bluuebunny/crossref_metadata_2025 huggingface dataset:
Influence of Knowledge and Cultural Beliefs on Attitudes Toward HPV Vaccination Among Israeli Nurses and Nursing Students: Implications for Vaccine Advocacy
Authors: Gendler Yulia , Ben-Aroya Nurit , Blau Ayala
Published: September 2024

Background: Human papillomavirus (HPV) poses a significant health burden, yet the vaccine which successfully prevents HPV and its associated cancers remains underutilized. Nurses play a crucial role in patient education and advocacy for HPV vaccination. This study explores how knowledge, along with cultural, religious, and social beliefs, shapes the attitudes of Israeli nurses and nursing students toward the HPV vaccine and their advocacy efforts.
Methods: A cross-sectional study was conducted from August 2023 to January 2024 using an anonymous online questionnaire distributed via Facebook groups targeting Israeli nurses and nursing students. The questionnaire assessed demographic data, HPV-related knowledge, and attitudes toward HPV vaccination.
Results: The study included 458 participants (229 nurses and 229 nursing students). Significant knowledge gaps were found, with 52% of participants incorrectly believing that the vaccine can cure existing infections and 47% mistakenly believing that it is administered in a single dose. Logistic regression revealed that nurses working in community settings were more likely to have positive attitudes toward HPV vaccination (OR=2.98, 95% CI: 1.84–4.85). Higher levels of HPV-related knowledge (OR=3.35, 95% CI: 2.10–5.35) and secular or traditional religious affiliations (OR=2.45, 95% CI: 1.52–3.97) were strongly associated with positive attitudes toward and advocacy for the vaccine.
Conclusions: Targeted educational programs addressing knowledge gaps, especially those tailored to Israel's cultural and religious diversity, are crucial for empowering nurses and nursing students as advocates for HPV vaccination. Enhancing their understanding of HPV can increase vaccine uptake, reduce the incidence of HPV-related diseases, and strengthen public health initiatives in Israel.
Revision of Robotic Prostheses Manufactured with 3D Printing: Advances, Challenges and Future Perspectives
Authors: Salazar Maxwell , Portero Paola , Zambrano Marcelo , Rosero Ricardo
Published: September 2024

3D printing has significantly transformed the design and manufacture of robotic prostheses, making these devices more accessible, customized, and functional. This paper examines the historical evolution of prosthetic technology, tracing its development from rudimentary mechanical devices to the integration of advanced technologies, such as 3D printing. This innovation has enabled the production of prostheses at lower costs while enhancing their adaptability and performance. The review highlights how 3D printing has driven a disruptive shift in prosthetic customization, and how emerging technologies—including smart materials and artificial intelligence—have expanded the capabilities of prosthetic devices, offering more adaptive and natural movement. However, challenges persist, particularly regarding the need for standardization and infrastructure expansion to ensure equitable access to these technologies. Future research into novel materials and manufacturing techniques holds the potential to improve further the functionality, affordability, and accessibility of prosthetic devices. In conclusion, while 3D printing has marked a significant milestone in the evolution of robotic prosthetics, overcoming existing challenges is essential to realize its global impact and benefits fully.
Inflammatory and Lipid Biomarkers in Early Atherosclerosis: A Comprehensive Analysis
Authors: Namitokov Alim , Karabakhtsieva Karina , Malyarevskaya Olga
Published: September 2024

Atherosclerosis is a leading cause of cardiovascular disease, characterized by lipid accumulation and chronic inflammation within arterial walls. Early detection in young adults is crucial for preventing adverse cardiovascular events. This study investigates the associations between inflammatory indices, lipid biomarkers, and the presence of atherosclerosis in patients aged 18 to 55 years. Methods: A cross-sectional study was conducted involving 89 participants divided into two groups: 62 patients with documented atherosclerosis (main group) and 27 healthy controls without significant atherosclerosis. Comprehensive data—including demographic information, medication use, imaging results, laboratory parameters, and calculated inflammatory indices (SIRI, SII, AISI, NLR, PLR, MLR)—were collected. Statistical analyses included correlation assessments, group comparisons using the Mann-Whitney U test, logistic regression modeling, feature importance analysis with Random Forest and Gradient Boosting classifiers, receiver operating characteristic (ROC) curves, and K-means clustering. Results: Significant differences were observed between the main and control groups. Patients with atherosclerosis exhibited elevated inflammatory indices (SIRI, NLR, MLR, SII) and lipid profile abnormalities (higher TC and LDL-C, lower HDL-C). Lp(a) and ANGPTL3 levels were significantly higher in the main group (p < 0.001 and p < 0.01, respectively). Logistic regression identified SIRI and ANGPTL3 as significant predictors of atherosclerosis, with the model demonstrating high accuracy (77%) and sensitivity (93%). Feature importance analysis confirmed the significance of SIRI and ANGPTL3, alongside traditional lipid biomarkers, in predicting disease presence. ROC analysis showed excellent model performance (AUC > 0.80). Clustering analysis revealed two distinct patient subgroups characterized by predominant inflammatory profiles or lipid metabolism disturbances. Conclusions: Systemic inflammation and lipid abnormalities play significant roles in early atherosclerosis among young adults. Elevated SIRI and ANGPTL3 levels are potent predictors of disease presence. The integration of inflammatory indices and lipid biomarkers into predictive models enhances risk stratification and supports personalized medicine approaches. Further research with larger cohorts is warranted to validate these findings and inform targeted prevention and intervention strategies.
Power Signal Histograms: A Method of Power Grid Data Compression on the Edge for Real-time Incipient Fault Forensics
Authors: Tyler Joshua H. , Reising Donald R. , Cooke Thomas , Murphy Anthony
Published: September 2024

