Artificial intelligence in academic research: Benefits, challenges, and ethical dimensions in doctoral studies by Zaki EL HANI, Jaouad KARROUM, Abdelmajid ELOUADI, Aniss MOUMEN

“…However, this transformation is accompanied by challenges, including ethical concerns such as algorithmic bias, risks to data privacy, and over-reliance on automation, which may erode critical thinking and human judgment. …”
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AI IN CYBER DEFENSE: PRIVACY RISKS, PUBLIC TRUST, AND POLICY CHALLENGES by Abdullah Azizi, Mohammad Qias Mohammadi, Abdul Wahid Samadzai

“…The results reveal that while AI-based systems improve threat detection and response times, they also raise significant concerns about data privacy, surveillance, and the potential for algorithmic bias. …”
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Balancing tech and humanity by Linda Cottone

“…As threats like cyber insecurity and AI-based decision-making rise, the role of both state and non-state actors becomes essential in safeguarding rights while managing migration. While technology can enhance efficiency, as shown in Lebanon's response to the Tripoli bomb attack, it must adhere to international legal standards, especially privacy protections in the ICCPR and UDHR. …”
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Generation of Genuine Multipartite Entangled States via Indistinguishability of Identical Particles by Kobra Mahdavipour, Farzam Nosrati, Stefania Sciara, Roberto Morandotti, Rosario Lo Franco

“…The presented theoretical approach, while already implementable with current linear optics architectures, has the potential to bring clear advantages over existing technologies, such as in quantum computing search algorithms and in the design of new experiments in quantum optics or other platforms.…”
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The Double-Edged Sword of Social Media in the European Union Crisis Management: A Literature Review by Tănase Tasențe

“…Key themes include the paradoxical nature of social media as a “double-edged sword”: enabling real-time updates and grassroots mobilization while also fueling polarized discourse and disinformation. …”
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Immune-Mediated Adverse Events Associated with Ipilimumab CTLA-4 Blockade Therapy: The Underlying Mechanisms and Clinical Management by Ahmad Tarhini

“…The skin and gastrointestinal tract are most frequently affected, while hepatic, endocrine, and neurologic events are less common. …”
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PREDICTION INTERVALS IN MACHINE LEARNING: RESIDUAL BOOTSTRAP AND QUANTILE REGRESSION FOR CASH FLOW ANALYSIS by Wa Ode Rahmalia Safitri, Farit Mochamad Afendi, Budi Susetyo

“…Time series forecasting often faces challenges in producing reliable predictions due to inherent uncertainty in dynamic systems. While point predictions are commonly used, they may not adequately capture this uncertainty, especially in financial systems where forecasting accuracy directly impacts decision-making. …”
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Experimental and machine learning based analysis of pervious concrete enhanced with fly ash and silica fume by Siva Shanmukha Anjaneya Babu Padavala, Siva Avudaiappan, Venkatesh Noolu

“…SVM achieved the highest predictive accuracy (R2 = 0.98), while KNN and ANN showed lower performance (R2 = 0.69 and 0.71, respectively). …”
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DREFNet: Deep Residual Enhanced Feature GAN for VVC Compressed Video Quality Improvement by Tanni Das, Kiho Choi

“…Different compression tools in modern video codecs are vital for minimizing artifacts that arise during the encoding and decoding processes. While the advanced algorithms used by these modern codecs can effectively decrease file sizes and enhance compression efficiency, they frequently find it challenging to eliminate artifacts entirely. …”
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Visual impairment prevention by early detection of diabetic retinopathy based on stacked auto-encoder by Shagufta Almas, Fazli Wahid, Sikandar Ali, Ahmed Alkhyyat, Kamran Ullah, Jawad Khan, Youngmoon Lee

“…Leveraging a comprehensive dataset from KAGGLE containing 35,126 retinal fundus images representing one healthy (normal) stage and four DR stages, our proposed model demonstrates superior accuracy compared to existing deep learning algorithms. Data augmentation techniques address class imbalance, while SAEs facilitate accurate classification through layer-wise unsupervised pre-training and supervised fine-tuning. …”
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Enhancing stone matrix asphalt performance with sugarcane bagasse ash: Mechanical properties and machine learning-based predictions using XGBoost and random forest by Hamed Khani Sanij, Rezvan Babagoli, Reza Mohammadi Elyasi

