bluuebunny/crossref_metadata_2025 huggingface dataset:
The use of AI tools and their impact on the assessment of postgraduate courses in the technological field
Authors: Hernando-Castro Susana , López-Arquillo Juan Diego , Perea-Álvarez-de-Eulate Martín
Published: February 2025

This study analyzes the impact of using freely accessible generative AI in the evaluation of students in the Master's Program in Renewable Energies at Universidad Europea de Canarias, with the aim of proposing strategies to ensure that students maintain the necessary knowledge and technical skills. The case study focused on the "Renewable Energy Startups" module, worth 6 ECTS, where students completed practical activities with the assistance of AI tools.The evaluation of AI-generated results was conducted using the same rubric applied in a previous edition, when these tools were not yet available. Additionally, the AI-generated responses to exam questions based on the official syllabus were analyzed, and the time spent was compared with the minimum times outlined in the university's study plan.The findings show that, while AI can reduce the time needed to complete tasks, it is essential to redesign activities to integrate AI in an ethical and effective way. When approached correctly, AI can become a tool that enhances learning, improving students' technical skills without compromising the depth of knowledge.
A Study on the Vibration and Noise Reduction of Scrolling-Type Electric Compressor for Electric Vehicles
Authors: KIM ChaeSil , Ha NeungGyo
Published: February 2025

In this study, the causes of vibration and noise reduction occurring in electric compressors for electric vehicles are analyzed and a reduction plan is proposed. First, the impact hammer modal of the electric compressor housing was measured and compared with the ANSYS modal analysis. As there was no significant difference between the modal analysis results and the impact hammer modal measurement results, the modal analysis was judged to be reliable. The noise measurement results showed that the main noise sources of the development were analyzed in the 600-800Hz band, 4,000-5,000Hz band, and 10,000Hz band. From the competitor's analysis of the housing structure and noise measurement results, the 10,000Hz band was able to reduce noise caused by changes in carrier frequency of the motor inverter, and the 4,000-5,000Hz band showed a significant effect by adjusting the clearance during discharge, and it was confirmed that noise in the 600-800Hz band could be reduced to some extent only by changing the housing structure such as rib and mounting reinforcement of the housing and thickness change.
An Open-Source Simulation for Compression Analysis of Corrugated Boards
Authors: Metar Mohmad-Akram , Fitas Ricardo
Published: February 2025

In the packaging industry, corrugated boards are widely used due to many factors like bio-biodegradability, high strength-to-weight ratio, and also ease of manufacturing. In this study, the finite element analysis of corrugated cardboards under the flat compression test was performed using the open-source FEA Software Salome-meca. The corrugated board consists of a flute sandwiched between the top and the bottom liner. The study was performed with the help of Python scripting in order to iteratively perform many studies by varying the geometric shape of the flute. The pressure distribution along the top and the bottom liner was analyzed. The load-deflection curve for the corrugated cardboard was also analyzed as a part of this study. The boundary condition and the loading condition were chosen in such a way as to correctly represent the situation in real-life flat crush test in the lab. The contact zone was identified a priori and defined during the preparation of the study. Finally, the Code-Aster (The solver utilized by the Salome-Meca) was used to solve the finite element solution to the problem.
Resilience Selection: A Grave Potential Bias in Clinical Trials
Authors: Watve Milind , P Shunyaka , Keskar Ashwini
Published: February 2025

Physiological and psychological resilience has important implications for health, disease and treatment. Resilience is shown to boost treatment compliance as well as response and thereby reduce mortality. We consider the possibility that individuals having lower resilience are more likely to discontinue treatment in response to side effects of a drug. In randomized control trials (RCT) if a greater proportion of individuals discontinue from the treatment group than the control group, the average resilience in the remaining treatment group would be greater. As a result, the frequency or severity of adverse outcomes in the treatment group will be smaller than the control even when the drug has no effect. This bias is more likely to be serious for drugs with more frequent and/or serious side effects such as the GLP 1RAs. We suggest testable predictions of the resilience selection bias hypothesis along with ways to quantify and correct for the bias in RCTs. Attempts to detect, measure and correct for the resilience selection bias should be considered necessary for realistic evaluation of drug action in a clinical trial.
Homocysteine and Stroke: A 30-Year Bibliometric Study Uncovering Research Trends and Future Directions
Authors: Wei Loo Keat , Menon Saras , Griffiths Lyn R.
Published: February 2025

Recent years have seen a rapid expansion in research examining the relationship between homocysteine and stroke. In this study, we conducted a comprehensive bibliometric analysis of 233 articles related to homocysteine and stroke, published over the past 30 years in the Web of Science Core Collection. Our findings reveal a significant global increase in research on homocysteine and stroke, with China emerging as a leader, contributing 39.9% of total publications. Employing advanced methodologies such as co-citation analysis, bibliographic coupling, keyword co-occurrence, and citation burst analysis, we identified key research themes and emerging trends within the field. Notably, the results indicate a shift in focus from viewing homocysteine solely as a biomarker to recognizing its potential role in stroke prevention and management. These insights provide a valuable roadmap for future research directions and clinical strategies aimed at enhancing stroke prevention and improving patient outcomes.
Short-Term Changes of Vegetation and Soil Properties in Scots Pine (Pinus sylvestris L.) Plantations in Northern Mongolia
Authors: Nyam-Osor Batkhuu , Byambadorj Ser-Oddamba , Bayasgalankhuu Lyankhua , Ganbat Byambaa , Sukhbaatar Gerelbaatar , Um Tae-Won
Published: February 2025