Across the power grid infrastructure, deployed power transmission systems are susceptible to incipient faults that interrupt standard operations. These incipient faults can range from being benign in impact to causing massive hardware damage and even loss of life. The power grid is continuously monitored, and incipient faults are recorded by Digital Fault Recorders (DFRs) to mitigate such outcomes. DFR recorded data allows power quality forensics and event analysis, but this capability comes at the cost of high data storage and data transmission requirements. It is common for data older than two weeks to be overwritten due to storage limitations and without being analyzed. This inhibits the creation of long-term data libraries that would enable incipient fault forensics and the characterization of behavior that precedes them, which limits the development and implementation of preventive measures; thus, there is a critical need to reduce DFR recorded data storage requirements. This work addresses this critical need by leveraging the cyclic and residual histograms and introducing the frequency, and Root Means Squared (RMS) histograms, which alleviate current high data storage requirements and provides effective Incipient Fault Prediction (IFP). The residual, frequency, and RMS histograms are an extension of the cyclic histogram, reduce the date storage requirement by up to 99.58%, can be generated on the DFR without interrupting its normal operations, and are capable of predicting voltage arcing six hours before it is strong enough to trigger a DFR recorded event.
Relationships Between PM2.5 and Hemoglobin Among Reproductive Women in Africa
Authors: Saeed Muhammad , Majeed Haris , Saeed Mohammad , Sayed Mashael , Lohe Arav , Ali Olivea , Zaidi Adeena , Khokhar Harris
Published: September 2024

The effects of toxic air in the form of air pollution are known to harm women’s health. New data has shown that air pollution has effects on maternal anemia. Yet the effects of particulate matter 2.5 (PM2.5) on hemoglobin among reproductive maternal (15-49 years) has been understudied. In this population-based study, we study the region-specific associations between prevalence of hemoglobin among reproductive women and PM2.5 in 43 countries of Africa from 2000-2019. Using generalized linear regression models, we found that after adjusting for key covariates, PM2.5 had a slight negative association with hemoglobin among reproductive women. Other studies are needed in other low-income settings to expand our findings.
Prediction of Gas-Water Multiphase Flow Behaviour and Hydrates Severity in Gas-Dominant Subsea Pipeline
Authors: Umuteme Oghenethoja Monday , Islam Sheikh Zahidul , Hossain Mamdud , Karnik Aditya
Published: September 2024

This study focuses on enhancing the prediction of flow characteristics in gas pipelines under hydrate-forming conditions using a validated CFD model. Four-Quadrants approach was introduced to analyse the relationship between gas and water flowrates, and to provide further insights into hydrate formation, agglomeration, deposition, and pipeline plugging. The analysis considered subcooling temperatures, water volume fractions, and gas velocities, to assess the risk of hydrate plugging in subsea gas pipelines. Results indicate that higher subcooling temperatures significantly increase the risk of hydrate formation and plugging, especially at lower gas velocities. At subcooling temperatures above 7.1 K, hydrate agglomeration and deposition become more pronounced, leading to a greater risk of plugging. Similarly, water volume fractions above 0.06 were found to increase the likelihood of hydrate blockages. However, higher gas velocities were shown to reduce this risk by promoting the sloughing of hydrates and preventing deposition. The findings align with existing literature and offer practical insights for flow assurance in gas pipeline operations.
Exploring NLP Challenges and Opportunities Forlanguages with Extensive Character Sets: A Casestudy on Nepali
Authors: Jha Basab
Published: September 2024

This study provides a detailed examination of Natural Language Processing (NLP) for the complexscript of Nepali. We analyze available data resources today and discuss relevant points includingcharacter encoding, advanced tokenization methods and morphological complexity. This allows us tocontrast Nepal’s unique language and technology ecosystem with Hindi and Thai in terms of NLPadvancements. Quantitative assessment of existing tools and resources is offered by this investigationwhich highlights immediate weaknesses as well as areas that need more effort. Various ethicalconcerns are addressed here while potential topics for future research as e-governance, healthcare oreducation with a focus on new domain-specific applications, and cross-lingual transfer learning aresuggested. The objective of this attempt is to enhance understanding of natural language processing(NLP) in Nepali language and beyond aimed at developing NLP technologies that are more efficient,inclusive, culturally appropriate across diverse linguistic communities.
Research on the Influence of Matrix Shape on Percolation Threshold Values for Current Flow Conducted Using the Monte Carlo Simulation Method
Authors: Bondariev Vitalii , Okal Pawel , Rogalski Przemyslaw , Pogrebnjak Alexander , Zukowski Pawel
Published: September 2024

