Factors Influencing the Implementation and Adoption of Digital Nursing Technologies: Systematic Umbrella Review by Stefan Walzer, Christoph Armbruster, Sonja Mahler, Erik Farin-Glattacker, Christophe Kunze

“…MethodsWe used an umbrella review methodology to synthesize the evidence on DNTs and the complexities of their implementation. …”
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The role of artificial intelligence in enhancing personalized learning pathways and clinical training in dental education by Chengchen Hu, Fang Li, Shengguo Wang, Zhi Gao, Shan Pan, Maofeng Qing

“…The review also addresses the expanding integration of AI into educational settings, highlighting both the benefits and the ethical challenges, including issues related to data privacy, algorithmic bias, and the evolving role of human educators. …”
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AI adoption in Chinese universities: Insights, challenges, and opportunities from academic leaders by Xibing Wang, Shuli Zhao, Xiaoshu Xu, Huanhuan Zhang, Vivian Ngan-Lin Lei

“…Additionally, resource allocation, funding constraints, and concerns over data privacy and security present significant barriers. …”
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Human Dignity in Genetics and Reproductive Health in the Digital Age by Archibong EI, Ukeagu LOC, Arinmi AO, Emeka EE, Igalawuye GO

“…The study’s significance lies in the view that technology determines the trajectory of the rules of engagement in the comity of humans and even medical practice with the imperative of prioritising human dignity in the development and use of genetic and reproductive health technologies. …”
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A novel half-complementary cipher for in-situ secure computing-in-memory by Ying Zhou, Wenbiao Zhang, Yinuo Shi, Xiaomi Chen, Jianting Liu, Xiang Feng, Tiejun Zhou, Bo Liu

“…The advent of the new AI era has led to an increase in the number of intelligent terminals in use and the generation of a vast amount of data, driving the development of novel AI accelerator techniques. …”
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Integrating Large Language Models into Robotic Autonomy: A Review of Motion, Voice, and Training Pipelines by Yutong Liu, Qingquan Sun, Dhruvi Rajeshkumar Kapadia

“…We also highlight the use of physics-informed neural networks (PINNs) to model object deformation and support precision in contact-rich manipulation tasks. …”
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Implementation of NGS and SNP microarrays in routine forensic practice: opportunities and barriers by Sharlize Pedroza Matute, Sasitaran Iyavoo

“…Conversely, SNP microarrays offer a cost-effective solution for extended kinship testing, Forensic Investigative Genetic Genealogy (FIGG), and phenotypic prediction, though they are less effective with low-quality samples and DNA mixtures. Ethical, legal, and privacy concerns, particularly surrounding the use of Forensic DNA Phenotyping (FDP) and consumer genetic data in FIGG, further complicate their integration into forensic workflows. …”
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Decentralized electrochemical biosensors for biomedical applications: From lab to home by Pramod K. Kalambate, Vipin Kumar, Dhanjai

“…However, potential risks such as data security vulnerabilities, privacy concerns, and regulatory challenges must be addressed to ensure safe and ethical deployment of these technologies. …”
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Comprehensive Review and Future Research Directions on ICT Standardisation by Mohammed Najah Mahdi, Ray Walshe, Sharon Farrell, Harshvardhan J. Pandit

“…Standardisation also solves problems, such as the use of mobile devices, which requires travel abroad when out of range. …”
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Ethical and Safety Challenges of Implantable Brain-Computer Interface by Ihab Abdulrahman Satam, Róbert Szabolcsi

“…The study of brain-computer interfaces (BCIs) holds immense potential across various fields, particularly in Human-Robot Interaction, where invasive BCIs offer precise and direct communication between the human brain and robotic devices. However, the use of invasive BCIs raises significant ethical, safety, and security concerns that must be addressed to ensure their responsible deployment. …”
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Domain-Specific Modeling Language for Security Analysis of EV Charging Infrastructure by Anas Motii, Mahmoud El Hamlaoui, Robert Basmadjian

“…This interconnection raises concerns about security, privacy, and the expanding risk of cyber-attacks within the electric vehicle landscape. …”
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Beijing’s urbanization reflected in apartment layouts: a computer vision and isovist analysis (1970–2020) by Yanhua Yao, Ashutosh Kumar, Martina Mazzarello, Fábio Duarte, Lei Shao, Limin Song, Carlo Ratti

