bluuebunny/crossref_metadata_2025_split huggingface dataset:
SEGNN4SLP: Structure Enhanced Graph Neural Networks for Service Link Prediction
Authors: Lin Yuxi , Li Mengfei , Chen Nuo 
Published: January 2025

Abstract
For the provision of accurate link prediction, this study's neural network-based method for API recommendation uses structure encoding to capture topological context. SEGNN4SLP, a Graph Neural Network (GNN) framework that integrates node attributes and graph structure to enhance GNNs' link prediction skills, makes a substantial contribution. Utilizing an actual dataset with 21,900 APIs, 6,435 Mashups, and 13, 340 interactions, ProgrammableWeb.com was the source of the evaluation. Eighty percent of the data were test sets and twenty percent were training sets after single API-invocation Mashups were eliminated. The results demonstrate high link prediction accuracy, which is attributed to the incorporation of structural encoding in embedding learning and improved collaborative signal extraction from users and APIs, which improves API recommendation performance overall.
Improvement of Helmet Detection Algorithm Based on YOLOv8
Authors: Li Danyang , Wang Jianguo 
Published: January 2025

Abstract
In order to solve the problems of safety helmets in complex factory environments due to the complex background, dense targets, etc., which cause the YOLOv8s algorithm to be prone to leakage and misdetection, and low recognition accuracy, a safety casque detection algorithm based on the YOLOv8s improved YOLOv8s-improved is proposed. By incorporating a deformable convolutional module into the backbone network of YOLOv8s, the occurrences of false negatives and false positives are effectively reduced, and detection accuracy is enhanced. To tackle the issue of small target detection being easily disturbed by image backgrounds and noise, the CBAM attention mechanism is embedded to sift out the relatively important information from a large amount of information, and enhances the ability of helmet information extraction; for the problem that the loss of small target classification and localization is not easy to calculate, a new For the problem of small target classification and localization loss is not easy to calculate, a new IoU loss function is introduced to improve the training effect of the model. The experiment shows that the detection accuracy mAP of the improved YOLOv8s algorithm in this paper is 1.3% higher than that of the original YOLOv8s algorithm. Experimental results have shown that the improved algorithm proposed in this paper not only reduces false positives and false negatives in helmet wearing detection, but also enhances the detection capability for small targets, thus improving the performance of helmet wearing detection to a certain extent.
Cognitive Map Construction Based on Grid Representation
Authors: Du Yuxin , Yao Hongge 
Published: January 2025

Abstract
This paper investigates a grid-representation-based approach to spatial cognition for intelligent agents, aiming to develop an effective neural network model that simulates the functions of the olfactory cortex and hippocampus for spatial cognition and navigation. Despite progress made by existing models in simulating biological nervous system functions, issues such as model simplification, lack of biological similarity, and practical application challenges remain. To address these issues, this paper proposes a neural network model that integrates grid representation, reinforcement learning, and encoding/decoding techniques. The model forms a grid representation by simulating the integration of grid cells in the medial entorhinal cortex (MEC) with perceptual information from the lateral entorhinal cortex (LEC), which encodes and retains spatial location information. By leveraging attractor networks, convolutional neural networks (CNNs), and multilayer perceptrons (MLPs), the model achieves the storage of spatial location and environmental information, as well as the construction of cognitive maps. The experimental results show that after using this model, the map generation accuracy increased by 15%, the navigation accuracy of the agent in complex environments by 20%, and the target localization error was reduced to less than 10%, demonstrating a significant overall performance improvement in the grid-based cognitive map construction.
A Novel Variance Reduction Proximal Stochastic Newton Algorithm for Large-Scale Machine Learning Optimization
Authors: Ahmed Mohammed Moyed 
Published: January 2025