In this study, in order to determine the effect of matrices shape on percolation threshold values, computer simulations were performed using the Monte Carlo method for a 200x200 square-shaped matrix and rectangular matrices containing the same number of nodes as the square matrix. Based on the simulations, the average values of percolation thresholds and standard deviations for current flow along and across the matrices were determined. It was determined that for a square-shaped matrix, the average values of percolation thresholds in both directions of current flow were the same. Extending the rectangular matrix while reducing its height causes the average value of the percolation threshold in the direction of current flow along the matrix to increase from 0.592740 to 0.759847, while in the transverse direction it decreases from 0.592664 to 0.403614. The values of the classical asymmetry coefficients of the probability distributions of percolation thresholds for both directions of current flow were determined. Histograms of the probability distributions of percolation threshold values for square-shaped matrix and rectangular matrices were made and compared with normal distributions. It was found that the occurrence of two percolation thresholds in rectangular layers should be considered when analyzing electrical conductivity measurements of nanocomposite thin films.
Stochastic H∞ Filtering of the Attitude Quaternion
Authors: Choukroun Daniel , Cooper Lotan , Berman Nadav
Published: September 2024

Several stochastic H∞ filters for estimating the attitude of a rigid body from line-of-sight measurements and rate gyro readings are developed. The measurements are corrupted by white noise with unknown variances. Our approach consists of estimating the quaternion while attenuating the transmission gain from the unknown variances and initial errors to the current estimation error. The time-varying H∞ gains are computed through differential and algebraic linear matrix inequalities whose parameters are independent of the state. The case of a gyro drift is addressed, too. Extensive Monte Carlo simulations show that the proposed stochastic H∞ quaternion filters perform well for a wide range of noise variances. The actual attenuation, which improves with the noise level and is worst in the noise-free case, is better than the guaranteed attenuation by one order of magnitude. The proposed stochastic H∞ filter produces smaller biases than a standard quaternion Kalman filter and similar standard deviations at large noise levels. An essential advantage of this H∞ filter is that the gains are independent of the quaternion, which makes it insensitive to modeling errors. This desired feature is illustrated by comparing its performances against those of unmatched Kalman filters. When provided with too high or too low noise variances the Kalman filter is outperformed by the $H_\infty$ filter, which essentially delivers identical error magnitudes.
Impact and Effectiveness of COVID-19 Vaccines Using Machine Learning to Analyze a Time Series: A Population-Based Study
Authors: Garcia-Carretero Rafael , Ordoñez-Garcia Maria , Vazquez-Gomez Oscar , Belen Rodriguez-Maya Belen , Gil-Prieto Ruth , Gil-de-Miguel Angel
Published: September 2024

Background: Although confirmed cases of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been declining since late 2020 due to general vaccination, little research has been done regarding the impact of vaccines against SARS-CoV-2 in Spain in terms of hospitalizations and deaths. Objective: Our aim was to identify the reduction in severity and mortality of coronavirus disease 2019 (COVID-19) at a nationwide level due to vaccination. Methods: We designed a retrospective, population-based study to define waves of infection and to describe the characteristics of the hospitalized population. We also studied the rollout of vaccination and its relationship with the decline in hospitalizations and deaths. Finally, we developed two mathematical models to estimate non-vaccination scenarios using machine learning modeling (with the ElasticNet and RandomForest algorithms). The vaccination and non-vaccination scenarios were eventually compared to estimate the number of averted hospitalizations and deaths. Results: In total, 498,789 patients were included, with a global mortality of 14.3%. We identified six waves or epidemic outbreaks during the observed period. We established a strong relationship between the beginning of vaccination and the decline in both hospitalizations and deaths due to COVID-19 in all age groups. We also estimated that vaccination prevented 170,959 hospitalizations (CI 95% 77,844–264,075) and 24,546 deaths (CI 95% 2,548–46,543) in Spain between March 2021 and December 2021. We estimated a global reduction of 9.19% in total deaths during the first year of COVID-19 vaccination. Conclusions: Demographic and clinical profiles changed over the first months of the pandemic. Patients over 80 years old and other age groups obtained clinical benefit from early vaccination. The severity of COVID-19, in terms of hospitalizations and deaths, decreased due to vaccination.
Antifungal Activity of Citrus Essential Oil in Controlling Sour Rot in Tahiti Acid Lime Fruits
Authors: Moura Vanessa Santos , Orlandin Lara Dias , Mariano Beatriz Saraiva , Rodrigues Josiane , Devite Fernando Trevizan , DE AZEVEDO FERNANDO ALVES , Bastianel Marines
Published: September 2024