“…Our findings show a trend in the isovist intensity of living rooms, dining rooms, and kitchens, indicative of shifts toward privacy and mixed-use spaces, shaped by household occupancy patterns. …”
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HELA-CMM: capability maturity model for adoption of learning analytics in higher education by Diana Šimić, Nina Begičević Ređep, Sabina Rako, Nikola Kadoić, Wim Van Petegem, Bart Rienties, Nati Cabrera Lanzo, Michael Eichhorn, Lourdes Guàrdia, Sandra Kučina Softić, Alexander Tillmann

“…The proposed maturity model comprises 28 capabilities grouped into eight categories: (1) Teaching / Learning / Assessment, (2) Data Management and Analytics, (3) Ethics, Privacy, Legal Issues, (4) People Competences, (5) Management / Leadership, (6) Culture, (7) Infrastructure, and (8) Quality Assurance. …”
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A Deep Learning-Based Ensemble Framework for Robust Android Malware Detection by Sainag Nethala, Pronoy Chopra, Khaja Kamaluddin, Shahid Alam, Soltan Alharbi, Mohammad Alsaffar

“…The exponential growth of Android applications has resulted in a surge of malware threats, posing severe risks to user privacy and data security. To address these challenges, this study introduces a novel malware detection approach utilizing an ensemble of Convolutional Neural Networks (CNNs) for enhanced classification accuracy. …”
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Modern Trends in the Digitalization of Higher Physical Education in China by Chen RUI

“…Additionally, the study emphasizes the need for educator training and professional development, as many physical education teachers lack digital literacy or are resistant to new technologies. Data privacy and security issues are another significant challenge, particularly with the collection and use of personal and health data from wearable devices and online platforms. …”
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Barriers and facilitators of the electronic medical record adoption among healthcare providers in Addis Ababa, Ethiopia by Tadesse Alemu Bekele, Lemma Derseh Gezie, Herman Willems, Jonathan Metzger, Biruhtesfa Abere, Blen Seyoum, Loko Abraham, Naod Wendrad, Selamawit Meressa, Bethel Desta, Tariku Nigatu Bogale

“…Methods A descriptive-phenomenological approach was used. Data were collected from one hospital and three health centers from 5–13 June, 2023, that implemented the EMR. …”
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Zero-Touch Network Security (ZTNS): A Network Intrusion Detection System Based on Deep Learning by Emad-Ul-Haq Qazi, Tanveer Zia, Muhammad Hamza Faheem, Khurram Shahzad, Muhammad Imran, Zeeshan Ahmed

“…The rapid evaluation of smart cities has revolutionized the research and development field to a very extensive level which presents challenges in handling massive amounts of data. However, the integration of IoT into various aspects of life has introduced various challenges related to the security and privacy of IoT systems. …”
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Detecting Learning Behavior in Programming Assignments by Analyzing Versioned Repositories by John Chen, Serena Lau, Juho Leinonen, Valerio Terragni, Nasser Giacaman

“…The Polivr ecosystem comprises three key modules: Polivr Anonymiser, which ensures data privacy by anonymising student identities; Polivr Core, which mines learning metrics from Git repositories; and Polivr Web Viewer, which transforms the raw metrics into insightful visualisations for educators. …”
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Large Language Model and Traditional Machine Learning Scoring of Evolutionary Explanations: Benefits and Drawbacks by Yunlong Pan, Ross H. Nehm

“…Few studies have compared Large Language Models (LLMs) to traditional Machine Learning (ML)-based automated scoring methods in terms of accuracy, ethics, and economics. Using a corpus of 1000 expert-scored and interview-validated scientific explanations derived from the ACORNS instrument, this study employed three LLMs and the ML-based scoring engine, EvoGrader. …”
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Contrastive Self-Supervised Learning for Sensor-Based Human Activity Recognition: A Review by Hui Chen, Charles Gouin-Vallerand, Kevin Bouchard, Sebastien Gaboury, Melanie Couture, Nathalie Bier, Sylvain Giroux

“…Next, we comprehensively review data augmentation methods for sensor data and commonly used benchmark datasets for activity recognition. …”
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