bluuebunny/crossref_metadata_2025 huggingface dataset:
Academic performance in children and young people with vision impairment: A comprehensive systematic review
Authors: Wang Siqi , Cheng Yiyuan , Sideropoulos Vasileios , Hayton Jessica
Published: December 2024

Closing the attainment gap for all children and young people (CYP) is vital. Yet, little is known about CYP with vision impairment (CYPVI). Our systematic review investigates academic performance amongst CYPVI, compared with sighted peers. Following the PRISMA guidelines, a systematic search across four databases identified 4,220 articles, of which seven met the inclusion criteria. Included articles were appraised using the Critical Appraisal Skills Programme checklist, achieving moderate to high quality. All study participants aged 6-18 years, had vision impairment(s) and/or blindness that could not be corrected with prescription lenses. Despite differences in research design, educational outcomes measured, and methodologies among the seven included studies, our review consistently highlighted that educational research is focused on reading and literacy skills, and for these two domains there is a significant disparity between CYPVI and their sighted peers. Our findings emphasise the persistent educational challenges that CYPVI face and identify the need for continuous support to reduce this attainment gap. We discuss the lack of research in other key academic areas, i.e., maths, and consider associated implications.
On modes of disease transmission and the hidden shape of pandemics: A review of Asymptomatic by Joshua Weitz
Authors: Ogbunugafor C. Brandon
Published: December 2024

The importance of asymptomatic transmission was a key discovery in our efforts to study and intervene in the COVID-19 pandemic. In Asymptomatic (Johns Hopkins University Press, 2024), Joshua Weitz uses this aspect of SARS-CoV-2 natural history to discuss many counterintuitive characteristics of the pandemic. In this essay, I engage the arguments in the book, and discuss why asymptomatic transmission is such a critical dimension to the study of infectious diseases. I explore ideas contained within Asymptomatic and connect them to related issues in evolutionary virology and disease ecology, including epistemic uncertainty and the evolution of virulence. Further, I comment on the broader messages in the text, including the gap between scientific knowledge and social understanding.
Network Approaches for Physical Activity and Mental Health Research
Authors: Huong Christopher , Bernstein Emily Ehrich , Curtiss Joshua , Kolar David R. , Brown Denver M. Y.
Published: December 2024

Physical activity has shown positive effects for depressive and anxiety disorders, and is considered as potentially remediating for other mental health problems. Nevertheless, the exact mechanisms of action, symptom-specific effects, and individual differences in treatment response to physical activity are not fully understood. The network approach to psychopathology facilitates studying how the symptoms of mental disorders are interconnected in a complex system, rather than arising from a single (latent) underlying cause as implied in conventional analytic methods. Including physical activity in these symptoms networks can advance understanding of the role physical activity plays across various mental health problems, such as symptom-specific effects and influences on symptom-symptom connections (i.e., network structure). We discuss actual and potential applications of adopting network approaches in research seeking to understand the relationships between physical activity and mental health problems using cross-sectional and (intensive) longitudinal data structures, as well as their limitations.
Fast and furious: the productivity effects of the geography of experienced internet speeds
Authors: Tranos Emmanouil , Kitsos Tasos , Wolf Levi John
Published: December 2024

The discussion about the productivity gains from digital technologies is almost as old as digital technologies themselves. From early futuristic approaches to the various forms of the productivity paradox, there are still open questions regarding if and how the internet can lead to positive economic effects as well as their spatial heterogeneity. The usual caveat to unpack this relationship is data about internet usage that is detailed enough to be linked both to economic outputs and places. We develop a multilevel modelling framework and combine firm-level microdata with novel internet speed microdata illustrating how connectivity has been experienced by end-users. Although it is not possible to directly observe the online activities of individuals, these data allow us to approximate business usage. Additionally, we can distinguish between upload and download speeds, which is important as these channels can support different internet functions (e.g. video streaming vs. synchronous communications). We then observe firms, their productivity, and other firm characteristics and estimate the firm productivity effects of broadband speeds after accounting for spatial effects and platial characteristics, which are also associated with the underpinning digital divides. We find that increases in a place's internet speeds can lead to higher firm productivity whilst the opposite holds for instability of internet speeds. These results vary by sector and firm characteristics. Our results have significant policy implications, highlighting the economic impact of high-speed internet infrastructure planning decisions and presenting policymakers with a clear efficiency vs. equity trade-off.
Leveraging AI to Improve Eligibility Verification and Fraud Detection in Health and Human Services Agencies (Public Sector)
Authors: Kamlakshya Tikhnadhi
Published: December 2024

Abstract: Artificial Intelligence (AI) is revolutionizing eligibility verification processes in Health and Human Services (HHS) agencies, offering significant improvements in efficiency and accuracy. This study examines the role of AI in streamlining operations, enhancing fraud detection, and optimizing resource allocation within HHS eligibility verification systems. By leveraging machine learning algorithms, AI can rapidly analyze vast datasets, cross-reference information with existing databases, and identify patterns that may indicate eligibility or potential fraud. The implementation of AI not only accelerates the decision-making process but also reduces human error, particularly in complex cases. Moreover, AI's ability to flag discrepancies for human review allows agencies to focus their resources on high-risk cases, potentially preventing fraudulent claims and ensuring that services reach those truly in need. This research highlights the transformative potential of AI in HHS eligibility verification and its natural progression towards more sophisticated fraud detection mechanisms, ultimately improving the integrity and effectiveness of social service programs.Keywords: Artificial Intelligence (AI), Government Public Sector, Health and Human Services (HHS), Salesforce, Apex, AWS, Fraud Detection.
Developing ALiF: A Systematic Protocol for Building and Validating an Artificial Intelligence Literacy Framework in Higher Education
Authors: Zary Nabil
Published: December 2024