Sour rot, caused by Geotrichum citri-aurantii, is a significant post-harvest disease in citrus, resulting in economic losses due to the lack of effective fungicides. This study investigates the antifungal activity of essential oils from Late IAC 585 willowleaf and Pera IAC sweet orange in controlling sour rot in Tahiti acid lime fruits. Essential oils were extracted via hydrodistillation and tested in vitro and in vivo. In vitro, assays evaluated mycelial growth inhibition at concentrations ranging from 2 to 32 µl ml⁻¹. In vivo trials involved preventive and curative treatments on artificially inoculated fruits stored at 25°C ± 2. Results showed that Pera IAC sweet orange oil, at 32 µl ml⁻¹, reduced disease severity by 96% in curative treatments. In contrast, Late mandarin oil demonstrated moderate inhibition (44%) at the highest concentration in vitro. The oils did not affect key fruit quality parameters such as juice yield and total soluble solids. These findings suggest that citrus essential oils could be natural alternatives to synthetic fungicides for post-harvest sour rot management, combining effectiveness with maintaining fruit quality. Further research is needed to explore the mechanisms of action and commercial application potential.
Improving the Sustainability of Caciocavallo Ragusano Cheese Production and Enhancing Its Role on Consumer Health and Liking
Authors: Litrenta Federica , Cincotta Fabrizio , Russo Nunziatina , Cavallo Carmelo , Amato Annalisa , Lopreiato Vincenzo , Merlino Maria , Verzera Antonella , Randazzo Cinzia Lucia , Liotta Luigi
Published: September 2024

In this study, Caciocavallo Ragusano, a typical cheese produced in Sicily Island (Italy), was ob-tained from milk of dairy cows fed with and without enriched olive cake (ECO and CTR, respec-tively) in order to evaluate nutritional, microbiological, volatile, and sensory differences in cheeses. ECO cheese showed greater (p < 0.05) MUFA and PUFA and polyphenols content, and lower SFA content than CTR cheese. Microbiological analyses revealed the absence of Salmonella, Listeria monocytogenes, Escherichia coli, and E. coli O157, and no significant differences in the vi-able counts of the remaining microbial groups analyzed, between samples. Thermophilic lacto-cocci were more prevalent in ECO cheese. The implementation of culture-independent method, such as PCR-DGGE analyses, revealed the presence of a more diverse microbial population in both cheeses. Regarding the volatile compounds profile, long-chain free fatty acids were more abundant in the ECO cheese resulting in a healthier free fatty acid profile. This study also showed that, especially for their appearance and taste, the consumers mostly appreciated the ECO cheese. Results showed that using enriched olive cake could enhance the sustainability and the quality of Ragusano cheese, improving not only the health of the consumers but also positively influencing tastes and acceptability.
Factors Affecting Financial Risk Tolerance of Rural Households in Ludhiana District of Punjab
Authors: Gupta Srishti , Aggarwal Navdeep
Published: September 2024

The present study aims to find out the financial risk tolerance scores of the rural residents of Ludhiana district. Also, how drivers such as socio-demographic factors, namely, gender, age, education, annual income, existence of loan, occupation, employment status and psychological factors, namely, deliberative thinking, optimism and personality type A/ B impact financial risk tolerance of rural residents. The study is important for financial policy makers as they will become aware about scenario of rural residents and frame policies accordingly. Stepwise regression analysis was carried on. The result was found out that optimism positively and deliberative thinking negatively impacted financial risk tolerance, but personality type A/B did not have a significant impact on financial risk tolerance. Socio-demographic factors such as existence of loan, full-time salaried individuals, marital status significantly impacted financial risk tolerance. Other factors failed to have impact on financial risk tolerance of rural residents in the current study.
Is Water the Engine of Protein Folding?
Authors: Campanile Marco , Graziano Giuseppe
Published: September 2024

No one can dismiss the fundamental role played by water in several important biochemical processes, including the folding of globular proteins. The so-called hydrophobic effect is the theoretical construction to rationalize how water molecules stabilize the folded state. However, over the years, analyses have been published that lead to the conclusion that water destabilizes the folded state. The aim of the present work is to state that the gain in translational entropy of water molecules (due to the decrease in water accessible surface area associated with folding) is the driving force of protein folding.
Generative AI for Culturally Responsive Assessment in Science: A Conceptual Framework
Authors: Nyaaba Matthew , Zhai Xiaoming , Faison Morgan Z.
Published: September 2024

This study presents the core tenets that constitute culturally responsive science assessments (CRSciA) for K-12 education and aligned them with the capabilities of generative AI (GenAI). The tenets were identified based on their dominance in the literature, including Indigenous Language, Race and Ethnicity, Religious Beliefs, Family and Community, and Indigenous Knowledge. These tenets were instrumental in developing the GenAI-CRSciA framework and the subsequent prompts to generate CRSciAs aligned with the Next Generation Science Standards (NGSS) while comparing it with standard prompt strategies. The results showed that the GenAI-CRSciA approach outperformed standard prompting strategies in terms of generating CRSciAs, proving its effectiveness in addressing the ongoing challenges in science assessments. Even though the GenAI-CRSciA framework presented assessments that cover a range of the cultural backgrounds, it presents potential challenges such as compromising curricula core competencies and overgeneralization of students’ backgrounds; overlooking subcultural variations within a country or region, for example differences between urban and rural students, or between different ethnic or linguistic groups within the same nation, which can lead to bias and less effective CRSciA outputs. To address this, we recommend that teachers provide comprehensive and specific background information about their students when using the GenAI-CRSciA prompting, ensuring that the generated content is truly reflective of the students’ unique cultural contexts. In larger class settings, teachers could implement comprehensive local data indexing, where detailed student background information is uploaded and retrievable for use in crafting more personalized CRSciAs. We recommend educators make conscious efforts to validate the generated assessments with input from human experts, including community or family, educators, and even students who are knowledgeable about the cultural nuances. We also suggest continuous professional development would be necessary to enhance teachers’ understanding of the cultural tenets.
Impact of Zirconium Carbide Particles on the Microstructure and Mechanical Characteristics of As-Cast and Heat Treated Al7475-Zirconim Carbide Composites
Authors: R Vijayakumar , Pujar Vidyadhar , T Hemanth Raju , T Jagadeesha , S Udayashankar , Goudar Dayanand M. , Raju K. , Pinto Deesy G.
Published: September 2024