This study looked at the impact of planting year differences on vegetation and soil parameters in Pinus sylvestris plantation forests in northern Mongolia. Tujiin nars region has three study sites: 18- to 20-year-old plantation forests planted in 2003, 2004, and 2005, as well as natural regeneration stand, natural forest, and steppe area. Three plots with distinct plantation stand types were constructed at each location to investigate changes in vegetation and soil attributes. Species richness, total coverage, and biomass accumulation were significantly higher in the oldest plantation (2003). This is consistent with the results, where BBS (2003 plantation) had the highest species richness (32 species), plant coverage (58.5%), and above-ground biomass (1159.6 g m2). Soil pH across plantations, with steppe and forest edge soils being alkaline and plantation soils slightly acidic. This matches the results, where soil pH ranged from 6.52 to 7.41, with plantations being slightly acidic. Available nitrogen (3.16 mg kg-1), soil organic carbon (10.1 g kg-1), and carbon stock (9.16 Mg ha-1) were higher in top soil and decreased by depth of profile and differed in plantations by year-of-planting. Furthermore, the change in understory vegetation was significantly correlated with soil moisture, fertility, and species composition was driven by over story density and crown parameters.
Pneumonia-Related Mortality in the Elderly: A Focus on ICU Outcomes and Risk Factors
Authors: ARI Maşide , Haykır Solay Aslı , Ozdemir Tarkan , Yıldız Murat , Menteş Oral , Tüten Ömer Faruk , TETİK MANAV Hüsra , Celik Deniz , Didik Melek , Doğanay Güler Eraslan , Ari Emrah , Usul Eren
Published: February 2025

Objectives: Individuals aged 80 and above, classified as the oldest old, are a growing population frequently requiring intensive care unit (ICU) admissions due to pneumonia. The disease in this group is complicated by comorbidities, immune dysfunction, and antibiotic-resistant infections. This study aimed to identify factors influencing mortality in elderly ICU patients. Materials and Methods: This retrospective study included 135 patients aged 80+ diagnosed with pneumonia in the ICU. Demographic data, clinical findings, laboratory results, and outcomes were analyzed. APACHE-II and SOFA scores were calculated upon admission. One-month in-hospital mortality was the primary endpoint, and predictors of mortality were examined. Results: The average age was 86.87, with a 39.2% mortality rate. APACHE II and SOFA scores were strong predictors of mortality. Factors associated with increased mortality included hemodialysis(p<0.001), invasive mechanical ventilation(p<0.001), low albumin(p=0.006), high procalcitonin(p=0.003), Neutrophil Percentage/Albumin Ratio (NPAR)(p<0.001), urea (p<0.001), and creatinine(p=0.010). Chronic Obstructive Pulmonary Disease (COPD) emerged as an independent risk factor. Conclusions: Mortality in elderly pneumonia patients is multifactorial. APACHE II, SOFA scores, and markers such as NPAR and COPD significantly affect outcomes. These findings underscore the importance of strategies to prevent organ dysfunction, monitor nutritional status, and manage infections in this vulnerable population.
Exploring Students’ Attitude Toward COVID-19 Vaccination
Authors: Barrios Marvien Maraggun
Published: February 2025

This study aimed to investigate students' attitudes toward COVID-19 vaccination measures by evaluating their demographic characteristics, vaccination status, and willingness to be immunized. Conducted at a State College in North Cotabato, Philippines, with a sample of 462 students from various year levels, the research utilized descriptive statistics and Binary Logistic Regression (BLR) for data analysis. The findings revealed that 387 respondents were young adults, predominantly female, and mostly freshmen. While 85% of the students had not been vaccinated, 65% expressed a willingness to receive the vaccine. The study highlighted that students generally perceived themselves as vulnerable to COVID-19 and acknowledged its severe impact. They also demonstrated confidence in the vaccine's ability to prevent the disease and viewed vaccination as a means to protect others and alleviate their fear of COVID-19-related illness. Additionally, it was found that students' beliefs about their susceptibility and the severity of COVID-19 significantly influenced their willingness to be vaccinated, with an effect size of 2.60%. This indicates that those who perceive themselves as more at risk are more likely to be willing to get vaccinated. These findings emphasize the need to address individuals' perceptions of risk and severity in shaping their attitudes toward vaccination. Therefore, it is recommended that the government intensify its information campaigns, focusing on enhancing community understanding of susceptibility and severity to improve public health policies and increase vaccination uptake.
Ancient Maroon Rice Songs Suggest Secret Rice Cultivation During Slavery in Suriname
Authors: Van Andel Tinde , Pinas Nicholaas
Published: February 2025

