bluuebunny/crossref_metadata_2025 huggingface dataset:
SPARQL Query Execution in Networks of Web Browsers
Authors: Grall Arnaud  , Molli Pascal  , Skaf-Molli Hala
Published: February 2025

Decentralizing the Web means that users gain the ability to store their data wherever they want, users can store their data in their web browsers. Web browsers allow decentralized applications to be deployed in one click and enable interaction with end-users. However, querying data stored in a large network of web browsers remains challenging. A network of web browsers gathers a very large number of browsers hosting small data. The network is highly dynamic, many web browsers are now running on mobile devices with limited resources, this raises issues on energy consumption. In this paper, we propose Snob, a query execution model for SPARQL query over RDF data hosted in a network of browsers. The execution of a query in a browser is similar to the execution of a federated SPARQL query over remote data sources. In Snob, direct neighbours in the network are the data sources and results received from neighbours are stored locally as intermediate results. As data sources are renewed every shuffling, the query continues to progress and could produce new results after each shuffling without congesting the network. To speed up query execution, browsers processing similar queries are connected through a semantic overlay network. Experimentation shows that the number of answers produced by queries grows with the number of executed queries in the network while the number of exchanged messages is always bounded per user.
Granular Computing Approach to Cybersecurity Problem
Authors: Isah Sani Suleiman  , Selamat Ali  , Ibrahim Roliana  , Anuar Syahid
Published: February 2025

Cybersecurity has a lot of challenging problems, from intrusion to illegal actions and destruction. These challenges have attracted so many interests from researchers and practitioners in providing sustainable solutions. The presence of big data has increased the hope in curbing the aforementioned challenges due to its advantage of providing the platform for improved technology-based advancements. With the rapid development in the adoption of cloud-based services and migration of data to the cloud, there is a genuine need for advanced protection and prediction techniques. With this regard, Granular Computing is introduced as a new paradigm capable of providing solution to myriad of problems among which are related to cybersecurity. In this study, by taking the advantage of Granular Computing and Big Data, an improved k-means information granulation framework that incorporate similarity measure from the pre-clustering stage as well as segregation technique is proposed based on Granular Computing to identify threats from a time series dataset. The experiments on public available dataset shows that the method have good recognition performance better than other known predictive analysis classifiers – kNN and naive bayes. This study also provides research direction towards enhancing data granulation techniques in handling uncertainties.
OASIS: An Active Framework for Set Inversion
Authors: Nguyen Binh T.  , Nguyen Duy M.  , Ho Lam Si Tung  , Dinh Vu
Published: February 2025

In this work, we introduce a novel method for solving the set inversion problem by formulating it as a binary classification problem. Aiming to develop a fast algorithm that can work effectively with high-dimensional and computationally expensive nonlinear models, we focus on active learning, a family of new and powerful techniques which can achieve the same level of accuracy with fewer data points compared to traditional learning methods. Specifically, we propose OASIS, an active learning framework using Support Vector Machine algorithms for solving the problem of set inversion. Our method works well in high dimensions and its computational cost is relatively robust to the increase of dimension. We illustrate the performance of OASIS by several simulation studies and show that our algorithm outperforms VISIA, the state-of-the-art method.
General-Purpose Lithuanian Automatic Speech Recognition System
Authors: Salimbajevs Askars  , Kapočiūtė-Dzikienė Jurgita
Published: February 2025

This paper describes the development of a general-purpose automatic speech recognition system for Lithuanian. The system is capable of performing both the transcription of user submitted audio recordings and real-time speech-to-text conversion. The comparative evaluation results prove that the presented system outperforms all other ASR systems for the Lithuanian language. The system also includes number and date normalization and is paired with an automatic punctuation restoration model that achieves state-of-the-art results for the Lithuanian language. Importantly, the system is publicly available to any Lithuanian speaker for testing via its web-page and mobile application.
Linguistically-Motivated Automatic Classification of Lithuanian Texts for Didactic Purposes
Authors: Grigonytė Gintarė  , Kovalevskaitė Jolanta  , Rimkutė Erika
Published: February 2025

This paper presents an effort to provide a level-appropriate study corpus for Lithuanian language learners. The collected corpus includes levelled texts from study books and unlevelled texts from other sources. The main goal is to assign the level-appropriate labels (A1, A2, B1, B2) to texts from other sources. For automatic classification we use preselected surface features, based on text readability research, and shallow linguistic features. First, we train the model with levelled texts from study books; second, we apply the learned model to classifying other texts. The best classification results are achieved with Logistic Regression method.
Hybrid Modeling for Structural Dynamics of Complex Systems Based on Neural Network
Authors: Li Xingmin  , Zhao Tianli  , Zhao Heming
Published: February 2025

To vibration isolation system composed of four wire ropes for the study, and a hybrid modeling method was adopted which neural network mode and a priori knowledge model are connected in series. Multi-DOF hybrid neural network model is established. A method of determining indirectly restoring force of isolation system by the experimental data was proposed through the establishment of the rigid body dynamics equation of vibration isolation system. Through the network training, the neural network model to describe the restoring force characteristics of the four wire rope isolator was established. The simulation results show that the hybrid neural network modeling method has the advantages of high precision, small amount of the training sample data and the modeling cycle is short, etc. Hybrid model contains the physical parameters of the system, and it is very convenient to analyze the effect of parameters.
Self-Information of the Variation in Spatial Parameter Based Audio Attention Model
Authors: Zhu Hua-Dong  , Zhang Cong  , Hang Bo  , Wang Song  , Liu Yu
Published: February 2025

