bluuebunny/crossref_metadata_2025 huggingface dataset:
RNN-Based Models for Predicting Seizure Onset in Epileptic Patients
Authors: Mounagurusamy Mathan Kumar , V S Thiyagarajan , Rahman Abdur , Chandak Shravan , Balaji D , Jallepalli Venkateswara Rao
Published: January 2025

Early management and better clinical outcomes for epileptic patients depend on seizure prediction. The accuracy and false alarm rates of existing systems are often compromised by their dependence on static thresholds and basic Electroencephalogram (EEG) properties. A novel Recurrent Neural Network (RNN)-based method for seizure start prediction is proposed in the article to overcome these limitations. As opposed to conventional techniques, the proposed system makes use of Long Short-Term Memory (LSTM) networks to extract temporal correlations from unprocessed EEG data. It enables the system to adapt dynamically to the unique EEG patterns of each patient, improving prediction accuracy. The methodology of the system comprises thorough data collecting, preprocessing, and LSTM-based feature extraction. Annotated EEG datasets are then used for model training and validation. Results show a considerable reduction in false alarm rates (average of 6.8%) and an improvement in prediction accuracy (90.2% sensitivity, 88.9% specificity, and AUC-ROC of 93). Additionally, computational efficiency is significantly higher than that of existing systems (12 ms processing time, 45 MB memory consumption). About improving seizure prediction reliability, these results demonstrate the effectiveness of the proposed RNN-based strategy, opening up possibilities for its practical application to improve epilepsy treatment.
Shifting Herbal Knowledge: The Ecology and Culture Behind Wild Plant Use in the Southern Occitan Alps
Authors: Alrhmoun Mousaab , Sulaiman Naji , Pieroni Andrea
Published: January 2025

This study explores the evolving plant knowledge in the Alpine Southern Occitan area, an ecologically rich and culturally resilient region, by analyzing temporal and cultural shifts in botanical use across multiple decades. Drawing on ethnobotanical data from the Maira Valley (1970, 2022), Stura Valley (2004), and Grana Valley (2011), this research examines changes in the identification and utilization of plant taxa, reflecting the region's shifting ecological, socio-economic, and cultural landscapes. A total of 308 botanical taxa were recorded, with significant variation in plant families across the studies. The most prominent families, such as Asteraceae and Lamiaceae, remarkably declined in later collected data (2022), reflecting the erosion of traditional ecological knowledge (TEK), while other families, like Brassicaceae and Amaranthaceae, emerged more frequently, possibly due to changing cultural or economic factors. A notable shift in plant part utilization was also observed, with medicinal uses predominating in earlier studies, and a gradual shift toward the use of fruits, fodder, and food plants in more recent years. Logistic regression models identified altitude as a key determinant of plant diversity, with higher altitudes (600-1,600 masl) supporting greater botanical variety. Additionally, participant age was positively correlated with the richness of plant knowledge, suggesting that older generations preserve more diverse ethnobotanical knowledge. This study highlights the dynamic relationship between local ecological systems and cultural practices, illustrating the resilience and transformation of plant knowledge in response to socio-economic pressures and environmental changes in the Alpine Southern Occitan region.
Stress, Anxiety, Depression, Burnout and Insomnia Among Greek Nurses One Year After the End of the Pandemic: A Moderated Chain Mediation Model
Authors: Pachi Argyro , Sikaras Christos , Melas Dimitrios , Alikanioti Sofia , Soultanis Nikolaos , Ivanidou Maria , Ilias Ioannis , Tselebis Athanasios
Published: January 2025

Background: Several studies have reported alarming rates of mental health issues and sleep problems among nurses even in the post-pandemic era. Objectives: To investigate the prevalence of stress, anxiety, depression, burnout and insomnia among nurses in Greece one year after the end of the pandemic and to construct a mediation model evaluating the impact of stress on insomnia, the chain mediating roles of depression and burnout, as well as the moderating role of anxiety in the model. Methods: This cross-sectional study was conducted online in July 2024 and included 380 hospital nurses who completed the Depression Anxiety Stress Scale (DASS-21), the Copenhagen Burnout Inventory (CBI) and the Athens Insomnia Scale (AIS). Results: The prevalence rates of stress, anxiety, depression, burnout and insomnia were 33.9%, 33.3%, 35%, 46.8% and 56.1%, respectively. Multiple regression analysis indicated that the Depression subscale of the DASS-21 explained 40.6% of the variance in AIS, while an additional 7.6% was explained by CBI and another 1.3% rate by the Stress subscale of the DASS-21. Mediation analysis revealed that stress affected insomnia both directly and indirectly through the chain mediating roles of depression and burnout. Anxiety moderated the chain mediation path by enhancing the negative impact of stress on depression. Conclusions: The proposed moderated chain mediation model introduces certain factors influencing insomnia and explains how changes in any one of these factors effectuate changes in the other factors, offering insights for individualized interventions.
Numerical Analysis of Gas Flow Distribution Characteristics in a 5 kW Molten Carbonate Fuel Cell Stack
Authors: Szczesniak Arkadiusz , Martsinchyk Aliaksandr , Milewski Jarosław , Shuhayeu Pavel , Dybiński Olaf , Sienko Arkadiusz , Xing Wen
Published: January 2025