During slavery, music has often been used as a tool to convey secret messages. Songs of enslaved Africans have been documented extensively for the US, but less so for other plantation societies in the Americas. Here we discuss two versions of a work song known by some Maroon rice farmers in Suriname and French Guiana. While the cryptic lyrics are about mamoo going away to return next year or mamoo being killed and buried, these songs communicate that rice was being harvested or sown. They probably originated on a plantation in Suriname, where the enslaved secretly grew rice in their own food plots to plan their escape or to exchange with runaways hiding behind plantations. The use of using at least two different African terms for rice (mamoo and saka) reflects their ingenuity to communicate with each other in spite of linguistic differences and also indicates knowledge about rice that predated their transatlantic voyage, which confirms the African agency in rice cultivation in the Americas. Ancient songs about Maroon agriculture remain largely undocumented and are in danger of getting lost, but reveal an unwritten history of slavery and the successful struggle of the Maroons for freedom.
Combatting IT Industry Burnouts with Centralized AI Monitoring of Work Patterns
Authors: Barnabas Barnty , Marvelous Olatunji
Published: February 2025

In recent years, the IT industry has experienced a significant rise in burnout rates, primarily driven by the high demands, long working hours, and continuous pressure on employees to meet deadlines and targets. This article explores the potential of centralized AI monitoring systems to combat burnout by tracking and analyzing work patterns in real-time. By leveraging advanced machine learning algorithms, AI can detect early signs of burnout through the analysis of key indicators such as task completion rates, work hours, stress levels, and communication patterns. Centralized systems can provide managers and team leaders with actionable insights, enabling them to intervene proactively, adjust workloads, and implement wellness initiatives. This approach not only promotes healthier work environments but also ensures better work-life balance, leading to improved employee retention and productivity. The paper discusses the benefits, challenges, and ethical considerations of integrating AI-driven monitoring systems within organizations, and how such technologies can be a key component in reshaping the future of work in the IT industry.
Behaviors of Shelter Dogs During Harnessing and Leash Walks: Prevalence, Demographics, and Length of Stay
Authors: McGuire Betty , Guy Bailey , Garland Miles , Jackson Alexandra
Published: February 2025

Length of stay is an important metric for shelters, and studies have identified physical characteristics of dogs, and some behaviors, that predict length of stay. Although many shelters include leash walks when introducing dogs to potential adopters, it is unknown whether behaviors during harnessing and walking influence length of stay. During 707 walks of 120 dogs at a New York shelter, we recorded excitable behaviors, such as jumps on, grabs the leash, and pulls on the leash, whose measures of prevalence were largely unknown for shelter dogs. We also examined whether dog demographic characteristics predicted behaviors and whether behaviors predicted length of stay. During harnessing, jumps on had the highest prevalence (45%) and during walking, pulls on the leash (86%). Although we expected measures of prevalence to be higher for dogs in shelters due to limited space and exercise, we found that measures were similar to or lower than reported for dogs in homes, possibly because dogs in shelters are less comfortable with their handlers. Dog age was the most common demographic predictor of behaviors, with jumps on and total pulls/walk decreasing with age. Grabs the leash predicted length of stay, with longer stays for dogs that displayed this behavior. These two findings suggest that it would be beneficial for shelter staff and volunteers to focus training efforts on younger dogs, and especially those that grab the leash.
Evidence for Cognitive Spatial Models from Ancient Roman Land-Measurement
Authors: Riggsby Andrew M.
Published: February 2025

Influential studies in the history of cartography have argued that map-like representations of space were (virtually) unknown in the Classical Mediterranean world and that the cause of this was an absence of underlying cognitive maps. That is, persons in that time/place purportedly had only route/egocentric type mental representations, not survey/allocentric ones. The present study challenges that cognitive claim by examining the verbal descriptions of plots of land produced by ancient Roman land-measurers. Despite prescription of a route-based form, actual representations persistently show a variety of features which suggest the existence of underlying survey-type mental models and the integration of those with the route-type ones. This fits better with current views on interaction between types of spatial representation and of cultural difference in this area.
Efficacy Study: Comparison of an Insomnia Therapy Developed for Shift Workers with the Standard Treatment (Cognitive Behavioral Therapy for Insomnia) in an Online Group Setting: RCT with an Active Control Group, Completer Analysis
Authors: Grünberger Tanja , Höhn Christopher , Schabus Manuel , Pletzer Belinda Angela , Laireiter Anton-Rupert
Published: February 2025

Background. Shift workers are at increased risk for insomnia or shift work disorder. The standard treatment (cognitive behavioral therapy for insomnia) is challenging for this group. Although there are new promising approaches, they are still considered inadequate. Aims and objectives. For the present study, a customized treatment was developed in which interventions on regularity were replaced by methods to treat anxiety or depression, for example. This approach also aims to shift the focus away from disturbed sleep. Methods. Linear mixed models were used (RCT, completer analysis) to compare two active conditions (standard vs. tailored therapy) at three measurement points (pre-, post-treatment, 3-month follow-up). Primary outcomes are sleep quality, insomnia severity, sleep onset latency, and total sleep time. Secondary outcomes are anxiety, depression, tension, concern, emotional instability. Non-inferiority or equivalence tests were also performed. Results. The newly developed treatment is equivalent to standard care. Both resulted in significant and stable improvements in all variables. Thus, only the main effect across measurement points is significant, not the condition or the interaction. Outlook. Future studies should consider attrition and compliance. The treatment should be revised based on these results. The approach of improving sleep with implicit interventions should be pursued further, as it seems well suited to shift workers.
Enhancements to the Insufficient Ramping Resource Expectation (IRRE) for Energy-Constrained Power Systems with Application to the Brazilian Electricity Grid
Authors: Vardiero Pedro , Pereira Jr. Amaro Olimpio , Diuana Fabio A. , Morais Rafael
Published: February 2025