When the spatial orientation of audio object changes rapidly, the human brain will pay attention to audio object. Traditional audio attention model cannot effectively express the situation when the spatial orientation of audio object changes rapidly. In view of the limitations of the existing audio attention model, the self-information of the variation in spatial parameter based audio attention model is proposed. The variation of interaural level difference is used to characterize the variation in spatial orientation of audio object, and the probability matrix of the interaural level difference of each sub-band in audio frame is obtained by off-line statistics of substantial audio training sequences. From the probability matrix and the calculation formula of self-information, the self-information of the variation in interaural level difference of each sub-band in the current frame is obtained. Finally, the audio attention model is established by summing the self-information. After theoretical analysis of the proposed audio attention model, the feasibility of the model is proved.
Detection of Globular Clusters in the Halo of Milky Way
Authors: Mohammadi M.  , Petkov N.  , Peletier R.F.  , Bibiloni P.  , Bunte K.
Published: February 2025

Finding interesting stellar structures inside large astronomical datasets is a challenging task. Depending on the type of data different techniques are needed to tackle this challenge. In this paper, we focus on the GAIA survey DR1, which provides the sky positions and G-band magnitudes for more than 109 stars. We compare the use of the magnitude distribution (or luminosity function) and Difference of Gaussian filtering extracted from small patches of the sky to detect globular clusters (GC). By using a Nearest Neighbor Retrieval strategy we find windows which depict similar magnitude distribution or filter responses compared to the ones extracted from known GCs. Our first results show that the Difference of Gaussian filters are advantageous to find spherical structures such as GC if only limited information, such as sky position and G-band magnitudes, are available.
Three Dimensions in Human-Robot Cooperation
Authors: Fiebich Anika
Published: February 2025

In this paper, I will argue for a three-dimensional approach to cooperation. On this approach, any cooperative phenomenon can be located on the continua of (i) a behavioural axis, (ii) a cognitive axis, and (iii) an affective axis. For example, cooperation can be located on a behavioural axis, ranging from complex to simple coordinated behaviours. The cognitive requirements of cooperation are, according to this model, a matter of degree: they range from cognitively demanding cooperative activities involving shared intentions that presuppose sophisticated social cognitive skills such as having a theory of mind, to basic forms of cooperation like intentional joint attention. Finally, cooperative activities may be influenced by (shared) affective states. The three-dimensional approach trumps alternatives insofar as it facilitates dialogue among disciplines. For example, as I will show, it allows us to determine whether and to which extent particular skills and capacities are implementable in robots and to identify cases in which human-robot cooperation differs in one way or another from human-human cooperation.
The Digitalization of the Working Environment: The Advent of Robotics, Automation and Artificial Intelligence (RAAI) from the Employees Perspective—A Scoping Review
Authors: Terminio Rosanna  , Rimbau Gilabert Eva
Published: February 2025

Robotics, automation and artificial intelligence (RAAI) are changing how work gets done, to the point of putting 47% of existing jobs in the USA at risk of becoming redundant in 5 to 15 years. RAAI and their cognitive abilities have a potential impact on employees' sense of self-worth and career satisfaction and, in turn, on organizations and the society as a whole. In spite of the significant debate on whether there is a real risk of job losses or simply a need of re-skilling, the impact of RAAI on the individual employee has received little attention in academic literature. Therefore, we conducted a scoping review to explore the existing research and professional publications of different quality on the topic and analyze which aspects have received less attention, to properly support policymakers as well as managers' decisions. Existent research, covering different aspects, suggests that the majority of potentially affected workers is not aware nor worried about this ongoing transformation process and they are not properly planning their career. Involvement of the individual in this transition has been proved to bring positive results. However, to get such individual involvement, it will be necessary to identify the correct messages to inform and motivate to the change and avoid producing protests and resistance. For a successful transition, all the stakeholders, including the labor force, have to be part of this dialogue.
Integrating Robotics and Artificial Intelligence in Business Processes—An Organization Theoretical Analysis
Authors: Filzmoser Michael  , Koeszegi Sabine T.
Published: February 2025

In the future work will be characterized by increased collaboration of humans on the one hand and robots and artificial intelligent agents on the other hand. Division of labor, process integration, delegation and accountability are identified as major challenges in such joint business processes. This paper analyzes these topics from an organization theoretical perspective.
A Hybrid Correction Method of English Grammar Error for Chinese Learners' Essays
Authors: Huang Guimin  , Fan Chunli  , Sun Zhenglin
Published: February 2025

Nowadays, English as a Second Language (ESL) learners in China often make errors in grammar while writing English essay. Different approaches to high-quality Grammatical Error Correction (GEC) have been proposed recently. Two typical approaches are rule-based method and statistical-based method when correcting grammatical errors in English essays. The former can't cover all grammar errors in English essays of ESL learners and this led to low accuracy when the former corrects grammar errors in English essays of ESL learners. In contrast, the latter uses statistical approaches to train English essays of ESL learners and get the knowledge of their grammatical errors. This paper proposes GEC method for Chinese English learners and a hybrid approach which combined statistical-based method and rule-based method to GEC. On the one hand, some rules are introduced to solve most of grammar errors, for instance, subject-verb agreement is more complicated and is more effective to determine the errors by linguistic and grammatical rules. On the other hand, the statistical-based method has the advantage in the correction of replacement preposition. The experiment shows that it is able to detect and correct many kinds of grammatical errors and obtained a higher F0.5 score for correction.
Research on the Management Evaluation of the Enterprises Directly Affiliated to a State-Owned Enterprise Group Based on DEA
Authors: Wu Qiaoling  , Zhang Shanshan
Published: February 2025