Introduction: The rapid adoption of artificial intelligence (AI) in higher education demands systematic frameworks to develop AI literacy across diverse institutional stakeholders. Existing approaches often lack clarity, inclusivity, and progression pathways, limiting their effectiveness. This protocol outlines a methodology for creating the AI Literacy Framework (ALiF), a comprehensive model designed to address the needs of students, faculty, and staff in higher education.Methods: ALiF will be developed using a three-phase mixed-methods approach. Phase 1 involves a systematic literature review and expert consultation to design the initial framework. Phase 2 refines the framework through Delphi studies and stakeholder focus groups. Phase 3 validates the framework via expert evaluation and pilot implementation across three higher education institutions. Data collection includes 30 expert interviews, 24–30 focus groups, and quantitative and qualitative analysis of pilot outcomes.Expected Outcomes: The study will deliver (1) a validated AI literacy framework, (2) detailed progression pathways for diverse stakeholder groups, (3) implementation strategies tailored to higher education contexts, and (4) tools for assessing institutional readiness and literacy levels. Supporting outputs will include assessment instruments and toolkits for implementation.Significance: This protocol provides a foundation for institutions to systematically develop, implement, and assess AI literacy programs. Its multi-stakeholder focus and robust methodology contribute significantly to addressing gaps in existing research and practice. Potential limitations include resource-intensive implementation and the need for longitudinal validation.
Physiological Analytes and Callous-Unemotional Traits in Young People: A Systematic Review and Theoretical and Methodological Considerations
Authors: Goulter Natalie , Kaouar Silvana , Kimonis Eva
Published: December 2024

Burgeoning evidence supports multiple developmental pathways to antisocial behavior. However, a comprehensive mechanistic understanding is lacking, and insights into the development of different presentations might be gained by investigating analyte concentration levels of physiological systems related to socioaffective functioning and adverse experiences. Thus, we aimed to systematically review correlates of hypothalamic-pituitary-adrenal steroid hormones, hypothalamic-pituitary-gonadal steroid hormones, neurohypophysial peptide hormones, autonomic nervous system enzymes, and inflammatory proteins in association with callous-unemotional (CU) traits (and the affective dimension of psychopathy) in samples of young people (≤18 years old). Given established variability in physiological activity across developmental stage and biological sex, we further aimed to assess evidence of development and sex differences. Finally, we aimed to analyze methodologies applied to test analyte levels. In total, we identified 32 articles for summary, across which seven distinct analytes were identified: cortisol, testosterone, oxytocin, dehydroepiandrosterone, estradiol, α-amylase, and C-reactive protein. Overall, these studies provided some support for allostatic load, although findings were mixed, including for cortisol that was the most widely studied analyte. Studies used a wide variety of methodological approaches, with scant research on inflammatory markers. We discuss how two key factors might contribute to the lack of clarity: diverse conceptualization of adversity (e.g., acute v. chronic, proximate v. distal) across studies, and limited consideration of primary and secondary variants of CU/psychopathic traits that are expected to show opposing physiological patterns. Best methodological practices are offered, and implications of findings for informing CU theory, future research, and intervention efforts are discussed.
Exploring Neural Gradient Architectures for Generative Precision in Large Language Models
Authors: Roova George , Heathcote Jonathan , Huntington Yasmin , Nethercott Jocelyn , Ravenscroft Gregory
Published: December 2024

The integration of Neural Gradient Architectures (NGA) into large language models (LLMs) has led to significant advancements in natural language processing, enhancing the precision and coherence of generated text. By employing gradient-driven computations, NGA dynamically adjusts internal pathways based on contextual cues, enabling LLMs to adapt more effectively to diverse linguistic tasks. This approach has demonstrated improvements in tasks such as machine translation, summarization, and dialogue generation, where contextual understanding is crucial. The incorporation of NGA has also contributed to a reduction in common issues like repetitive or irrelevant outputs, thereby increasing the overall quality of generated content. Furthermore, the adaptability of NGA allows for more efficient fine-tuning of LLMs across various domains, facilitating their application in specialized fields without extensive retraining. The empirical results demonstrate the efficacy of NGA in refining the generative processes of LLMs, highlighting its potential to substantially elevate the performance of natural language processing systems. Consequently, the adoption of NGA represents a pivotal progression in the evolution of LLM architectures, offering a robust framework for the development of more responsive and contextually aware language models.
Geoscience for Earth Stewardship, Sustainability and Human Well-being: a conceptual framework for integrating planet, prosperity and people
Authors: Stewart Iain
Published: December 2024