The increasing integration of variable renewable energy sources (VRES) into modern power systems presents significant challenges in ensuring operational flexibility, highlighting the need for robust methodologies to evaluate and ensure system reliability. The Insufficient Ramping Resource Expectation (IRRE) has emerged as a critical metric for quantifying the probability of ramping deficiencies in power systems. However, its traditional application, designed primarily for capacity-constrained systems, may not fully capture the operational dynamics of energy-constrained systems, such as those dominated by hydropower generation. This study critically reviews the IRRE methodology and proposes enhancements to incorporate additional constraints, including seasonal and monthly hydrological variability and operational reserve requirements, to better reflect the flexibility limitations in energy-constrained systems. A case study of the Brazilian electricity system evaluates these modifications by comparing traditional and enhanced IRRE results across varying scenarios, including higher VRES penetration. The findings reveal significant increases in ramping insufficiencies when additional constraints are considered, particularly in subsystems with constrained hydropower resources. By integrating more realistic and specific operational constraints, this study advances IRRE's applicability as a planning tool and to guide policy decisions, ensuring enhanced system reliability in the face of escalating renewable energy integration specially into energy-constrained systems.
Histochemical and Immunohistochemical Evaluation of the Effects of a Low Input Diet on Different Chicken Breeds
Authors: Fonsatti Elisa , Bortoletti Martina , Birolo Marco , Bordignon Francesco , Xiccato Gerolamo , Trocino Angela , Bertotto Daniela , Vascellari Marta , Radaelli Giuseppe , Ballarin Cristina
Published: February 2025

Reducing the environmental impact of poultry farming aligns with the European Green Deal’s goal of climate neutrality and sustainable food production. Local chicken breeds and low-input diets are promising strategies to achieve this. This study evaluated the effects of the diet (standard vs. low-input, formulated with reduced soybean meal in favour of local ingredients) on gut health in fast-growing chickens (Ross 308), local breeds (Bionda Piemontese. BP; Robusta Maculata, RM), and their crosses with Sasso (SA) hens (BP×SA, RM×SA). Histological samples from the jejunum were collected at slaughter (47 days for Ross 308, 105 days for others). Jejunal morphology was assessed focusing on villi height, crypt depth, goblet cell density, and immune markers (CD3+ and CD45+ cells). Local breeds, particularly RM, exhibited superior villus height-to-crypt depth ratios, related to better nutrient absorption compared to fast-growing genotypes. Ross chickens had higher goblet cell densities, reflecting greater sensitivity to environmental stress. The low-input diet reduced villi height and villus-to-crypt ratio but tended to increase CD3+ cell density. These effects may be ascribed to the replacement of soybean with fava beans and its antinutritional factors. These findings highlight the resilience of local breeds to dietary changes, supporting their suitability for alternative poultry production systems.
ChatGPT in PhD Mentoring: Exploring the Potential of Generative AI for Academic Guidance and Sustainable Educational Practices
Authors: Iatrellis Omiros , Bania Areti , Samaras Nicholas , Kosmopoulou Ioanna , Panagiotakopoulos Theodor
Published: February 2025

While the applications of Generative AI in education and academic research are growing, its potential for supporting PhD-level mentoring and academic counseling remains underexplored. This exploratory study evaluates the relevance and appropriateness of ChatGPT-generated recommendations for PhD research, with a particular emphasis on its potential to promote sustainable and resource-efficient practices in doctoral education. Using a real-world case study on disaster risk management, input prompts were designed with varying levels of contextual detail, including naïve prompts, keywords selected by supervisors, keywords generated by ChatGPT, and topic-specific concepts derived from literature on advanced academic frameworks. The outputs were evaluated by a panel of five external academic experts who assessed their relevance, depth, and applicability to the research objectives. Further analysis explored tailored prompts designed to align with distinct research pathways. The results demonstrated that outputs based on topic-specific concepts received the highest appropriateness ratings, with strong interrater agreement. Naïve prompts also produced relevant outputs, while keyword-based prompts were rated lower, often failing to integrate core elements into cohesive recommendations. Tailored prompts reflecting specific research pathways were consistently rated as highly actionable and contextually grounded, highlighting ChatGPT’s ability to align with academic goals and contribute to sustainable educational innovation. These findings underscore ChatGPT's potential to complement PhD supervision by offering structured guidance, actionable insights, and timely feedback, paving the way for the "tripartite mentoring model," where AI collaborates with supervisors and students to address complex academic challenges in a sustainable and impactful manner.
[Act on Integrated Support for Community Care Including Medical Cure and Nursing Care] and the Role of Tertiary Hospital in the Republic of Korea
Authors: Park Byeungtae , Kim Pyeong-Man , Kim Chul-Min , Choi Chang-Jin , Shin Hyun-Young
Published: February 2025