It is very important to study about the management evaluation of the enterprise, which can help to improve the enterprise's management and complete the strategy of sustainable development. This paper uses DEA evaluation method to evaluate and analyze the enterprises directly affiliated to a State-owned enterprise group. Taking the number of assets and employees as input indicators, and using net profit, income growth rate and social contribution as output indicators, 8 enterprises directly affiliated to the group are selected as evaluation targets. The results were calculated by software. According to the results, the 8 enterprises were deeply evaluated and compared, and the management efficiency of each enterprise was analyzed. Finally, the paper gave some related suggestions and measures for improvement under the content of the analysis.
Construction of the statistical prediction model for the probability of liver cancer based on interpretable artificial intelligence logic
Authors: Wang Zhongxing
Published: February 2025

Current machine learning models under artificial intelligence can only improve prediction accuracy, but their underlying logic remains incomprehensible. Therefore, to provide high prediction accuracy and enhance the interpretability of the model through machine learning, the study selects the Extreme Gradient Boosting (XGBoost) model by comparing multiple models under single learner and integrated learning. Then a cancer probability statistical prediction model is constructed through parameter optimization, and its performance and interpretability are analyzed. The experimental results showed that the Receiver Operating Characteristic (ROC) Area under Curve (AUC) value in the single learner was generally lower than 80%, while the AUC value was 84.4%, surpassing that of the comparison model. Simultaneously, an increase in Alpha-Fetoprotein value greater than 13.5 had a stronger predictive effect when combined with other factors. Smaller serum Alanine Aminotransferase and Alpha-Fetoprotein assay near 0 may produce negative or positive effects, whereas a higher value is more likely to produce a positive effect. This is in line with its clinical significance. Overall, XGBoost effectively improves the out-of-sample prediction accurate and interpretability, which is significant for the actual liver cancer diagnosis prediction.
Design of multi-objective consensus algorithm for logistics industry and transaction services
Authors: Zhang Min , Yang Jining
Published: February 2025

In response to the low efficiency of intelligence in traditional logistics industry and transaction services, the lack of effective consensus mechanisms, and the difficulty in fully considering the mutual influence and conflict between multiple objectives, this article adopts multi-objective consensus algorithm (MOCA) to study the optimization of objectives in the logistics industry and transaction services. Firstly, the needs and objective functions of the shipper, logistics service provider, and recipient can be modeled, and the Analytic Hierarchy Process (AHP) and exponential smoothing methods can be used for target weighting and dynamic weight adjustment. Then, the Multi-Objective Particle Swarm Optimization (MOPSO) algorithm can be introduced to balance the benefits of all parties and find the optimal solution set for the optimization objective. Finally, a consensus mechanism can be established by combining Nash equilibrium and bargaining solution game theory models to achieve fairness in cooperation among the shipper, logistics service provider, and recipient. The experiment collected daily operation records and management systems from a logistics enterprise in Wuhan from June to December 2023. The results showed that in terms of overall efficiency, MOPSO game theory reached 96.5%, an improvement of 6.3% compared to PSO (Particle Swarm Optimization) game theory, and the Benefit Fairness Index (BFI) reached 90.5%. By combining MOCA to optimize the objectives of logistics and transaction services, the intelligence efficiency is greatly improved, ensuring the maximization of benefits and satisfaction for stakeholders.
Open capacity of distribution network including distributed power supply and network reconfiguration
Authors: Zhu Yidong , Zhang Zhe , Liu Hengyu , Zhao Bo , Wang Tong
Published: February 2025

Load access point planning based on network security is the open capacity assessment for distributive networks to reduce power loss. Distribution network operators must meet consumers’ qualitative and statistical power demands and ensure their satisfaction. The distribution network function aims to minimize power loss by determining the network’s maximum power supply capacity while considering parameters like power flow dispersion, node voltage, line capability, and other limitations. The emergence of new flexible loads presents opportunities and challenges. The study suggested Open Capacity Distribution Network solutions incorporating Distributed Power Supply and Network Reconfiguration (OCDN-DPS and NR). The paper proposes a novel technique to optimize distribution networks’ open capacity, addressing the issues faced by the expanding use of distributed energy sources. The proposed study produces a rise of 18% in inaccessible capacity and a decrease in power losses by combining distributed electrical power and reconfiguration of network approaches, demonstrating the efficacy of the presented methodologies. The study uses second-order cone relaxing theory to estimate the distribution of the system’s power supply capability on typical days, taking uncertainty into account to satisfy optimization goals. Comparative analysis indicates the unique approach’s superiority, stressing its significance in promoting sustainable energy options in distribution system optimization while maintaining consumer happiness and network security.
Improving Stabilizer Approximation with Quantum Strategy
Authors: Zuo Fen
Published: February 2025