There is a growing view that the mission of the Earth sciences ought to be reframed around the global sustainability agenda, and specifically the grand challenges of the UN Sustainable Development Goals. Yet the SDGs are criticised for lacking a coherent sense of the complex interconnections and synergies between its economic, environmental and social ambitions, for maintaining the impetus of economic growth, and for the absence of a compelling narrative for what a sustainable future world might look like. Given those limitations, this paper offers an alternative meta-narrative to the global sustainability challenge in the form of coupled planetary and human well-being. It is a narrative that emerges from an overview of five decades of environmental discourse and debate to emphasise the central importance of Earth stewardship as a unifying theme. It presents the Daly Triangle as a holistic conceptual framework to link the health of the planet’s natural resource base, through the operations of a sustainable economy, to the ultimate ends of long-term well-being for all.
Modeling a Simplified Wind Power System with Wireless Data Transmission
Authors: Baig Talha Imtiaz , Iqbal Ahsan
Published: December 2024

This paper presents a low-fidelity model of a wind power system using a Simplified Generator block, designed for planning and pitch control studies. The model integrates renewable energy generation with an air interface-based wireless network to enable efficient data communication. QPSK, known for its high spectral efficiency, low latency, and flexible frequency bands, transmits key operational data such as power output, wind speed, and system diagnostics. The physical layer of the network, including free space path loss, limited bandwidth, RF receiver dynamics, and demodulation, is simulated using MATLAB and Simulink. The study explores the impact of wireless communication on transmitted signals, analyzing the effects of channel characteristics and system design on data integrity and performance. Results demonstrate the viability of using QPSK networks for real-time monitoring and control in wind power systems, offering insights into the efficient integration of wireless technology for renewable energy applications.
Horizontal Stratification of Higher Education and Gender Earnings Gap in the Early Labor Market
Authors: Hwang Inchan
Published: December 2024

This study investigates whether higher education—often regarded as an equalizing force that reduces group inequalities—can effectively address gender wage gaps. Despite the narrowing of gender disparities in access to higher education in Korea, this study examines whether obtaining a university degree reduces gender wage inequality. It focuses on the effects of college selectivity and field of study, analyzing how horizontal stratification in higher education influences the gender wage gap in the early labor market. Furthermore, it compares results from traditional linear regression with debiased machine learning, which accounts for selection bias and high-dimensional data.Using data from the Graduate Occupational Mobility Survey (GOMS), the analysis reveals that linear regression estimates a consistent gender wage gap of roughly 10% across all levels of higher education. In contrast, double machine learning identifies a 15% wage gap for graduates of two-year colleges and around 10% for those with four-year degrees. By field of study, linear regression reports consistent gaps, while double machine learning identifies a 6% gap in the humanities, 10-12% in education, natural sciences, and social sciences, and 14% in engineering. This study underscores that accounting for selection bias and high-dimensional data reveals nuanced insights, uncovering significant gender wage gaps among two-year college graduates and notably larger gaps in engineering compared to other fields.
AI-Augmented Cultural Sociology: Guidelines for LLM-assisted text analysis and an illustrative example
Authors: Wilderom Rens , Price Taylor , Heitland Tom
Published: December 2024

The advent of large language models (LLMs) presents a promising opportunity for how weanalyze text and, by extension, can study the role of culture and symbolic meanings in sociallife. Using an illustrative example focused on the concept of “personalized service” withinMichelin-starred restaurants, this research note demonstrates how LLMs can reliably identifycomplex, multifaceted concepts similarly to a qualitative data analyst, but in a more scalablemanner. We extend existing validation approaches, offering guidelines on the amount ofmanually coded data needed to evaluate LLM-generated outputs, drawing on sampling theoryand a data simulation. We also discuss broader applications of LLMs in cultural sociology,such as investigations on established concepts (e.g., cultural consecration) and emergingconcepts (e.g., future-oriented deliberation). This discussion underscores that AI-tools cansignificantly augment the empirical scope of research projects, building on rather thanreplacing traditional qualitative approaches. Our study ultimately advocates for an optimisticyet cautious engagement with AI-tools in social scientific inquiry, highlighting both theiranalytic potential and the need for ongoing reflection on their ethical implications.
Description of athlete physical conditions of sports at volleyball and basketball ball games at learning education and training center (pplp) dispora riau province in 2018
Authors: Zainur  , Aref Vai  , Triana Risca Enita
Published: December 2024

The purpose of this study was to find out the description of the physical condition of volleyball athletes and basketball of students education and training center (PPLP) in the Province of Riau Province in 2018, and to find out the differences in physical conditions of volleyball athletes, basketball students education and training centers (PPLP ) Riau Province Dispora in 2018. The type of this research is Quantitative Descriptive, where this study will clearly illustrate the PPLP test data from the Riau Province Physical Conditions team. Based on the results and discussion, it can be concluded that the results of the physical condition data of PPLP Volleyball athletes and PPLP basketball in Riau Province in 2018 are as follows: Physical condition of PPLP Volleyball Women's athletes in Riau Province in 2018 are in good category with a percentage of 12.5%, medium category which is 3 people with a percentage of 37.5%, the less category which is 3 people with a percentage of 37.5, and the category is very less which is 1 person with a percentage of 12.5%. While the physical condition of PPLP Women's Basketball athletes in Riau Province in 2018 is in the good category which is 1 person with a percentage of 20%, there are medium categories of 2 people with a percentage of 40%, the less category which is 2 people with a percentage of 40%, while there is no very less category. Thus, the condition of PPLP Women's Basketball Ball athletes is better than the condition of PPLP Women's Volleyball athletes
Performance Evaluation of Multiple Deep Learning Models for Wine Quality Prediction
Authors: Fabiyanto Dedik , Rianto Yan
Published: December 2024