This work presents an advanced CFD model of a 5kW Molten Carbonate Fuel Cell stack intended to provide a broad analysis and deliver improved design through optimizing flow distribution. The goal is to provide variant analysis of flow distribution in the internal channels through the CFD model. SolidWorks was used to design the MCFC stack, and SOLIDWORKS® Flow Simulation was utilized to model the flow distribution inside the stack. The simulated stack was validated through an experimental investigation of a 5kW MCFC stack, empirically measuring pressure and flow distribution in an experimental laboratory station optimized for multi-scale fuel cell stack testing. The test was designed to examine a variety of internal flow distribution factors. The verified CFD model was employed for sensitivity analysis on various scales. To enhance the design, the influence of stack and single-cell constructional characteristics on the 5 kW MCFC was investigated.
Impact of the COVID-19 Pandemic on Life Expectancy in Korea, 2019–2022
Authors: Song Soo Jin , Lim Dar Oh
Published: January 2025

This study investigated changes in life expectancy due to the COVID-19 pandemic by analyzing the contributions of age, gender, and cause of death in 2019 and 2022. Korea’s simplified life table and cause-of-death statistics from 2019 to 2022 were used to assess mortality changes by age, gender, and cause of death during the pandemic. Joinpoint regression analysis was applied to detect trends, and the Arriaga decomposition method was used to quantify the contributions of age, gender, and cause of death to life expectancy changes. Joinpoint regression identified a slow increase in life expectancy in 2007 and a decline in 2020, coinciding with the COVID-19 pandemic. Life expectancy decreased markedly for men (-0.36 years per year, 95%CI: -0.68 to -0.03) and women (-0.45 years per year, 95%CI: -0.71 to -0.18). Age-specific contributions revealed declines across age groups, with the steepest reductions in the older population (80 years or older: -0.35 years for men; -0.52 years for women). Women (-0.68 years) contributed more to the decline in life expectancy than men (-0.41 years). COVID-19 ranked as the third leading cause of death in 2022, significantly contributing to the decline in life expectancy among the older population (aged 80 years or older: -0.306 years for men, -0.408 years for women). Women in Korea were more affected than men, reducing the gender gap in life expectancy by 0.3 years. Before the pandemic, non-communicable diseases such as malignant neoplasms, heart disease, and cerebrovascular disease dominated Korea’s top 10 causes of death. During the pandemic, however, COVID-19 rose to third place by 2022. Notably, intentional self-harm (suicide) contributed to an increase in life expectancy, suggesting shifts in the relative impact of various causes of death.
Further Development of SAMPDI-3D: Machine Learning Method for Predicting Binding Free Energy Changes Caused by Mutations in Either Protein or DNA
Authors: Rimal Prawin , Paul Shamrat Kumar , Panday Shailesh Kumar , Alexov Emil
Published: January 2025

Background/Objectives: Predicting the effects of mutations in proteins and DNA on the binding free energy of protein-DNA complexes is crucial for understanding how DNA variants impact wild-type cellular function. As many cellular interactions involve protein-DNA binding, accurately predicting changes in binding free energy (ΔΔG) is valuable for distinguishing pathogenic mutations from benign ones. Methods: The study describes the further development of the SAMPDI-3D machine learning method, which is trained on an expanded database of experimentally measured ΔΔGs. This enhanced model incorporates new features, including the 3D structure of the mutant protein, structural features of the mutant structure, and a position-specific scoring matrix (PSSM). Benchmarking was conducted using 5-fold cross-validation. Results: The updated SAMPDI-3D model achieves a Pearson Correlation Coefficient (PCC) of 0.68 for mutations in proteins and a PCC of 0.80 for mutations in DNA. These results represent significant improvements over existing tools. Additionally, the method’s rapid execution time enables genome-scale predictions. Conclusions: The advancements in SAMPDI-3D enhance its predictive performance and utility for analyzing mutations in protein-DNA complexes. By leveraging structural information and an expanded training dataset, SAMPDI-3D provides researchers with a more accurate and efficient tool for mutation analysis, contributing to the identification of pathogenic variants and improving our understanding of cellular function.
Physicochemical Characterization of a Nano-Hydroxyapatite/β-Tricalcium Phosphate (n-HA/β-TCP) and Type 1 Collagen Composite: An In Vitro Study
Authors: Brum Igor da silva , Elias Carlos Nelson , Ciambarella Bianca Torres , Fonseca Guilherme Aparecido Monteiro Duque da , Frigo Lucio , Carvalho Marco Antonio , de Carvalho Jorge José
Published: January 2025

Materials science has contributed to developing new nano-biomaterials for specific dentistry applications. The present work aims to characterize the physicochemical properties of a composite nanomaterial scaffold in the form of blocks for maxillofacial bone regeneration application. The scaffold had block shapes and was a mixture of nano-hydroxyapatite, β-Tricalcium phosphate, and type I collagen of bovine origin. The biomaterial was characterized by scanning electron microscopy (SEM), transmission electron mcroscopy (TEM), chemical composition microanalysis, and X-ray diffractometry (XRD). In the SEM and TEM analyses, it was possible to identify the layers of the materials and, with microanalysis, quantify the chemical composition. The XRD spectra showed the presence of nano-hydroxyapatite and nano-ß-TCP. The results showed that the composite does not contain contamination from manufacturing procedures. It can be concluded that the n-HA/β-TCP and type 1 collagen composite is free of manufacturing contaminants and can be suited for clinical application.
PRISMA-7 as a Frailty Screening Tool in Primary Care: Evidence from Community-Dwelling Older Adults in South Tyrol with a Focus on Gender Bias
Authors: Ausserhofer Dietmar , Mahlknecht Angelika , Barbieri Verena , Engl Adolf , Piccoliori Giuliano , Wiedermann Christian Josef
Published: January 2025

