bluuebunny/crossref_metadata_2025 huggingface dataset:
Implementing a rapid application development course in higher education and measuring its impact using Kirkpatrick’s model: a case study at Vilnius Gediminas Technical University
Authors: Radvilaitė Urtė , Kalibatienė Diana , Stankevič Jelena
Published: October 2024

Nowadays, technological development and improvement in business is happening rapidly, so higher education (HE), and not only, studies should constantly provide and develop new up-to-date knowledge and skills to students, in order to train competitive specialists, address digital transformation by developing digital readiness of higher institutions, and increase employment opportunities of students. Consequently, this paper discusses the implementation of the newly developed courses for teaching Rapid Application Development (RAD) on the Oracle Application Express platform into the studies at Vilnius Gediminas Technical University (VILNIUS TECH) and presents the effectiveness of the implementation of this course measured using Kirkpatrick’s model. The obtained results show that students’ knowledge of RAD increased after attending the course. In addition, a 76% agreed that this course increased their knowledge of the subject matter.
Efficient Survey Design for Finding High-redshift Galaxies with JWST
Authors: Vujeva Luka , Steinhardt Charles L. , Jespersen Christian Kragh , Frye Brenda L. , Koekemoer Anton M. , Natarajan Priyamvada , Faisst Andreas L. , Hibon Pascale , Furtak Lukas J. , Atek Hakim , Cen Renyue , Sneppen Albert
Published: October 2024

Several large JWST blank field observing programs have not yet discovered the first galaxies expected to form at 15 ≤ z ≤ 20. This has motivated the search for more effective survey strategies that will be able to effectively probe this redshift range. Here, we explore the use of gravitationally lensed cluster fields, which have historically been the most effective discovery tool with the Hubble Space Telescope. In this paper, we analyze the effectiveness of the most massive galaxy clusters that provide the highest median magnification factor within a single JWST NIRCam module in uncovering this population. The results of exploiting these lensing clusters to break the z > 15 barrier are compared against the results from large-area, blank-field surveys such as JADES and CEERS in order to determine the most effective survey strategy for JWST. We report that the fields containing massive foreground galaxy clusters specifically chosen to occupy the largest fraction of a single NIRCam module with high magnification factors in the source plane while containing all multiple images in the image plane within a single module provide the highest probability of both probing the 15 ≤ z ≤ 20 regime as well as discovering the highest-redshift galaxy possible with JWST. We also find that using multiple massive clusters in exchange for shallower survey depths is a more time-efficient method of probing the z > 15 regime.
Modeling the Time Evolution of Compact Binary Systems with Machine Learning
Authors: Yan Jianqi , Luo Junjie , Zeng Yifan , Leung Alex P. , Feng Jie , Zhang Hong-Hao , Lin Weipeng
Published: October 2024

This work introduces advanced computational techniques for modeling the time evolution of compact binary systems using machine learning. The dynamics of compact binary systems, such as black holes and neutron stars, present significant nonlinear challenges due to the strong gravitational interactions and the requirement for precise numerical simulations. Traditional methods, like the post-Newtonian approximation, often require significant computational resources and face challenges in accuracy and efficiency. Here, we employed machine learning algorithms, including deep learning models like long short-term memory (LSTM) and temporal convolutional network (TCN), to predict the future evolution of these systems based on extensive simulation data. Our results demonstrate that employing both LSTM and TCN even as black-box predictors for sequence prediction can also significantly improve the prediction accuracy without physics-informed neural networks (as partial differential equation solvers with prior knowledge or inductive bias. By employing LSTM and TCN, we obtained R
2 values of 99.74% and 99.19% for the evolutionary orbits of the compact binaries data set, respectively. Our models demonstrate the ability to effectively capture the dynamics of the binaries, achieving high prediction performance with significantly reduced computational overhead by a factor of 40, compared to conventional numerical methods. This study paves the way for more effective and computationally scalable approaches to the understanding of gravitational phenomena and predictive modeling in gravitational-wave astronomy.
Subhalos in Galaxy Clusters: Coherent Accretion and Internal Orbits
Authors: Han Chi , Wang Kuan , Avestruz Camille , Anbajagane Dhayaa
Published: October 2024

Subhalo dynamics in galaxy cluster host halos govern the observed distribution and properties of cluster member galaxies. We use the IllustrisTNG simulation to investigate the accretion and orbits of subhalos found in cluster-size halos. We find that the median change in the major axis direction of cluster-size host halos is approximately 80° between a ∼ 0.1 and the present day. We identify coherent regions in the angular distribution of subhalo accretion, and ∼68% of accreted subhalos enter their host halo through ∼38% of the surface area at the virial radius. The majority of galaxy clusters in the sample have ∼2 such coherent regions. We further measure angular orbits of subhalos with respect to the host major axis and use a clustering algorithm to identify distinct orbit modes with varying oscillation timescales. The orbit modes correlate with subhalo accretion conditions. Subhalos in orbit modes with shorter oscillations tend to have lower peak masses and accretion directions somewhat more aligned with the major axis. One orbit mode, exhibiting the least oscillatory behavior, largely consists of subhalos that accrete near the plane perpendicular to the host halo major axis. Our findings are consistent with expectations from inflow from major filament structures and internal dynamical friction: most subhalos accrete through coherent regions, and more massive subhalos experience fewer orbits after accretion. Our work offers a unique quantification of subhalo dynamics that can be connected to how the intracluster medium strips and quenches cluster galaxies.
A Deeper Look into eFEDS AGN Candidates in Dwarf Galaxies with Chandra
Authors: Sanchez Adonis A. , Reines Amy E. , Bogdán Ákos , Kraft Ralph P.
Published: October 2024