We introduce a quantum strategy from nonlocal games to improve the stabilizer approximation we proposed previously. The resulting approach turns out to be a qubit-by-qubit gauging procedure for standard stabilizers, which could involve discrete or continuous gauge parameters. We take examples from many-body physics and quantum chemistry to show such a procedure leads to an improvement of the performance.
Make-A-Character 2: Animatable 3D Character Generation From a Single Image
Authors: Liu Lin , Wang Yutong , Chen Jiahao , Li Jianfang , Xue Tangli , Li Longlong , Ren Jianqiang , Bo Liefeng
Published: February 2025

This report introduces Make-A-Character 2, an advanced system for generating high-quality 3D characters from single portrait photographs, ideal for game development and digital human applications. Make-A-Character 2 builds upon its predecessor by incorporating several significant improvements for image-based head generation. We utilize the IC-Light method to correct non-ideal illumination in input photos and apply neural network-based color correction to harmonize skin tones between the photos and game engine renders. We also employ the Hierarchical Representation Network to capture high-frequency facial structures and conduct adaptive skeleton calibration for accurate and expressive facial animations. The entire image-to-3D-character generation process takes less than 2 minutes. Furthermore, we leverage transformer architecture to generate co-speech facial and gesture actions, enabling real-time conversation with the generated character. These technologies have been integrated into our conversational AI avatar products.
Dermatoglyphics: The Future of Screening Type 2 Diabetes Mellitus?
Authors: Ahmed Bilal , Sherazi Syed Raza Mehdi , Amir Urwa , Salahuddin Nimra , Tariq Ramisha , Faiz Abdul Rehman , Butt Muhammad Zuama Zafar , Zahid Rimsha , Rafique Aqib , Mumtaz Asfa
Published: February 2025

BACKGROUND: Dermatoglyphics is a very old technique utilized for identity and distinguishing purposes, as it is firmly related to genetics. Researchers are attempting to utilize fingerprints to diagnose various diseases. This study was aimed at determining the percent distribution of fingerprint patterns and to find out any potential variation between the fingerprints of diabetic and healthy individuals.

METHODS: A comparative study was carried out on 200 individuals at Diabetic Clinic of a tertiary care hospital. 100 participants were patients with uncontrolled diabetes mellitus type 2 (cases) and 100 healthy individuals (controls) were enrolled. Fingerprints of participants were obtained with care on white sheets following the "Cummins and Midlo" method and then categorized as whorls, loops, and arches using Henry's categorization methodology. Fingerprint patterns were compared among both groups, and statistical analysis was done to compare variations.

RESULTS: The mean age of participants was 57.5 ± 9.2 years, and there were 48% males and 52% females. Whorl patterns were found to be more common in both cases and controls (56.2% and 60.8%), followed by loops (38.8% and 31.6%), and then arches (7.6% and 5%). Overall, we found that loops were more prevalent in all fingers of diabetics except the thumbs (57%), where loops were significantly lower (40%). Similarly, whorls were more common in the fingers of healthy individuals (53%), except in the thumbs, where whorls were less prevalent (42%).

CONCLUSION: Present investigation proposes that finger patterns in thumbs can be helpful in differentiating between diabetics and non-diabetics, however, it is difficult to use Henry’s classification for mass screening of diabetes mellitus, but there is a beam of hope that further patterns identification and itemized investigations can help us use dermatoglyphics in screening of different diseases.
Challenges and Perspectives of Corporate Social Responsibility in Madagascar: An Overview of Research and a Strategy Model
Authors: Andrianaivoarimanga Justin Nathanaël
Published: February 2025

This article explores Corporate Social Responsibility (CSR) in Madagascar through various academic studies conducted in key sectors of the country's economy. These studies highlight the importance of CSR in the economic and socio-environmental development of local businesses and the nation. The methodology includes a review, synthesis, and analysis of CSR research carried out over the past five years in the academic field, using the open-source software Iramuteq for lexicometric analysis. The three research questions addressed are: (1) What are the CSR areas already explored? (2) What are the key ideas within each area? (3) What is the current state of CSR research in Madagascar, and what future research directions can be identified? The primary objective of the research is to assess the state of CSR in Madagascar. Specific objectives include (i) identifying CSR areas related to Malagasy businesses, (ii) defining the key ideas of each area, and (iii) establishing research perspectives for CSR in Madagascar. The sectors analyzed include mining, foreign direct investments, the food industry, environmental and social practices, information technologies, construction, and agriculture industry. The findings reveal three main areas: the CSR model, performance management, and the CSR approach. These multidimensional areas highlight that CSR serves as a crucial lever for the economic and social development of businesses in Madagascar, as well as contributing to environmental preservation. Furthermore, the results provide a framework for CSR in Madagascar, encompassing its scope, challenges, and perspectives for applied CSR research. It serves as a valuable alternative to hierarchical and sectarian models. It promotes a deeper understanding of corporate social responsibility across various contexts.
Machine Learning-Driven System for Real-Time Air Quality Monitoring and Prediction
Authors: Dr. S.Usha  , Sadhari Viswa Teja  , Vemula Siva Dilip  , R Subhash Reddy
Published: February 2025

