bluuebunny/crossref_metadata_2025 huggingface dataset:
Analisis Proses Rekrutmen dan Seleksi Karyawan di Tok Patok Guluk-Guluk: Perspektif Ekonomi Syariah dan Dampaknya terhadap Kinerja Karyawan
Authors: Iftikhori Ach , Maksum Maksum
Published: February 2025

Abstrak: Pengelolaan sumber daya manusia dalam suatu organisasi sangat diperlukan untuk mencapai tujuan yang dituju dalam suatu perusahaan. Penelitian ini bertujuan untuk menganalisis proses rekrutmen dan seleksi karyawan di resto Tok Patok Guluk-Guluk, Sumenep, serta mengkaji dampaknya terhadap kinerja karyawan dari perspektif ekonomi syariah. Proses rekrutmen menggunakan metode internal dan eksternal, di mana metode internal dilakukan dengan pemberitahuan kepada karyawan lama terkait posisi yang tersedia, sedangkan metode eksternal dilakukan melalui media sosial, pamflet, dan informasi kepada mahasiswa magang. Langkah-langkah yang dilakukan meliputi identifikasi kebutuhan jabatan, seleksi administrasi, wawancara, hingga konfirmasi kandidat melalui komunikasi daring. Dari perspektif ekonomi syariah, proses ini menunjukkan penerapan prinsip keadilan, transparansi, dan amanah dalam pemilihan karyawan, dengan memberikan peluang yang adil kepada semua kandidat berdasarkan meritokrasi. Hasil penelitian menunjukkan bahwa proses rekrutmen dan seleksi yang sistematis tidak hanya berkontribusi pada peningkatan kinerja karyawan dalam melayani konsumen tetapi juga mendukung terciptanya keberkahan usaha melalui praktik yang etis dan bertanggung jawab
Keywords: Rekruitmen, Seleksi Karyawan, Ekonomi Syariah
The Study of Internet Hot Words from the Perspective of Linguistics
Authors: Li Meiqian
Published: February 2025

In the era of new media, with the popularization of the Internet, there are many Internet buzzwords and hot phrases in daily life, which reflect the characteristics of the times and the development of language in the ever-changing changes. The recent popularity of talk shows and the popularity of buzzwords such as C, Cow, Horse, O, Oi, Kid and You Logo have once again highlighted the importance of language. This paper will examine the sociolinguistic, cognitive and linguistic aspects of language. In this paper, the author will study the above mentioned Internet buzzwords from the perspectives of sociolinguistics and cognitive linguistics, and discuss their causes and variations. It is found that the variation phenomenon is embodied in three aspects: phonology, semantics and syntax, and the reasons for the variation phenomenon are found to be the arbitrariness of the combination of phonology and semantics, the aggregation of linguistic symbols, the cultural background, the diversity of communication media and the time factor; finally, the reasons for the emergence of Internet buzzwords are studied in terms of both internal and external aspects. Regulating the development trend of the Internet language phenomenon is also necessary.
Thriving in the Guochao Era: Strategic Insights for ChaPanda and Chagee in the Ready-to-Drink Tea Market
Authors: Liu Yijia
Published: February 2025

The ready-to-drink tea industry in China has grown significantly due to rising incomes and the guochao trend, which promotes cultural revival with local products. This paper examines ChaPanda's strategies in product innovation, marketing, and market expansion. We offer strategic recommendations for Chagee to improve its market position, including regional customization, youth-focused marketing, reinforcing guochao elements, and exploring international opportunities. This analysis aims to help Chagee leverage cultural identity and trends for sustainable growth in a competitive market market.
A Review of China's Electric Vehicle Consumption Market: The Impact of the Unique Chinese Culture on Car Buying Behavior
Authors: Wei Qianhe
Published: February 2025

In recent years, the electric vehicle (EV) sector in China's passenger car market has grown significantly, with domestic brands' market share increasing year by year. In contrast, the market share of imported fuel vehicles has been gradually squeezed, and imported electric vehicles have performed poorly. This paper analyzes the deep-seated reasons for this market change through a literature review and empirical research, including consumer demand, government policies, technological progress, and cultural factors. The study found that government support policies and domestic enterprises' technological breakthroughs have improved the competitiveness of domestic electric vehicles; the face culture and collectivism culture in Chinese culture have profoundly influenced consumers' car purchase decisions; and the emerging middle class's demand for high-quality new technology products has also driven market growth. At the same time, foreign automakers face the challenges of fierce competition and policy changes in the Chinese market and have failed to adapt to local market demand promptly, resulting in a decline in market share. By studying the impact of Chinese culture on consumer purchasing decisions, we can better understand and predict consumer behavior in the Chinese market and provide a reference for companies to formulate effective product development and marketing strategies.
Analysis of the Development Strategy of Museum Cultural and Creative Industry
Authors: Lu Leer
Published: February 2025