The ability to accurately discern active massive black holes (BHs) in nearby dwarf galaxies is paramount to understanding the origins and processes of “seed” BHs in the early Universe. We present Chandra X-ray Observatory observations of a sample of three local dwarf galaxies (M
* ≤ 3 × 109
M
⊙, z ≤ 0.15) previously identified as candidates for hosting active galactic nuclei (AGN). The galaxies were selected from the NASA-Sloan Atlas with spatially coincident X-ray detections in the eROSITA Final Equatorial Depth Survey. Our new Chandra data reveal three X-ray point sources in two of the target galaxies with luminosities between log(L
2−10 keV [erg s−1]) = 39.1 and 40.4. Our results support the presence of an AGN in these two galaxies and an ultraluminous X-ray source (ULX) in one of them. For the AGNs, we estimate BH masses of M
BH ∼ 105−6
M
⊙ and Eddington ratios on the order of ∼10−3.
Progress or burden? Formal description of every apparently new species available in collections is neither necessary nor useful
Authors: Huber Bernhard A. , Szymański Hubert , Bennett-West Alice
Published: October 2024

A new species of the Sub-Saharan spider genus Quamtana Huber, 2003 is described that has been collected in garden centers in Poland and the UK. Its closest known relative is probably Q. lotzi Huber, 2003, known from Free State Province in South Africa. Working on the premise that placing species in time and space is the fundamental task of taxonomy, and acknowledging that we cannot provide biologically meaningful spatial information for this species, we prefer open nomenclature to make this species known to science without formally describing it, using the unique provisional name Quamtana sp. ZFMK Ar 24490 aff. lotzi. We argue that the judicious use of open nomenclature can serve to improve the quality of species lists, reducing the noise in large-scale analyses of biodiversity data. We expand this argument to ‘fragmentary’ species descriptions in general, such as single-sex descriptions in large genera with many male-only and female-only descriptions. Not every taxonomic act allowed by the Code is necessarily beneficial. Under certain conditions, the informal description of a putatively new species may serve science better than a formal description based on inadequate material or data.
Treba li Republika Hrvatska potvrditi Konvenciju o odgovornosti i naknadi štete u svezi prijevoza opasnih i štetnih tvari morem iz 2010.?
Authors:   Pravni fakultet Sveučilišta u Rijeci, Ćorić Dorotea , Tuhtan Grgić Iva ,   Pravni fakultet Sveučilišta u Rijeci
Published: October 2024

Sustav građanskopravne odgovornosti za štete nastale onečišćenjem mora s brodova na međunarodnoj razini još uvijek nije potpun, jer na snagu nije stupila Međunarodna konvencija o odgovornosti i naknadi štete u svezi prijevoza opasnih i štetnih tvari morem iz 2010. Konvenciju je potvrdilo osam država, a tri su države za znatnom količinom kontribuirajućeg tereta u završnom postupku pripremnih radnji za njezino potvrđivanje, pa se može očekivati da će Konvencija u doglednoj budućnosti skupiti 12 država stranaka i time ispuniti uvjete za stupanje na snagu. Povećan promet opasnih i štetnih tvari morem na području Republike Hrvatske i povećan rizik koje takav promet sa sobom nosi svakako nameću potrebu preispitivanja potrebe za potvrđivanjem ove Konvencije svakoj državi, a posebice onim državama kojih je gospodarstvo oslonjeno na prihode iz obalnog turizma, kao što je Republika Hrvatska. U radu se skreće pozornost na fragmentarno uređenje ove materije u nacionalnom pravu te se daje prikaz konvencijskih rješenja, primjena kojih bi osigurala pravičnu i učinkovitu naknadu za sve štete nastale prijevozom opasnih i štetnih tvari morem. Konvencija predviđa dvoslojni sustav odgovornosti – uz vlasnika broda, u drugom sloju odgovara HNS fond. Autori su snažnog uvjerenja da bi Republika Hrvatska trebala započeti s pripremnim radnjama koje je potrebno provesti prije potvrđivanja Konvencije, vezanima uz uspostavu sustava za izvješćivanje o primateljima tereta i količini tereta koji podliježe plaćanju doprinosa prema Fondu, a potom Konvenciju i potvrditi.
The Ban of Political Parties – An Analysis of the Criteria Developed by the German Federal Constitutional Court and the European Court of Human Rights and their Interconnection
Authors:   Faculty of Law of the University of Maribor, Dacar Rok
Published: October 2024