This project introduces a machine learning-driven system for real-time air quality monitoring and prediction, utilizing MQ-135, MQ-9, and MQ-6 sensors alongside a DHT sensor. The MQ-13 sensor measures the concentration of carbon dioxide (CO2) and ammonia (NH3), the MQ-9 sensor detects methane (CH4) and liquefied petroleum gas (LPG), while the MQ-6 sensor monitors alcohol and carbon monoxide (CO) levels. The DHT sensor provides concurrent temperature and humidity data. This multi-sensor data is collected and transmitted to a machine learning model to compute the Air Quality Index (AQI), which represents the overall air quality. The system aims to deliver accurate, real-time air quality assessments and predictive insights, enabling timely interventions and better environmental management. By combining diverse sensor data with advanced machine learning techniques, this approach enhances the precision and effectiveness of air quality monitoring and prediction.
Architecting for Digital Inclusion: Building and Training for Accessible Web Systems at Scale
Authors: Murali Ajit Varma
Published: February 2025

Digital inclusion has emerged as a critical architectural consideration in modern web development, fundamentally reshaping how organizations approach system design and implementation. This article presents a comprehensive framework for building accessible web systems at scale, exploring the integration of accessibility throughout the technical stack. It examines component-level architecture patterns, performance optimization strategies, and DevOps practices that enable truly inclusive digital experiences. Through analysis of real-world implementations and industry case studies, this study demonstrates how systematic approaches to accessibility can be effectively scaled across large organizations while maintaining performance and developer efficiency. It also indicates that early integration of accessibility considerations into architectural decisions leads to more sustainable and inclusive systems, reducing technical debt and improving user experiences across diverse populations. Drawing from established research and industry practices, this article contributes to the growing knowledge on scalable accessibility implementation, offering practical insights for technical leaders and development teams building enterprise-scale accessible web systems.
ДІЯЛЬНІСТЬ ОРГАНІВ КІБЕРБЕЗПЕКИ В УКРАЇНІ ЯК НАПРЯМ ЗАПОБІГАННЯ ТА ПРОТИДІЇ НАСИЛЬСТВА В ДЕРЖАВІ
Authors: ЛЕПЕХ Юлія
Published: February 2025

Подано законодавче визначення кібербезпеки в Україні та статистичні дані щодо цього питання. Зазначено про низьку кількість наукових праць із даного питання. Визначено основні причини кіберзлочинності. Подано причини прогалин у нормативно-правовому регулюванні питання забезпечення кібербезпеки в Україні. Виокремлено психологічні, соціальні та економічні аспекти вищевказаного. Зазначено, що кібербезпека є терміном ширшим за своїм значенням, ніж кіберзахист. Подано систему суб’єктів кібербезпеки в Україні. Визначено рівні суб’єктів забезпечення кібербезпеки в Україні. Подано перелік спеціальних суб’єктів у сфері забезпечення кібербезпеки в Україні. Визначено структурні елементи механізму протидії та запобігання кіберзлочинності. Зазначено про низьку кількість наукових праць та досліджень у сфері реалізації механізму забезпечення кібербезпеки в Україні. Зроблено висновок щодо міжнародного досвіду запобігання та протидії насильства у сфері кіберзлочинності. Зроблено висновок про те, що відсутність належного механізму протидії та запобігання кібербезпеки в Україні призводить до виникнення, поширення психологічного, економічного, сексуального, фізичного насильства, що є загрозою функціонування правової Української держави та розвитку громадянського суспільства. Подано пропозицію щодо отримання працівниками кібербезпеки вищої освіти у спеціальних навчальних закладах, та при необхідності проходити спеціальні курси. Звернено увагу на те, що освітній напрям підготовки працівників кібербезпеки, зважаючи на темпи зростання кіберзлочинності в Україні, в умовах сьогодення повинен здійснюватися з урахуванням матеріальних потреб суспільства та можливостей їхніх громадян.Запропоновано зазначити те, що належний економічний соціальний розвиток держав та суспільства сприяє відсутністю високих показників вчинення кіберзлочинів.
РЕЗОЛЮЦІЇ ООН ЩОДО РОСІЙСЬКОЇ АГРЕСІЇ ПРОТИ УКРАЇНИ 2014–2023: АНАЛІЗ ДИСКУРСУ
Authors: СОЛОВЕЙ Галина , КРУГЛЬОВ Володимир
Published: February 2025

Організація Об’єднаних Націй є головною міжнародною організацією, яка з моменту свого заснування після закінчення Другої світової війни має на меті запобігти розв’язанню Третьої світової війни. Резолюції Генеральної Асамблеї ООН, попри те, що мають рекомендаційний, а не обов’язковий для виконання усіма державами характер, формують контекст і смислові рамки значень термінів у глобальній системі міжнародних відносин. Метою дослідження є з’ясування особливостей риторики ООН щодо російської агресії проти України протягом 2014–2023 років у рамках теорії конструктивізму. Задля цього було здійснено дискурс-аналіз резолюцій, прийнятих ООН щодо України, протягом обраного часового проміжку за методологію Т. ван Дейка, що є провідним спеціалістом у сфері дискурс-аналізу. Дослідники оцінюють реакції ООН на російську агресію з позиції міжнародного права [1] чи з позиції лібералізму, діаметрально протилежно оцінюючи ефективність ООН як міжнародної інституції, мета якої полягає у запобіганні та вирішенні конфліктів [2, 3, 4, 5]. Новизною цього дослідження є методологічний підхід, адже за допомогою методу дискурс-аналізу можна проаналізувати всі прийняті ООН резолюції щодо збройного конфлікту в Україні з 2014 по 2023 рік і визначити зміну риторики цієї організації. Було з’ясовано, що з 2014 року і до початку повномасштабної війни в Україні у 2022 році, війна Росії проти України не називається війною в резолюціях ООН, а Росія прямо не називається агресором, натомість виступає державою, відповідальною за безпеку в регіоні. Після початку повномасштабної війни, Росія в резолюціях ООН визнається агресором, що є повною мірою відповідальним за свої вчинки, проте, війна все одно не називається війною, а є «ситуацією», «кризою» або «конфліктом». Така риторика впливає на сприйняття подій в Україні лідерами світових держав та міжнародним суспільством як заспокоююча та така, що не сприяє закінченню війни за допомогою консолідованих зусиль світового співтовариства проти країни-агресора, а робить її можливою через ігнорування реальності.
РЕФОРМУВАННЯ ТА ТРАНСФОРМАЦІЯ СИСТЕМИ ПУБЛІЧНОГО УПРАВЛІННЯ В УМОВАХ НОВИХ РЕАЛІЙ
Authors: БУРИК Зоряна , КАРСІМ Андрій
Published: February 2025