Museum cultural and creative products have become an important medium for culture transmission today, and have the potential that cannot be ignored in cultural communication. This paper mainly studies the development strategy of museum cultural and creative Industries, so as to achieve the purpose of attracting and being closer to and giving consumers' spiritual needs. This research can lay a more effective and natural development for the development of museum culture and creativity in the future, combining cultural creativity with connotation and the product itself, so as to achieve the purpose of high-quality development. This study uses the literature analysis method to sort out and summarise the cultural creations of museums on the market based on the background of relevant literature and put forward corresponding views. After analysis, this paper finds that the meaning and connotation of cultural and creative products is to convey culture and close the relationship between people's daily lives and culture. Therefore, designers can't just stack elements when designing. It is equally important to study the wishes of consumers.
Algorithm Transparency and Its Impact on Mobile App User Experience: A YouTube Case Study
Authors: Liu Hongyi
Published: February 2025

This study examines the relationship between transparency perception and trust in video content consumption and further discusses the mediating role of trust between perceived transparency and purchase intention. The impact of transparency perception on trust was evaluated using a linear regression model. The regression model revealed that for every 1 unit increase in transparency perception, trust increases by 0.494 units (p < 0.01). The models R-squared value of 0.251 indicates that transparency perception explains 25.1% of the variation in trust. In addition, demographic trends in video platform usage, including frequency of use and content preferences, were analyzed. Finally, reliability and validity tests supported the robustness of the measurement tools, with Cronbachs coefficients of 0.876, 0.877, and 0.847 for transparency perception, trust, and purchase intention, respectively. A mediating effect of trust on the relationship between transparency perception and purchase intention was also found, which means that improving transparency perception can improve trust and further affect purchase intention through trust.
Strategies for Cost Optimization in Supply Chains with a Focus on Green Development
Authors: Wang Jielin
Published: February 2025

As global sustainability advances, businesses face demands in their quest for green transformation. However, in this process, companies face many cost control problems. Although researchers have conducted extensive studies on supply chain cost control strategies, there is still a lack of research on cost optimization in the context of green development. The research topic of this paper focuses on the cost optimization strategy of enterprise supply chains under the perspective of green development. Taking Sam's Club as a case study, this paper analyzes the measures implemented by the company to achieve green transformation, and then analyzes the cost management problems and proposes corresponding optimization strategies. The study found that some of the cost control measures taken increased the operating costs as well as the promotional costs of the firms. The research in this paper aims to provide a reference for enterprises to effectively carry out cost optimization under the framework of green development, to promote enterprises to achieve sustainable development, and to provide theoretical support for practice in related fields.
Evaluating the Financial Impact of ESG Performance in Developed Markets: Insights from Advanced Machine Learning and Statistical Models
Authors: Li Yunhao
Published: February 2025

This study investigates the financial implications of Environmental, Social, and Governance (ESG) performance in developed markets through the application of advanced machine learning and statistical methods, including Generalized Additive Models (GAM), Support Vector Regression (SVR), Random Forest, and XGBoost. Using a dataset from Bloomberg comprising ESG disclosures, financial indicators, and market performance metrics, the research explores the nonlinear and interactive effects of ESG factors on Year-to-Date (YTD) Total Return. The findings reveal that ESG Score significantly impacts financial outcomes, with Random Forest emerging as the most effective model, achieving the highest predictive accuracy. Feature importance analysis highlights the pivotal role of ESG Score and technical indicators like RSI_14_Days, while greenhouse gas emissions demonstrate limited direct influence. This study underscores the need for nuanced, context-specific approaches to integrating ESG considerations into financial strategies and contributes to the discourse on balancing sustainability with economic objectives in corporate governance.
Elo in MOBA: Algorithm Comparison and Application Discussion
Authors: Dong Jialong , Jiao Haiyang , Liu Yue
Published: February 2025

Online multiplayer games are supposed to match single players or squads with similar abilities. They depend on different kinds of rating systems to ensure a fair and competitive gaming environment. Traditional rating systems generally focus on single evaluation criteria, such as Elo scores or number of killings. However, games like Overwatch, which have more rating aspects, such as the usage of items and skills and the corporation of a whole team, need some more complex rating systems. Because of these, those traditional rating systems cannot satisfy the needs of modern multiplayer online games. Thus, it is urgent to develop new rating systems with new modes. In this paper, we are going to explore the newly designed Elo system with new models, especially its application in MOBA games. We will also talk about the TrueSkill and TrueSkill2 rating systems. These are two rating systems with high accuracy in win rate prediction, which can match fair games for players and teams.
Emotion-Driven Interior Design Using Sentiment Analysis from Social Media
Authors: Chu Liyang , Zhou Keting
Published: February 2025

The gradual development and expansion of online social media provides a stage for people to share their personal views and opinions. Many experts and scholars have collected and analyzed these emotions, created numerous emotional models and data sets, which are widely used in various fields including architectural interior design. Through sentiment analysis techniques, it has become an important branch in interior design to investigate how to optimise users emotional experience, such as comfort, sense of belonging and well-being. This paper selects GoEmotions as the dataset for sentiment classification and analysis of text, which is currently the largest manually annotated dataset. By analyzing the comments on Instagram posts related to interior design, the study investigates the impact of residential interior space design on people's emotions, and then trains a Low-Rank Adaptation (LoRA) model that can generate interior spaces with certain emotional feelings.
Enhancing Small Target Detection in Aerial Imagery Based on YOLOv8
Authors: Huang Cheng , Tan Beihai
Published: February 2025

