Mental Health Apps Available in App Stores for Indian Users: Protocol for a Systematic Review by Seema Mehrotra, Ravikesh Tripathi, Pramita Sengupta, Abhishek Karishiddimath, Angelina Francis, Pratiksha Sharma, Paulomi Sudhir, Srikanth TK, Girish N Rao, Rajesh Sagar

“…Additionally, the apps will be reviewed for quality using the Mobile Application Rating Scale. The data analysis and synthesis strategy will incorporate descriptive statistics based on quality evaluation using the Mobile Application Rating Scale and examining the content of the apps for generating descriptive information. …”
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Features of Structured, One-to-One Videoconference Interventions That Actively Engage People in the Management of Their Chronic Conditions: Scoping Review by Yu-Ting Chen, Michelle Lehman, Toni Van Denend, Jacqueline Kish, Yue Wu, Katharine Preissner, Matthew Plow, Tanya L Packer

“…Studies reporting assessment or routine care were excluded. Extracted text data were analyzed using thematic analysis and published taxonomies. …”
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ARTIFICIAL INTELLIGENCE IN ACADEMIA: OPPORTUNITY OR CHALLENGE? by L.H. Grigoryan, M. V. Badalyan, A.Z. Grigoryan

“…On the other hand, the growing reliance on AI raises serious concerns related to academic integrity, data privacy, algorithmic bias, and the potential deskilling of educators. …”
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Dynamics of Robo-Advisory Financial Services in Saudi Arabia by Heba Gazzaz

“…The key limitations of adopting Robo-advisory services include algorithmic bias, a lack of trust and transparency, legal and regulatory issues, privacy and data security concerns, and limited financial literacy. …”
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Context-Aware Trust and Reputation Routing Protocol for Opportunistic IoT Networks by Jagdeep Singh, Sanjay Kumar Dhurandher, Isaac Woungang, Han-Chieh Chao

“…Simulation experiments using the ONE simulator show that CATR is superior to the Epidemic protocol, the so-called beta-based trust and reputation evaluation system (denoted BTRES), and the secure and privacy-preserving structure in opportunistic networks (denoted PPHB+), achieving an improvement of 22%, 15%, and 9% in terms of average latency, number of messages dropped, and average hop count, respectively, under varying number of nodes, buffer size, time to live, and message generation interval.…”
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AI Robotics in Healthcare Between the EU Medical Device Regulation and the Artificial Intelligence Act<subtitle>Gaps and Inconsistencies in the Protection of Patients and Care Reci... by Martin Ebers

“…The growing inclusion of social robots in therapeutic situations raises a variety of unresolved legal and ethical issues, including risks to patient autonomy, human dignity and trust, the potentially life-threatening effects of inaccurate or malfunctioning technology, diminished privacy due to the reliance on enormous amounts of personal (sensitive health) data, new challenges to data security due to the cyber-physical nature of robots, and the problem of how to obtain informed consent to medical treatments based on opaque AI decision making. …”
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Federated learning-based user access strategy and energy consumption optimization in cell-free massive MIMO network by Yuanyuan YAO, Yiqiu LIU, Sai HUANG, Chunyu PAN, Xuehua LI, Xin YUAN

“…To solve the problem that how users choose access points in cell-free massive multiple-input multiple-output (CF-mMIMO) network, a prioritized access strategy for poorer users based on channel coefficient ranking was proposed.First, users were evaluated and ranked for their channel quality and stability after channel sensing, and suitable access points were selected in sequence according to the order of the channel state information.Second, considering issues such as users' energy consumption and data security, a federal learning framework was used to enhance user's data privacy and security.Meanwhile, an alternating optimization variables algorithm based on energy consumption optimization was proposed to optimize the multi-dimensional variables, for the purpose of minimizing the total energy consumption of the system.Simulation results show that compared with the traditional user-centric in massive MIMO, the proposed access strategy can improve the average uplink reachable rate of users by 20%, and the uplink rate of users with poor channels can be double improved; in terms of energy consumption optimization, the total energy consumption can be reduced by much more than 50% after optimization.…”
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Examining Factors Impacting Online Survey Response Rates in Educational Research: Perceptions of Graduate Students by Amany Saleh, Krishna Bista

“…The authors used descriptive statistics (percentage, average mean) and inferential statistics (chi-square and correlations) to report the data analysis and findings. …”
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Assessing the Effects of Cancer Diagnosis and Coping Strategies on Patients in Vhembe District Hospitals, Limpopo Province by Dorah Ursula Ramathuba, Takalani Friddah Rafundisani, Maria Sonto Maputle

“…A self-administered questionnaire was used to collect data, and the data were analyzed using a software package for descriptive statistics (SPSS version 23). …”
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Pooled Rideshare in the U.S.: An Exploratory Study of User Preferences by Rakesh Gangadharaiah, Johnell Brooks, Lisa Boor, Kristin Kolodge, Haotian Su, Yunyi Jia