“…This dual approach—experimental validation and ML-based prediction—confirms that SCBA can effectively serve as a sustainable filler in SMA, offering performance gains while reducing environmental impact. Additionally, the successful integration of ensemble ML algorithms provides a reliable framework for forecasting key performance metrics in asphalt engineering. …”
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Routine and Adaptive Experts: Individual Characteristics and Their Impact on Multidigit Arithmetic Strategy Flexibility and Mathematics Achievement by Lóa Björk Jóelsdóttir, Pernille Bødtker Sunde, Peter Sunde, Paul Andrews

“…Students offering multiple solutions to a task were defined as flexible, while arithmetic experts (defined by accuracy) were distinguished by their use of shortcut strategies; routine experts never used them, while adaptive experts used them in at least one third of all tasks. …”
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Edge-based detection and localization of adversarial oscillatory load attacks orchestrated by compromised EV charging stations by Khaled Sarieddine, Mohammad Ali Sayed, Sadegh Torabi, Ribal Atallah, Chadi Assi

“…The edge-based detection relies on the behavioral characteristics of the power grid in the presence of interconnected EVCS while combining cyber and physical layer features to implement deep learning algorithms for the effective detection of oscillatory load attacks at the EVCS. …”
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ARTIFICIAL INTELLIGENCE IN ACADEMIA: OPPORTUNITY OR CHALLENGE? by L.H. Grigoryan, M. V. Badalyan, A.Z. Grigoryan

“…AI presents a dual reality for academic institutions: it brings forward unprecedented opportunities for innovation and efficiency, while simultaneously introducing complex ethical, pedagogical, and operational challenges. …”
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Heterogeneity in willingness to share personal health information: a nationwide cluster analysis of 20,000 adults in Japan by Miho Sassa, Akifumi Eguchi, Keiko Maruyama-Sakurai, Takanori Fujita, Yumi Kawamura, Takayuki Kawashima, Yuta Tanoue, Daisuke Yoneoka, Hiroaki Miyata, Takanori Yamashita, Naoki Nakashima, Shuhei Nomura

“…Abstract Background While Personal Health Records (PHRs) are increasingly adopted globally, understanding public attitudes toward health information sharing remains crucial for successful implementation. …”
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Enhancing Power Efficiency in 4IR Solar Plants through AI-Powered Energy Optimization by S. Boobalan, TR. Kalai Lakshmi, Shubhangi N. Ghate, Mohammed Hameeduddin Haqqani, Sushma Jaiswal

“…The AI-powered system relies on intelligent algorithms to identify the most efficient energy sources for the industry’s needs and adjust them accordingly while learning from every task it is given. …”
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Adapting e-Genius for Next-Level Efficient Electric Aerotow with High-Power Propulsion and Automatic Flight Control System by Stefan Zistler, Dalong Shi, Walter Fichter, Andreas Strohmayer

“…An advanced propulsion system is developed using high-performance batteries and available electric drive components, while the AFCS is designed following a systematic process of developing flight control algorithms. …”
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Authenticity Recognition of Rice Varieties Based on Polarization Imaging Technology by Jie FU, Yue WU

“…Utilizing six convolutional neural network algorithms (AlexNet, VGG16, GoogLeNet, ResNet34, DenseNet, and ConvNeXt V2), models were established to identify the authenticity of japonica and indica rice varieties based on various image types and algorithms. …”
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Optimizing cervical cancer classification using transfer learning with deep gaussian processes and support vector machines by Emmanuel Ahishakiye, Fredrick Kanobe

“…Machine learning (ML) algorithms have been used in the automated classification of cervical cancer. …”
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Rigorous and extensive accuracy assestment of automatically classified LiDAR data: a case study in the city of Milan, Italy by D. Lodigiani, V. M. Casella

“…We created a comprehensive ground truth dataset to validate our filtering method through valid and well-known algorithms like TerraSolid, and that obtained in an industrial environment where expert users applied these algorithms under time constraints. …”
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