Among the numerous deep learning-based object detection algorithms, the YOLO (You Only Look Once) series has become a preferred choice for various detection scenarios due to its fast detection speed, high accuracy, and strong adaptability. However, its performance remains suboptimal when applied to unconventional images, such as aerial images, which often feature complex content and small detection targets. To overcome this limitation, a novel model called YOLOv8-TDE (Tiny Detection Enhanced) is introduced in this work. First, to more effectively differentiate between key features and noise and to comprehensively capture multi-scale target features, the feature extraction network is improved by employing pooling convolution kernels of various sizes and incorporating a lightweight attention mechanism. Second, the GeoIoU (Geometric Intersection over Union) loss function is introduced to reduce sensitivity to aspect ratio and center point distance, addressing the limitations of the original CIoU loss function, which is overly sensitive to small changes in these parameters. Finally, a novel detection head, the FAD Head, is proposed to dynamically generate detection head parameters based on the input image's features, enabling better feature extraction for targets of different sizes in complex scenes. This enhancement improves the model's adaptability across various scenarios, as well as detection accuracy and stability. Experiments on the VisDrone2019 dataset demonstrate that the proposed model outperforms the original YOLOv8n, achieving a 15.5% improvement in mAP@0.5 and a 17.6% improvement in mAP@0.5:0.95.
Technological Innovations in the Silver Economy: AI-Driven Financial Management, Smart Products, and Entrepreneurial Support for Aging Populations
Authors: Wang Zhangyu
Published: February 2025

The silver economy is a new discipline, whose purpose is to solve the particular challenges and opportunities of a retiring society. The subject of this piece is how tech will impact the silver economy, and in particular Artificial Intelligence (AI)-based financial management systems, smart products, and entrepreneurs aids for the elderly. A systematic review of recent developments concludes the paper on how AI can enhance financial decisions for the elderly through personalized guidance, fraud prevention and retirement planning. Moreover, the combination of wearables, automation at home, and telemedicine also proves to make older people healthier, safer and better lives. At the end of the paper we see an increasing focus on entrepreneurship in the silver economy specifically digital platforms and support networks that allow older adults to start businesses and stay economically and socially engaged. It was found that, when deployed appropriately, technology could meet the economic and social needs of the elderly to increase independence and improve long-term well-being. In sum, the findings underscore how technological innovation has the capacity to make a sustainable, inclusive silver economy.
Federated Learning for Privacy-Preserving Medical Data Sharing in Drug Development
Authors: Yang Mingxuan , Huang Decheng , Wan Weixiang , Jin Meizhizi
Published: February 2025

This study explores the potential of Federated Learning (FL) to facilitate the sharing and collaboration of medical data in drug development under the premise of privacy protection. While traditional centralized data processing methods limit effective collaboration across agencies due to data privacy and compliance concerns, federated learning avoids the risk of privacy breaches through a distributed architecture that allows participants to train artificial intelligence (AI) models together without sharing raw data. In addition, this study explores the scalability and generality of federated learning in the medical field, and points out that the technology is not only suitable for drug development but also has broad cross-industry application potential, especially in areas such as finance and insurance, where data privacy is critical.
Simulation Study on the Effects of Methane Blending on the Auto-Ignition Mechanism of High-Pressure Hydrogen Leakage
Authors: Liu Huan , Cui Gan
Published: February 2025

As a clean energy source, hydrogen plays a crucial role in driving energy transitions. However, its highly flammable and explosive characteristics limit its safety in applications. This paper employs numerical simulation to investigate the influence of methane blending at varying concentrations on the auto-ignition and flame propagation characteristics of high-pressure hydrogen. The study focuses on analyzing the mechanisms by which methane blending affects shock wave intensity, ignition delay, and flame propagation behavior. The results indicate that methane blending significantly reduces shock wave intensity, prolongs ignition delay, and suppresses the integrity and intensity of flame propagation both inside and outside the pipeline. Furthermore, these effects are enhanced with increasing methane concentration. These findings provide theoretical support for safe design under conditions of high-pressure hydrogen blended with methane, contributing to the safer application of hydrogen energy in industrial and transportation fields.
Application of traditional Chinese medicine in the treatment of breast cancer
Authors: Han Shaojie
Published: February 2025