Research utilizing a dataset from the UCI repository evaluated the predictive accuracy of nine machine learning models for wine quality. The models employed include Logistic Regression, K-Nearest Neighbor (KNN), Decision Tree, Support Vector Machine (SVM), Random Forest, XGBoost, LightGBM, CatBoost, and Gradient Boosting. The dataset comprises 1,599 samples with 12 chemical parameters. Data preprocessing, including oversampling, normalization, standardization, and seeding, was performed to enhance model performance.The study's findings indicate that the models with the highest accuracy values were LightGBM (87.80%), CatBoost (86.60%), and Random Forest (85.70%). A voting classifier combining these three models achieved an accuracy of 87.29%. Further analysis using a confusion matrix demonstrated that this combined model effectively predicts the "Good" and "Not Good" classes.In conclusion, the combination of LightGBM, CatBoost, and Random Forest models proves to be an effective approach for predicting wine quality based on chemical parameters, with an accuracy value of 87.29%.
A Survey of Veterinary Student Perceptions on Integrating ChatGPT in Veterinary Education Through AI-Driven Exercises
Authors: Alonso Sousa Santiago , Flay Kate Jade
Published: December 2024

Artificial intelligence (AI) in education is rapidly gaining attention, particularly with tools like ChatGPT, which have the potential to transform learning experiences. However, the application of such tools in veterinary education remains underexplored. This study aimed to design an AI-driven exercise and investigate veterinary students’ perceptions regarding the integration of ChatGPT into their education, specifically within the Year 5 Equine Medicine and Surgery course at City University of Hong Kong. Twenty-two veterinary students participated in an AI-driven exercise, where they created multiple-choice questions (MCQs) and evaluated ChatGPT's responses. The exercise was designed to promote active learning and a deeper understanding of complex concepts. The results indicate a generally positive reception, with 72.7% of students finding the exercise moderately to extremely engaging and 77.3% agreeing that it deepened their understanding. Additionally, 68.2% of students reported improvements in their critical thinking skills. Students with prior AI experience exhibited higher engagement levels and perceived the exercise as more effective. The study also found that engagement positively correlated with perceived usefulness, overall satisfaction, and the likelihood of recommending similar AI-driven exercises in other courses. Qualitative feedback underscored the interactive nature of this exercise and its usefulness in helping students understand complex concepts, although some students experienced confusion with AI-generated responses. While acknowledging the limitations of the technology and the small sample size, this study provides valuable insights into the potential benefits and challenges of incorporating AI-driven tools into veterinary education, highlighting the need for carefully considered integration of such tools into the curriculum.
Комунікативна компетентність як фактор формування у майбутніх працівників сектору безпеки й оборони України готовності до професійної діяльності
Authors: Tyurina Valentyna , Koziar Mykhailo , Malaniuk Nataliia
Published: December 2024

Обґрунтовано актуальність проблеми формування комунікативної компетентності майбутнього офіцера поліції як фактора формування і розвитку його готовності до професійної діяльності. Розкрито значення сформованості комунікативної компетентності для формування і розвитку готовності офіцерів поліції до професійної діяльності. Дано визначення понять «комунікативна компетентність», «готовність до професійної діяльності», «квест-технологія», «освітній квест», «поліцейський квест». Розкрито зміст завдань «поліцейського квесту» як ситуацій, що максимально наближені до реальної професійної діяльності працівників поліції. Обґрунтовано й експериментально доведено доцільність впровадження інтерактивних технологій, зокрема «поліцейського квесту», у процес професійної підготовки майбутніх офіцерів поліції з метою формування у них комунікативної компетентності як основи формування готовності до професійної діяльності. Показано статистично вірогідну наявність позитивної динаміки результатів за більшістю показників в експериментальних групах після вивчення спецкурсу, написання творчих і курсових робіт, участі у практичних заняттях у формі «поліцейського квесту».
The Role of Internal Communication on the Effectiveness of Employee Decision Making
Authors: Sulaiman Ibrahim Fahad , Owolabi Oluwatosin Sunday , Zaabnot Salem Mohammed Muslim , Malik Ahmed Abdul , Abubakar Ismail Yau
Published: December 2024

