came for TBS, 250 came for LDE) and 19 melanomas were histologically confirmed (10 in the TBS group, 9 in the LDE group). Positive predictive value was 26.7%. Melanomas were diagnosed more often in male sex (73.7%; p=0.013) and in older patients (mean age 64.5 years old; p=0.016). Patients in the TBS group were younger and more frequently associated with a positive risk factor for melanoma, compared to patients in the LDE group (p<0.001). Even though thicker melanomas (≥0.8mm) were found more often in patients who came for LDE visits, this finding was not confirmed to be statistically significant (p=0.350). TBS visits were, therefore, not associated with the diagnosis of melanoma at earlier stages. Among patients with melanoma diagnosis, no demographic, histologic or clinical characteristics were different between TBS and LDE groups. Conclusions: Lesion-directed examination, when performed by dermatologists, can be an alternative to standard total-body screening visits for the detection of melanoma at earlier stages in the general population.
Mitochondrial-Derived Vesicles Mediate Interorganellar Communication via Selective Cargo Transfer Under Oxidative Stress
Authors: Sharma Ashutosh
Published: February 2025

Mitochondrial-derived vesicles (MDVs) are essential for mitochondrial quality control, yet their cargo specificity and role in interorganellar communication remain poorly characterized. Here, we demonstrate that under oxidative stress, MDVs selectively transport antioxidant enzymes (e.g., peroxiredoxin-3, SOD1) to peroxisomes and lysosomes via Rab32-dependent trafficking. Using super-resolution microscopy and SILAC-based proteomics in HeLa and primary murine fibroblast models, we observed a 3-fold increase in MDV biogenesis post-H2O treatment (p < 0.001), with Rab32 knockout cells exhibiting 50% higher cytosolic mitochondrial DNA (mtDNA) leakage and NLRP3 inflammasome activation. Live-cell imaging confirmed MDV-peroxisome fusion via PEX14 and lysosomal delivery via LAMP1, revealing a redox-sensitive mechanism that prevents oxidative damage. These findings establish MDVs as critical mediators of interorganellar coordination, offering novel therapeutic strategies for diseases linked to mitochondrial dysfunction, such as Parkinson’s disease.
A DNA-Based Plasmonic Nano-Ruler
Authors: Cencini Aura , Bortoluzzi Mary , Rilievo Graziano , Tonolo Federica , Vianello Fabio , Magro Massimiliano , Cecconello Alessandro
Published: February 2025

DNA is an exceptional building block for the fabrication of dynamic supramolecular systems with chemically switchable geometries. Here, a self-assembled, fine-tunable plas-monic-fluorescent ruler was developed. A precise sliding motion mechanism was operated through the strict control of strand displacement reactions, shifting two ssDNA rails over a ssDNA quasi-ring structure. The DNA ruler, reconfigured as a nano-mechanical slider, and gen-erated six discrete configurations, setting specific distances between a tethered gold nanoparticle (AuNPs), and a fluorophore unit (Cy3), placed at two different distinct sites on the rigid nano-structure. In order to optimize the system, the reversible distance-dependent fluorescence quenching or enhancement phenomena were investigated by testing gold nanoparticles with diameters 5, 10 and 15 nm AuNPs. The best performances in terms of Cy3 fluorescence mod-ulation were yielded by 10 nm AuNPs , as experimentally demonstrated by fluorescence emis-sion kinetics during the strand-displacement operated reconfigurations. Furthermore, a geomet-ric model of the system was produced, confirming the observed results. The fluoro-phore-plasmonic surface positioning, conferred by the DNA ruler, led to an overall finite state nano-machine with six alternative signal outputs. This mechanism, working as a fluorescent re-porter, could find application in multiple responsive detection of single-strand nucleic acid, such as virus or miRNA.
Simulation of Combined Aging Effects for Battery Operated Trains: A Benchmark Case Study on the Line Between Reggio Calabria and Catanzaro
Authors: Pugi Luca , Povolato Tommaso Elios , Tiezzi Nico
Published: February 2025