Breast cancer is one of the common nasty tumors that seriously endanger women's health problems. Its incidence and mortality rate rank first among female malignant tumors in the world. At the same time, the prevalence and mortality rate of women in China remain high, and it shows a trend of younger age. With the acceleration of social rhythm, irregular diet, increasing pressure and other reasons, the incidence of breast cancer in women is increasing year by year. Currently, the treatment of breast cancer usually includes surgery, chemoradiotherapy, endocrine therapy, targeted drugs, etc. Although these combined therapies are effective in reducing the mortality rate of breast cancer, the side effects on the patients body are still large. Most of the previous studies focused on the perspective of western medicine, but this paper analyzed the theory, cognition and the therapeutic effects of traditional Chinese medicine on breast cancer from the perspective of Chinese medicine. The results of this study show that traditional Chinese medicine treatment of breast cancer and prognosis have good performance, especially in alleviating complications and alleviating the side effects of chemoradiation.
Consciência histórica
Authors: Grever Maria , Adriaansen Robbert-Jan
Published: February 2025

Para tornar a consciência histórica possível para a pesquisa em Ensino de História, é necessário desvendar seus fundamentos multidisciplinares, de modo a evitar abordagens e resultados contraditórios. O objetivo deste artigo, portanto, é esclarecer o enigma de seus diferentes paradigmas. Discutiremos dois paradigmas inter-relacionados: um que interpreta a consciência histórica como um fenômeno coletivo característico da sociedade ocidental moderna, e o outro que trata a consciência histórica em um nível individual como uma categoria cognitivo epistemológica. Mostraremos que vários equívocos na pesquisa educacional sobre a consciência histórica resultam da confusão entre essas duas conceitualizações e seus paradigmas subjacentes. No entanto, ao destacar a noção de Wirkungsgeschichte (efeito histórico) de Hans-Georg Gadamer, argumentamos que ambas as conceituações não são totalmente mutuamente exclusivas. Incluir a consciência historicamente afetada na noção de consciência histórica oferece uma ampla gama de oportunidades, tanto para os estudiosos da educação em História quanto para os educadores de História.
Ensino de história a partir da imprensa sindical do setor elétrico (1992-1993)
Authors: Dos Santos Junior Edson
Published: February 2025

Este artigo discorre sobre o ensino de história a partir da imprensa sindical de trabalhadores urbanitários do setor elétrico em Foz do Iguaçu, cidade situada na fronteira trinacional entre Argentina, Brasil e Paraguai. Para isto, recolhe suas fontes entre as páginas do Jornal Alerta Geral, nos anos de 1992 e 1993, discutindo possibilidades do ensino da história de trabalhadores em vista de questões como a luta por direitos, desenvolvimento social e emancipação humana. A metodologia empregada parte da lógica das mediações, conforme nos propõe Maria Ciavatta, e observa as relações entre capital e trabalho. Ao final do texto, encontram-se algumas considerações sobre possibilidades e limites da utilização da imprensa sindical enquanto recurso didático.
Identifying the Factors Influencing Customer Satisfaction; A Case Study on ABC Bank PLC, Sri Lanka
Authors:   Sri Lanka Institute of Information Technology, Malabe, Sri Lanka, Gunasekara T. P. A. D. , Mendis P. H. P. B. ,   Sri Lanka Institute of Information Technology, Malabe, Sri Lanka, Perera H. G. N. D. ,   Sri Lanka Institute of Information Technology, Malabe, Sri Lanka, Malshan U. B. ,   Sri Lanka Institute of Information Technology, Malabe, Sri Lanka, Yapa Shanta Rajapaksha ,   Sri Lanka Institute of Information Technology, Malabe, Sri Lanka, Kothalawala Charuka ,   Sri Lanka Institute of Information Technology, Malabe, Sri Lanka
Published: February 2025

This study aims to determine the specific factors that influence Customer Satisfaction in the banking sector of Sri Lanka because the economic growth and stability of a country depend on the soundness of its banking sector. The sole participants in this research are clients of ABC Bank in the Colombo district. The technique is based on primary data gathered using a well-structured questionnaire. A hundred individuals were chosen at random from the database of ABC Bank. The respondents of the study are existing ABC Bank customers living in the Colombo district aged between 18-40 years. Descriptive statistics and correlation analysis were used in the examination of the data that was gathered. According to the findings, customer happiness may be affected by Service Quality, accessibility, product pricing, and e-banking. The management of the bank should determine the elements that might reduce Customer Satisfaction and work to improve them while simultaneously enhancing the variables that can boost customers.
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Keywords: Accessibility, Customer Satisfaction, E-Banking, Product Pricing and Service Quality.
Time Series Model to Forecast Fresh Coconut Exports from Sri Lanka
Authors:   Sri Lanka Institute of Information Technology, Malabe, Sri Lanka, Suban K. , Hettiarachchi S. N. ,   Sri Lanka Institute of Information Technology, Malabe, Sri Lanka, Himaanthri S. ,   Sri Lanka Institute of Information Technology, Malabe, Sri Lanka, Aththachchi S. D. F. ,   Sri Lanka Institute of Information Technology, Malabe, Sri Lanka, Wickramarachchi C. N. ,   Sri Lanka Institute of Information Technology, Malabe, Sri Lanka, Peiris T. S. G. ,   Sri Lanka Institute of Information Technology, Malabe, Sri Lanka
Published: February 2025