It is possible to ban political parties in many modern democracies. However ideologically extreme they may be, their ban constitutes a violent interference in the political sphere and should therefore only be applied in particularly justified cases. The article analyses the relevant case law of the German Federal Constitutional Court and the European Court of Human Rights. It comes to the conclusion that the jurisprudence of the two courts is closely linked and builds on each other. Moreover, by today’s standards, it is not possible to ban a political party that has an unconstitutional programme, even if it tries to implement it aggressively and violently, as long as it is not in a position to actually implement it, i.e. it does not have the necessary political power.
Human Resource Management in the Epoch of Generative AI
Authors: Gowrishankkar V. , Shanmugam Vidhya , Muhammed Adamu Abubakar , Sanjeevan B. , Veerachamy R. , Maheswaran M.
Published: October 2024

Artificial intelligence is revolutionizing various business functions, including human resources, and is becoming integral to human resource practices. Generative AI enhances the management of human capital, leading to more equitable, performance-based, and market-responsive compensation structures. Artificial intelligence-enabled predictive analytics and automation capabilities can also revolutionize benefits administration. However, integrating artificial intelligence poses challenges such as ethical considerations, data security, and potential unintended biases. Human resource leaders must navigate artificial intelligent integration with a focus on upholding employee rights and fostering a culture of trust and transparency. This chapter explores the intersection of artificial intelligent and human resources, the opportunities and challenges it presents for modern human resource professionals, its impact on their roles, and guiding principles to consider.
Human Resource Management Practices in the Age of Industrial Automation
Authors: Praba K. , Vijay B. , Abuya Joshua Olang'o , Poreddy Deepthi , Mulakala Srinivas , Manoharan Sendhilkumar
Published: October 2024

The advent of industrial automation has ushered in a transformative era, fundamentally altering operational dynamics and workforce structures across various sectors. Technologies such as robotics, artificial intelligence, and machine learning have enhanced efficiency, productivity, and precision in industries ranging from manufacturing and logistics to healthcare and finance. However, these advancements present unique challenges and opportunities for human resource management, necessitating a reevaluation of traditional practices. Human resource management must adapt to the integration of automated systems with human labor, focusing on talent acquisition, training, performance management, and employee engagement. As automation reshapes job roles and skills requirements, HR professionals must manage a hybrid workforce, address ethical considerations, and ensure data privacy and security. The goal is to equip HR professionals and industry stakeholders with the knowledge and tools to navigate the evolving landscape of industrial automation and its implications for the future workforce.
Artificial Intelligence for Sustainable Futures
Authors: Samanvitha C. , Dharmendra H. , Nethravathi N. , Velmurugan Palanivel Rathinasabapathi
Published: October 2024

Artificial intelligence (AI) is emerging as a transformative force in promoting environmental and social sustainability. This chapter explores the multifaceted role of AI in navigating the complex landscape of sustainable futures. By leveraging advanced algorithms and data analytics, AI offers innovative solutions for optimizing resource management, reducing carbon footprints, and enhancing biodiversity conservation. Moreover, AI-driven technologies are pivotal in addressing social challenges, fostering inclusive economic growth, and ensuring equitable access to resources. The integration of AI into sustainable practices underscores the potential for creating resilient and adaptive systems that align with global sustainability goals. This comprehensive analysis highlights the critical intersections of AI, environmental stewardship, and social responsibility, advocating for a balanced approach that harnesses technological advancements to foster a sustainable and equitable future.
Exploring the Intersection of Social Work and the Future of Technology
Authors: Rahman Mirshad , B. S. Sachin , Channabasaiah Kumaraswamy , C. R. Rashmi , Deepika N. , Velusamy Kalyani
Published: October 2024

The intersection of social work and technology represents a transformative frontier poised to revolutionize service delivery and accessibility. This chapter explores how technological advancements enhance social work, focusing on integration strategies, ethical implications, and future adoption recommendations. The significance lies in tackling resource limitations and accessibility barriers. AI and machine learning enable predictive analytics for identifying at-risk populations, while automation streamlines administrative tasks, enhancing direct client interactions. Big data guides decisions and interventions, while telehealth improves remote mental health access. Mobile apps enhance engagement, monitoring, and communication but raise ethical concerns about human connection, data privacy, and equitable access. Balancing efficiency gains with job displacement risks is crucial. This chapter equips stakeholders with insights for navigating this evolving landscape, aiming for effective, ethical, and equitable social work practice rooted in core values.
Emerging Trends of Graphene-Based Nanomaterials as Digital Materials for Data Generation in Industry 4.0
Authors: Sundar Sasikala , Nitin Sheetal
Published: October 2024