The process of decision-making among employees at the Office of the Minister of State in the Dhofar Governorate, Sultanate of Oman, relies on effective internal communication. Three independent variables were examined: administrative communication, formal communication, and informal communication in relation to employee decision-making. The study adopted a systematic literature approach to review methods for synthesising the fundamentals of internal communication among employees in government sectors. A sample of 238 employees was stratified using a quota sampling procedure to select respondents. The study used a questionnaire, adopted and adapted from the Internal Communication Questionnaire (ICSQ) and the Employee Participation in Decision Making Questionnaire (EPDM). Correlation analysis and Multiple Regression Analysis (MRA) were used to examine the relationships among the variables. The results showed a significant positive relationship between administrative, formal, and informal communication and employee decision-making in the government institution. The most influential variable among these was formal communication, with a beta coefficient of 0.240 and a significance level of 0.000. Additionally, the model summary accounted for 20.3% of the variance, with an ANOVA significance of 0.000. Therefore, adopting internal communication within governmental sectors is recommended to achieve organisational goals, as this accounts for 20.3% of the variance with a positive significance level of 0.000. This implies that adopting such internal communication practices in employee decision-making is a suitable methodology for achieving organisational goals.
Assessing the Alignment of Teaching Strategies with Respect to Malcolm Knowles' Model of Andragogy for Prospective Teachers
Authors: Khan Saeed Ullah , Khan Hafiz Muhammad Athar
Published: December 2024

The current study aimed to explore the teaching strategies employed by prospective teachers in relation to Malcolm Knowles' Andragogical Assumptions. This study was quantitative in nature. Researchers collected the data using a self-developed questionnaire that used a five-point Likert scale. The sample of the study consisted of 320 students purposively selected, 08 universities in southern Punjab were included. Researchers selected students pursuing B.Ed, B.Ed, and BS(education). The data were analyzed through SPSS. The result shows that teaching strategies generally align with andragogical principles. Teachers exhibited a strong alignment with principles such as motivation to learn and readiness to learn. Gender-based analysis revealed no significant differences in responses between male and female participants. Students enrolled in B.Ed programs reported higher alignment scores compared to those in B.Ed and BS (education) programs. It was recommended a closer integration of andragogical principles into teaching practices to enhance the effectiveness of teacher preparation programs.
Perceived Effectiveness and Learning in Foundation Course of Medical Undergraduate Program at Patan Academy of Health Sciences: A Multi Method Study
Authors: Shakya Tripti , Maharjan Babu Raja , Bhandary Shital , Acharya Balakrishnan M , Sharma Paban , Gongal Rajesh Nath
Published: December 2024

Introduction: Foundation course was introduced in medical undergraduate curriculum of a medical college in Nepal, to provide students with essential knowledge and skills for their pursuit of learning in their medical undergraduate program. This study aimed to measure perceived effectiveness of the foundation course course of medical students. Methods: A multi method study was conducted among students completing the foundation course at a medical college in Nepal. The perceived effectiveness of foundation course was evaluated by applying three levels of Kirkpatrick’s model i.e. reaction (satisfaction), learning and behavior. Quantitative data is presented as frequency, percentage, mean±standard deviation. Qualitative data was analyzed by coding and categorized into different themes and subthemes. Ethical approval was taken from Instutional Review Committee (Reference number: bss 2207081655). Results: A majority of students perceived the foundation course as a memorable experience that helped them to familiarize to new college environment. Students felt that it oriented them to the newer teaching learning and assessment system of the medical college. Assessment scores showed that students had significant learning in foundation course which students perceived applicable in basic and clinical science years. Conclusions: Foundation course learning has been very beneficial and applicable to the students in their medical studies. This course has helped students to get oriented to a new education system and learning environment.
Thyroid Disorders in Patients with Polycystic Ovarian Syndrome in a Tertiary Care Center: An Observational study
Authors: Sharma Jyotshna , Mahat Bimita , Tiwari Sanjeeb , Singh Niraj Kumar , Thapa Durga , Yadav Ranjana
Published: December 2024

Introduction: Polycystic ovarian syndrome is the most common endocrine and metabolic disorder in women of childbearing age, affecting 3–15% of women worldwide, leading to reproductive, metabolic, and psychological issues. Patients with polycystic ovarian syndrome require rigorous thyroid function detection, monitoring, and correction over time. In this study, we aimed to evaluate the clinical presentations and thyroid dysfunction in patients with polycystic ovarian syndrome.Methods: An observational study was done in patients with polycystic ovarian disease presenting to a tertiary care centre over six months, from December 2023 to May 2024 Total population sampling was done. All the women during the study period diagnosed with polycystic ovarian disease based on Rotterdam criteria were included in the study after getting ethical approval from the institutional review board. (Reference number: 20102023/03).Results: The mean age of women in the study was 24.74±5.01 years. A total of 28 (31.46%) patients of polycystic ovarian disease had hyperthyriodism, hypothyroidism was found in 13 (14.60%) and subclinical hypothyroidism was found in 6 (6.74%) patients. All the women had menstrual irregularities. Regarding androgenic characteristics, 53 (59.55%) of patients presented with hirsutism, 43 (48.51%) presented with acne, 13 (14.61%) women had alopecia, and 4 (4.49%) women had acanthosis.Conclusions: Hyperthyroidism, hypothyroidism and subclinical hypothyroidism were prevalent in polycystic ovarian disease patients, emphasizing the need for thorough thyroid evaluation in polycystic ovarian disease patients due to its impact on metabolic and reproductive health. High rates of menstrual irregularities, androgenic symptoms like hirsutism and acne, and fertility challenges were also prevalent, aligning with findings from similar studies.
World Health Organization Tool for Benchmarking Ethics Oversight of Health-Related Research with Human Participants
Authors: Ghimire Namita , Basnet Rojina , Acharya Richa , Adhikari Santoshi , Verma Shashi , Sharma Mohan Raj
Published: December 2024