Coconut accounts for approximately 12% of all agricultural produce in Sri Lanka with the total land area under cultivation covering 409, 244 hectares ranking second to rice production. The primary regions for coconut cultivation are the Puttalam and Kurunegala districts in North-Western Province and Gampaha district in the Western Province, forming what is known as the Coconut Triangle. This region accounts for 232,270 hectares (50.94%) of the overall coconut cultivation area. The remaining coconut cultivation areas are found in the Southern Province, specifically in the districts of Galle (13,833 hectares), Matara (14,946 hectares), and Hambantota (25,837 hectares), and in non-traditional regions of the Eastern and Northern provinces. The annual coconut production varies between 2,800 to 3,000 million nuts. Having advanced knowledge of exporting coconuts offers numerous advantages to Sri Lanka, particularly in terms of establishing forward contracts with other countries. Based on secondary data of annual fresh coconut exports from 1981 to 2020 obtained from the Coconut Development Authority (CDA) of Sri Lanka, the paper developed ARIMA (2,1,0) model to forecast export. The model was selected out of three parsimonious models which were identified from the Sample Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) of the stationary series and a comparison of significant parameters and lowest values of Akaike Information Criterion (AIC), Schwarz Bayesian Information Criterion (SBIC) and Hannan-Quinn Information Criterion (HQIC). The errors of the fitted model were found to be random and constant variance. The model was validated using 2021 and 2022 data. The percentage errors for 2021 and 2022 are 20.23% and -29.57% respectively. The predictions for 2023 and 2024 are 14696 and 15052 respectively. The model can be used effectively by the Coconut Development Authority for decision-making. However, it is suggested to develop the model further to reduce the percentage error.
Keywords: ARIMA model, Forecast, Fresh Coconut Exports and Validate.
Paddy Disease Identification and Impact Calculation Using Machine Learning
Authors:   Sri Lanka Institute of Information Technology, Malabe, Sri Lanka, Sandeepanie Nilakshi , Rathnayake Samadhi ,   Sri Lanka Institute of Information Technology, Malabe, Sri Lanka, Gunasinghe Amali ,   Sri Lanka Institute of Information Technology, Malabe, Sri Lanka
Published: February 2025

Rice is a crucial staple crop globally, providing over half of humanity's caloric intake. It supports the livelihoods of small-scale farmers and landless laborers worldwide. With the growing population, there is a high demand for rice production. Sri Lanka is renowned for its high- quality rice and has a long history of paddy cultivation. However, not all the country's 708,000 hectares of land dedicated to paddy cultivation are utilized due to water scarcity and unstable terrain. The objective of this paper is to explore the ways of enhancing the quality of the paddy crop during its vegetative phase by early identification of diseases through the utilization of emerging technologies. The vegetative phase constitutes a critical stage in the growth of paddy, exerting significant influence on the overall yield, resistance to pests and diseases, nutrient assimilation, and the environmental implications of agricultural practices. The primary emphasis of this paper is to identify diseases to which paddy crops are susceptible during the vegetative phase and subsequently present a visual representation of their locations on a map, serving as the output for end-users. Early identification of paddy diseases is crucial for effective crop management and high yields. These diseases, caused by different pathogens, can significantly hinder plant growth and productivity if not detected and treated promptly. Identifying them early allows farmers and experts to take timely and targeted actions, like applying suitable fungicides or implementing cultural practices, to control their spread and minimize crop damage.
Keywords: Diseases, Machine Learning, Object Detection, Paddy Cultivation, Web Development and YOLO v8.
Keynote Speech
Authors:   Eindhoven University of Technology, California, Bogers Marcel
Published: February 2025

Marcel Bogers is a Professor of Open & Collaborative Innovation at the Innovation, Technology Entrepreneurship & Marketing group at the Department of Industrial Engineering & Innovation Sciences of Eindhoven University of Technology. He is also an Affiliated Professor of Innovation & Entrepreneurship at the Department of Food and Resource Economics at the Faculty of Science of the University of Copenhagen as well as a Garwood Research Fellow at the Garwood Center for Corporate Innovation at the Haas School of Business of the University of California, Berkeley. His main interests center on the design, organization and management of technology, innovation, and entrepreneurship. More specifically, his research explores openness and participation in innovation and entrepreneurial processes within, outside and between organizations. In this context, he has studied issues such as open innovation, business models, family businesses, users as innovators, collaborative prototyping, improvisation, and university-industry collaboration.
Professor Marcel Bogers has received honors that highlight excellence in research, teaching and outreach. His honors include the Web of science highly cited researcher recognition, most cited and most read article in journals as Journal of Product Innovation Management, California Management Review and Industry & Innovation, several Best Paper Proceedings listings at the Academy of Management, Finalist for the Best Dissertation Awards of the ISPIM, DRUID and the TIM Division at the Academy of Management, a Best Teacher Award at the University of Southern Denmark, recognition as Top Professor on Twitter, most followed scientist in the Greater Copenhagen area and Denmark, and the SCIENCE Dissemination Award from the Faculty of Science at the University of Copenhagen.
Revolutionizing Drug Development: Harnessing the Potential of Organ-on-Chip Technology for Disease Modeling and Drug Discovery
Authors: Zeb Jehan
Published: February 2025