Expected life and reliability of components is a critical aspect for railway applications where the expected life and maintenance intervals of rolling stock are quite demanding issues both in terms of equivalent mileage and duration. For these reasons when mileage of the mission is within 100 kilometers adopted accumulators are based on lithium titanate chemistry which, despite a relatively low density assure a very long operational life both in terms of cycle and time aging. In this work authors introduce a benchmark test case, an Italian line between Reggio Calabria and Catanzaro, in which the required autonomy, more than 170km, involves the usage of high energy batteries such LiNMC or LiFePO4 derived from corresponding automotive applications. In this work authors propose a simulation model based on IEC 62864-1:2016 to investigate how the combined effect of cycle and time aging should influence in different ways the design of the system and how relatively small interventions like the partial electrification of small intermediate section of the line should improve the overall stability and reliability of the performed engineering analysis.
Characterization of the Pozzolanic Potential of Oil Palm Kernel Shell Ash Obtained Through Optimization of Physicochemical Processes
Authors: ORTEGA RAMON TORRES , Luna Velasco Maria , Baldovino Jair de Jesús Arrieta
Published: February 2025

Oil palm kernel shell ash (POFA), a byproduct of the highly cultivated agro-industrial sector in Colombia, has been widely used for its pozzolanic properties, which enhance the mechanical and durability characteristics of concrete. Six POFA samples were analyzed after undergoing drying, cutting, grinding, crushing, and calcination at temperatures ranging from 500°C to 1000°C. SEM-EDS/EDX analysis, X-ray fluorescence (XRF), and Loss on Ignition (LOI) tests were conducted to characterize its pozzolanic potential. The results revealed that the SiO₂ content increased with the calcination temperature, reaching a peak of 76.8% at 1000°C. However, calcination at 600°C was identified as the optimal temperature, as it balances impurity removal without inducing the formation of crystalline silica, which would negatively affect the material's reactivity. Considering the optimal calcination temperature and the high initial LOI values, which exceeded 70% in the first calcination stage, a second calcination was performed on the 500°C sample by increasing the temperature to 600°C. This resulted in an LOI of 3.33%, according to ASTM C311 standards for natural pozzolans used in Portland cement concretes.
Tooth Wear and Salivary Factors: Insights from a Cohort of Dental Students
Authors: Nobre Manuel , Almeida Laura , Magalhães Madalena , Carvalho Rui , Rua João , Proença Luís , Vieira Ana M.
Published: February 2025

Background/Objectives: Tooth wear is a progressive and multifactorial condi-tion influenced by mechanical and chemical factors. Saliva plays a crucial role in mod-ulating erosive wear through its buffering capacity and remineralization potential. This study aimed to assess the prevalence and severity of erosive tooth wear among dental students and explore its correlation with salivary factors such as flow rate and pH. Methods: A cross-sectional study was conducted on 96 individuals from the Egas Moniz School of Health & Science. Erosive wear was evaluated using the Basic Erosive Wear Examination (BEWE) index. Unstimulated and stimulated saliva samples were collected to measure salivary flow rate and pH. Statistical analyses included Spearman’s correlation and multinomial logistic regression. Results: All individuals were classified as no risk (BEWE Score 0 - 2) or low risk (BEWE Score 3 - 8). The most affected teeth were the lower first molars and the 4th and 6th sextants. Salivary analysis showed a mean unstimulated flow rate of 0.5 ml/min and stimulated flow of 1.7 ml/min. A significant negative cor-relation (rho = -0.224, p = 0.029) was found between stimulated salivary pH and BEWE score, indicating higher acidity contributes to greater erosive wear. Conclusions: This study highlights the impact of salivary properties on erosive tooth wear, emphasizing the protective role of higher salivary pH. Regular monitoring of saliva and preventive strategies should be integrated into early diagnosis and management of erosive wear in young adults.
XMU-MP-1, Inhibitor of STE20-like MST1/2 Kinases of the Hippo Signaling Pathway, Induces Hematopoietic Tumor Cells Death by Suppressing the Cell Cycle and Activating Apoptosis, Necroptosis and Autophagy
Authors: Stepchenko Alexander G. , Georgieva Sofia G. , Pankratova Elizaveta V. V.
Published: February 2025