Industry 4.0 represented the ongoing transformation of manufacturing and industry through the integration of digital technologies, automation, and data exchange. Key technologies driving Industry 4.0 include the internet of things (IoT), artificial intelligence (AI), big data analytics, robotics, and additive manufacturing (3D printing). This revolution aims to create “smart factories” that are more efficient, flexible, and interconnected, enabling the optimization of production processes and the customization of products to meet individual customer needs. In this chapter, the authors have analysed the conception, challenges, and the future scope of Industry 4.0 by the role of grapheme-based 2D material-enhanced composites, which can serve as a bridge between real-world and virtual environments. An overview of the use of graphene-based smart embedded sensors in real-time structural health monitoring is presented, along with their application at different stages of the manufacturing processes for composites. They have also addressed the technical challenges associated with integrating digital space with graphene-based sensing networks. Moreover, a summary provides the importance of graphene-based devices and structures are integrated with related technologies like artificial intelligence, machine learning, sensors, energy storage devices, and blockchain technology. Owing to its advantageous characteristics and the synergistic benefits that arise from combining its various properties, graphene is hailed for several applications. Graphene is already being used in a wide range of commercial applications, and more are still being developed. Graphene is also anticipated to have an impact on industrial automation shortly. Absolutely, the transition towards automation in manufacturing and industrial processes, often referred to as Industry 4.0, brings about numerous benefits like cost efficiency, automation, system monitoring, early warning systems, and optimization with minimal human input.
Intelligent Machine Learning Solutions for Cybersecurity
Authors: Singh Bhupinder , Kaunert Christian
Published: October 2024

Cybersecurity threats have dramatically advanced over the last 10 years, with cybercriminals using increasingly sophisticated techniques to infiltrate systems. Ransomware attacks, phishing schemes, and advanced persistent threats (APTs) are just a few examples of the myriad challenges that organizations face globally. The financial losses and reputational harm from these incidents highlight the critical need for strong cybersecurity measures. Machine learning has become an essential tool in the fight against cyber threats. With utilizing large datasets, ML algorithms can detect patterns and anomalies indicative of malicious activity. This ability significantly improves the effectiveness of cybersecurity systems in identifying, responding to, and mitigating attacks in real-time, thus narrowing the window of opportunity for cybercriminals. This chapter comprehensively explores the diverse arena of the intelligent machine learning solutions for cybersecurity concerning legal and ethical considerations in global context.
Leveraging Intelligent Process Automation for Customer Engagement in Sales and Marketing
Authors: Sharma Anil , Gangwar Veer P. , Bhattacharyya Atanu , Giri Udayan , Chavan Ganesh , Mahato Surendra
Published: October 2024

Customer engagement is a crucial system for managing business relationships with clients, aiming to build strong alliances and enhance interactions through data analysis and historical evaluation. Digital transformation shifted customer engagement, using technologies like automation, big data analytics, cloud computing, and artificial intelligence to improve efficiency, effectiveness, and personalization. This transformation enhances customer experiences, streamlines processes, and gains an edge. It enables organizations to gather and analyze vast amounts of customer data, providing valuable insights for personalized marketing campaigns, product recommendations, and tailored experiences. Automation and AI play a crucial role in this transformation, streamlining processes and proactive customer care. This chapter explores the impact of digital transformation on customer engagement, focusing on improving customer loyalty and engagement. It reviews strategies, resources, and best practices for digital CE projects, emphasizing benefits, challenges, success factors for organizations.
Role of Intelligent Process Automation in the Banking and Financial Services Industry
Authors: Rajput Kanchan Gulabsing , C. Shree Harsha , Lingam Muthu Aravinthan Muthu , Duraisamy Durairaj , Bhargavi Chittimalla , Sravanthi M. , S. E. Mahrinasari
Published: October 2024

The banking and financial services industry is experiencing a transformative shift due to intelligent process automation (IPA) technologies. This chapter examines how IPA is revolutionizing operational processes, enhancing efficiency, accuracy, and customer experience. Through a literature review and case studies, the authors explore IPA techniques such as robotic process automation (RPA), artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) in customer service, risk management, compliance, and back-office operations. The benefits and challenges of IPA implementation are highlighted, emphasizing strategic planning, stakeholder engagement, and organizational readiness. This chapter provides valuable insights and practical guidance for banking professionals, policymakers, researchers, and industry stakeholders aiming to harness IPA for operational excellence and sustainable growth.
DDM
Authors: Nasurudeen Ahamed N. , Sridevi S.
Published: October 2024

To create a campaign blueprint, data-driven marketing optimizes client details. To comprehend our clients entails gathering complicated data through online and physical channels and evaluating it. Through the collection and analysis of information, advertisers create and execute highly customized advertising efforts. Digital advertising is an essential tool for advertising tactics because it's a great way to promote and sell products as well as raise brand knowledge and visibility. Even with the rise of online communities and networking sites, marketing through email remains the most popular way to educate, impact, and create business opportunities. Big Data is thought to revolutionize corporate intelligence, a discipline that depends on statistical analysis to gain understanding and improve making choices. Although the idea of big data is not exclusive to advertising or trade, the growth of e-commerce and online advertising has been crucial in raising awareness of the problem. These industries indeed produce enormous amounts of data by nature that need to be processed.
Enabling Hyper-Personalization in AI-Powered BI Systems
Authors: Kanagaraj Prabavathy , Chellathurai Samuel
Published: October 2024