“…The study incorporated 77 actionable items developed from the results of the 2021 survey to assess whether addressing specific user-generated topics such as safety, reliability, convenience, and privacy can improve pooled rideshare use. A side-by-side comparison of the 2021 and 2025 data revealed shifts in transportation behavior, with personal rideshare usage increasing from 22% to 28%, public transportation from 21% to 27%, and pooled rideshare from 6% to 8%, while personal vehicle (79%) use remained dominant. …”
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DAMPAK PEMANFAATAN ARTIFICIAL INTELLIGENCE (AI) DALAM PERILAKU PENGAMBILAN KEPUTUSAN TERHADAP ETIKA BISNIS DAN KEBERLANJUTAN ORGANISASI by Putu Ayu Diah Widari Putri, Nyoman Yudha Astriayu Widyari, Ida Ayu Komang Tiara Pratistha Sari

“…In an increasingly complex and competitive business era, AI has become a strategic tool that can increase the speed, accuracy, and objectivity of data-based decision-making. However, its use also poses significant ethical challenges, such as issues of transparency, algorithmic bias, accountability, and data privacy. …”
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Towards AI-Powered Applications: The Development of a Personalised LLM for HRI and HCI by Khashayar Ghamati, Maryam Banitalebi Dehkordi, Abolfazl Zaraki

“…Furthermore, this study engages with the broader ethical dimensions of PLLM, critically discussing issues of generalisability and data privacy concerns in AI research. Our findings demonstrate the usability of using the PLLM in a human–robot interaction scenario in real-world settings, highlighting its applicability across diverse domains, including healthcare, education, and assistive technologies. …”
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Bibliometric analysis of digital transformation on organization design by Božić Katarina

“…Using the Bibliometrix software package in the R programming language, bibliographic data analysis was performed in order to identify the most influential authors, key topics and future research directions. …”
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Energy Efficiency of Kernel and User Space Level VPN Solutions in AIoT Networks by ALEKSANDAR JEVREMOVIC, Zona Kostic, Ivan Chorbev, Dragan Perakovic, Andrii Shalaginov, Ivan Cvitic

“…The ability to process data locally using complex algorithms is becoming increasingly important in Internet of Things (IoT) contexts. …”
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Integrating Model‐Informed Drug Development With AI: A Synergistic Approach to Accelerating Pharmaceutical Innovation by Karthik Raman, Rukmini Kumar, Cynthia J. Musante, Subha Madhavan

“…However, several challenges, including the availability of relevant, labeled, high‐quality datasets, data privacy concerns, model interpretability, and algorithmic bias, must be carefully managed. …”
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AI-driven multimodal colorimetric analytics for biomedical and behavioral health diagnostics by Desta Haileselassie Hagos, Saurav Keshari Aryal, Patrick Ymele-Leki, Legand L. Burge

“…In addition, we highlight the need for robust data management systems and interpretable AI/ML models to ensure security, privacy, and reliability in biomedical and behavioral research. …”
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GLOBE Observer: A Case Study in Advancing Earth System Knowledge with AI-Powered Citizen Science by Peder V. Nelson, Russanne Low, Holli Kohl, David Overoye, Di Yang, Xiao Huang, Sriram Chellappan, Farhat Binte Azam, Ryan M. Carney, Monika Falk, Joan Garriga, Larisa Schelkin, Rebecca Boger, Theresa Schwerin

“…GLOBE citizen science data has been used to develop automated data classification routines that enable information discovery of mosquito larvae and land cover labels. …”
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Enabling All In-Edge Deep Learning: A Literature Review by Praveen Joshi, Mohammed Hasanuzzaman, Chandra Thapa, Haithem Afli, Ted Scully

“…Moreover, most of the time central cloud servers are used for such computation, thus opening up other significant challenges, such as high latency, increased communication costs, and privacy concerns. …”
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Exploring the Knowledge and Utilization of Video-Based Surgical Learning Among Medical Students in a Teaching Hospital in Nigeria: A Mixed-Methods Study by Asogun Daniel, Akhaine Jesu-Oboh Precious, Sulymon A. Saka, Vivian Oghobaghase, Ojeh-Oziegbe Oseyomon, Francis Ufuah, Adomi Solomon

“…Quantitative data were analyzed using SPSS version 21 for descriptive statistics, while thematic coding was applied to qualitative data using NVivo. …”
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A distributed robust state estimation method based on alternating direction method of multipliers for integrated electricity‐heat system by Yanbo Chen, Yulong Gao, Zhe Fang, Jiaqi Li, Zhenda Hu, Yichao Zou, Jin Ma, Chunlai Li, Qinze Xiao, Zeyu Chen

“…Simulations demonstrate that the proposed method has higher estimation accuracy in both general and strongly correlated adverse data tests and also can ensure data privacy, good robustness and high estimation accuracy. …”
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