Currently there is little knowledge on the molecular mechanisms of the “non-canonical” Hippo signaling pathway in hematopoietic tumor cells. We have showed that targeting the MST1/2 kinases, the key molecules in the Hippo signaling pathway may prove to be an effective way to treat hematologic tumors. In the present study, we have shown that inhibitor MST1/2 kinases - XMU-MP-1 effectively inhibits the growth of tumor B- and T-cells. XMU-MP-1 blocking the cell cycle and inducing cell death by apoptosis, necroptosis, and autophagy. XMU-MP-1 enhances doxorubicin effects. RNA-Seq analysis has demonstrated that XMU-MP-1 suppresses the expression of the key cell cycle regulators in the Namalwa cells: E2F, cell division cycle genes (CDC6,7; CDC20; CDC25A,В,С, CDC45), cyclins CCNА2, CCNB1,B2; MCM2-7, ORC1, ORC6. At the same time, XMU-MP-1 increases the expression of the apoptosis activator genes APAF1, caspases 6 and 7, FAS; BBC3, BCL2A1, MOAP1; XAF1. Some Namalwa cells may undergo necroptosis: XMU-MP-1 causes an increase in the expression of the necroptosis activator genes RIPK1, TNFSF10, TRADD, PEA15. The expression of the key genes activating autophagy is significantly increased (beclin1; DEPP1; DAP; VPS18; VPS39, autophagy regulator AMBRA1). The use of MST1/2 kinase inhibitors in the treatment of hematologic tumors may be extremely promising.
The Elastic Cosmos: Eliminating Dark Energy Through Planck-Scale Rebound and Holographic Entropy Renewal
Authors: Ladhani Amrit
Published: February 2025

This study presents a cyclic cosmological model where the universe’s accelerated expansion arises from spacetime’s intrinsic rebound mechanics, eliminating the need for dark energy. Central to this framework is a conserved Cosmic Scale (C_s), a finite spatial extent derived from the Planck length (l_p) via a dimensionless constant N≈10^61. The model unifies holographic entropy principles, modified Friedmann dynamics, and Planck-scale quantum gravity to resolve the cosmological constant problem, Hubble tension, and Tolman’s entropy paradox. By postulating spacetime’s elastic response to contraction-phase potential energy, the rebound mechanism triggers expansion without singularities, mimicking dark energy’s effects. Key predictions include suppressed large-scale CMB polarization (l<30), phase shifts in baryon acoustic oscillations (BAO), and gravitational wave signatures detectable by LISA. Observational validation shows H_0=73.2±1.3 "km/s/Mpc" , resolving the Hubble tension between SH0ES and Planck data. The entropy reset at V_"min" ∼l_p^3 avoids infinite entropy growth, addressing Tolman’s paradox. This work bridges quantum geometry and cosmic evolution, offering a falsifiable alternative to ΛCDM cosmology with implications for unifying general relativity and quantum mechanics. Future efforts will focus on quantizing the rebound mechanism and leveraging next-generation telescopes for validation.
Effects of B Vitamins on Homocysteine Lowering and Thrombotic Risk Reduction - A Review of Randomized Controlled Trials in Last 10 Years
Authors: Li Mengyan , Ren Ruodi , Wang Kunkun , Wang Shan , Chow Allison , Yang Andrew K , Lu Yun , Leo Christopher
Published: February 2025