Процеси європеїзації в Україні вимагають інституційних змін та перебудови системи публічного управління задля покращення якості публічних послуг, забезпечення ефективності діяльності державного апарату та службовців, посилення їх спроможності до задоволення суспільних потреб та вимог. У статті висвітлюються процеси реформування системи публічного управління в умовах нових реалій за такими складовими, як стратегічні засади реформування, формування та координація політики, реформування державної служби та управління людськими ресурсами, підзвітність, надання публічних послуг, управління державними фінансами та державним бюджетом, публічні закупівлі, зовнішній аудит. До основних переваг реформування публічного управління віднесено електронне врядування та цифровізацію адміністративних послуг; зростання рівня підзвітності та прозорості управління публічними фінансами; розвитку законодавчої бази як основи для управління; зростання ролі місцевої влади в управління територіями; покращення стратегічних засад в різних сферах публічного менеджменту та середньострокового планування політик. При цьому, існує ряд проблем, які варто вирішити для продовження процесів трансформації: управління в державній службі та оплата праці державних службовців; зменшення залежності реформи від зовнішніх консультативних служб та зовнішнього фінансування; середній або низький рівень виконання завдань та заходів реформування; корупційні ризики та бюрократичні процедури. Процеси реформування системи публічного управління потребують запровадження кількісних індикаторів вимірювання фактичного стану запровадження заходів для покращення різних сфер суспільного життя.
La Inteligencia Artificial y su Impacto en la Contabilidad Pública un Análisis Teórico.
Authors:   Universidad de Colima/Colima/ México, Lino Gamiño Juan Alfredo
Published: February 2025

La contabilidad está experimentando una transformación gracias a la Inteligencia Artificial (IA). Esta tecnología automatiza tareas repetitivas, permitiendo a los contadores enfocarse en análisis estratégicos. La IA procesa grandes volúmenes de datos contables rápidamente, identificando patrones y anomalías que pueden ayudar a detectar fraudes y tomar mejores decisiones.
Este estudio, basado en una revisión bibliográfica, revela que la IA aumenta la productividad y precisión en la contabilidad, reduciendo costos y tiempo. Entre los beneficios se encuentran la automatización de tareas rutinarias, la detección de fraudes y la generación automática de informes. Sin embargo, su implementación presenta desafíos, como los costos y la necesidad de capacitación.
A pesar de los obstáculos, los beneficios de la IA, como la precisión en las predicciones financieras y la mejora de la seguridad, superan ampliamente las dificultades, posicionándola como una herramienta fundamental para el futuro de la contabilidad.
Eficiencia de la inteligencia artificial como modelos de optimización y pronóstico en los mercados bursátiles
Authors:   Universidad de Guadalajara/Jalisco/México, Corona Pacheco cesar , Olivares Medina Kevin Omar ,   Universidad de Guadalajara/Jalisco/México, Moreno Flores Dante ,   Universidad de Guadalajara/Jalisco/México
Published: February 2025

El documento muestra un análisis realizado por medio de modelos de Inteligencia Artificial para hacer comparativas en las predicciones de carteras de inversión en México y Estados Unidos, se utilizó los modelos ARIMA para la predicción de series temporales en comparación con la red neuronal de perceptrón multicapa y enjambre de partículas en la selección óptima de cartera. También se aplica la teoría de Markowitz (1952), para identificar el tipo de cartera en la frontera eficiente. El estudio muestra que la inteligencia artificial puede ayudar al diseño de mejores estrategias de inversión en un tiempo determinado. El estudio tiene como limitante que solo se tomaron las principales empresas de los países antes mencionados, pero el modelo se puede replicar con muestras más grandes incluso en otras bolsas de valores.
ADEQUACY OF INFLATION-INDEXED LIFE ANNUITY: A CASE OF DEFINED CONTRIBUTION PENSION PLAN IN MALAYSIA
Authors: Kamal Zarul Khaliff , Ismail Noriszura
Published: February 2025