Background/Objectives: Frailty screening is essential for identifying older adults at risk for adverse health outcomes. The Program of Research to Integrate Services for the Maintenance of Autonomy 7 (PRISMA-7) is a widely utilised self-reported frailty tool; however, concerns persist regarding its potential gender bias due to item 2, which assigns a frailty point for the male sex. This study aimed to assess the suitability of PRISMA-7 for population-level frailty screening in South Tyrol, Italy, evaluate the impact of item 2 on frailty classification, and investigate the feasibility of PRISMA-6 (excluding item 2) as an alternative tool. Methods: A cross-sectional survey was conducted among 1,695 community-dwelling older adults aged ≥ 75 years in South Tyrol. Frailty was assessed using the PRISMA-7 and PRISMA-6. Sociodemographic, health, and lifestyle data were collected to explore associations with frailty classifications. Logistic regression models were used to identify the frailty predictors for each scoring system. The agreement between the PRISMA-7 and PRISMA-6 was analysed, and internal consistency was evaluated. Results: The prevalence of frailty was 33.9% using PRISMA-7 and 27.0% using PRISMA-6. Under PRISMA-7, men had a higher prevalence of frailty (34.7%) than women (33.0%), whereas PRISMA-6 reversed this pattern (men, 21.4%; women, 33.0%). Removing item 2 improved internal consistency (Cronbach’s alpha for PRISMA-7 = 0.64 vs. PRISMA-6 = 0.75) and aligned frailty classifications with known predictors including age, health status, and physical activity. Logistic regression models highlighted significant sex differences under PRISMA-7 but not under PRISMA-6. Conclusions: PRISMA-7 introduces a gender bias by overestimating frailty in men, whereas PRISMA-6 offers a more equitable alternative. Validation of the PRISMA-6 against established frailty tools is recommended to ensure robust and unbiased frailty screening for primary care integration in South Tyrol and beyond.
Genotypic Characterization of Human Parvovirus B19 Circulating in the 2024 Outbreak in Tuscany, Italy
Authors: Beligni Giada , Cusi Maria Grazia
Published: January 2025

Human Parvovirus B19 (B19V) is a widespread virus, causing erythema infectiosum in children and several clinical manifestations from acute to persistent infections in adults. In early 2024, ECDC reported an increased human parvovirus B19 circulation in 14 European countries. A Parvovirus B19 outbreak was also reported in Tuscany, Italy, prompting a detailed investigation of its genetic characteristics. This study is the first Italian report on this outbreak, which carries out a phylogenetic analysis based on the complete coding B19V genomes of 23 positive samples. Phylogenetic clustering assigned all isolates to the G1a genotype, although with some mutations in NS1, VP1 and VP2, compared to the Reference strains.
Advancing Cell Immunotherapy for Autoimmune Diseases: CAR-T and CAR-Treg Therapies
Authors: Chasov Vitaly
Published: January 2025

Autoimmune diseases, characterized by chronic immune-mediated tissue damage, pose significant therapeutic challenges due to their complexity and limited long-term solutions. Recent advancements in cell immunotherapy, particularly CAR-T cells and CAR-Treg therapies, present groundbreaking avenues to directly modulate immune dysfunction. This review examines the mechanisms, therapeutic applications, and ongoing developments in these innovative strategies, detailing how CAR-T cells target autoreactive immune components and CAR-Tregs reestablish immune homeostasis. By addressing critical challenges such as safety, scalability, and clinical integration, this work highlights the potential of these therapies to redefine the landscape of autoimmune disease management.
Head Tumor Segmentation and Detection Based on Resunet
Authors: YuChuan Deng , Cui Wenwei , Liu XueYing
Published: January 2025

Deep learning algorithms have demonstrated remarkable efficacy in the medical imaging field, particularly when it comes to segmentation and classification of brain tumors. This algorithm is being trained and tested using the MRI brain tumor segmentation dataset provided by Kaggle. ResNet50 is used for tumor classification tasks due to its powerful feature extraction capability. Through its deep residual structure, ResNet50 can effectively extract different lesion features and improve classification accuracy. At the same time, ResUNet combines the feature extraction capabilities of ResNet with the segmentation advantages of U-Net, accurately capturing tumor boundaries and achieving high-quality tumor segmentation. For the MRI dataset, the accurate segmentation rate of the model is 91.68%, which provides a certain reference for the medical field. In summary, this study validates the integration of ResUNet50 and ResNet for precis brain tumor detection, contributing to advancements in automated medical image classification analysis. In the field of medical image analysis, accurate brain tumor segmentation and classification are crucial for clinical diagnosis and treatment planning, and provide new ideas and methods for future medical image analysis and clinical applications.
Optimizing Mandibular Reconstruction Through Surgeon-Bioengineer Collaboration: Proposed Protocol for Virtual Surgical Planning
Authors: Shin Dong-Ho , Kim Hyo-Joon , Oh Ji-Su , Moon Seong-Yong
Published: January 2025

