DEVELOPMENT OF CLIP THINKING OF HIGHER EDUCATION STUDENTS IN INFORMATION ENVIRONMENT by Sergey Bushuyev, Halyna Korchova, Yurii Krasylnyk, Mykola Rudenko, Borys Kozyr

“….), ensuring an individual approach to the organization of educational and cognitive activities, taking into account the motives, needs and opportunities of higher education seekers, the variability of the selection of IT learning technologies and their combination. …”
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Aspectos de la gramatización antigua de la lengua vasca by Aurélie Arcocha-Scarcia, Joseba Andoni Lakarra

“…In §3 we address aspects of the grammatization of RS, contrasting it with Garibay and other old testimonies: in 3.1 we analyse the size of RS and the "direction" of the translation (Basque/Spanish); in 3.2 we examine certain very marked spellings of RS within the Basque text tradition ( and apical affricate sibilant), related more to the French than the Hispanic tradition; in 3.3 we demonstrate that Mares and not Porralis was the true publisher of the RS and in 3.4 that, in reality, this work was above all a teaching / learning instrument for languages (partic. Basque), a function demonstrated by its singular structure with numbers over each word (§3.5) and in §3.6 we include a coda about the origins of RS incuding the role of Mares is included. …”
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Enhancing antimicrobial resistance strategies: Leveraging artificial intelligence for improved outcomes by Aeshah M. Mohammed, Mohammed Mohammed, Jawad K. Oleiwi, Azlin F. Osman, Tijjani Adam, Bashir O. Betar, Subash C.B. Gopinath, Falah H. Ihmedee

“…By synthesizing current research and applications, the potential of AI-driven technologies—ranging from machine learning models that predict resistance patterns to algorithms enhancing antibiotic discovery—is illuminated to augment our arsenal against AMR. …”
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Risk prediction models for dysphagia after radiotherapy among patients with head and neck cancer: a systematic review and meta-analysis by You Pu, Jin Yang, Lian Shui, Qianlong Tang, Xianqin Zhang, Guangguo Liu

“…Of these models, most were constructed based on logistic regression, while only two studies used machine learning methods. The area under the receiver operating characteristic curve (AUC) reported values for these models ranged from 0.57 to 0.909, with 13 studies having a combined AUC value of 0.78 (95% CI: 0.74-0.81). …”
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PEDAGOGICAL CONTENT THREE-FACTOR MODEL OF EDUCATING HIGH-SCHOOL STUDENTS FOR PROFESSIONAL ACTIVITIES by T. A. Lopatukhina, A. V. Rynkevich

“…In the long run, in the author’s opinion, this system should succeed in creating some special platform for student’s further self-upbringing and self-learning. The model described in the paper is considered on the example of the discipline «A foreign language in the professional sphere». …”
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Impact of training dairy farm personnel on milking routine compliance, udder health, and milk quality by Zelmar Rodriguez, Mario Lopez-Benavides, Marianna B. Gentilini, Pamela L. Ruegg

“…The training session was delivered using an active learning approach prioritizing group discussions, and focused on the pathogenesis, identification, and risk factors for mastitis, as well as the rationale and importance of each step in the milking routine. …”
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Early Detection of Multiwavelength Blazar Variability by Hermann Stolte, Jonas Sinapius, Iftach Sadeh, Elisa Pueschel, Matthias Weidlich, David Berge

“…For this purpose, we have developed a novel deep learning analysis framework, based on data-driven anomaly detection techniques. …”
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Health profession students’ perceptions of ChatGPT in healthcare and education: insights from a mixed-methods study by Lior Moskovich, Violetta Rozani

“…The findings highlight benefits such as serving as a convenient tool for accessing information, reducing human errors, and fostering innovative learning approaches. However, they also underscore areas of concern, including ethical considerations, challenges in fostering critical thinking, and issues related to verification. …”
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Supporting implementation of universal prevention initiatives in K-12 schools: impacts on fidelity through organizational readiness and team functioning in a cluster-randomized tri... by Christopher M. Fleming, Hannah G. Calvert, Lindsey Turner

“…Abstract Background Rural School Support Strategies (RS3) is a bundle of implementation supports (including training, technical assistance, and a virtual learning collaborative) designed for the scale-up of universal prevention initiatives. …”
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The Principal Leadership in Developing Inclusive Education for Diverse Students by Shinta Setia, Pwee Leng, Yurillah Endah Mauliate, Dian Ekowati, Dwi Ratmawati

“…Such practices can also be learned, adapted and imitated by other schools.…”
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The adolescent Internet Adaptability Scale: Development and psychometric properties by Weijun Wang, Jianmei Ye, Rouchun Dong, Shihao Ma, Dawei Huang, Xin Zhao

“…The AIAS, comprising eight dimensions—Internet curiosity, Internet self-efficacy, Internet learning ability, Internet socialization ability, Internet information search ability, Internet information protection ability, Internet self-control ability, and Internet positive coping ability—demonstrates strong reliability and validity. …”
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Artificial intelligence driven clustering of blood pressure profiles reveals frailty in orthostatic hypertension by Claire M. Owen, Jaume Bacardit, Maw P. Tan, Nor I. Saedon, Choon‐Hian Goh, Julia L. Newton, James Frith