The integration of Artificial Intelligence (AI) into Business Intelligence (BI) systems has become a game-changing tool for enterprises navigating the intricacies of a quickly changing digital ecosystem. Traditionally, business intelligence methods have concentrated on compiling and examining huge datasets in order to extract broad insights. The ability of artificial intelligence (AI) to drive hyper-personalization—which enables businesses to recognize and address the unique needs of each individual customer, employee, and stakeholder—will be crucial to the future of business intelligence (BI). This chapter offers to investigate the paradigm change toward hyper-personalization in AI-powered BI systems, focusing on the technology breakthroughs, trends, and future directions guiding this transformative journey. Augmented Analytics, a disruptive method that uses AI and machine learning algorithms, has emerged as a catalyst for enabling hyper-personalization in AI-powered Business Intelligence (BI) systems.
Adaptação transcultural e validação estatística do assessment of interprofessional team collaboration scale ii
Authors: Farias Emanuella Pinheiro de , Rossit Rosana Aparecida Salvador
Published: October 2024

Estudo metodológico que teve como objetivo descrever os critérios de construção, validaçãode conteúdo e aparência do instrumento “Escala de Avaliação da Colaboração Interprofissional em Equipe – AITCS II” (ORCHARD, 2015). A validação seguiu quatro etapas: Avaliação de equivalências conceitual e de itens; Avaliação da equivalência semântica; Equivalência Operacional; e Equivalência de Mensuração. Para avaliar a consistência interna do instrumento, empregou-se o coeficiente Alfa de Cronbach nos conjuntos de itens que compõem cada uma das três dimensões. Para estudar a concordância entre as duas avaliações realizadas, foram construídos gráficos de Bland-Altman, calculados coeficientes de correlação intraclasses e aplicados o Teste t de Student para amostras relacionadas e o Teste do Sinal. Conclui-se que o instrumento possui validade de conteúdo e de aparência para avaliar a atuação e prática interprofissional, tendo obtidocoeficientes de consistência e concordância com índices superiores a 0,8.
Temas de análises clínicas 2
Authors: Baratieri Sabrina , Hirata Bruna Karina Banin , Mossini Simone  Aparecida Galerani , Manchinski Junior Miguel , Hirata Bruna Karina Banin , Lonardoni Maria Valdrinez Campana , Nakama Raquel Pires , Pinge-Filho Phileno , Aguera Raul Gomes , Zacarias Joana Maira Valentini , Visentainer Jeane Eliete Laguila
Published: October 2024

O carcinoma mamário, com exceção do câncer de pele não melanoma, é o tipo  de câncer que mais acomete a população feminina, com uma estimativa de 73.610 novos  casos para o ano de 2023, no Brasil. O microambiente tumoral mamário pode apresentar  infiltrado de diferentes células do sistema imunológico, incluindo as células Natural Killer  (NK) e os linfócitos T citotóxicos (CTL), que exercem efeito anti-tumoral, através da  liberação de granzima B.
Assessing Supply-Side Determinants of Passenger Satisfaction in Long-Distance Expressway Bus Services in Sri Lanka: A Case Study of Southern Expressway
Authors: Abeywickrama K. L. S. , Danthanarayana C. T.
Published: October 2024

The transportation sector plays a vital role in fostering economic growth, societal connectivity, and individual mobility. Long-distance bus services have emerged as a prominent mode of transportation, offering an efficient and cost-effective means of travel for both urban and intercity commuters. This study aims to comprehensively assess and elucidate the supply-side determinants that significantly impact passenger satisfaction with long-distance expressway bus service in Sri Lanka. To ensure the collection of detailed and relevant insights from frequent users of the Southern Expressway's long-distance bus services, a purposive sampling technique was employed. Data collection was guided by variables identified in the literature review, and exploratory factor analysis was used to analyse the sample data. The study identified six salient supply-side factors affecting passenger satisfaction: service quality, comfort, accessibility and convenience, safety and security, cost, and customer service. These factors explained 74% of the total variance, with service quality being the most influential, accounting for 18% of the total variance. The findings recommend upgrading the bus fleet, maintaining cleanliness, optimizing scheduling, enhancing reservation systems, implementing staff training, improving safety measures, ensuring fair pricing, enhancing customer service, raising passenger awareness, and encouraging innovation to improve expressway bus services, attract more passengers, and build a reliable public transport system.
Wernicke encephalopathy due to hyperemesis gravidarum in pregnancy
Authors: Hendawitharana N. E. , Punchihewa G. D.
Published: October 2024

Wernicke’s encephalopathy is a life-threatening acute or sub-acute neurological emergency characterized by a triad of ataxia, confusion, ophthalmoplegia caused by thiamine deficiency, mostly observed in chronic alcohol users. Wernicke's encephalopathy due to causes other than alcohol abuse is uncommon and often misdiagnosed.  In pregnancy, it is an unknown pathology, with poor prognosis, which occurs secondarily to hyperemesis gravidarum. We present a rare case of a 30-year-old female with mild learning disability, at 15 weeks of gestational age, with a history of previous hospital admission for severe vomiting and referred to Maternal Mental Health Clinic for abnormal behaviour. She had classic symptoms of Wernicke’s Encephalopathy on presentation, and was immediately treated with thiamine. Her symptoms improved in a few days.
The comprehensive geriatric assessment in emergency and intensive unit settings
Authors: Cozza Mariagiovanna , Paglia Annalisa , Dini Simone , Di Francesco Vincenzo , Dal Santo Pierluigi , Boccardi Virginia
Published: October 2024