Benchmarking ethics oversight is a process of aligning comparing and evaluating the strengths and room for improvement of ethical review and approval process across different institutions or the country. The World Health Organization tool for benchmarking ethics oversight is designed to help countries assess and improve their systems for ethically overseeing health-related research involving human participants. It identifies gaps in legal frameworks, committee structures, resources, accountability and transparency while promoting best practices and policy alignment. Nepal has made progress through the research regulations body like the Nepal Health Research Council , but challenges such as inconsistent implementation, oversight of the implementation and resource limitations remain. The tool offers an opportunity to strengthen Nepal’s health research governance and regulation but it must be adapted to fit local contexts, emphasizing accountability, transparency, capacity-building, and improved communication.
Nasal Myiasis in a Female with Christ–Siemens–Touraine Syndrome: A Case Report
Authors: Maharjan Leison , Shah Anju , Yadav Dhirendra , Shrestha Namita
Published: December 2024

Ectodermal dysplasia is a rare disease that belongs to a diverse group of inherited monogenic disorders involving defects in one or more ectodermally or mesodermally derived tissues. Hypohidrotic ectodermal dysplasia, also known as Christ-Siemens-Touraine syndrome is a type of ectodermal dysplasia characterized by a triad of anhidrosis, dysodontia, and hypotrichiasis. The most prevalent method of transmission is X-linked recessive, manifesting fully in men and only partially in female carrier heterozygotes. Atrophic rhinitis and nasal myiasis are rare characteristics of this condition. We hereby report a case of a 52-year-old female with atrophic rhinitis and nasal myiasis who was managed conservatively.
TRABZON GÜMRÜK MUKATAASINDA KADILARIN FONKSİYONLARI: TEFTİŞ, TAKİP VE TASDİK (1600-1650)
Authors: Tosun Miraç , Tütüncü Bekir
Published: December 2024

Kadıların bilinen idari ve adli meselelere ilaveten, merkez maliyesi ve idaresi tarafından kendilerine tevdi edilen ve imparatorluğun erken devirlerinden itibaren başta mukataa müfettişliği ve nazırlık olmak üzere birtakım mali işlerle de ilgilendiklerin bilinmektedir. Bilhassa XVII. yüzyıl gibi muhtelif krizlerin yaşandığı bir dönemde mali bürokrasinin, imparatorluğun merkezden uzak bölgelerindeki gelir-gider kalemlerinin ahvalini sorgulatmak ve teftiş ettirmek gibi meselelerde yerel kadılıklarla iş birliği içinde olduğu arşiv kayıtlarından anlaşılmaktadır. Bu çalışmada imparatorluğun sosyal, ekonomik ve askeri pek çok alana inhisar eden meselelerinde hem merkezin hem de yerel bölgedeki unsurların doğrudan başvurdukları bir makam olan kadılıkların, tanzim ettikleri arzlar ve dava hüccetleri incelenmek suretiyle Trabzon gümrüğünün tevcihinde ve mukataa olarak işletilmesindeki rolleri üzerinde durulmaya çalışılmıştır.
DEVELOPING A KINETIC MODEL FOR MICROWAVE HYDRO DIFFUSION AND GRAVITY WITH STEAM FLOW ON EXTRACTION OF ESSENTIAL OILS FROM Amomum compactum SEEDS
Authors: M. Mahfud  , Nabila A. R. , Y. Variyana
Published: December 2024

Lampung cardamom (Amomum compactum) has the potential to produce essential oils used for aromatherapy, cosmetics, and pharmaceutical purposes. This research aims to study the kinetics model that can represent the extraction process using the MHG method with the addition of steam flow. The operating variables considered include microwave power (300-600 W), extraction time (20-180 minutes), and the feed-to-distiller volume (F/D) ratio (0.15- 0.2 g/ml). To determine the best model for describing the essential oil extraction process from local cardamom seeds using the MHG method, six kinetic models were analyzed: first-order, second-order, power law, hyperbolic, Weibull, and Elovich’s. The results show that the Weibull model is the most accurate for representing the extraction process. This conclusion is based on its superior statistical performance, with the highest coefficient of determination (R²) among the models, averaging 0.9933, and the lowest sum of squared errors (SSE), averaging 0.0072. Furthermore, the Weibull D parameter reveals that extraction efficiency increases as the F/D ratio rises, enabling the process to reach its maximum efficiency more rapidly. These findings underscore the suitability of the Weibull model for effectively capturing the dynamics of essential oil extraction from Lampung cardamom seeds.
EFFECT OF DIFFERENT STOCKING DENSITIES IN BIOFLOC-BASED CATFISH (Clarias batrachus) CULTIVATION ON WATER QUALITY AND PRODUCTION PERFORMANCE
Authors: D. Deswati  , R. Zein  , S. Syafrizayanti  , S. Latifah  , A. Putra  , P. Ramadhani
Published: December 2024