“…Given the richness of non‐invasive beat‐to‐beat data, artificial intelligence (AI) offers a solution to detect the subtle patterns within it. Applying machine learning to an existing dataset of community‐based adults undergoing postural assessment, we identified three distinct clusters (iOHYPO, OHYPO and OHYPER) akin to initial and classic orthostatic hypotension and orthostatic hypertension, respectively. …”
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Predicting the tumor microenvironment composition and immunotherapy response in non-small cell lung cancer from digital histopathology images by Sushant Patkar, Alex Chen, Alina Basnet, Amber Bixby, Rahul Rajendran, Rachel Chernet, Susan Faso, Prashanth Ashok Kumar, Devashish Desai, Ola El-Zammar, Christopher Curtiss, Saverio J. Carello, Michel R. Nasr, Peter Choyke, Stephanie Harmon, Baris Turkbey, Tamara Jamaspishvili

“…Here, we introduce HistoTME, a novel weakly supervised deep learning approach to infer the tumor microenvironment (TME) composition directly from histopathology images of NSCLC patients. …”
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LipBengal: Pioneering Bengali lip-reading dataset for pronunciation mapping through lip gesturesHugging Face by Md. Tanvir Rahman Sahed, Md. Tanjil Islam Aronno, Hussain Nyeem, Md. Abdul Wahed, Tashrif Ahsan, R Rafiul Islam, Tareque Bashar Ovi, Manab Kumar Kundu, Jane Alam Sadeef

“…Captured under diverse and uncontrolled conditions, LipBengal stands as the most extensive Bengali lip-reading dataset to date, designed to facilitate robust benchmarking and validation of novel deep learning architectures. Detailed annotations extend from phoneme- level classifications to full sentence constructions, providing a granular and comprehensive dataset. …”
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Integrated Analysis and Validation of Ferroptosis-Related Genes Associated with Ischemia/Reperfusion Injury in Lung Transplantation by Li Q, Yin J, Lin Q, He J, Shi X, Nie H

“…Weighted gene co-expression network analysis (WGCNA) was used to identify module genes, and overlapping genes were further analyzed using two machine learning algorithms. The CIBERSORT algorithm was applied to assess immune cell infiltration, while Mendelian randomization (MR) analysis was used to investigate causal relationships between candidate genes and PGD. …”
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A Digital-based Talent Acquisition Framework for Start-ups: A Qualitative Multiple Case Study by Mohammad Hosein Kenarroodi, Hasan Boudlaie

“…The final stage of research coding identified ten key themes for talent acquisition in startups, including: taking an aggressive approach to talent acquisition, creating a strong employer brand, managing relationships with talents, identifying risks in talent selection, designing selection criteria and methods, determining selection quality, setting onboarding timelines, and developing learning methods and content for onboarding.     Conclusion Drawing from the identified themes, this study proposes three digitalization-driven strategies to enhance talent acquisition in startups: talent recruitment, talent selection, and onboarding processes. …”
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SFMHANet: Surface Fitting Constrained Multidimensional Hybrid Attention Network for Aero-Optics Thermal Radiation Effect Correction by Yu Shi, ShanLin Niu, Lei Wang, Liang Ye, YaoZong Zhang, HanYu Hong

“…In order to handle multiple types of aero-optics thermal radiation effects effectively and to combine the advantages of image prior constraints and deep learning networks, we propose a surface fitting constrained multidimensional hybrid attention aero-optics thermal radiation correction network (SFMHANet) in this article. …”
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Identification of a novel immunogenic cell death-related classifier to predict prognosis and optimize precision treatment in hepatocellular carcinoma by Dongjing Zhang, Bingyun Lu, Qianqian Ma, Wen Xu, Qi Zhang, Zhiqi Xiao, Yuanheng Li, Ren Chen, An-jiang Wang

“…A reliable risk model named ICD score was constructed via machine learning algorithms to assess the immunological status, therapeutic responses, and clinical outcomes of individual HCC patients. …”
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Evolution and Recent Radiation Therapy Advancement in Uganda: A Precedent on How to Increase Access to Quality Radiotherapy Services in Low- and Middle-Income Countries by Awusi Kavuma, Solomon Kibudde, Daniel Kanyike, Joseph Kigula-Mugambe, Tianyu Zhao, Hiram Gay, Baozhou Sun, Jackson Orem

“…This review can be a learning lesson for the more than 25 countries in Africa and other low-middle-income countries globally that do not have access to radiotherapy and/or are in the process of starting such facilities.…”
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Halal or Not: Knowledge Graph Completion for Predicting Cultural Appropriateness of Daily Products by Van Thuy Hoang, Tien-Bach-Thanh do, Jinho Seo, Seung Charlie Kim, Luong Vuong Nguyen, Duong Nguyen Minh Huy, Hyeon-Ju Jeon, O-Joun Lee

“…Recently, various machine learning-based strategies, e.g., image-based methods, have shown remarkable success in predicting the halal status of cosmetics. …”
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