Abstract
This paper introduces the Variance Reduction Proximal Stochastic Newton Algorithm (SNVR) for solving composite optimization problems in machine learning, specifically minimizing F(w) + Ω(w), where F is a smooth convex function and Ω is a non-smooth convex regularizer. SNVR combines variance reduction techniques with the proximal Newton method to achieve faster convergence while handling non-smooth regularizers. Theoretical analysis establishes that SNVR achieves linear convergence under standard assumptions, outperforming existing methods in terms of iteration complexity. Experimental results on the "heart" dataset (N=600, d=13) demonstrate SNVR's superior performance: Convergence speed: SNVR reaches optimal solution in 5 iterations, compared to 14 for ProxSVRG, and >20 for proxSGD and ProxGD. Solution quality: SNVR achieves an optimal objective function value of 0.1919, matching ProxSVRG, and outperforming proxSGD (0.1940) and ProxGD (0.2148). Efficiency: SNVR shows a 10.5% reduction in objective function value within the first two iterations. These results indicate that SNVR offers significant improvements in both convergence speed (180-300% faster) and solution quality (up to 11.9% better) compared to existing methods, making it a valuable tool for large-scale machine learning optimization tasks.
Interobserver and sequence variability in the delineation of pelvic organs at risk on magnetic resonance images
Authors: Zheng Wanjia , Yang Xin , Cheng Zesen , Lian Jinxing , Li Enting , Mo Shaoling , Liu Yimei , Huang Sijuan 
Published: January 2025

Abstract

Background
This study evaluates the contouring variability among observers using MR images reconstructed by different sequences and quantifies the differences of automatic segmentation models for different sequences.

Patients and methods
Eighty-three patients with pelvic tumors underwent T1-weighted image (T1WI), contrast enhanced Dixon T1-weighted (T1dixonc), and T2-weighted image (T2WI) MR imaging on a simulator. Two observers performed manual delineation of the bladder, anal canal, rectum, and femoral heads on all images. Contour differences were used to analyze the interobserver and intersequence variability. A single-sequence automatic segmentation network was established using the U-Net network, and the segmentation results were analyzed.

Results
Variability analysis among observers showed that the bladder, rectum, and left femoral head on T1WI yielded the highest dice similarity coefficient (DSC) and the lowest 95% Hausdorff distance (HD) (all three sequences). Regarding sequence variability analysis for the same observer, the difference between T1WI and T2WI was the smallest. The DSC of the bladder, rectum, and femoral heads exceeded 0.88 for T1WI–T2WI. The differences between automatic segmentations and manual delineations were minimal on T2WI. The averaged DSC of automatic and manual segmentation of all organs on T2WI exceeded 0.81, and the averaged 95% HD value was lower than 7 mm. Similarly, the sequence variability analysis of automatic segmentation indicates that the automatic segmentation differences between T2WI and T1WI are minimal.

Conclusions
T1WI and T2WI yielded better results in manual delineation and automatic segmentation, respectively. The analysis of variability among three sequences indicates that the yielded good similarity outcomes between the T1WI and T2WI cases in manual and automatic segmentation. We infer that the T1WI and T2WI (or their combination) can be used for MR-only radiation therapy.
Predictive Analytics in Finance Using the Arima Model. Application for Bucharest Stock Exchange Financial Companies Closing Prices
Authors: Spulbar Cristi , Ene Cezar Cătălin 
Published: January 2025