The Republic of Korea is transitioning into a super-aged society. In response to this demographic shift, the Act on Integrated Support for Community Care Including Medical Cure and Nursing Care was passed in 2024, with full implementation scheduled for 2026. This law aims to integrate medical and long-term care services in local communities. Given the growing demand for elderly care, tertiary hospitals are expected to play a key role in the evolving healthcare system, bridging hospital-based care and community-based support. Seoul St. Mary’s Hospital, a major tertiary hospital in Korea, formed a multidisciplinary task force to explore its potential contributions to integrated care for an aging society. This study discusses the roles of tertiary hospitals in managing integrated care, particularly in the context of transitional care, home medical services, and the establishment of home medical centers. A key aspect of this role is the involvement of family medicine departments, which are central in coordinating patient care between tertiary hospitals and local communities. The study highlights the importance of collaboration between medical, caregiving, and social welfare professionals, and the need for policy changes to support these efforts. It also explores the potential of digital healthcare, including telemedicine and remote patient monitoring, as key tools for facilitating “aging in place.” The findings emphasize the need for a holistic, patient-centered approach to healthcare that ensures continuity of care, enhances the role of tertiary hospitals, and fosters a more sustainable healthcare model for Korea’s aging population.
Evaluating the Performance of Hydrological Models for Flood simulation in Wangchu River Basin, Bhutan
Authors: Dahal Damudar , Kojima Toshiharu
Published: February 2025

Flood has become a major hazard globally, and Bhutan with its steep terrain and erratic rainfall has caused significant economic damages in recent years. Given these challenges, there is a lack of accurate flood prediction and management strategies. This study, there-fore, evaluates three hydrological models—Integrate Flood Analysis System (IFAS), Hy-drologic Engineering Centre Hydrologic Modeling System (HEC-HMS), and Group on Earth Observation Global Water Sustainability version 1 (GEOGloWS)—and identifies the most suitable model for simulating flood events in Wangchu River Basin of Bhutan. Fur-ther, it also examined the model performance for Large and Small Basins using Nash-Sutcliffe Efficiency (NSE), Percentage Bias (PBIAS) and Peak Flow Error (PFE) met-rics. Overall, the GEOGloWS model demonstrated the highest accuracy in simulating flood in large basin, achieving the NSE, PBIAS and PFE values of 0.93, 3.21 and 4.48, re-spectively. In small basin, the IFAS model showed strong performance with an NSE value of 0.84, although the discharge was underestimated. The GEOGloWS model provides simulated discharge but need to be bias corrected before use. The calibrated parameters can be used in IFAS and HEC-HMS models to simulate flood in Wangchu Basin and adjacent basins having similar geographical characteristics for future studies.
Unmasking Nuances Affecting Loneliness: Using Digital Behavioural Markers to Understand Social and Emotional Loneliness in College Students
Authors: Qirtas Malik Muhammad , Zafeiridi Evi , White Eleanor Bantry , Pesch Dirk
Published: February 2025

Loneliness is a global issue which is particularly prevalent among college students, where it poses risks to mental health and academic success. Chronic loneliness can manifest in two primary forms: social loneliness, which is defined by a lack of belonging or a social network, and emotional loneliness, which comes from the absence of deep, meaningful connections. Differentiating between these forms is crucial for designing personalized and targeted interventions. Passive sensing technology offers a promising, unobtrusive approach to detecting loneliness by using behavioural data collected from smartphones and wearables. This study investigates behavioural patterns associated with social and emotional loneliness using passively sensed data from a student population. Our objectives were to (1) identify behavioural patterns linked to social and emotional loneliness, (2) evaluate the predictive power of these patterns for classifying loneliness types, and (3) determine the most significant digital markers used by machine learning models in loneliness prediction. Using statistical analysis, machine learning, and SHAP-based feature importance methods, we identified significant differences in behaviours between socially and emotionally lonely students. Specifically, there were distinct differences in phone use and location-based features. Our machine learning analysis shows a strong ability to classify types of loneliness accurately. The XGBoost model achieved the highest accuracy (78.48%) in predicting loneliness. Feature importance analysis found the critical role of phone usage and location-based features in distinguishing between social and emotional loneliness.
Revolutionizing Peer Review: A Comparative Analysis of ChatGPT and Human Review Reports in Scientific Publishing
Authors: Shopovski Jovan , Mohdali Raihana , Marolov Dejan
Published: February 2025