The aluminum alloys are prominently employed in the automotive, defense and aerospace industries owing to their excellent properties as compared to that of other metals and alloys. The present work has been centered on the synthesis and the evaluation of mechanical properties of cast and heat treated Al7475-Zirconium carbide composites. The composites were prepared by stir casting method. In order to enhance the properties, Al7475 alloy and Al7475-Zirconium carbide composite were subjected to a T6 heat treatment. The microstructural analysis and tensile, compression, impact and hardness tests were performed on the as-cast as well as T6 heat treated composite specimens. The microstructure of as-cast and heat treated Al7475-Zirconium carbide composite has revealed that the matrix of Al7475 alloy consisted of uniformly dispersed Zirconium carbide particles. The scanning electron microscopy image of heat-treated composite showed a decrease in grain size due to heat treatment effect, resulting in an increase in the strength of the composite. The mechanical properties of heat-treated Al7475-Zirconium carbide composite are superior compared to the as-cast composite. The ultimate tensile strength, yield strength, compression strength, impact strength and hardness of heat treated composite are 16.8%, 15.5%, 18.7%, 18.75% & 22.3% respectively higher than that of as-cast composite.
A Circle-Drawing Task for Studying Reward-Based Motor Learning in Children and Adults
Authors: van Mastrigt Nina M. , Smeets Jeroen B.J. , van Leeuwen A. Moira , van Wijk Bernadette C.M. , van der Kooij Katinka
Published: September 2024

Childhood is an obvious period for motor learning since children’s musculoskeletal and nervous systems are still in development. Adults adapt movements based on reward feedback about success and failure but it is less established whether school-age children also exhibit such reward-based motor learning. We designed a new ‘circle-drawing’ task suitable for assessing reward-based motor learning in both children and adults. Participants drew circles with their unseen hand on a tablet. They received binary reward feedback after each attempt based on the proximity of the average radius of their drawing to a target radius set as double the radius of their baseline drawings. We rewarded about 50% of the trials based on a performance-dependent reward criterion. Both children (7-17 years old) and adults increased the radius of their drawings in the direction of the target radius. We observed no difference in learning between children and adults. Moreover, both groups changed the radius less following reward than following reward absence, which is a sign of reward-based motor learning. We conclude that school-age children, like adults, exhibit reward-based motor learning.
Regressive Machine Learning for Real-Time Monitoring of Bed-Based Patients
Authors: Joseph Paul , Ali Husnain , Matthew Daniel , Thomas Anvin , Jose Rejath , Mayer Jonathan , Bekbolatova Molly , Devine Timothy , Toma Milan
Published: September 2024

This research presents an ensemble model developed to enhance the safety of bedridden patients in healthcare settings. The model utilizes a unique dataset capturing six typical movements performed by patients laying in bed, such as rolling over, falling off the bed, etc. The aim is to automate the classification of these movements, thereby enabling real-time monitoring of patients without the constant presence of hospital personnel in the room, a common practice in current healthcare settings. The dataset is preprocessed and balanced using the Synthetic Minority Over-sampling Technique, and then split into training and test sets for model training and evaluation. Three different models are explored: a Decision Tree Regressor, a Gradient Boosting Regressor, and a Bagging Regressor. The Bagging Regressor is an ensemble model that utilizes the Decision Tree Regressor as its base regressor. Each model’s performance is evaluated using accuracy, R2 score, and Mean Squared Error on both the training and test sets. The ensemble model demonstrates promising results, indicating the potential of machine learning to improve patient safety in healthcare settings. The study also employs K-Fold cross-validation and learning curves to validate the robustness of the ensemble model. This research contributes to the growing body of knowledge on the application of machine learning in healthcare and opens up new avenues for improving patient safety through real-time monitoring and classification of patient movements.
Developmental Predictors of Suicidality in Schizophrenia: A Systematic Review
Authors: Benster Lindsay , Stapper Noah , Rodriguez Katie , Daniels Hadley , Villodas Miguel , Weissman Cory , Daskalakis Zafiris , Appelbaum Lawrence
Published: September 2024