Homocysteine is an amino acid derived from methionine, metabolized via vitamin B6 (pyridoxine)- and vitamin B12 (cobalamin)-dependent pathways. Supplementation of B vitamins has been shown to effectively reduce plasma homocysteine levels. Previous research has also demonstrated an association between lower plasma homocysteine levels and decreased risk of myocardial infarction, stroke and venous thromboembolism. However, it remains inconclusive if supplementation of B vitamins is associated with risk reduction in thromboembolic events and confers clinical benefits. This article aims to review clinical trials in the last ten years to determine the effects of B vitamin supplementation in plasma homocysteine lowering, and evaluate its impact on reducing the risk of arterial and venous thromboembolism.
Quantitative Evaluation of Iron-containing Proteins Bound to Mesoporous Silica Microspheres by Inductively Coupled Plasma Mass Spectrometry and Confocal Laser Raman Microscopy
Authors: Miyashita Shin-ichi , Ogura Toshihiko , Matsuura Shun-ichi , Fukuda Eriko
Published: February 2025

Inductively coupled plasma mass spectrometry (ICP-MS) is important in the biological and biochemical fields as it can quantify trace elements. Confocal laser Raman micros-copy (CLRM), a powerful tool for the compositional analysis of biological samples, or-ganic materials, and inorganic materials, can be used to analyze samples in aqueous solutions. Despite their analytical strength, the quantitative evaluation of proteins bound to mesoporous silica (SiO2) microspheres, which are promising candidates for drug delivery systems and vaccine carriers, has not been sufficiently explored. Therefore, we investigated the applicability of ICP-MS and CLRM to quantify lactoferrin (LF), a widely studied iron-containing protein bound to mesoporous SiO2 microspheres (SBA24). The bound LF amount was measured using ICP-MS, selectively monitoring iron derived from LF as a marker element, and CLRM. The results were compared with those obtained using a conventional bulk analysis technique. The amounts and trends of the signal intensities obtained using ICP-MS and CLRM agreed with each other and with the bulk analysis results. Our findings demonstrate that ICP-MS and CLRM are applicable for the quantitative evaluation of iron-containing proteins bound to SBA24. These methods offer a reliable platform for quantification of biomolecules on micro-particles and provide valuable insights for biomedical research and quality control in related industries.
Making Timber Accessible to Forest Communities: A Study on Locally-Adapted, Motor-Manual Forest Management Schemes in the Eastern Lowlands of Bolivia
Authors: Pokorny Benno , Montero Terrazas Juan Carlos , Johnson James , Mendoza Ortega Karen , Cano Cardona Walter , de Jong Wil
Published: February 2025

Forest communities around the world have great difficulties in utilizing the economic potential of their forests, especially timber, under current technical requirements and legal frameworks. The present study examines the feasibility of motor-manual forest management among indigenous Chiquitano communities in Bolivia's Eastern Lowlands. With a focus on sustainable timber harvesting, it evaluates local practices, tests technical optimization options, and assesses their technical, financial, and environmental impacts. Findings reveal that traditional motor-manual timber production is scarcely profitable, exacerbated by burdensome legal frameworks and limited market access. However, motor-manual forest management remains an essential source of income for communities, and it constitutes an important option for rural development. Field tests demonstrate that with the use of better equipment such as high quality chainsaws, and improved maintenance and workflows, productivity and profitability of local logging can be enhanced. Despite low environmental impact, optimized motor-manual forest management continues to be constrained by governance challenges, logistical limitations, and limitrfd markets for locally produced timber. The study recommends a holistic approach to optimize these aspects, including targeted technical support, market development, simplified legal frameworks, and the setting up of robust local governance structures instead of ineffective centralized command and control approaches. These improvements would enable communities to sustainably manage forests while addressing their socio-economic needs. The findings underscore the potential of logging by local communities as an alternative to large-scale mechanized logging.
Logistic Regression-Based Detection of Parkinson’s Disease
Authors: Verma Vanshika , Sinha Bhawesh
Published: February 2025