This review discusses the challenges that hospitals face when caring for older patients in emergency departments and intensive care units. Beyond chronic diseases, the older person is often affected by acute events, which require, in addition to the typical knowledge of emergency medicine and anesthesia, the holistic and targeted approach of the comprehensive geriatric assessment in the emergency room and intensive care setting. With Italy’s health centers struggling to manage the increasing pressure of patients, the COVID-19 pandemic has highlighted the need for a geriatric approach to address this challenge. This review outlines the Geriatric 5Ms Model of Care, which addresses five domains, and the Domain Management Model, which provides acute medical management.
Diffuse idiopathic skeletal hyperostosis is associated with greater complexity of coronary artery disease burden on coronary angiography
Authors: Adami G. , Zanon S. , Fassio A. , Pesarini G. , Pighi M. , Scarsini R. , Tavella D. , Rossini M. , Gatti D. , Ribichini F.
Published: October 2024

Objective. Diffuse idiopathic skeletal hyperostosis (DISH) is a common disorder characterized by ossification of tendons and ligaments. DISH has been largely associated with an increased risk of metabolic syndrome and type 2 diabetes. The objective of the present study is to investigate the role of DISH on the risk of coronary artery disease (CAD).
Methods. We conducted an observational cross-sectional study of patients without a history of rheumatic musculoskeletal diseases who underwent coronary angiography between March 2016 and April 2021. The SYNergy between percutaneous coronary intervention with TAXus and cardiac surgery (SYNTAX) score was calculated based on coronary angiography images. DISH diagnosis was based on standard X-ray images and computed tomography scans (Resnick criteria). Demographic and clinical characteristics were retrieved from electronic medical records. Multinomial and binary logistic regression models were employed to determine the association between SYNTAX score (dependent variable) and DISH (independent variable).
Results. The study included 187 patients, 82.9% of whom were men, with valid radiological imaging. 83 (44.4%) patients had a confirmed radiological diagnosis of DISH. Diagnosis of DISH was associated with a higher SYNTAX score [adjusted odds ratio (aOR) 34.1, 95% confidence interval (CI) 1.41-79.2 p=0.049], independently from traditional cardiovascular risk factors. In patients aged <70 years, DISH was associated with a 7-fold higher risk of belonging to the highest category of SYNTAX (≥34), compared to non-DISH (aOR 7.23, 95% CI 1.08-48.4; p=0.041). The extension of vertebral calcification was significantly associated with SYNTAX score (r2 0.378, p<0.0001).
Conclusions. DISH diagnosis is common in patients at high risk of cardiovascular disease or with definitive CAD. DISH was independently associated with higher CAD complexity.
Development of Technological Learning Media to Increase Students' Civic Knowledge
Authors: Purnama M. Malik , Adha M. Mona , Perdana Ryzal , Maulina Dina
Published: October 2024

Objective: This study focused on developing Bekatal learning media (Digital Civics Education) to enhance students' civic knowledge. This was motivated by issues identified in students' understanding of civic knowledge. The study analyzed the feasibility and effectiveness of Bekatal learning media for enhancing students' civic knowledge. Method: The research employed the Four D (4D) model, involving samples from both experimental and control classes. Results:  The findings indicate that the Bekatal learning media developed to enhance students' civic knowledge is feasible for use, with expert The findings show that the Bekatal learning media which was developed to increase students' civic knowledge is suitable for use, with the categories of very appropriate assessment from subject matter experts, very appropriate from media experts, very appropriate from language experts, and very appropriate from evaluation experts. Furthermore, from the results of the t-test, it can be concluded that there is an increase in students' civic knowledge before and after using Bekatal learning media. Based on these data, it can be concluded that the Bekatal learning media is feasible and effective in enhancing students' understanding of civic knowledge. Novelty: This research provides an innovative technological learning media that makes users feel the sensation of playing with learning materials by the learning objectives. So that users feel energized and like they are learning but feel like they are playing.
Determinants of E-Learning Acceptance in Indonesia Post-COVID-19 and Its Impact on Students’ Technopreneurship
Authors: Yudiana Fetria Eka , Famularsih Sari , Rosyidha Alfin
Published: October 2024

Objective: This research aims to address the gaps in country-specific e-learning studies by examining the key factors influencing e-learning adoption in Indonesia. Grounded in a comprehensive literature review on flow theory, service quality, and technology acceptance models, the study develops a research model that includes four independent variables (instructor characteristics, teaching materials, content design, and enjoyment), two belief variables (perceived usefulness and perceived ease of use), and one dependent variable (intention to use e-learning). Method: Data were collected from 404 respondents, comprising students and lecturers at state Islamic universities in Indonesia, using convenience sampling. The study employed SEM-PLS for data analysis, validating the research instrument's reliability and validity. Results:  The results offer insights into the managerial implications and suggest directions for future research in e-learning adoption. Its results confirm six hypotheses. Novelty: This study fills a gap in e-learning adoption research by focusing on Indonesia and integrating flow theory, service quality, and technology acceptance models. It highlights the roles of perceived playfulness, ease of use, and instructional content design in influencing e-learning adoption while challenging the expected impact of instructor characteristics. This research provides fresh insights into technology-driven learning in the context of developing countries.
Quantifying phenotypic relationships among Arsi, Bale and Jemjem cattle breeds of Ethiopia
Authors: Mustefa Amine , Melak Awoke , Kenfo Hizkel , Sinke Seble , Abdela Ahmed , Hailu Abebe
Published: October 2024