Biofloc Technology (BFT) is an innovation in fish farming aimed at improving feed efficiency and water quality by assisting heterotrophic bacteria. This study aims to improve water quality (ammonia, nitrite, nitrate, sulfate, phosphate) and fish production performance (average daily growth/ADG, average body weight/ABW, production, specific growth rate/SGR, feed conversion ratio/FCR, survival rate/SR). Catfish with an initial weight of 18.7±0.1 g and length of 11.48±0.02 cm were reared for 40 days with feed amounting to 2-4% of body weight. Parameters were measured every 10 days and analyzed using a Completely Randomized Design (CRD) with 4 treatments (A: without biofloc; B, C, D: using biofloc with densities of 100, 125, and 175 fish/m³). The results showed that biofloc improved water quality (ammonia 0.2165-0.5322 mg/L, nitrite 0.0044-0.0616 mg/L, nitrate 0.2863-19.6422 mg/L, phosphate 0.0169-0.8865 mg/L, and sulfate 2.6097-34.0627 mg/L), and enhanced fish production performance (ADG 1.625-3.85 g/fish/day, ABW 65-154 g/fish, production 5.251-16.176 kg, SGR 3.633-4.642%, FCR 0.849-1.007, and SR 65-89%). Biofloc technology effectively supports catfish survival up to a density of 175 fish/m³, demonstrating that BFT is a cost-effective, sustainable, and environmentally friendly aquaculture technology.
Analytical review of confidential artificial intelligence: methods and algorithms for deployment in cloud computing
Authors: Shiriaev Е. М. , Nazarov А. S. , Kucherov N. N. , Babenko М. G.
Published: December 2024

The technologies of artificial intelligence and cloud systems have recently been actively developed and implemented. In this regard, the issue of their joint use, which has been topical for several years, has become more acute. The problem of data privacy preservation in cloud computing acquired the status of critical long before the necessity of their joint use with artificial intelligence, which made it even more complicated. This paper presents an overview of both the artificial intelligence and cloud computing techniques themselves, as well as methods to ensure data privacy. The review considers methods that utilize differentiated privacy; secret sharing schemes; homomorphic encryption; and hybrid methods. The conducted research has shown that each considered method has its pros and cons outlined in the paper, but there is no universal solution. It was found that theoretical models of hybrid methods based on secret sharing schemes and fully homomorphic encryption can significantly improve the confidentiality of data processing using artificial intelligence.
ЗАСТОСУВАННЯ КОНЦЕПЦІЇ «РОЗУМНЕ МІСТО» У РЕАЛІЗАЦІЇ ЗАСАД СТАЛОГО РОЗВИТКУ ТЕРИТОРІАЛЬНИХ ГРОМАД
Authors: КІНАШ Ірина
Published: December 2024

The article aims to study the main components of the concept of "smart city", focusing on the features of its implementation in a specific territorial community. This concept serves as a tool that contributes to the sustainable development of territories. The implementation of the concept of "smart city" creates solutions that are able to solve the environmental, economic and social problems of our cities. It has been established that numerous cities around the world have adopted this concept. Its goal is to improve the well-being of citizens. The goal is achieved by improving the existing infrastructure to achieve the status of "smart city" or by actively seeking ways to adapt existing resources and networks. The city is transformed into "smart" through the use of various information computer technologies. These technologies are superimposed on each other: software, infrastructure and digital data. Sustainable development is important for meeting our current needs without sacrificing the ability of future generations to meet their own. Research materials indicate that more and more experts and researchers from different fields are working together to create solutions that will help solve environmental, economic and social problems to support the sustainable development of our cities. One of the tools that contributes to the sustainable development of territories is the concept of "smart city".
The key definitions of the concept of "smart city" and its components are summarized. The characteristics of the outlined components are given. "Smart city" projects are considered using the example of one of the regional centers of Ukraine - the city of Ivano-Frankivsk. Here, the city authorities focused on the following aspects of implementing the studied concept: a service universe has been created, SMS-informing of the population is carried out, there is a feedback code, infographics are created, electronic queues operate, there are personal accounts of residents, various electronic services are provided. The most successful project of the city is "Transport". It is concluded that the application of the "smart city" concept through decentralized approaches in community management provides more effective management of important resources, urban dynamics and operations in real time and, thereby, contributes to the sustainable development of the territory.
Los Antecedentes literarios y paremiológicos de la minificción hispanoamericana
Authors: Handar Mustapha
Published: December 2024

Microfiction stands out as the most hybrid literary genre; a characteristic that is not only due to the author's writing art and aesthetic touch, but also to the diversity of his origins. This research seeks to demonstrate the polygenesis of minifiction, showing that its emergence is not limited to a single literary model, as some critical voices maintained, but that it has been nourished by dissimilar influences. The micro-story is the result of the combination of features belonging to archaic, modernist and extra-literary literary genres, especially paremiological. At a methodological level, a contrastive analysis is proposed between the microstory and these genres to identify similarities and differences in terms of structure, style, language, themes and narrative techniques. This analysis will allow us to identify the chromosomes inherited from each ancestor and define the DNA of the microstory as an independent narrative genre. Microfictions will be examined along with representative examples of the genres that have influenced their development.
Analisis Kemampuan Pemecahan Masalah Matematis Menggunakan Soal Pisa Ditinjau dari Motivasi Belajar Siswa
Authors: Mutialawati Elena , Nurcahyono Novi Andri , Balkist Pujia Siti
Published: December 2024