ChatGPT-4 and other large language models (LLMs) and their use in academic writing have raised questions regarding their capacity to facilitate the peer review process. This research article compares AI-generated peer review reports (using ChatGPT-4 with tools) with traditional review reports generated by humans. The review reports were received for 198 manuscripts submitted to the European Scientific Journal (ESJ) between January and September 2024. Each manuscript underwent a parallel evaluation process. First by human reviewers of the journal and by ChatGPT-4 with tools paid version afterward. However, each manuscript received review reports from at least two human reviewers and only one AI-generated review report. Both review types used the ESJ’s standardized evaluation form. The ChatGPT-4 was prompted to review the papers objectively and critically. Statistical analyses were conducted to compare the grades of different parts of the manuscripts, recommendation distributions, and consistency between the AI and human review reports. Kolmogorov-Smirnov test; Pearson Chi-Square test, Mann-Whitney U test; and Cohen's kappa test were used to analyze the data. Results showed that ChatGPT-4 reviewers consistently awarded higher grades and were less rigorous than the human reviewers. The ChatGPT-4 review reports mostly recommended minor revisions and have never recommended rejection of a manuscript. On the other hand, human reviewers demonstrated a more balanced distribution of recommendations, including stricter score evaluations. However, a lack of agreement between the human review reports was registered. While LLM tools can enhance the efficiency of the peer review process, their ability to uphold rigorous academic standards remains limited. Editors who use LLM tools as reviewers have to remain vigilant and not rely their decisions solely on LLM-generated reports. The existing version of ChatGPT-4 is not trained in peer review and cannot replace human expertise in peer review. However, it can be used as an assistant that under human oversight can provide useful comments and recommendations for content improvement of the manuscripts. Future research should focus on LLM tools trained for peer review in various academic fields as well as on the ethical frameworks for LLM integration in peer review.
Overview of Roles of Novel Components in the Regulation of DNA Damage Repair in BRCA1-deficient Cancers: An Update
Authors: Nguyen Nhat , Tran Tien Manh
Published: February 2025

Cancers that are arising from germline mutations of the breast cancer associated gene 1 (BRCA1), which is a crucial player of homologous recombination (HR) DNA repair, are vulnerable to DNA damaging agents such as platinum and PARP inhibitors (PAR-Pi). Increasing evidence suggests that BRCA1 is an essential driver of all phases of the cell cycle, thereby maintaining orderly steps during cell cycle progression. Specifically, loss of BRCA1 activity causes the S-phase, G2/M, spindle checkpoints and centrosome duplication to be dysregulated, thereby blocking cell proliferation and inducing apop-tosis. In vertebrates, loss of HR genes such as BRCA1 and/or BRCA2 is lethal since HR is prerequisite for genome integrity. Thus, cancer cells utilize alternative DNA repair pathways such as non-homologous end joining (NHEJ) to cope with loss of BRCA1 function. In this review, we attempt to update and discuss how these novel compo-nents are crucial for regulating DNA damage repair (DDR) in BRCA1-deficient can-cers.
Variability Between Radiation-Induced Cancer Risk Models in Estimating Oncogenic Risk in Intensive Care Unit Patients
Authors: Quaia Emilio , Zanon Chiara , Torchio Riccardo , Dughiero Fabrizio , De Monte Francesca , Paiusco Marta
Published: February 2025

Purpose: To compare the oncogenic risk related to radiation exposure in patients frequently exposed to ionizing radiation for diagnostic purposes, specifically ICU patients, according to different risk models, including the BEIR VII, ICRP 103, and US EPA models.
Methods: This was an IRB-approved observational retrospective study. Seventy-one patients (58 male, 13 female; median age, 66 years; interquartile range [IQR], 71-56 years) admitted to the CU who underwent x-ray examinations between October 1, 2021, and February 28, 2023 were included. For each patient, the cumulative effective dose during a single hospital admission was calculated. Lifetime attributable risk (LAR) was estimated based on the BEIR VII, ICRP 103, and US EPA risk models to calculate additional oncogenic risk related to radiation exposure. The Friedman test repeated-measures analysis of variance was used to compare risk values between different models. The intraclass correlation coefficient (ICC) was used to assess the consistency of risk values between different models.
Results: Different organ, leukemia, and all-cancer risk values estimated according to different oncogenic risk models were significantly different, but the intraclass correlation coefficient revealed a good (>0.75) or even excellent (>0.9) agreement between different risk models. The ICRP 103 model estimated a lower all-cancer (median 69.05 [IQR 30.35-195.37]) and leukemia risk (8.22 [3.02-27.93]) compared to the US EPA (all-cancer: 139.68 [50.51-416.16]; leukemia: 23.34 [3.47-64.37]) and BEIR VII (all-cancer: 162.08 [70.6-371.40]; leukemia: 24.66 [12.9-58.8]) models.
Conclusions: Cancer risk values were significantly different between risk models, though inter-model agreement in the consistency of risk values was found to be good, or even excellent. The ICRP 103 risk model estimated the lowest all radiation-induced cancer and leukemia risk.
Evaluation of the Spatio-temporal Variation of Extreme Cold Events in Southeastern Europe Using an Intensity-duration Model and Excess Cold Factor Severity Index
Authors: Malcheva Krastina , Neykov Neyko , Bocheva Lilia , Stoycheva Anastasiya , Neykova Nadya
Published: February 2025