Abstract
Stock markets can be volatile, thus accurate predictions can greatly help investors and stakeholders to make wise financial choices. The main goal of this paper is to test how well the Autoregressive Integrated Moving Average (ARIMA) model can capture and predict changes in closing prices. The ARIMA model is the combination of autoregressive (AR) and moving average (MA) processes of an integrated or differenced time series model. Moreover, the selected model is part of the time series analysis under prediction algorithms, the purpose of the research being to predict the prices of the selected shares. Our analysis compiles daily trading data of financial companies on the BSE using a quantitative methodology. We preprocess the dataset to ensure reliability and accuracy, then conduct an exploratory data analysis to identify underlying patterns and correlations. Next, we use the ARIMA model, carefully optimizing the parameters through selection and a validation process, to forecast the closing prices over a 30-day period, we also evaluate the model’s performance. The preliminary results show that the ARIMA model seems to be efficient at predicting closing stock prices accurately. The model appears to understand the patterns and fluctuations in the stock market data, which gives useful information about future price changes. The forecasts we generated show similarities with the real market results, capturing important patterns, and making it a viable option for forecasting market performance.
Exploring the Synergy Between Artificial Intelligence and Human Resources: A Qualitative Review of Business Management Literature
Authors: Girlovan Aura , Horobet Alexandra , Botoroga Cosmin-Alin , Belascu Lucian , Lucian Paul 
Published: January 2025

Abstract
This paper portrays the role of the interplay between artificial intelligence and human resources as evidenced by an extensive review of academic literature. The study investigated 402 abstracts of scholarly articles published in the Business Management and Accounting domain of the Scopus database spanning from 2000 to 2023. Using QDA Miner 2024, a novel approach based on content, link, and proximity analysis was employed to conduct the literature review. Three major findings were revealed by our investigation. First, while codes such as ‘AI’ and ‘employees’ dominate the academic discourse, there is an evolving trend toward more sophisticated analyses of AI-human resources interactions, including their impact on business strategies and performance. Second, research methods show significant diversification over time, going from more descriptive approaches to sophisticated quantitative and qualitative methodologies. Third, several areas appear to lack research focus, such as the connection between employee recruitment and future career paths with AI and business progress. The findings contribute to understanding how the technological revolution shapes business operations, particularly workforce management, while highlighting the need for structural reforms in organizational approaches to AI adoption, and provide valuable insights for both scholars and practitioners interested in the integration of AI in human resource management.
Contribution of Personnel Management to the Generation of Innovation Capabilities in Medium and Large Companies in Colombia
Authors: Rubio-Rodríguez Gustavo Adolfo , Ortiz Yeison Farid Méndez , Cardoso Elizabeth Palma , Perdomo Efraín Enrique Granados 
Published: January 2025

Abstract
The purpose of this research is to determine the contribution of human resources management in the development of innovative capabilities in medium and large companies in the city of Ibagué, Colombia. The study is exploratory and uses a mixture of quantitative techniques for its development, being non-experimental. The study population is made up of 107 medium-sized companies and 23 large companies in the city of Ibagué. Since the population to be studied is finite and known, a stratified random probability sampling with finite population adjustment is carried out, since the possibility of selecting one or another element is equal. In addition, the aim is to ensure that all the units of analysis (medium and large companies) are duly represented. The results showed that businessmen understand the importance of human resources management and innovation for the organization; most managers recognize that, through human resources management, employees are capable of innovating in all areas in which they work. However, their development has been stagnated in some cases due to lack of management within the organization itself.
Role of Microfinance in Entrepreneurial Development in Low-Income Areas
Authors: Ullah Saif , Ali Mirza Raza , Sidiki Shehla Najeeb 
Published: January 2025

Abstract
This study examines microfinance’s role in developing entrepreneurship in low-income areas. Entrepreneurship is one of the better ways to eradicate the most critical problems, such as poverty, income inequality, and unemployment. The study uses a paired sample t-test on 200 small entrepreneurs from low-income areas to investigate the difference between before and after availing of a microfinance facility. Furthermore, the microfinance gap is calculated by taking feedback from entrepreneurs before and after getting the financing facility. The microfinance gap is employed to examine whether microfinance plays a role in developing entrepreneurial skills. The results show that the microfinance gap positively contributed to entrepreneurial development. The microfinance facility has proved to be a technique for entrepreneurial development for poor and young unemployed youth. MFIs are considered the best tool to reduce poverty and unemployment and increase entrepreneurial development.
The Effect of Managerial Ability on Risk Reporting in Indonesia: Evidence for Energy and Palm Oil Companies
Authors: Zairin Gentiga Muhammad , Khairunnisa Hera , Respati Dwi Kismayanti , Putri Nur Afni Camelia , Sang Lim Thien , Ulupui I Gusti Ketut Agung 
Published: January 2025