Background/Objectives: Computer-assisted mandibular reconstruction requires sophisticated technical expertise alongside surgical knowledge. This study aims to establish and validate an efficient collaborative protocol between oral and maxillofacial surgeons and bioengineers for virtual surgical planning in mandibular reconstruction. Methods: We developed a structured protocol with four sequential phases: (1) generation of 3D models from CT data, (2) virtual resection planning, (3) reconstruction design, and (4) surgical guide fabrication. Protocol efficiency was assessed through seven simulation trials measuring planning duration and required revisions. Clinical validation was performed in four mandibular reconstruction cases. Accuracy was evaluated by comparing virtual surgical plans to postoperative outcomes using 3-matic software analysis. Results: Protocol implementation showed consistent efficiency across simulations with mean planning duration of 2.86 working days (SD = 1.35). Only two of seven simulations required design revisions. Clinical application in four cases (three ameloblastomas, one odontogenic myxoma) demonstrated high precision with mean virtual-to-actual discrepancy of 0.90 mm (SD = 0.34). Successful reconstructions were achieved across varying defect spans (29-53 mm) using both bicortical DCIA flaps and monocortical iliac block bone grafts. The collaborative workflow resulted in optimized surgical guide design, reduced planning iterations, and improved surgical precision. Conclusions: The established surgeon-bioengineer collaborative protocol enhances the efficiency and accuracy of computer-assisted mandibular reconstruction while making advanced surgical planning techniques more accessible. While initial results are promising, future studies with larger patient cohorts and extended follow-up periods are needed to fully validate the protocol's long-term benefits and broader applicability.
Counterfactual Imaginative Culture as Evidence Hallucination in Support of Entropy Reduction
Authors: Carney James Patrick
Published: January 2025

Why do human beings invest work in creating representations of objects and situations that do not exist, cannot be proven to exist, or exist by cultural convention? This study explains this phenomenon by identifying counterfactual cultural production as a form of evidence hallucination, where anxiety-reducing cultural and cognitive models are made to be `true’ by flooding the perceptual environment with fabricated evidence of their truth. The theoretical framework builds on concepts from information theory, thermodynamics, and active-inference approaches to agent-environment interactions; it is validated against two cultural phenomena—religious evangelism as articulated in the four Gospels of the King James Version (KJV) Bible and symbols of collective identity in the form of national flags. The first study encodes English words into 64 categories using their sensorimotor associations, and predicts that the KJV should address existential anxiety by over-sampling positively valenced words with large semantic size from each sensory category—and in doing so, generate an implicit world-model that is lower in unpredictability than that of background English. The second study predicts that the visual entropy of national flags will positively scale with endogenous anxiety (collective worry about internal conflict) and that internal contrast will negatively scale with exogenous anxiety (collective worry about external threats)—with contrast anchoring entropy in the low contrast position. These studies show that it is, in principle, possible to predict detailed features of high-level cultural activity from affective dispositions using a straightforward formalism and without a ‘thick’ model of human cognition.
Obesity and Discrimination in the Workplace: A Narrative Review and New Perspectives for Breaking Out of the Negative Spiral
Authors: Kokubun Keisuke
Published: January 2025

It is known that obesity is not only easily linked to various diseases, but can also reduce the performance of workers. However, poor performance due to obesity leads to worsening working conditions, which further reduces their performance. This vicious cycle is difficult to escape once people fall into it, as it is reinforced by stigma and there is a certain rationality in employment discrimination against risky individuals at the organizational level. However, it may be possible to save these people by creating a consensus for social acceptance of obese people under the initiative of local governments and the country. In this review paper, we review previous research on obesity and discrimination in the workplace and provide a perspective that supports the rationality of supporting obese people to escape the vicious cycle, not only for obese individuals but also for society.
Orbiting Obstacles: Navigating Space Debris with Advanced Surveillance and Tracking Solutions
Authors: Wani Irfan Nazir , Kumar Manoj , Kumar Shukla Pushpendra , Nayak Ramesh Kumar
Published: January 2025

Space Debris or orbital debris, also called Space waste or junk present in Earth's orbit, offers a substantial challenge to space exploration. Satellite operations and other space-based activities. This research paper delves into the causes and effects of space debris accumulation, explores current mitigation techniques, and presents a hopeful outlook on the potential for future sustainable space activities. The paper emphasizes the necessity of addressing planetary fragments to ensure durable sustainability in universe exploration and utilization. It examines various strategies for mitigating space debris, including debris removal technologies, spacecraft design improvements, and international collaboration efforts. Additionally, the paper highlights the importance of space debris monitoring and tracking systems in preventing collisions and minimizing the growth of orbital debris. By comprehending the complexities of space debris and implementing effective mitigation measures, the space industry can work towards a future where sustainable space activities are achievable.
The Effect of Cardiometabolic Drugs on Non-Alcoholic Fatty Liver Disease (NAFLD), Metabolic Dysfunction-Associated Fatty Liver Disease (MAFLD), and Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD)
Authors: Zisis Marios , Chondrogianni Maria Eleni , Androutsakos Theodoros , Rantos Ilias , Oikonomou Evangelos , Chatzigeorgiou Antonios , Kassi Eva
Published: January 2025