Recent studies have revealed a rise in extreme heat events worldwide, while extreme cold has shown a decline. It is highly likely that human-induced climate forcing will double the risk of severe heat waves by the end of the century. Although extreme heat is expected to have greater socioeconomic impacts than cold extremes, the latter contributes to a wide range of adverse effects on the environment, various economic sectors and human health. People can somewhat adapt to extreme temperatures when they experience repeated heat and cold waves, but these extreme events can have more severe health consequences when they occur earlier in the respective season or last unusually long. A few studies have re-cently analyzed extreme heat events on a European scale using the excess heat factor (EHF) that accounts for short-term acclimatization. This approach is also analogously ap-plicable to extreme cold events by employing the excess cold factor (ECF). The present re-search aims to evaluate the spatiotemporal variations of extreme cold events in South-eastern Europe through the intensity-duration model developed for quantitative assessment of cold weather in Bulgaria. We demonstrate the suitability of indicators based on minimum temperature thresholds to evaluate the severity of extreme cold events in the period 1961–2020 both at individual stations and Köppen’s climate zones using daily temperature data from 70 selected meteorological stations. The ability of the used intensity-duration model to estimate the severity of extreme cold events has been compared with the ECF severity index on a yearly basis.
Competitiveness Strategies of Key Small Modular Light Water Reactor Projects
Authors: Pieńkowski Ludwik
Published: February 2025

It is widely recognized that economies of scale enhance the competitiveness of large-scale nuclear reactors compared to small modular light-water reactors (SMRs). As such, choosing an appropriate strategy to enhance competitiveness is crucial for the future of SMRs. Their development is still in the early stages, and among the leading projects, two distinct approaches to technical innovation can be observed. In some projects, technical innovations are rejected because they are perceived as triggers for risky, costly, and long-term processes. In other projects, technical innovations are viewed as a means to achieve substantial cost reductions. Currently, it is challenging not only to identify the most promising SMR projects but also to determine which approach to technical innovation will ultimately be more effective. First, it is worth examining how leading SMR projects have improved their competitiveness. Additionally, even if light-water SMRs are not deployed, it is likely that some of their innovative solutions will be incorporated into other advanced nuclear power plant designs and potentially beyond the nuclear industry.
Toward In-Vivo Cancer Detection: X-Ray Scattering on Thick Phantom Samples
Authors: Kubytskyi Viacheslav , Khonkhodzhaev Masroor , Tanaka Aika , Nguyen Audrey , Lazarev Alexander , Aram Byron , Rogers Keith , Mourokh Lev , Lazarev Pavel
Published: February 2025

As the number of new breast cancer cases grows around the world, there is an unmet need for fast, accurate, and low-cost methods of early cancer detection. It was previously shown that X-ray diffraction on lipid molecules can provide the necessary structural biomarker. However, these measurements were performed on small ex-vivo samples, and to ensure the progress to in-vivo diagnostics, the approach should be extended to larger tissues. We use the phantom fat samples to establish such a procedure. In the obtained X-ray diffraction patterns, we observe the characteristic features for the inter-fatty-acid molecular distance. The large size of the samples led to the peak broadening, but the features remain visible up to 10 centimeters in thickness. The experimental data is in excellent agreement with the Monte-Carlo simulations based on the form factors obtained from the small samples. Our results usher the way for in-vivo monitoring of structural biomarkers of breast cancer.
Electrochemical Analysis and Inhibition Assay of Immune-Modulating Enzyme, Indoleamine 2,3-Dioxygenase
Authors: Mie Yasuhiro , Mikami Chitose , Yasutake Yoshiaki , Shigemura Yuki , Yamashita Taku , Tsujino Hirofumi
Published: February 2025

An accurate and rapid analysis of human indoleamine 2,3-dioxygenase (hIDO) is crucial for the development of anticancer pharmaceuticals because of the role of hIDO in promoting tumoral immune escape. However, the conventional assay of hIDO is limited by interference from reductants, which are used to reduce the heme iron to begin the hIDO catalytic reaction. Herein, we report a direct electrochemical method to control the redox state of the heme iron and the electrochemical investigation of hIDO. Although the conventional gold electrode did not offer a visible signal for the electron transfer between the electrode and hIDO, the anodized nanostructured gold electrode exhibited a clear nonturnover electrochemical response in an Ar atmosphere. In the presence of oxygen, the bioelectrocatalytic current for the reduction of oxygen, which competes with the oxidation of tryptophan upon the addition of the substrate, was observed, confirming an electrochemically driven hIDO reaction. A well-known inhibitor of hIDO, epacadostat, hindered this catalytic signal according to its concentration, demonstrating the rapid evaluation of its inhibition activity for the hIDO reaction. Through an in silico study using the proposed electrochemical assay system, we discovered a strong inhibitor candidate with a half-maximal inhibitory concentration of 10 nM, similar to that of epacadostat. This suggests the usefulness of the proposed system in drug discovery for hIDO and kynureine pathway-targeted immunotherapy.
Vitacrystallography: Appearance and Development of Cancer-Induced Structural Biomarkers in a Mouse Model
Authors: Avdieiev Oleksii , Denisov Sergey A. , Ajeer Ash , Adams Lois , Greenwood Charlene , Nesbitt Heather , Thomas Keith , Rogers Keith , Solovyeva Olga , Mourokh Lev , Lazarev Pavel
Published: February 2025