Defined Contribution (DC) pension plans in some Asian countries are currently operated by the lump-sum withdrawal scheme, which allows retirees to withdraw all accrued savings in a single withdrawal. This type of withdrawal does not protect pensioners from the longevity risk. This study examines the adequacy of an alternative for the lump-sum withdrawal system, namely the withdrawal system based on the Inflation-Indexed Life Annuity (IILA). This study proposes two types of IILA: the immediate IILA and the deferred IILA. The adequacy of a life annuity is measured using the ratio of projected wealth to the projected consumption at the retirement age. For the deferred IILA, this study uses the Euler-Lagrange method to assess the optimal amount that will be set aside to finance the annuity scheme. The IILA and deferred IILA will protect retirees from purchasing under-valued annuities by adjusting the IILA to inflation risk. Furthermore, deferred IILA may improve the life quality of retirees by providing adequate retirement income during the deferment years. Analysis of data from the Household Income and Expenditure Survey (HEIS, 2014) indicates that the immediate IILA offers an average lifetime income of over 50%, while the deferred IILA provides more than 40%.
Reseña de Zopa (2022) Silencia tu mente. Enciende tu corazón
Authors: Lopez Ruiz Patricia Teresa
Published: February 2025

Hay obras que nos deslizan hacia mundos posibles de ensueño y fantasía, otras que transitan sombras que nos adentran en la trágica separación de la unidad que oprime al mundo y otras que iluminan los vastos y profundos ámbitos del ser, impulsándonos, con un saber más pleno, a resbalar hacia una vida más enriquecida por sensaciones anteriormente no interceptadas. Silencia tu mente. Enciende tu corazón pertenece a la estirpe de obras del tercer tipo, difíciles de hallar, más aún cuando se busca que mantengan ese complejo equilibrio entre lo riguroso, sustancial, especializado y veraz y la sencillez, amenidad y hermetismo narrativo.
Influencia de sustratos de arena y soluciones orgánicas en la concentración de compuestos fenólicos de albahaca (Ocimum basilicum L.) extraídos con solventes orgánicos
Authors: Moncayo-Lujan María del Rosario , Ramírez-Aragón Mercedes Georgina , Ortiz-Escobar Tania Breshkovskaya , Guzmán-Silos Tania Lizeth , Segura-Castruita Miguel Ángel
Published: February 2025

El tipo de sustrato y solución nutritiva influyen en el contenido de compuestos fenólicos en plantas de consumo humano; no obstante, el tipo de solvente que se utiliza para la extracción de los compuestos fenólicos puede jugar un papel preponderante en los resultados. Los objetivos de este estudio fueron determinar la producción de compuestos fenólicos (CF) de albahaca cultivada en dos sustratos con aplicaciones de cuatro soluciones nutritivas bajo condiciones de invernadero, y evaluar el efecto de tres solventes orgánicos en solución acuosa sobre la extracción de CF. Los resultados mostraron que la albahaca cultivada en arena con aplicaciones de una solución nutritiva de vermicomposta tuvo una concentración de CF de hasta 10.60 mg AG equiv/g BS, cuando se extrajo con acetona en solución acuosa.
Pensiones por jubilación en la ley del seguro social: primeros cambios paramétricos
Authors: Atlatenco-Ibarra Quetzalli , De la Garza-Carranza María Teresa , López-Lemus Jorge Armando
Published: February 2025

Mediante el ramo de retiro, cesantía en edad avanzada y vejez, los trabajadores que prestan sus servicios a la iniciativa privada, reciben una pensión por jubilación si cumplen con algunos requisitos de edad y tiempo de aportaciones al sistema de seguridad social. En julio de 1997 entró en vigor una modificación estructural a dicho ramo que cambió radicalmente la forma de cálculo y financiamiento de las pensiones por jubilación y fue hasta enero de 2021 que se implementaron las primeras reformas paramétricas que hacen más asequible para los trabajadores recibir una pensión. En este trabajo se hace una revisión de dichas modificaciones y de algunas que se efectuaron anteriormente relacionadas con el régimen de inversión de los recursos aportados por trabajadores, patrones y Gobierno Federal que, durante la vida laboral en el sector formal, se acumulan en cuentas individuales creada para financiar las pensiones por jubilación de los trabajadores.
Atributos relevantes del trabajo en equipo basados en la percepción de estudiantes de posgrado y su efecto para generar aprendizaje
Authors: Urbina-Nájera Argelia Berenice
Published: February 2025

El objetivo de este estudio es determinar los atributos más relevantes que según la percepción de los estudiantes de posgrado definen al trabajo en equipo. El diseño de la investigación es de tipo no experimental y comparativa sobre los atributos que definen al trabajo en equipo antes y después de la pandemia por COVID-19. Para ello, se aplicó una encuesta adaptada a 308 estudiantes de posgrado y se analizaron mediante el algoritmo selección de atributos. Los resultados muestran que el trabajo en equipo facilita el aprendizaje individual y colectivo, desarrolla habilidades interpersonales y comunicativas, siendo la comunicación, la confianza, la empatía y el liderazgo los atributos más importantes a fortalecerse; que el trabajo en equipo es una práctica pedagógica que favorece el sentido de pertenencia, agrado por el trabajo y ayuda a que desaparezcan emociones perturbadoras.
Mapa de isosistas de las aceleraciones sísmicas máximas del suelo, provocadas por el sismo ocurrido el 7 de septiembre de 2021 en el estado de Guerrero
Authors: Flores-Martínez Ricardo , Arroyo-Matus Roberto , Ramos-Bernal Rocío Nayelly
Published: February 2025