One of the groundbreaking advancements in the field of biomedical research is the development of organoids or organ on chip technology. Promising potential of this technology has reshaped the future of disease modelling and drug discovery. Organoids are microfluidic devices which can mimic the physiological functions of natural organs of human body. Animal models are being used in laboratories to evaluate the drug effectiveness but due to the recent ethical concerns, regarding the use of animals, are affecting drug development and treatment for various diseases. But organ on chip is an emerging tool which is filling the gap between animal models and outcomes of drug treatment by eliminating the ethical concerns.
Demand for precision medicine is growing due to rapid arousal of various deadly disease but traditional methods of developing drugs fall short as they can’t exactly replicate the human physiology. So instead of using animal models or cell cultures to design drug, to detect the its efficacy and toxicity, organ on chip technology is perceived to be a best option. It saves the time and resources that were being wasted, due the use of animal models, during the preclinical and clinical trials of the drug.  On the other hand, organoids are more reliable in satisfying the demand of precision medicine.   These artificial organs provide a bioengineered platforms mimicking the specific functions of living organs such as gut peristalsis and lung breathing in a very controlled manner. Moreover, different organs communication after drug treatment is also being studied by developing multi-organ systems so that the utility of these micro-engineered organs can be enhanced. These organs generate more accurate data about the drug effectiveness and toxicity. Moreover, it generates it in real time thus reducing the reliance on the animal models on which testing is usually time taking and can give false results.  Furthermore, molecular basis of numerous complex diseases like cancer, diabetes and neurogenerative diseases can be predicted with this technology and it is very helpful in producing precision medicine. Controlled drug delivery is one of the best applications of these organoids eliminating the chance of false hits. Therefore, this technology has demonstrated a paradigm shift in biomedical research providing a better alternative in case of efficiency and reliability.
Now the integration biosensors, artificial intelligence in organ on chip technology has enhanced its predictivity power and also allow the real time imaging and monitoring of cellular responses to the particular drug.  Though, there some obstacles regarding the adoption of this technology but efforts are being made continuously to accelerate its usage in mainstream research. Thus, paving the way for a new era of personalized medicine.
Human Resource Competencies and Their Role in Raising the Efficiency of Contemporary Organizations
Authors: Awni Saadiyah Owaid , Ali Salih Sawsan Muhammad
Published: February 2025

The research aims to form comprehensive intellectual visions and clear perceptions about the relationship between human resources competences and their role in increasing the efficiency of business organizations in light of globalization, dynamic changes in the business environment, and the increasing war on talents, in an attempt to generalize the model and the extent of its applicability in the Iraqi environment. The research was launched from an intellectual problem represented in the existing intellectual disparity due to the novelty of the subject and to bridge the knowledge gap between philosophical proposals and application, with the aim of identifying the impact of human resources competences in enhancing the efficiency of the organization. The research relied on the descriptive analytical approach by deriving hypotheses and testing them based on a questionnaire distributed to (86) senior management and employees in a sample of hotels in Baghdad (Taj Hotel, Babylon Hotel, Baghdad Hotel). To analyze the data, statistical methods and tools were used to analyze the data through statistical programs (SPSS), (AMOS 23). The results showed the validity of all the main and sub-hypotheses of the research. Based on that, a set of conclusions was formulated that recommend the necessity for the hotels in the research sample to increase investment in human resources competencies, renew ideas, develop hotel services provided to guests, and pay attention to building trust and creating a combination of creative and innovative human resources.
Sustainable automation: Reducing carbon footprint with energy-efficient RPA solutions
Authors: Singh Chandra Prakash
Published: February 2025

Sustainable automation through energy-efficient Robotic Process Automation (RPA) solutions plays a critical role in reducing carbon footprints by optimizing energy use in IT operations. Leveraging RPA technology, we developed a system that automates energy-saving operations in central monitoring equipment installed in buildings. This system operates seamlessly over a local area network, allowing it to perform optimizations irrespective of the central equipment's specifications. Key energy-saving measures include optimizing heat source system operations, adjusting supply water temperatures, setting room temperatures, and managing outside-air intake volumes. By automating these tasks, the system alleviates the burden on operations managers while significantly reducing energy consumption and emissions. In a trial implementation at a large shopping mall, the system achieved a 44% reduction in energy consumption for outside-air processing and a 47% decrease in CO2 emissions.
Transforming supply chain logistics in oil and gas: best practices for optimizing efficiency and reducing operational costs
Authors: Onukwulu Ekene Cynthia , Fiemotongha Joyce Efekpogua , Igwe Abbey Ngochindo , Ewim Chikezie Paul-Mikki
Published: February 2025