Background/Objectives: Schizophrenia (SZ) is a severe psychiatric disorder characterized by a complex interplay of genetic, developmental, and environmental factors that significantly increase the risk of suicidal ideation (SI) and suicide attempts (SAs). This systematic review synthesizes current research on the developmental predictors of SI in individuals with SZ, aiming to delineate the multifactorial etiology of suicide within this population. Methods: A comprehensive search across Medline, PsycINFO, and EMBASE databases identified 23 eligible studies, emphasizing the varied methodological approaches and the global distribution of research efforts. Results: These studies demonstrate a robust association between early life adversities, particularly childhood trauma such as physical neglect, emotional abuse, and sexual abuse, and the increased prevalence of SI and SAs in SZ. This review also highlights the significant genetic factors associated with development of suicidality in SZ, suggesting that polymorphisms in inflammation-related genes and neurodevelopmental abnormalities may influence susceptibility to SI. Notably, family history of psychiatric conditions may exacerbate the risk of SI through both hereditary and environmental mechanisms. Environmental factors, including socioeconomic status and social support, are also implicated, underscoring the role of broader socio-environmental conditions influencing outcomes. Conclusions: This review supports the integration of biopsychosocial models in understanding SI in SZ, advocating for interventions addressing the complex interplay of risk factors and the need for longitudinal studies to elucidate the dynamic interactions between risk factors over time. This comprehensive understanding is crucial for developing targeted preventative strategies and enhancing the clinical management of SZ, aiming to reduce suicidality in this vulnerable population.
Fuzzy Logic based Energy Management Strategy for Hybrid Fuel Cell Electric Ship's Power and Propulsion System
Authors: Nivolianiti Evaggelia , Karnavas Yannis L , Charpentier Jean-Frédéric
Published: September 2024

The growing use of proton-exchange membrane fuel cells (PEMFC) in hybrid propulsion systems, aimed at replacing traditional internal combustion engines and reducing greenhouse gas emis-sions. Effective power distribution between the fuel cell and the energy storage system (ESS) is crucial, which has led to a growing emphasis on developing energy management systems (EMS) to efficiently implement this integration. To address this goal, this study examines the performance of a fuzzy logic rule-based strategy for a hybrid fuel cell propulsion system in a small hydro-gen-powered passenger vessel. The primary objective is to optimize fuel efficiency, with particular attention to reducing hydrogen consumption. The analysis is carried out under typical operating conditions encountered during a river trip. Comparisons between the proposed strategy with other approaches —control-based, optimization-based and deterministic rule-based— are con-ducted to verify the effectiveness of the proposed strategy. Simulation results indicated that EMS based on fuzzy logic mechanisms was the most successful in reducing fuel consumption. The superior performance of this method stems from its ability to adaptively manage power distri-bution between the fuel cell and energy storage systems.
A Comparative Health Disparities Analysis Across Continents : A Comparative Analysis of African and European Countries.
Authors: Ould-Boudia Ahmed , Adusei-Mensah Frank , Olaleye Sunday Adewale , Balogun Oluwafemi Samson
Published: September 2024

This analysis investigates health outcomes by cause and income group across European and African countries, highlighting significant disparities tied to economic status. Low and lower-middle-income countries in Africa face a greater burden of disease, particularly in acute lower respiratory infections, diarrheal diseases, bacterial infections, HIV/AIDS, and maternal conditions. This is primarily due to limited access to clean water, sanitation, and healthcare services. In contrast, high-income African countries exhibit better health outcomes. European countries show variations: lower-middle-income nations suffer more fro4m acute respiratory infections and HIV/AIDS, while high-income countries report higher incidences of cancer and bacterial infections. These differences reflect disparities in healthcare quality and social determinants. The study emphasizes the need for targeted policy initiatives to address these disparities by focusing on socioeconomic factors and improving healthcare access and quality across all income groups.
Tackling Infectious Diseases in the Caribbean and South America: Epidemiological Insights, Antibiotic Resistance, and Immunological Advances
Authors: Justiz-Vaillant Angel , Gopaul Darren , Arrozarena-Fundora Rodolfo , Asin-Milan Odalis , Akpaka Patrick
Published: September 2024

This paper explores various aspects of microbiology and immunology, focusing on the epidemiology and molecular characterisation of infectious diseases in the Caribbean and South America. Key areas of investigation include tuberculosis (TB), nosocomial infections, Salmonella infections, and bloodborne pathogens. A retrospective study in Jamaica underscores the high mortality rates in HIV-positive TB patients and the need for early HIV diagnosis and integrated care. Research in Trinidad and Tobago reveals the genetic diversity of Mycobacterium tuberculosis strains, highlighting high HIV-TB co-infection rates. The paper also examines the challenges posed by nosocomial infections, particularly those caused by antibiotic-resistant Gram-negative bacteria and methicillin-resistant Staphylococcus aureus (MRSA), and emphasises the importance of infection control. In addition, the study investigates Salmonella prevalence in poultry in Jamaica and the risks associated with foodborne infections. The paper further explores transfusion-transmitted infections and the development of IgM antibodies in egg whites for bacterial antigen detection. Lastly, it addresses immune responses in patients with immunodeficiency disorders, such as severe combined immunodeficiency (SCID) and chronic granulomatous disease (CGD), highlighting their susceptibility to a wide range of infections.
The Utilization of PRAME in the Diagnosis, Prognosis, and Treatment of Melanoma
Authors: Blount Samuel L , Liu Xiaochen , McBride Jeffrey Don
Published: September 2024