Abstract
Risk reporting is a critical aspect of risk management for energy and palm oil companies as they address complex industry challenges. This article examines the influence of management ability on risk reporting in both industries. The results show that managerial ability has an impact on credit risk assessment, risk behavior, financial reporting, timeliness, stock price crash risk, and tax results. Management’s discretionary disclosure behavior allows it to exercise subjectivity in determining both the content and manner of disclosure. This research identifies a risk reporting factor associated with competent managers that indicates their desire to disclose risk-related information in annual reports in highly competitive markets. This work complements previous research on competent managers in competitive markets and provides valuable insights into the risk reporting practices of highly skilled managers in such environments.
Influence of Organic Mulching on Soil Thermoregulation in the Tocantina Region of Maranhão
Authors: Santos Yuri Nascimento , Silva Cristiane Matos da , Viana Jonathan dos Santos , Silva Wilson Araújo da 
Published: January 2025

Objective: This study investigates the influence of organic mulching on soil thermoregulation in the Tocantina Region of Maranhão, evaluating its thermal effects and implications for the sustainable management of agricultural production.

Theoretical Framework: The research discusses the benefits of mulching for sustainable agriculture, such as thermal regulation, moisture conservation, and soil biological activity, providing a solid foundation for the study.

Methodology: The experiment was conducted at the Agricultural Sciences Center of UEMASUL, using two 1 m² plots: one covered with straw mulch and the other uncovered (control). Soil temperature measurements were taken at depths of 2.5 cm and 7.5 cm using a digital thermometer, with data collected every 5 minutes between 2:00 p.m. and 3:00 p.m.

Results and Discussion: Organic mulch significantly reduced soil temperature, with an average of 36.13°C in covered areas compared to 48.09°C in uncovered ones. Depth also influenced temperature, with the mulch showing a more pronounced effect. These findings were contextualized within the theoretical framework, highlighting practical implications and study limitations.

Implications: The research provides insights into agricultural management practices, emphasizing thermal efficiency, water conservation, increased productivity in tropical climates, sustainability, and adaptation to climate change.

Originality/Value: This study contributes by exploring soil thermoregulation through organic mulching in a tropical region, promoting low-cost agricultural practices relevant to family farming and mitigating high temperatures.
Management of Waste Lubricating Oil and Its Packaging in the Municipality of Garanhuns-PE
Authors: Gonzaga Neide da Cruz , Vigoderis Ricardo Brauer , Molica Renato José Reis , Andrade Horasa Maria Lima da Silva , Bezerra João Vitor de Almeida , Souza José Nilton Silva de , Leite Glaudemir Santos , Lima Ayme Fernanda de Almeida Melo de , Silva José Robson Alves Ferreira da , Silva João Manoel da 
Published: January 2025

Objective: The objective of the study was to analyze the management of waste from used or contaminated lubricating oil and its packaging in establishments that carry out lubricating oil changes in Garanhuns-PE.

Theoretical Framework: Used or contaminated lubricating oil and its packaging are classified, according to the Brazilian Association of Technical Standards, as hazardous waste, and legal requirements regarding their collection, treatment and final disposal must be followed. Incorrect environmental management of these wastes affects human health and the environment.

Method: The methodology was based on bibliographic review, data collection through questionnaires and use of geoprocessing technologies.

Results and Discussion: Mechanical workshops stood out as potential agents in the generation of waste and effluents (liquid, solid or gaseous), which do not receive adequate treatment before being released into the natural environment, putting at risk the quality of water bodies and their preservation for use by current and future generations.