Structural biomarkers determined by X-ray scattering of the tissues can complement conventional diagnostics and provide a pathway for early detection of diseases. In the present study, mouse models were utilized to observe the progress of prostate cancer. We induced cancer in the left lobe of the mouse prostate, whilst the right lobe was left uninoculated. The mice were sacrificed at several time points (Days 2, 4, 7, and 16 after inoculation), and the lobes were analyzed using X-ray scattering. Control samples were also collected from healthy mice sacrificed at the same time points. This investigation revealed that the ratio between the X-ray scattering peaks associated with the lipids and water can serve as a structural biomarker of cancer, and this biomarker develops as the tumor advances. The obtained cancer trajectory can serve as a baseline for the determination of the disease stage, and the biomarker movement along the trajectory can be evidence of the healing or disease progression.
Longyearbyen Lagoon (Spitsbergen): Gravel Spits Movement Rate and Mechanisms
Authors: Marchenko Nataliya , Marchenko Aleksey
Published: February 2025

Understanding lagoon behavior is crucial for both scientific research and engineering, especially in delicate Arctic environments. Lagoons are vital to coastal areas, often bol-stering infrastructure resilience. Since Spring 2019, we've monitored the Longyearbyen lagoon (Spitsbergen), vital for coastal erosion defense and serving as a natural laboratory. The location's well-developed infrastructure and accessible logistics make it an ideal testing site available at any time. It can be used for many natural scientific studies.
Spanning 400x50m, the lagoon continually shifts due to waves and tides, with a maximum tidal range of 2m. This article focuses on gravel spit movement, accelerating in recent years to several meters monthly. Through methods like aerial and satellite images, laser scanning and hydrodynamic measurements, we've delineated processes, rates, and mechanisms behind this movement. Bed-load transport along the spit, coupled with gravel slides, primarily drives expansion and lagoon growth. Modeling these processes aids in forecasting lagoon system development, crucial for informed management and engineering decisions in Arctic coastal regions.
Efficacy of Quadratus Lumborum Block for Postoperative Pain Management in Single-Port Total Laparoscopic Hysterectomy: A Randomized Observer-blinded Controlled Trial
Authors: Chung Jihyun , Bang Seunguk , Lee Sangmook , Lee Youngin , Shin Hyun-Jung , Park Yoonji
Published: February 2025

Background and Objectives: Quadratus lumborum block (QLB) is a regional anesthesia technique widely utilized in multimodal analgesia strategies for abdominal surgeries. While a few studies have investigated its efficacy in multiport total laparoscopic hysterectomy (TLH), its effectiveness in single-port TLH remains uncertain. This study aimed to evaluate whether QLB reduces opioid consumption and postoperative pain in patients undergoing single-port TLH. Materials and Methods: This randomized, controlled, observer-blinded trial included 64 patients undergoing elective single-port TLH. Participants were randomly allocated to either the QLB group (n = 27) or the control group (n = 29). QLB was performed bilaterally under ultrasound guidance after surgery. The primary outcome was cumulative fentanyl consumption within 24 hours postoperatively. Secondary outcomes included pain scores at predefined intervals, time to first opioid demand, the incidence of postoperative nausea and vomiting (PONV) and other complications. Results: The 24-hour cumulative fentanyl consumption, which was the primary outcome, did not differ significantly between the QLB group 470 [191.6, 648.1] mcg and the control group 342.8 [220, 651] mcg (P = 0.714). Additionally, cumulative fentanyl consumption at other time points, including 2h, 4h, 8h, 12h, 32h, and 48h, as well as in the PACU, also showed no significant differences between the two groups. Pain scores measured at these time points, along with the time to first bolus on demand, similarly showed no significant differences between the groups. Conclusions: QLB did not significantly reduce opioid consumption or pain scores in patients undergoing single-port TLH.
Advancing Vision-Language Models with Generative AI
Authors: Vats Arpita , Raja Rahul
Published: February 2025

Generative AI within large vision-language models (LVLMs) has revolutionized multimodal learning, enabling machines to understand and generate visual content from textual descriptions with unprecedented accuracy. This paper explores state-of-the-art advancements in LVLMs, focusing on prominent models such as CLIP for cross-modal retrieval, Flamingo for few-shot video understanding, BLIP for self-supervised learning, CoCa for integrating contrastive and generative learning, and X-CLIP for enhancing video-text retrieval. These models demonstrate the flexibility and scalability of LVLMs across a variety of applications. Through an evaluation based on metrics such as image generation quality, perceptual loss, and CLIP score, we provide insights into their capabilities, limitations, and opportunities for future enhancement. As generative AI continues to evolve, this analysis underscores the importance of developing scalable, efficient multimodal models capable of addressing real-world challenges with minimal fine-tuning.
The Phenomenon of Silicon Plasma Outpacing Air Filamenta-Tion in Tightly Focused Femtosecond Laser Fields
Authors: Dou Xian-an , Li Xin , Ye Qing , Xie Yuntao
Published: February 2025

In the field of femtosecond laser physics, a phenomenon has been discovered wherein silicon plasma appears earlier than air filaments in tightly focused femtosecond laser fields. This phenomenon exhibits an advance time of several picoseconds. Analysis of the results reveals that the disparity in ionization thresholds between silicon and the surrounding air is the primary cause of this phenomenon. Moreover, the temporal contrast of the femtosecond laser pulses influences the extent of the advance time. The findings provide valuable insights into the complex interactions between laser-plasma and laser-material interactions, and have implications for advancements in the laser precision machining, laser remote sensing, and related applications.