The link between cardiovascular disease (CVD) and non-alcoholic fatty liver disease (NAFLD)/metabolic dysfunction-associated fatty liver disease (MAFLD)/metabolic dys-function-associated steatotic liver disease (MASLD) is well-established at both epidemi-ological and pathophysiological level.
Among the common pathophysiological mechanisms involved in the development and progression of both diseases, oxidative stress and inflammation, insulin resistance, lipid metabolism deterioration, gut dysbiosis along with genetic factors have been rec-ognized to play a pivotal role. Pharmacologic interventions with drugs targeting common modifiable cardiometabolic risk factors, such as T2DM, dyslipidemia, and hypertension is a reasonable strategy to prevent CVD development and progression of MASLD. Recently, a novel drug for MASH, resmetirom, has shown positive effects regarding CVD risk, opening new opportunities for the therapeutic approach of NAFLD/MAFLD/MASLD and CVD.
This review provides current knowledge on the epidemiologic association of NAFLD/MAFLD/MASLD to CVD morbidity and mortality and enlightens the possible underlying pathophysiologic mechanisms linking NAFLD/MAFLD/MASLD with CVD. It also highlights potential common therapeutic interventions with cardiometabolic drugs such as anti-hypertensive drugs, hypolipidemic agents, glucose-lowering medications, salicylic acid and the thyroid hormone receptor-beta agonist that may improve outcomes of NAFLD/MAFLD/MASLD.
Supra-Normal Ejection Fraction at Hospital Admission Stratifies Mortality Risk in HFpEF Patients Aged ≥70 Years
Authors: Sonaglioni Andrea , Lonati Chiara , Scime’ Valentina , Nicolosi Gian Luigi , Bruno Antonino , Lombardo Michele , Harari Sergio
Published: January 2025

Background: During the last few years, significant pathophysiological differences between heart failure (HF) patients with “normal” ejection fraction (EF) (50% to 64%) and those with supra-normal EF (≥65%) have been highlighted. However, these distinct EF phenotypes have been poorly investigated in elderly patients aged ≥70 yrs. Methods: All patients aged ≥70 yrs discharged from our Institution with a first diagnosis of HF with preserved EF (HFpEF) be-tween January 2020 and March 2021 entered the study. All patients underwent clinical evalua-tion, blood tests and transthoracic echocardiography. The primary endpoint was “all-cause mortality”, while the secondary one was the composite of “all-cause mortality or rehospitali-zation for all causes” over a mid-term follow-up. Results: A total of 200 HFpEF patients (86.4±6.6 yrs, 70% females) were retrospectively evaluated. The “normal” EF group (n=99) and the “supra-normal” EF one (n=101) were separately analyzed. Compared to patients with “normal” EF, those with “supra-normal” EF were older, with greater comorbidity burden and moderate-to-severe frailty status. During a mean follow-up of 3.6±0.3 yrs, 79 patients died and 73 were re-hospitalized. On multivariate Cox regression analysis, age (HR 1.09, 95% CI 1.03-1.16, p = 0.002), EF (HR 1.08, 95% CI 1.03-1.14, p = 0.004), tricuspid annular plane systolic excursion (TAPSE)/systolic pulmonary artery pressure (sPAP) ratio (HR 0.14, 95% CI 0.03-0.61, p = 0.009) and infectious disease (HR 7.23, 95% CI 2.41-21.6, p < 0.001) were independently as-sociated with all-cause mortality in the whole study population. EF (HR 1.04, 95% CI 1.01-1.07, p = 0.02) also predicted the secondary endpoint. EF ≥65% was the best cut-off to predict both endpoints. Conclusions: “Supra-normal” EF (≥65%) at hospital admission is independently associated with all-cause mortality and rehospitalization for all causes in elderly HFpEF pa-tients over a mid-term follow-up.
Long-Term Outcomes and Toxicity of Salvage Radiation Therapy Using TomoTherapy with Image-Guided Radiation Therapy for Postoperative Prostate Cancer Patients
Authors: Mukai Yuki , Omura Motoko , Minagawa Yumiko , Mase Misato , Nishikawa Yuta , Miura Ichiro , Hata Masaharu
Published: January 2025

Background: We aimed to evaluate the long-term outcomes, treatment-related toxicity, and factors affecting postoperative prostate cancer patients treated with intensi-ty-modulated radiation therapy and image-guided radiation therapy (IMRT-IGRT) using TomoTherapy as salvage radiotherapy (SRT). Methods: We included 71 consecutive patients who underwent SRT after radical prostatectomy between 2011 and 2023. Treatment outcomes, including the progression-free rate (PFR) and overall survival, were calculated using Kaplan–Meier curves. Associations between treatment outcomes and factors were analyzed using the Cox proportional hazards regression analysis. Results: The median follow-up time after SRT was 60 (range, 1–148) months. The 5-year and 10-year PFR were 69.05% and 54.73%, respectively. In multivariate analysis, PSA maximum after surgery (mas PSA) >0.7 ng/mL was significantly associated with worse PFR (p 0.7 ng/mL, providing critical insights into prognostication. SRT for prostate cancer with IMRT and IGRT using TomoTherapy showed similar treatment outcomes and low toxicity rates compared with those of previous studies.
Abalone Age Prediction and Analysis of Influencing Factors: Combining Machine Learning, Shap and Correlation Coefficient Methods
Authors: Cui Yukun , Xiao Zeqiu
Published: January 2025