Millions of people worldwide suffer with Parkinson's disease (PD), a neurodegenerative condition that impairs cognition and movement. For management and treatment to be effective, early detection is essential. This study uses logistic regression, a popular classification algorithm, to develop a model for Parkinson's disease detection. To differentiate between people with Parkinson's disease and healthy controls, the model uses a dataset that includes a number of speech features, such as fundamental frequency (MDVP: Fo), jitter (MDVP: Jitter, MDVP: RAP), shimmer (MDVP: Shimmer, Shimmer: DDA), noise-to-harmonics ratio (NHR), and several other acoustic features. It also uses additional dynamic parameters, such as RPDE, DFA, and D2. Using criteria for accuracy, precision, recall, and F1-score, the logistic regression model's performance is assessed, indicating its potential for PD early detection. The findings imply that logistic regression is a useful method for PD identification, providing medical practitioners in clinical settings with an easy-to-use and useful option.
Mapping Socio-Economic Vulnerability to Natural Hazard in Urban Areas Using Machine Learning and Indicator-Based Approaches
Authors: Dufitimana Esaie , Gahungu Paterne , Uwayezu Ernest , Mugisha Emmy , Bizimana Jean Pierre
Published: February 2025

Urbanization and climate change are increasing the risks of natural hazards, particularly in cities with significant socio-economic disparities. Existing hazard risk assessment frameworks often neglect socio-economic dimensions, limiting their utility in addressing community-level vulnerabilities. This study proposes an integrated machine learning and indicator-based framework for assessing flood susceptibility and socio-economic vulnerability, with a focus on data-scarce settings, using a case study of the City of Kigali. Socio-economic vulnerability was quantified through a composite index incorporating sensitivity and adaptive capacity. Multisource data were integrated and modeled using machine learning models, which included Multilayer Perceptron, Random Forest, Support Vector Machine, and XGBoost. In terms of model performance, the MLP has achieved high performance with an AUC score of 0.902 and F1-Score of 0.86. The results indicate intensified vulnerability in central and southern Kigali, with noticeable socio-economic disadvantages and high flood susceptibility. The resulting maps were validated using historical flood data, other socio-economic studies in the area, and local knowledge. The scalability of the framework was evaluated in Kampala, Uganda, and Dar es Salaam, Tanzania, demonstrating scalability with context-specific adaptations. This approach offers a robust methodology for integrating flood susceptibility and socio-economic vulnerability, enabling data-driven prioritization of interventions. The findings contribute to advancing urban resilience strategies, particularly in regions constrained by limited data availability.
A Micro Resonating Motor Based on Neuron Action Potential
Authors: Carcaterra Antonio , Roveri Nicola , Milana Silvia , Pepe Gianluca
Published: February 2025

This paper introduces a novel bioelectromechanical device converting the electrochemical potential energy of excitable cells into mechanical work by coupling the Hodgkin–Huxley (HH) neuronal model response to a mechanical resonator. Addressing key challenges in bioelectromechanical systems, including biocompatibility, miniaturization, and efficient energy conversion, the device leverages the membrane potentials of biological cells to drive mechanical oscillations within microelectromechanical systems (MEMS). Through a combination of numerical simulations and theoretical analyses, it is demonstrated that the coupled HH–resonator system achieves stable limit cycles and significant mechanical displacements via parametric amplification. This amplification arises from the nonlinear capacitive coupling, which leads to Mathieu-like equations governing the system’s dynamics, thereby enabling large oscillations from relatively small voltage inputs. Such parametric resonance is critical for the device's ability to sustain oscillatory motion, making it highly suitable for integration into compact and implantable MEMS applications. Potential applications include implantable sensors and actuators for real-time physiological monitoring, and advanced micro-scale systems that benefit from biologically sourced energy. The findings underscore the promise of bioelectromechanical systems in advancing biomedical and microengineering technologies, paving the way for innovative solutions in personalized medicine, bio-robotics, and beyond.