Melanoma, a deadly form of skin cancer, has seen improved survival rates due to advances in diagnosis and treatment, yet the need for further improvement remains critical. Tumor-associated antigens, such as PRAME (Preferentially Expressed Antigen in Melanoma), offer promising avenues for enhanced diagnostic precision, prognostic assessment, and targeted immunotherapy. PRAME, a cancer-testis antigen, is selectively expressed in various cancers, including melanoma, and plays a key role in promoting tumorigenesis through inhibition of retinoic acid signaling, epithelial-to-mesenchymal transition, and immune evasion. This review explores the diagnostic utility of PRAME in distinguishing melanoma from benign nevi, its prognostic value in aggressive melanoma subtypes, and its potential as a therapeutic target in cancer vaccines and adoptive T-cell therapies. While PRAME-targeted therapies face challenges such as tumor heterogeneity and immune suppression, ongoing research aims to overcome these barriers, offering hope for more effective melanoma treatments.
Cortical Organotypic Brain Slice Cultures to Examine Sex- and Age-Dependent Astrocyte-Mediated Synaptic Phagocytosis
Authors: Nagumanova Anastasiia , Seeholzer Lea R. , Di Benedetto Barbara
Published: September 2024

Astrocytes, the most abundant glial cells in the brain, are an integral part of the synaptic compartment and contribute to synaptic pruning, a key process for refining neural circuits during early postnatal development (PND). Dysregulations in this process are implicated in various neuropsychiatric disorders, including major depressive disorder (MDD). To investigate astrocyte functions in a physiologically relevant context, organotypic brain slice cultures (OBSCs) offer a powerful model, reproducing more closely in vivo conditions than traditional cell cultures and preserving complex brain architecture and interactions. Here, we present OBSCs as an ex vivo culturing method to provide a platform to explore astrocyte-mediated synaptic pruning dynamics in the rat prefrontal cortex (PFC) during PND. Our approach is based on assessing the role of MEGF10, a key protein involved in synaptic pruning, alongside the synaptic markers synaptophysin and PSD95, using Western blotting to analyse the expression levels of these markers in the cortex of developing rat pups. Additionally, we combine immunofluorescence staining with confocal imaging and IMARIS 9.8 software-assisted analysis to investigate the co-localization of the lysosomal marker LAMP1 with synaptic and astrocytic markers to evaluate the precise rate of synaptic engulfment. The methods presented here allow a deeper examination of an astrocyte-mediated synaptic remodelling in healthy and pathophysiological conditions.
Investigating the Performance of Open Vocabulary Classification Algorithms for Pathway and Surface Material Detection in Urban Environments
Authors: de Moraes Vestena Kauê , Phillipi Camboim Silvana , Brovelli Maria Antonia , Rodrigues dos Santos Daniel
Published: September 2024

Mapping pavement types, especially in sidewalks, is essential for urban planning and
mobility studies. Identifying pavement materials is a key factor in assessing mobility, such as
walkability and wheelchair usability. However, satellite imagery in this scenario is limited, and
in-situ mapping can be costly. A promising solution is to extract such geospatial features from
street-level imagery. This study explores using open vocabulary classification algorithms to
segment and identify pavement types and surface materials in this scenario. Our approach uses
Large Language Models (LLMs) to improve the accuracy of classifying different pavement types.
The methodology involves two experiments: the first uses free prompting with random
street-view images, employing Grounding Dino and SAM algorithms to assess performance across
categories. The second experiment evaluates standardized pavement classification using the
Deep-Pavements Dataset and a fine-tuned CLIP algorithm optimized for detecting
OSM-compliant pavement categories. The study presents open resources, such as the Deep
Pavements Dataset and a fine-tuned CLIP-based model, demonstrating a significant improvement
in the True Positive Rate (TPR) from 56.04% to 93.5%. Our findings highlight both the potential
and limitations of current open vocabulary algorithms and emphasize the importance of diverse
training datasets. This study advances urban feature mapping by offering a more intuitive and
accurate approach to geospatial data extraction, enhancing urban accessibility and mobility
mapping.
Trends and Challenges in Data Analytics and Machine Learning Using Call Detail Records in Telecom Systems
Authors: Barrett James , Legg Phil , Smith Jim , Barnes Tim , Boyle Charles
Published: September 2024

As telecommunication networks continue to grow, the volume, variety, and velocity of such `big data' poses an immense challenge for security and service analysts. A primary data format in such networks are Call Detail Records (CDRs), and more recently, eXtended Detail Records (XDRs), that capture a variety of information such as caller, receiver, duration, carrier, datetime, amongst other attributes. In this short paper, we investigate the current research trends and challenges that exist within this data-rich domain. As part of this, we look at the domain-specific tasks that analysts will seek to address, we look at how machine learning has been utilised to date within this domain, and we present our current findings on open research problems that are ripe for further investigation.
Morphological Characterization, Polyphenolic Profile, and Bioactive Properties of Limoncella, an Ancient Mediterranean Variety of Sweet Citrus
Authors: Potenza Lucia , Saltarelli Roberta , Palma Francesco , Di Patria Laura , Burattini Sabrina , Annibalini Giosuè , Gobbi Pietro , Valentini Laura , Caprioli Giovanni , Santanatoglia Agnese , Vittori Sauro , Barbieri Elena
Published: September 2024