In biology and fishery research, accurate prediction of the age of abalone helps to deeply understand the life characteristics of abalone and provides a basis for scientific abalone culture. The traditional method of abalone age prediction is to infer the age by observing the number of annual rings on the shell of abalone, which is widely used but has great limitations in accuracy and operability due to the influence of individual differences in abalone and environmental factors. This study aims to provide a more accurate and efficient method for abalone age prediction using machine learning techniques combined with Shapley's additive explanatory model (SHAP), and to analyze the key factors affecting the prediction results. By comparing six machine learning models using evaluation metrics such as MAE, RMSE and MAPE, the experimental results showed that the XGBoost model outperformed the other models in terms of prediction performance, with its MAE value reduced by 28.5% compared to other methods. In addition, the SHAP model was used to further reveal the main features affecting abalone age prediction, such as abalone shell morphology and environmental factors, which provided a more interpretable analytical framework for abalone age prediction.
Injectable Hydrogels for Minimally Invasive Joint Repair and Regeneration
Authors: Gutierrez Reyes Yvvonna
Published: January 2025

Injectable hydrogels have been utilized in therapies related to joints. Using biocompatible, tunable hydrogel systems, they may be applied without surgery to repair or regenerate a joint. They can incorporate therapeutic agents to deliver them immediately or locally into the affected tissues. Natural and synthetic polymers can be used to create these hydrogel systems that will imitate the extracellular matrix (ECM) in cartilage and allow controlled release of bioactive additives such as growth factors and even stem cells. Other innovative examples include the advent of an "intelligent" thermos-responsive and pH-responsive hydrogel, which dynamically changes in response to its environment to provide a targeted treatment. Preclinical trials have proven that hydrogels indeed facilitate cartilage repair under inflammatory conditions and will eventually be developed into clinical trials. Such advances, however, can be seen only at the very beginning of the road given existing roadblocks such as mechanical strength, biocompatibility, and scale-up. Future directions include bringing more multi-functionality into hydrogels, personalized therapies, and solid clinical validation to bridge the parlance gap between laboratory innovation and real-world application. This review offers deeper insights into the properties, applications, challenges, and future directions of these injectable hydrogels concerning joint repair and the transformative potential they possess in regenerative medicine.
Topic Modeling the Academic Discourse on Critical Incident Stress Debriefing and Management (CISD/CISM) for First Responders
Authors: Lundblad Robert , Jaeger Saul , Moreno Jennifer , Silber Charles , Rensi Matthew , Dykeman Cass
Published: January 2025

Background/Objectives: This study examines the academic discourse surrounding Critical Incident Stress Debriefing (CISD) and Critical Incident Stress Management (CISM) for first responders using Latent Dirichlet Allocation (LDA) topic modeling. Its aim is to uncover latent topical structures within the literature and critically evaluate underlying assumptions to identify gaps and limitations. Method: A corpus of 214 research article abstracts related to CISD/M was gathered from the Web of Science Core Collection. After preprocessing, we used Orange Data Mining software’s LDA tool to analyze the corpus. Models ranging from 2 to 10 topics were tested for log perplexity and topic coherence, with LDAvis visualizations guiding interpretation and labeling. A four-topic model offered the best balance of detail and interpretability. Results: Four topics emerged: (1) Critical Incident Stress Management in medical and emergency settings, (2) Psychological and group-based interventions for PTSD and trauma, (3) Peer support and experiences of emergency and military personnel, and (4) Mental health interventions for first responders. Key gaps included limited focus on cumulative trauma, insufficient longitudinal research, and variability in procedural adherence affecting outcomes. Conclusions: The findings highlight the need for CISD/M protocols to move beyond event-specific interventions and address cumulative stressors. Recommendations include incorporating holistic, proactive mental health strategies and conducting longitudinal studies to evaluate long-term effectiveness. These insights can help refine CISD/M approaches and enhance their impact on first responders working in high-stress environments.
Advancing Cyber Incident Timeline Analysis Through Retrieval-Augmented Generation and Large Language Models
Authors: Loumachi Fatma Yasmine , Ghanem Mohamed Chahine , Ferrag Mohamed Amine
Published: January 2025