The oil and gas industry operates within a highly complex and dynamic supply chain that demands efficiency, cost-effectiveness, and resilience. This study investigates the latest innovations in oil and gas supply chain logistics, focusing on process optimization techniques to enhance operational efficiency and reduce costs. Given the industry's volatility, optimizing supply chain processes such as cargo clearance, sales efficiency, and inventory management is critical for maintaining profitability and ensuring timely delivery. This paper explores best practices in digital transformation, automation, and data analytics that improve decision-making and streamline logistics operations. Advances such as blockchain-enabled tracking systems, AI-driven predictive analytics, and Internet of Things (IoT) applications in real-time monitoring have revolutionized supply chain visibility, reducing uncertainties and mitigating risks. By leveraging data-driven insights, companies can enhance demand forecasting, optimize transportation routes, and reduce bottlenecks in customs clearance, leading to faster throughput and minimized delays. Furthermore, supply chain resilience in oil and gas requires robust strategies for mitigating disruptions caused by geopolitical tensions, fluctuating oil prices, and environmental regulations. Adopting agile procurement models and strategic supplier partnerships fosters adaptability while ensuring cost-effectiveness. Additionally, integrating cloud-based enterprise resource planning (ERP) solutions with logistics networks improves coordination among stakeholders, reducing redundancies and improving overall efficiency. The study also examines how companies can implement sustainable logistics practices, such as fuel-efficient transportation modes, carbon footprint reduction strategies, and the use of renewable energy in supply chain operations. By incorporating sustainability measures, organizations not only align with global environmental policies but also enhance long-term cost savings. Drawing from real-world case studies and industry benchmarks, this research highlights the effectiveness of these innovations in optimizing oil and gas supply chains. The findingsunderscore the importance of digital transformation, process automation, and data-driven decision-making in achieving operational excellence. By implementing these best practices, oil and gas companies can significantly reduce operational costs, enhance efficiency, and improve delivery timelines, strengthening their competitive edge in a rapidly evolving global market.
Fibromyalgia Syndrome: It’s more than just a mere syndrome
Authors: Parvez Sidrah , Fatima Ghizal , Alhmadi Hekmat B , Hadi Najah , Fedacko Jan
Published: February 2025

Fibromyalgia Syndrome (FMS) is a complex, chronic condition characterized by widespread musculoskeletal pain, fatigue, sleep disturbances, cognitive difficulties, and a variety of other symptoms. Despite being one of the most common chronic pain conditions, affecting millions worldwide, FMS remains poorly understood and frequently misdiagnosed. This paper aims to delve deeper into the multifaceted nature of fibromyalgia, challenging the perception that it is merely a syndrome. The pathophysiology of FMS involves a combination of genetic, neurobiological, and environmental factors. Central sensitization, where the central nervous system becomes hypersensitive to pain stimuli, plays a crucial role. Additionally, imbalances in neurotransmitters, such as serotonin and norepinephrine, contribute to the heightened pain perception and emotional symptoms observed in FMS patients. The syndrome also often coexists with other conditions like irritable bowel syndrome, migraine, and temporomandibular joint disorders, further complicating its diagnosis and management. Traditional diagnostic criteria for FMS, based primarily on tender points and symptom reports, have evolved. Understanding the underlying mechanisms and interactions within the neuroendocrine-immune system is crucial for developing more effective interventions. This paper underscores the necessity of recognizing fibromyalgia as more than just a syndrome. It is a multifactorial condition with profound implications for patients' physical, emotional, and social well-being. Enhanced awareness, comprehensive diagnostic criteria, and integrated treatment strategies are essential for improving the quality of life for patients with FMS.
Artificial Intelligence Survey for 2020 by ACR Data Science Institute
Authors: Vagvala Prabhakar
Published: February 2025

An Outside of the healthcare industry, commercially available artificial intelligence (AI) algorithms have shown signs of racial, gender, and societal prejudice. The development of AI algorithms in the fields of radiologic sciences and healthcare is significantly impacted by these biases. The physician community should work with developers and regulators to create paths that guarantee algorithms sold for widespread clinical practice are secure, efficient, and free of unintended bias in order to prevent the introduction of bias in healthcare AI. Structured AI use cases with data elements have been developed by the ACR Data Science Institute to make it easier to create standardized datasets for AI testing and training at various universities. This project seeks to encourage the accessibility of a variety of data for algorithm development. Additionally, ACR Certify-AI and ACR Assess-AI, validation and monitoring services offered by the ACR Data Science Institute, integrate guidelines for minimizing algorithm bias and advancing health fairness. The ACR should support pricing methods for AI that guarantee access to AI technologies for all patients, regardless of their socioeconomic level or the resources available within their healthcare systems, in addition to promoting diversity. The ACR Data Science Institute conducted its first annual survey of ACR members to better understand how artificial intelligence (AI) is used in clinical practice and to create a baseline for tracking trends. Participants were asked to answer questions about their practice's demographics and to say whether or not they presently use AI in their clinical work, as well as in what capacity. AI has started to be used in mammography screening procedures. According to the report, larger practices were more likely to use AI than smaller ones. The majority of individuals who used AI in clinical practice did so to improve interpretation; the most frequent uses were for the early detection of cerebral hemorrhage, pulmonary emboli, and abnormalities in mammograms. According to the survey results, clinical practice has just recently begun to incorporate AI at a moderate rate. The data acquired from the poll will help researchers and business experts create AI solutions that can improve radiological practice, resulting in enhancements to the effectiveness and quality of patient care.
El papel de la robótica y la inteligencia artificial en los reemplazos de cadera y rodilla
Authors: González-Gutiérrez Bernal , Chambi-Serrano Dennis , González-Agüero Juan Pablo , Caterina-Ibañez Sandra , Anchía Alfaro Adriana , Quesada-Villaseñor Ricardo , Zavaleta-Monestel Esteban
Published: February 2025