Research Implications: Assist in studies related to activities that produce potentially polluting loads, resulting from human intervention, in areas susceptible to the risk of water contamination in the municipality of Garanhuns.
Originality/Value: This unprecedented study in the municipality of Garanhuns-PE, may contribute to guiding possible actions by the public authorities regarding future inspection and monitoring interventions of activity performance in the urban environment.
СТУПЕНИ ПАДЕНИЯ ИЛИ ФАШИЗМ НА УКРАИНЕ (ОТ Л.КРАВЧУКА ДО В. ЗЕЛЕНСКОГО)
Authors: Бруз В.В. , Солодилов А.В. 
Published: January 2025

В статье на основе анализа исторических фактов рассмотрены закономерности возникновения фашизма и характерные признаки его проявления в Украине, некогда братской стране при попустительстве ряда недружественных стран. В условиях проведения Специальной военной операции они пытаются в предверии 80 –летия Великой победы всячески защищать нелегитимное руководство Украины, оказывая прямую политическую и военную помощь, а также заявляют, что никакого проявления фашизма в стране нет. Статья полностью подтверждает обратное.
Based on the analysis of historical facts, the article examines the patterns of the emergence of fascism and the characteristic signs of its manifestation in Ukraine, once a fraternal country with the connivance of a number of unfriendly countries. In the context of a Special military operation, they are trying to defend the illegitimate leadership of Ukraine in every possible way on the eve of the 80th anniversary of the Great Victory, providing direct political and military assistance, and also declare that there is no manifestation of fascism in the country. The article fully confirms the opposite.
ПСИХОЛОГИЧЕСКАЯ СЕПАРАЦИЯ ОТ РОДИТЕЛЕЙ: ПОНЯТИЕ, КРИТЕРИИ И ПОСЛЕДСТВИЯ
Authors: Косолапова А.В. 
Published: January 2025

В статье представлен анализ литературных источников, посвященных проблеме психологической сепарации от родителей. Раскрываются основные подходы к определению данного понятия и выделению критериев успешного сепарационного процесса. Рассматриваются последствия незавершенной сепарации как для детей, так и для родителей, а также ошибки родителей, мешающие данному процессу. Отмечается, что психологическая сепарация от родителей – это важный и многогранный процесс, который происходит в жизни каждого человека и требует не только понимания со стороны детей, но и готовности родителей адаптироваться к новым условиям. Он начинается в подростковом возрасте и продолжается в ранней взрослости, когда молодые люди начинают осознавать свою индивидуальность и стремятся к автономии. При этом максимальная сепарационная активность человека совпадает с окончанием юношества (студенческого возраста). Многие исследователи рассматривают данный период в качестве нормативного кризиса переходного периода (юношество – ранняя взрослость), в ходе которого молодые люди заканчивают учебное заведение и впервые сталкиваются со сложностями, которыми полна самостоятельная жизнь. Подчеркивается, что определяющую роль в достижении личностной зрелости и обретении жизнеспособности молодыми людьми, которые готовы брать на себя производственные и социальные задачи, играет процесс сепарации от родителей, что актуализирует исследования взаимосвязи данных психологических феноменов.
The article analyzes literary sources devoted to the problem of psychological separation from parents. The main approaches to the definition of this notion and the allocation of criteria of successful separation process are revealed. The consequences of incomplete separation for both children and parents are considered, as well as parental mistakes that hinder this process. It is noted that psychological separation from parents is an important and multifaceted process that occurs in the life of every person and requires not only understanding on the part of children, but also the readiness of parents to adapt to new conditions. It begins in adolescence and continues in early adulthood, when young people begin to realize their individuality and strive for autonomy. The maximum separative activity of a person coincides with the end of adolescence (college age). Many researchers consider this period as a normative crisis of the transition period (adolescence - early adulthood), during which young people graduate from educational institutions and for the first time face the complexities of independent life. It is emphasized that the process of separation from parents plays a decisive role in achieving personal maturity and gaining viability of young people who are ready to take on production and social tasks, which actualizes the research of interrelation of these psychological phenomena.