Nine morphometric and 16 morphological traits were used to characterize and quantify phenotypic relationships among Arsi, Bale and Jemjem cattle breeds. A total of 441 randomly selected adult cattle (342 females and 99 males) from three purposively selected districts were used. Univariate and multivariate analysis procedures of statistical analysis software (SAS) were used to analyze the data. Clear morphological and morphometric variations were not observed among the cattle breeds. The majority of the studied cattle possessed uniform coat colour pattern (78%), black coat colour (61%), forward-oriented horns (65.8%), widely spaced horns (71.4%) and curved horns (76%). They mostly had erected humps (96.2%), small humps (66.7), mainly located at the cervicothoracic position (77.8%) with a straight face (100%) and back profile (92%) while their rump was sloppy (100%). Overall, 44.4% and 45.6% were medium- and long-tailed, respectively, while most (72.1%) of the cattle possessed medium dewlap width. Most (57.6%) of the males had medium perpetual sheaths while naval flap was not observed on most (53.2%) of their female counterparts. In addition to the univariate analysis, the multivariate analysis also failed to show significant separation among the breeds, as indicated by the short Mahalanobis distances and low eigenvalues. In conclusion, Arsi, Bale and Jemjem cattle breeds were found to be phenotypically inseparable. However, the observed phenotypic similarities among these breeds do not necessarily mean that these cattle breeds are genetically the same. Therefore, further molecular characterization is recommended to quantify the degree of genetic relationships among the studied breeds.
Інтерактивні технології як засіб активізації пізнавальної діяльності учнів початкових класів на уроках математики
Authors: Павлишин Софія , Шаран Олександра
Published: October 2024

У статті розглядається актуальна проблема методики навчання – активізація пізнавальної діяльності учнів початкових класів на уроках математики. Автори обґрунтовують важливість активної пізнавальної діяльності учнів під час навчання. Особливо це стосується навчання математики, адже завдяки активній діяльності відбувається «відкриття» учнями нового матеріалу, покращення його засвоєння, з’являється мотивація та інтерес до його вивчення та, як результат, підвищення результативності навчання. Проаналізовано дослідження, проведені різними авторами, стосовно активізації пізнавальної діяльності та використання задля цього різних педагогічних засобів. Описано ефективні педагогічні засоби, такі як: інтерактивні вправи та платформи, ігрові інтерактивні технології, вебквести, метод проєктів, групова робота, залучення електронно-освітніх ресурсів, навчальних відео, інтерактивних презентацій, використання нестандартних методів оцінювання та зворотного зв’язку тощо. Доведено, що використання інтерактивних технологій є одним з ефективних засобів активізації пізнавальної діяльності молодших школярів. Зокрема, розглянуто різні види інтерактивних технологій, особливості їх застосування на різних етапах уроку математики в початковій школі. Детально розглянуто практичні аспекти застосування відповідних інтерактивних засобів. Описано проведене експериментальне дослідження, визначені організаційно-педагогічні умови активізації пізнавальної діяльності молодших школярів на уроках математики та основні показники активізації пізнавальної діяльності учнів початкових класів. Зроблено висновок про доцільність та можливість застосування інтерактивних технологій на уроках математики в початкових класах. Окреслено перспективні напрямки дослідження у напрямі використання нових інтерактивних інструментів задля активізації пізнавальної діяльності учнів початкових класів на уроках математики.
Increasing Transformative Impact by Design in Education in the Caribbean
Authors: Mertens Donna
Published: October 2024

Educational researchers in the Caribbean have an opportunity to be part of the solutions to grand challenges, such as climate change, violence, and disparities in educational opportunities and outcomes. The transformative approach to research provides a framework that focuses on issues of inequities and power differences in a conscious effort to increase social, economic, and environmental justice. Examples of studies from different parts of the world are used to illustrate the application of this framework with the goal of increasing the research impact. The strategies used in the transformative approach, such as building culturally responsive relationships, integrating social activist strategies, developing coalitions, and addressing power inequities, can be applied in ways that are responsive to the culture and context of the Caribbean.
Multi-objective modeling and optimization of the thermal behavior of an AT10-type belt transmission using ANOVA, RMS and DF methods
Authors:   Laboratory of Mechanical Engineering, Materials and Structures, Tissemsilt University, Algeria, Haroun Abdelhak , Merghache Sidi Mohammed ,   Laboratory of Mechanical Engineering, Materials and Structures, Tissemsilt University, Algeria
Published: October 2024