El avance en el campo de la inteligencia artificial (IA) ha llevado a su adopción en diversos entornos, incluidos hogares, automóviles y centros médicos. En ortopedia y traumatología, la robótica y la IA han transformado el diagnóstico y tratamiento de trastornos musculoesqueléticos complejos. Tecnologías como la realidad aumentada y mixta mejoran la planificación y ejecución quirúrgica al proporcionar visualización en tiempo real, mientras que sistemas robóticos aumentan la precisión y reducen complicaciones en procedimientos como artroplastías de cadera y rodilla. La IA también optimiza la planificación preoperatoria y la rehabilitación posoperatoria, permitiendo ajustes en el tratamiento y la predicción de complicaciones a través de herramientas avanzadas como sensores y visión artificial. A pesar de los desafíos asociados, como altos costos, la necesidad de capacitación especializada, y preocupaciones éticas y regulatorias en ciberseguridad y privacidad de datos, la futura integración de la IA y la robótica promete personalización y precisión en los tratamientos. Estas innovaciones están revolucionando la medicina ortopédica, abriendo la puerta a procedimientos más efectivos y adaptados a las necesidades individuales de los pacientes.
Desórdenes hematológicos asociados a la vacunación contra SARS-CoV-2
Authors: Moraga Cabezas Mónica , Zavaleta-Monestel Esteban , García-Montero Jonathan , Murillo-Cubero Josué
Published: February 2025

La pandemia de COVID-19 ha impulsado el desarrollo acelerado de vacunas, pero ha revelado eventos adversos, como la trombosis. Esta revisión sistemática analiza la asociación entre las vacunas contra el SARS-CoV-2, causante de la COVID-19 y diversos trastornos hemorrágicos, incluyendo la trombosis del seno venoso cerebral, la trombocitopenia trombótica inmune inducida por vacunas y el síndrome de trombosis con trombocitopenia. Los resultados sugieren una asociación, particularmente con vacunas de vector de adenovirus. Se discute la posible fisiopatología, factores de riesgo y la importancia de la vigilancia post-vacunación. A pesar de estos eventos adversos, los beneficios de la vacunación superan los riesgos, y se enfatiza la necesidad de investigación continua para comprender mejor estos mecanismos y optimizar las estrategias de vacunación.
PENGGUNAAN MEDIA YOUTUBE AKUN KOK BISA DALAM UPAYA MENINGKATKAN KETERAMPILAN MENULIS TEKS TANGGAPAN PESERTA DIDIK KELAS VII SMP CITRA NUSA
Authors: Budiana Sandi , Budiana Sandi , Efendi Roy , Efendi Roy , Risyana Ariq Fauzan
Published: February 2025

Tujuan penelitian dilakukan untuk mengetahui kendala dalam penggunaan media YouTube Akun Kok Bisa? dalam upaya meningkatkan keterampilan menulis teks tanggapan peserta didik kelas VII SMP Citra Nusa serta Kabupaten Bogor yang dialami oleh peserta didik pada keterampilan menulis teks tanggapan. Penelitian ini menggunakan metode kuantitatif eksperimen dengan teknik pengumpulan data menggunakan tes, observasi, dan angket. Populasi yang terdapat pada penelitian ini sebanyak 147 peserta didik dan sampel yang diujicobakan sebanyak 58 peserta didik. Teknik pengambilan sampel menggunakan Cluster Sampling dan kelas yang terpilih VII D sebagai kelas kontrol dan VII sebagai kelas eksperimen. Berdasarkan analisis, hipotesis pertama dapat dibuktikan kebenarannya pada kelas eksperimen saat menerapkan prates mendapatkan rata-rata persentase 63,14% dengan kategori cukup mampu berbeda setelah diterapkan pascates mendapatkan 74,59% masuk kategori cukup mampu. Berdasarkan hasil mean dengan uji-t, bahwa to dengan nilai 2,96 dan d.b 56 lebih tinggi dari ttabel dengan nilai 2,66 dan 2,00, maka lebih besar dibandingkan ttabel dari taraf 1% dan taraf 5%, kemudian apabila dituliskan menjadi (2,662,00). Hipotesis kedua dapat dibuktikan kebenarannya sebanyak (59%) mengalami kendala dalam menentukan kaidah kebahasaan teks tanggapan (52%) mengalami kendala dalam menggunakan kaidah kebahasaan teks tanggapan. (55%) mengalami kendala dalam menuangkan ide dan gagasan dalam menulis teks tanggapan.