Limoncella of Mattinata, a rare and ancient Mediterranean citrus fruit, was investigated by sequence analysis of the ribosomal internal transcribed spacer regions, which assigns it as a variety of Citrus medica L. Morphological, chemical, and biomolecular approaches were used to characterize flavedo and albedo, parts usually rich of bioactive compounds. The morphological findings showed albedo and flavedo cellular structures as “reservoirs” of nutritional components. Both albedo and flavedo hydroalcoholic extracts were rich in polyphenols, but they were different in compounds and quantity. The flavedo is rich in p-coumaric acid and rutin, whereas the albedo contains high levels of hesperidin and quercitrin. Antioxidant, anti-inflammatory, and genoprotective effects for albedo and flavedo were found. The results confirmed the health properties of flavedo and highlighted that albedo is also a rich source of antioxidants. Moreover, this study valorizes Limoncella of Mattinata's nutritional properties, cueing its crops' repopulation.
Academic Profiles for EdTech Needs – an Analysis of Researcher Profiles
Authors: Leoste Janika , Marjanović Uglješa , Rakic Slavko , Kask Kristjan , Peña Sánchez Luis , Tomusk Voldemar , Saluveer Madis , Väät Sirly
Published: September 2024

In an era where collaboration between academia and the EdTech industry is crucial for innovation, this study explores how academic profiles align with industry needs. In this study we examine the professional profiles available online of educational researchers from the Tallinn University School of Educational Sciences across the international LinkedIn, national ETIS and institutional TLU platforms, to identify how researchers market their skills that are relevant to the EdTech sector. Our findings indicate that some of the key areas such as instructional design, project management and technical proficiency that are vital for EdTech industry remain often underrepresented in academic profiles. While LinkedIn facilitates networking, it may not necessarily reach the depth needed for comprehensive representation, whereas the Estonian national research database ETIS provides rich academic details with limited industry appeal. Our suggestions call for strategic improvements in how researchers can present their expertise online, in order to improve industry-academia collaboration. By creating more precise and strategically targeted professional profiles, researchers will stand better chances to attract EdTech industry’s attention.
A MEDT Study of the Reaction Mechanism and Selectivity of the Hetero Diels-Alder Reaction between 3-Methylene-2,4-chromandione and Methyl Vinyl Ether
Authors: Bouhaoui Abderrazzak , Moumad Aziz , Domingo Luis Ramon , Bouissane Latifa
Published: September 2024

The hetero Diels-Alder (HDA) reaction between the ambident heterodiene 3-methylene-2,4-chromandione (MCDO) and the non-symmetric methyl vinyl ether (MVE) is investigated within the Molecular Electron Density Theory (MEDT) at the B3LYP/6-311G(d,p) computational level. The aim of this study is to gain insight into the molecular mechanism and to elucidate the factors that control the selectivity found experimentally. DFT-based reactivity indices reveal that MCDO exhibits strong electrophilic character, while MVE displays a strong nucleophilic character. Meanwhile, Parr function explains the ortho regioselectivity of this HDA reaction. The highly polar nature of this HDA reaction, supported by the high global electron density transfer (GEDT) taking place at the transition state structures (TSs), accounts for the very low activation energy associated with the most favorable TS-4on. The ambident nature of MCDO allows the formation of two constitutional isomeric cycloadduct. In the case of MVE, the pseudocyclic selectivity is attained by a thermodynamic control. This polar HDA reaction displays an endo stereoselectivity and a complete ortho regioselectivity. A comparative Relative Interacting Atomic Energy (RIAE) analysis of the two diastereomeric TS-4on and TS-6on indicates a highly likeness between them, which explains the low pseudocyclic selectivity under kinetic control.
Pengaruh Penataan Fisik Permukiman Kumuh terhadap Kualitas Hidup Masyarakat Kelurahan Kricak, Kecamatan Tegalrejo, Kota Yogyakarta
Authors: Wekawati Rokhana Tri , Suminar Lintang , Rahayu Murtanti Jani
Published: September 2024

Permukiman kumuh yang tidak terkendali dapat menyebabkan berbagai masalah bagi suatu kota, seperti wajah dan lingkungan perkotaan yang menjadi buruk dan kotor, susahnya penertiban bangunan, masalah keamanan, serta masalah kesehatan yang berdampak pada penurunan kualitas hidup masyarakat penghuni permukiman kumuh. Dalam hal ini, pemerintah membuat berbagai program untuk mengatasi permukiman kumuh yang ada di Indonesia. Kelurahan Kricak merupakan salah satu kelurahan prioritas program KOTAKU (Kota Tanpa Kumuh) di Kota Yogyakarta, dimana dilakukan penataan permukiman kumuh sejak tahun 2017. Penelitian ini bertujuan untuk melihat pengaruh penataan fisik permukiman kumuh terhadap kualitas hidup masyarakat di Kelurahan Kricak menggunakan metode penelitian kuantitatif dengan teknik analisis regresi logistik ordinal. Hasil dari penelitian ini menunjukkan bahwa penataan fisik pada komponen permukiman kumuh memiliki pengaruh kuat terhadap peningkatan kualitas hidup masyarakat. Kualitas hidup masyarakat di Kelurahan Kricak mengalami peningkatan baik dari aspek fisik dan lingkungan, keamanan, ekonomi maupun aspek sosial setelah dilakukan penataan permukiman kumuh di lingkungan tempat tinggalnya.