Cyber timeline analysis or Forensic timeline analysis is critical in Digital Forensics and Incident Response (DFIR) investigations. It involves examining artefacts and events—particularly their timestamps and associated metadata—to detect anomalies, establish correlations, and reconstruct a detailed sequence of the incident. Traditional approaches rely on processing structured artefacts, such as logs and filesystem metadata, using multiple specialised tools for evidence identification, feature extraction, and timeline reconstruction. This paper introduces an innovative framework, GenDFIR, a context-specific approach powered by large language models (LLMs) capabilities. Specifically, it proposes the use of Llama 3.1 8B in zero-shot, selected for its ability to understand cyber threat nuances, integrated with a Retrieval-Augmented Generation (RAG) agent. Our approach comprises two main stages: (1) Data Preprocessing and Structuring: Incident events, represented as textual data, are transformed into a well-structured document, forming a comprehensive knowledge base of the incident. (2) Context Retrieval and Semantic Enrichment: A RAG agent retrieves relevant incident events from the knowledge base based on user prompts. The LLM processes the pertinent retrieved-context, enabling detailed interpretation and semantic enhancement. The proposed framework was tested on synthetic cyber incident events in a controlled environment, with results assessed using DFIR-tailored, context-specific metrics designed to evaluate the framework’s performance, reliability, and robustness, supported by human evaluation to validate the accuracy and reliability of the outcomes. Our findings demonstrate the potential of LLMs in DFIR and the automation of the timeline analysis process. This approach highlights the power of Generative AI, particularly LLMs, and opens new possibilities for advanced threat detection and incident reconstruction.
Tetraploidization Altered Phenotypic Traits and Metabolite Profile of Java Ginseng (Talinum paniculatum (Jacq.) Gaertn.)
Authors: Liu Ying-ying , Huang Xiao , Gao Xin-sheng , Zhang Xiao-fei , Huang Hua-sun , Li Wei-guo , Zhang Yuan-yuan
Published: January 2025

Polyploidization is a beneficial technique to enhance the biomass and secondary metabolites concentrations in plants. Java ginseng (Talinum paniculatum (Jacq.) Gaertn.) can be used as an alternative source of nutrition and has both ornamental and medicinal value. To improve the biomass and content of medicinal ingredients, this study established a speedy propagation system to induce polyploid of java ginseng, and tetraploids were successfully produced by exposing axillary buds to colchicine. The most favorable medium for inducing polyploidy was Murashige and Skoog medium devoid of hormonal substances, while immersing stem segments in a solution of 1-3mg/ml colchicine with 48 hours can achieve high rate of tetraploid induction with the maximum rate of 18.03%. Tetraploids were identified from diploids by flow cytometry, and the tetraploids exhibiting darker and thicker leaves, bigger fruit and pollen, larger stomata but less stomatal density, while the aboveground biomass yield reduced significantly, compared with diploids. Tetraploidization also altered the metabolite profile, with 22 metabolites concentrations significantly increased (P<0.05) and 74 metabolites concentrations significantly decreased (P<0.05) in the leaves of tetraploids. Autotetraploid produced in this study could provide novel insights for artificial polyploid breeding and can be utilized as a new germplasm to generate new polyploids.
Supply Chain Management to Improve the Operational Efficiency of the Logistics Area of a Municipality in Cajamarca
Authors: Strap Cesar Ronaldo Flores , Valle María de los Ángeles Guzmán
Published: January 2025

The present research aimed to propose Supply Chain Management for improving the operational efficiency of the logistics area of a municipality of Cajamarca, to achieve the above, an applied type study was carried out, in addition to a quantitative approach, as well as a non-experimental design. The sample was made up of critical operations in the logistics area. The results showed a productivity of services in works of 24%, a productivity of offices and institutions of 30%, in addition the operational quality was 71%, in the case of speed for institutions it was 57% and cycle times ranged between 3 - 7 days, the reliability of transport was S/. 35.00, this led to a logistics efficiency of less than 50%; likewise, this problem was addressed through the TIXTOOLS MRP software and the homologation of suppliers; in which a NPV of S/2,847.08, an IRR of 11%, a profitability index (RI) of 1.31 were obtained through the economic analysis. Therefore, there is evidence of the need to implement improvements to achieve increased operational and logistical efficiency.
The Impact of Organizational Silence on Organizational Performance in Jordanian Universities: An Applied Study on Academics at Al-Hussein Bin Talal in the Post- COVID-19 Era
Authors: Alleimoun Audeh , Altarawneh Ikhlas , ALAbaddi Zaid , Twaissi Naseem , khalaf Alia
Published: January 2025

purpose: The study's goal was to investigate the phenomenon of organizational silence and its impact on the performance of faculty members at Al-Hussein Bin Talal University. The survey encompassed a total of 370 faculty members from different colleges within the university.Design/methodology/approach: A quantitative research design is suitable for gathering and examining data. Data can be captured using a cross-sectional design. Ensure that the sample encompasses a diverse array of academic subjects, ranks, and levels of experience. Gathering data: Surveys and questionnaires are viable tools for gathering information. Verified scales and measures can be utilized to evaluate the extent of organizational quiet and the level of organizational performance. The poll allows academics to articulate their thoughts regarding organizational silence and its underlying factors. Statistical analysis can be applied to survey data. Descriptive statistics provide a summary of the sample and important factors. An inferential statistic can be employed to examine the correlation between factors and the moderating influence of organizational silence on organizational performance. The results can then be used to make informed decisions and improve overall effectiveness.Findings: The results of the study's to raise senior management's awareness of the idea of organizational silence and its effects on organizational performance. Other recommendations include using participatory management, avoiding overly centralizing decision-making, and encouraging faculty members to voice their opinions, even if they differ from those of others. showing no fear and giving them the impression that management is interested in what they have to say. Practical and social implications: The study on organizational quiet and performance at Jordanian institutions advances organizational silence research. It sheds light on organizational silence in Jordanian universities, adding to current knowledge. Post-COVID-19, it can help explain organizational silence's causes, effects, and methods. Jordanian universities' organizational silence and performance may be affected by COVID-19's problems and potential. The relationship between organizational quiet and performance may be mediated and moderated. Leadership styles, organizational culture, and technological adaption may affect this relationship.
Recent Advances and Industrial Applications of the Synergy Between Robots and Artificial Intelligence Globally in the Era of Industry 4.0
Authors: Ungureanu Liviu Marian , Munteanu Iulian Sorin , Vulturescu Viorel
Published: January 2025