This research work focuses on the analysis of the impact of different parameters, such as the angular speed N1, the resistant torque M2 and the setting tension T of the timing belt on its operation. The main objective is to optimize the performance of the belt by understanding how these parameters influence its thermal behaviour. By carefully examining these factors, it becomes possible to identify the adjustments needed to improve the overall efficiency of the belt. An in-depth statistical analysis was conducted using three different approaches: analysis of variance (ANOVA), response surface method (RSM) and desirability function (DF) method, in order to examine the temperature of the heating of the belt T1 and its efficiency η. Data from the experiment are examined and manipulated to develop mathematical models that demonstrate the correlation between various parameters and growth rates. The results clearly demonstrate that the resistant couple M2 plays a preponderant role, with contributions of 55.25% and 69.82%, respectively. In addition, the N1 angular speed also has a significant influence, contributing 7.58% and 17.84%, respectively. On the other hand, setting tension T makes a small contribution to the temperature of belt T1. And a strong influence of 21.91% on their performance. These results clearly indicate that better efficiency can be obtained by reducing the angular speed N1 and increasing the resistive torque M2. These results show that the developed models have been well established and that there is a good correlation between the experimental and predicted data.
Importance of Industry-Academia Collaboration in Robotics for Modern Education, Research and Industry
Authors:   University of Belgrade, School of Electrical Engineering, Serbia, Jovanović Kosta , Knežević Nikola ,   University of Belgrade, School of Electrical Engineering, Serbia, Gordić Zaviša ,   University of Belgrade, School of Electrical Engineering, Serbia
Published: October 2024

What were software and computers in the nineties, today are artificial intelligence and robots. Therefore, the quick and efficient adoption of robotic technologies in education, research, and industry can leapfrog the current technological and societal level to an advanced and modern one. To that end, a structured collaboration of academia and industry is essential. Collaborative robots entered the market as inherently safe, user-friendly, easy to program, and, as such, the fastest-growing robotics segment. Such features create new opportunities to make robotics technologies more affordable, accessible, and more appropriate for small and medium companies, new applications, businesses and education. This paper demonstrates an example of the University of Belgrade – School of Electrical Engineering collaboration with industry in robotics and the impact such collaboration makes on education, research, and industry. The collaborative activities include setting up join robotic system testbeds, creating open educational materials, organizing student competitions for a broader understanding of robotic applications and capabilities, providing real industrial needs, real data, and field testing for competitive and impactful research actions, conducting return of investment and proof of concept services for the industry. The role model shows the impact of academia-industry collaboration on creating new opportunities for talents in academia and industry.
Programming Languages in Development of Embedded Systems: Preliminary Review
Authors:   University of Novi Sad/Technical faculty “Mihajlo Pupin”, Zrenjanin, Serbia, Amižić Vuk , Kazi Ljubica ,   University of Novi Sad/Technical faculty “Mihajlo Pupin”, Zrenjanin, Serbia, Radosav Dragica ,   University of Novi Sad/Technical faculty “Mihajlo Pupin”, Zrenjanin, Serbia
Published: October 2024

In this work, a brief analysis of related work and comparation of programming languages in development of embedded systems has been presented. Focus of this paper is to show different programming languages used in various embedded systems as well as their popularity and efficiency in terms of speed and processing required data
Open Source Integrated Circuit Design Tools in Scientific Research: Yay or Nay?
Authors:   University of Kragujevac/Faculty of Technical Sciences Čačak, Serbia, Knežević Mihailo , Paunović Lidija ,   University of Kragujevac/Faculty of Technical Sciences Čačak, Serbia
Published: October 2024

The design of integrated circuits (IC) has a significant impact on the development of modern world technologies. The subject of this research is the examination of the potential application of open source tools for integrated circuit design in scientific research. This paper analyzes some open source tools. The research results show that the application of these tools has advantages and disadvantages as well, but most importantly, in the context of science that it is feasible and even recommended. Open source tools for integrated circuit design create positive outcome of the financial feasibility of scientific research activities, collaboration, and the advancement of scientific research. The paper also presents possible future research in this area.
Issues During Data Migration
Authors:   LANACO, Banja Luka, Republic of Srpska, Bosnia and Herzegovina, Marković Mirko , Davidović Nikola ,   University of East Sarajevo, Faculty of Electrical Engineering, East Sarajevo, Bosnia and Herzegovina, Vesković Milan ,   University of Kragujevac, Faculty of Technical Sciences Čačak, Serbia, Nogo Srđan ,   University of East Sarajevo, Faculty of Electrical Engineering, East Sarajevo, Bosnia and Herzegovina, Govedarica Jelena ,   University of East Sarajevo, Faculty of Electrical Engineering, East Sarajevo, Bosnia and Herzegovina
Published: October 2024

Virtualization represents one of the key technologies in modern computing, offering numerous advantages such as running multiple operating systems on a single computer, efficient resource utilization, process execution independence from specific hardware, and enhanced data security. This paper presents the process of virtual machine migration, including migration from one physical server to another without interrupting application operations. Additionally, it discusses some of the key benefits of virtual machines in various contexts, such as resource isolation, resource allocation flexibility, software testing, migration and backup, resource efficiency, and support for different operating systems. Through the analysis presented in this paper, the importance of virtualization as a fundamental technology in modern computing is highlighted, as well as the necessity of understanding the migration process and optimal use of virtual environments.