Kemampuan pemecahan masalah matematis merupakan hal yang penting yang harus dimiliki siswa. Salah satu faktor yang mendukung siswa dalam menyelesikan masalah matematis adalah motivasi belajar. kurangnya konsentrasi saat belajar, kurang bersemangat dalam mengikuti pembelajaran, tidak berupaya untuk menyelesaikan tugas dengan baik dapat menjadi salah satu penyebab kesulitan dalam memecahkan soal. Penelitian ini bertujuan untuk mengetahui kemampuan pemecahan masalah matematis menggunakan soal PISA konten kuantitas (quantity) yang ditinjau motivasi belajar. Penelitian ini dilakukan densn metode kualitatif jenis deskriptif. Instrument yang digunakan adalah tes dan non-tes, subjek penelitian adalah kelas XI di SMAN 1 Sukaraja yang berjumlah 31 siswa. Hasil penelitian ini menunjukkan bahwa: (1) siswa yang memiliki motivasi belajar tinggi, memiliki kemampuan pemecahan masalah matematis yang baik pada tahap mengenali/menyajikan masalah, mendefinisikan masalah, mengembangkan beberapa hipotesis, menguji beberapa hipotesis, dan memilih hipotesis terbaik. (2) siswa yang memiliki motivasi belajar sedang, belum dapat dikatakan memiliki kemampuan pemecahan masalah matematis yang baik dimana siswa hanya mampu mengenali/menyajikan masalah, mendefinisikan masalah, dan menguji beberapa hipotesis. (3) siswa yang memiliki motivasi belajar rendah, belum memiliki kemampuan pemecahan masalah matematis yang baik dimana siswa belum mampu mendefinisikan masalah, mengembangkan beberapa hipotesis, menguji beberapa hipotesis, dan memilih hipotesis terbaik.
Kata Kunci : Kemampuan pemecahan masalah, motivasi belajar, soal PISA konten kuantitas
Analisis Pelaksanaan Program Sekolah Ramah Anak di Sekolah Dasar
Authors: Wahyuni Aulia Putri , Nurasiah Iis , Uswatun Din Anwar
Published: December 2024

Penelitian ini bertujuan untuk mendeskripsikan pelaksanaan Program Sekolah Ramah Anak (SRA) di SDN Cisaat, Sukabumi. Program ini bertujuan menciptakan lingkungan belajar yang aman, nyaman, dan sehat bagi peserta didik, serta melindungi mereka dari kekerasan dan diskriminasi. Metode penelitian yang digunakan adalah deskripsi kualitatif dengan pengumpulan data melalui wawancara mendalam, observasi, dan dokumentasi. Hasil penelitian menunjukkan bahwa SDN Cisaat telah menjalankan program SRA dengan baik melalui kolaborasi dengan orang tua, Puskesmas, dan pihak kepolisian setempat untuk mendukung kesehatan dan keamanan peserta didik. Selain itu, sekolah juga menerapkan berbagai kegiatan seperti sosialisasi anti-bullying, pemeriksaan jajanan, dan program Kantin Sehat. Meskipun fasilitas sekolah secara umum sudah memadai, terdapat kekurangan ruang kelas dan guru Bimbingan Konseling (BK). Namun, antusiasme peserta didik dan dukungan dari orang tua dalam pelaksanaan program SRA sangat positif. Dengan program ini, SDN Cisaat diharapkan dapat terus menciptakan lingkungan belajar yang lebih aman, ramah, dan mendukung bagi seluruh peserta didik, serta meminimalisasi risiko kekerasan dan bullying di sekolah.
Pengaruh Peer Group Terhadap Minat Belajar Peserta Didik Beragam Buddha PKBM Homeschooling Kusalamitra Gunungkidul
Authors: Lestari Sri , Prasetyo Eko , Andati Maria Fransisca
Published: December 2024

Penelitian ini bertujuan untuk mengetahui pengaruh peer group terhadap minat belajar peserta didik di PKBM Homeschooling Kusalamitra, Gunungkidul. Menggunakan metode kuantitatif deskriptif dengan pendekatan korelasional, penelitian melibatkan 40 siswa sebagai sampel. Data dikumpulkan melalui kuesioner terstruktur dan dianalisis menggunakan regresi linear. Hasil penelitian menunjukkan bahwa peer group memiliki pengaruh signifikan terhadap minat belajar, dengan kontribusi sebesar 75,5% (R Square 0.755). Analisis regresi menghasilkan t hitung 10.667 dengan Sig. 0.000 ≤ 0.30, menunjukkan pengaruh yang signifikan. Rata-rata skor peer group adalah 63,13 (kategori tinggi) dengan persentase 76%, sementara rata-rata skor minat belajar adalah 46,37 (kategori tinggi) dengan persentase 74%. Penelitian ini menyimpulkan bahwa peer group berperan penting dalam meningkatkan minat belajar siswa di lingkungan homeschooling, terutama dalam mengatasi potensi isolasi sosial dan mendorong kolaborasi pembelajaran. Temuan ini memberikan implikasi penting bagi pengembangan strategi pembelajaran di PKBM Homeschooling Kusalamitra dan lembaga serupa.