This paper presents an in-depth and comprehensive analysis regarding the integration of robots and artificial intelligence in the automated production processes crucial for modern society, especially in the field of digitized and automated Industry 4.0, with a particular focus on contemporary competitive industrialized countries, with reference to the period 2012-2024, providing estimates of future developments. The authors meticulously explore the contemporary and evolving technological landscape, providing valuable technological introspection, bringing to the attention of researchers and academia a well-structured perspective of the notable advances recorded globally in robotic applications guided and controlled with increased autonomy by AI, highlighting the continued expansion, development and specialization of AI in close correlation with industrial robots, as a symbiosis that is already generating high-quality, intelligent and high-performance products at a fast and highly efficient pace.
Measurement and Decoupling of Hygrothermal-Mechanical Effects with Optical Fibers: Development of a New FBG Sensor
Authors: Aceti Pietro , Calervo Lorenzo , Bettini Paolo , Sala Giuseppe
Published: January 2025

Composite materials are increasingly used in the aviation industry for various aircraft components due to their lightweight and mechanical performances. However, these materials are susceptible to degradation due to environmental factors such as hot-wet environments and freeze-thaw cycles, which can compromise their performance and safety over time. This study develops an innovative Fiber Bragg Grating (FBG) sensor system designed to simultaneously measure and decouple the effects of temperature, humidity and strain on composite materials, particularly in aerospace applications. The system incorporates three FBG sensors: one for temperature, one for temperature and humidity and a third one for all the three factors. A theoretical framework based on linear strain superposition and constitutive laws was developed to isolate the individual contributions of each factor. Experimental validation in controlled hygrothermal conditions demonstrated the system's ability to accurately detect and decouple these effects, enabling the monitoring of moisture absorption and composite degradation over time. Since SHM/HUMS systems based on optical fibers are widely used for monitoring aerospace structures, to provide real-time data for improving maintenance strategies, the proposed system offers a reliable and efficient solution for long-term structural health monitoring, enhancing predictive maintenance, optimizing operational life and ensuring safety in composite components exposed to extreme environmental conditions in aerospace applications.
Microbial Influences on Amyotrophic Lateral Sclerosis: The Gut-Brain Axis and Therapeutic Potential of Microbiota Modulation
Authors: Ayala Victòria , Fontdevila Laia , Rico-Rios Santiago , Povedano Mònica , Andrés-Benito Pol , Torres Pascual , Serrano Jose C. E. , Pamplona Reinald , Portero-Otin Manuel
Published: January 2025

Background/Objectives
Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder characterized by the pro-gressive degeneration of motor neurons. The gut microbiota, a community of microorganisms residing in the digestive tract, has recently been implicated in ALS pathogenesis through its in-fluence on neuroinflammation and metabolic pathways. This review explores the potential role of digestive microbiota and its metabolites in ALS progression and investigates therapeutic ap-proaches targeting gut microbiota.
Methods
A comprehensive review of current literature was conducted to assess the relationship between gut microbiota composition, microbial metabolites, and ALS progression in patients. Special emphasis was placed on studies exploring short-chain fatty acids (SCFAs), bacterial amyloids (curli-like factors), and neurotoxins such as β-methylamino-L-alanine (BMAA). The role of the liver-gut axis was evaluated as well. The potential changes in microbiota would sustain the rationale of ther-apeutic strategies such as probiotics, prebiotics, fecal microbiota transplantation (FMT), and die-tary interventions.
Results
ALS patients exhibit gut dysbiosis, characterized by reduced SCFA-producing bacteria and an increase in potentially pathogenic genera. Of note, different studies do not agree on common patterns of microbiota being linked to ALS, supporting the need for further, larger studies. In some cases, dysbiosis correlates with systemic inflammation and disrupted liver function, amplifying neuroinflammatory responses. Key microbial metabolites, including SCFAs, bacterial amyloids, and BMAA, may exacerbate motor neuron degeneration by promoting protein misfolding, oxi-dative stress, and neuroinflammation. Emerging therapeutic strategies, including probiotics and FMT, show potential in restoring microbial balance, although clinical data in ALS patients remains limited.
Conclusions
The gut microbiota could modulate neuroinflammation and systemic metabolism in ALS. Mi-crobiota-targeted therapies, such as probiotics and dietary interventions, represent promising avenues for mitigating disease progression. Further research is required to validate these inter-ventions through large-scale, longitudinal studies, and to develop personalized microbiota-based treatments tailored to individual ALS phenotypes.