Este trabajo presenta los resultados obtenidos al analizar el comportamiento de las curvas isosistas generadas por las aceleraciones sísmicas máximas horizontales del suelo por el sismo ocurrido el 7 de septiembre de 2021 en el estado de Guerrero. Para la elaboración del mapa de isosistas se utilizó información de la Red Acelerográfica del Instituto de Ingeniería de la UNAM (RAII-UNAM), información complementada con la estimación de datos a partir de una regresión exponencial de los datos obtenidos mediante el programa curve expert. Se compararon curvas teóricas de atenuación de Clemente Chávez (2010) y García et al. (2005) con la curva generada por la regresión de los datos. La elaboración del mapa de isosistas se realizó con ayuda del software de los Sistemas de Información Geográfica (SIG), permitiendo identificar las zonas donde se presentaron mayores aceleraciones sísmicas y la atenuación de las aceleraciones respecto a la distancia.
enfoque narrativo para entender el proceso de cambio en las creencias de docentes de inglés sobre evaluación
Authors: Collazo-García José Armando , Gutiérrez-Marfileño Victoria Eugenia
Published: February 2025

La evaluación es parte clave del proceso de aprendizaje, pues informa sobre fortalezas y áreas de oportunidad tanto a docentes como estudiantes. Por ello, resulta importante entender cómo es concebida la evaluación desde las creencias del profesor y sus prácticas en el aula. El siguiente trabajo deriva de una tesis doctoral de enfoque cualitativo, cuyos resultados provienen del análisis narrativo temático de la información obtenida a través de entrevistas con 12 profesores de inglés en dos instituciones de nivel superior en el estado de Aguascalientes, México. Las conclusiones se resumen en que las creencias docentes sobre la evaluación se caracterizan por: 1) ser de naturaleza dinámica; 2) atravesar por un proceso de mediación al verse desafiadas por el entorno; y 3) estar relacionadas de manera parcial con lo que el docente hace en el aula, resultando en ajustes tanto en las creencias del docente como en sus prácticas evaluativas.
La experiencia directiva durante la suspensión de clases presenciales derivada de la pandemia COVID-19 en escuelas primarias públicas de Aguascalientes
Authors: Razo-Ruvalcaba Alma Cristina , Ruiz-Cuéllar Guadalupe
Published: February 2025

El artículo presenta hallazgos de una investigación cuyo objetivo fue explorar y describir la experiencia que vivieron los directivos de escuelas primarias públicas en Aguascalientes durante la suspensión de clases presenciales debido a la pandemia de la COVID-19. La metodología fue cualitativa con enfoque fenomenológico; se entrevistó a 16 directivos. Entre los hallazgos destaca que, de acuerdo con los directivos, su proceso de adaptación a la educación remota de emergencia estuvo marcado por la incertidumbre, la improvisación y la sobrecarga laboral. Para continuar con el servicio educativo remoto los directivos realizaron cambios en sus prácticas cotidianas tales como la incorporación de la tecnología y la forma de comunicarse con la comunidad educativa para crear estrategias en conjunto para continuar el aprendizaje de los alumnos.
Estudio analítico y numérico de probetas agrietadas sometidas a tensión
Authors: German-Carcaño Jesús Manuel , Urriolagoitia-Sosa Guillermo , Romero-Ángeles Beatriz , Maya-Anaya Daniel , Sánchez-Cervantes Arturo , Correa-Corona Martín Iván , Urriolagoitia-Calderón Guillermo Manuel
Published: February 2025

Este trabajo describe la evaluación analítica del Factor de Intensidad de Esfuerzo (SIF) para cuatro especímenes, sometidos a una tensión de 15 MPa y una longitud de grieta de 25 mm. Posteriormente, con ayuda del programa ANSY S® se realizan las simulaciones numéricas donde se obtiene el SIF, para los especímenes estudiados analíticamente. Adicionalmente, se muestran los campos de esfuerzos σx, σy, τxy, σMax, min y σVon Mises cercanos a la punta de la fisura. A continuación, se calcula el porcentaje de variación de los análisis antes realizados, con resultados positivos en todos los casos (< 0.4 %). Por lo que se puede aseverar que es confiable el uso del Método de Elementos Finitos (MEF) a través del programa ANSYS®, para la solución de problemas en fractura. Además, de que el trabajo numérico realizado puede proporcionar algunas pautas para mejorar la estimación del SIF en problemas bidimensionales.
Análisis de accidentabilidad en autopistas de dos carriles de la red federal de cuota en México
Authors: García-Díaz Cyntia Elizabeth , Morales-Rosales Luis Alberto , Hurtado-Beltran Antonio , Arreygue-Rocha José Eleazar
Published: February 2025

A diferencia de lo que ocurre en países desarrollados, donde las autopistas de la red troncal tienen una configuración multicarril, una parte significativa de la red troncal en México está constituida por autopistas de 2 carriles (un carril por sentido). Este artículo presenta un análisis descriptivo de los datos de accidentes reportados en la red de autopistas de 2 carriles de cuota en México, con la finalidad de conocer el estado actual de su fenómeno de accidentabilidad. Se encontró que el índice de accidentabilidad global en las autopistas de 2 carriles de cuota es aproximadamente el doble del observado en la red carretera nacional, revelando una accidentabilidad significativamente mayor. Adicionalmente, se identificaron los tramos carreteros que muestran una tendencia a agravar su fenómeno de accidentabilidad en el futuro próximo. Este estudio proporciona información valiosa a los tomadores de decisiones para mejorar los programas de gestión de la seguridad vial.