Deciphering microbial and metabolic influences in gastrointestinal diseases-unveiling their roles in gastric cancer, colorectal cancer, and inflammatory bowel disease by Daryll Philip, Rebecca Hodgkiss, Swarnima Kollampallath Radhakrishnan, Akshat Sinha, Animesh Acharjee

“…These models were then employed for cross-disease analysis, revealing that models trained on GC data successfully predicted IBD biomarkers, while CRC models predicted GC biomarkers with optimal performance scores. …”
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The unwell patient with advanced chronic liver disease: when to use each score? by Oliver Moore, Wai-See Ma, Scott Read, Jacob George, Golo Ahlenstiel

“…Incorporating artificial intelligence to personalise predictive algorithms may provide the most effective prognostication for all clinical phenotypes. …”
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Role of Roadside Units in Cluster Head Election and Coverage Maximization for Vehicle Emergency Services by Ravneet Kaur, Robin Doss, Lei Pan, Chaitanya Singla, Selvarajah Thuseethan

“…Efficient clustering algorithms are critical for enabling the timely dissemination of emergency messages across maximum coverage areas in vehicular networks. …”
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Post-Quantum Cryptography Resilience in Telehealth Using Quantum Key Distribution by Don Roosan, Rubayat Khan, Saif Nirzhor, Fahmida Hai

“…Methods A multi-layered design approach was adopted. PQC algorithms (e.g., CRYSTALS-Dilithium) were integrated at the blockchain consensus layer to resist quantum attacks. …”
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Low-light image enhancement method based on retinex theory and dual-tree complex wavelet transform by Yuqian Zhang, Jie Jiang, Zhan Wang, Qi Zhang, Yudi Jiang, Jun Liu, Zeyao Hou

“…To address these problems, various Low-light Image Enhancement (LIE) algorithms have been developed in recent years, including histogram-based methods, gamma correction, and approaches based on Retinex theory. …”
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Quantum-enabled topological optimization of distributed energy storage for resilient black-start operations by Yinchi Shao, Yu Gong, Xiaoyu Wan, Xianmiao Huang, Shanna Luo, Yuntao Cao, Tao Zhang

“…The approach is formulated through a comprehensive mathematical model that captures key interactions between network topology, energy flow dynamics, and black-start performance indicators such as restoration time, efficiency, and resilience. …”
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Design of an intelligent AI-based multi-layer optimization framework for grid-tied solar PV-fuel cell hybrid energy systems by Prashant Nene, Dolly Thankachan

“…The results validate its capability when compared against traditional methods such as Genetic Algorithms and Particle Swarm Optimization. With this, we now have a scalable and real-time energy-efficient solution for future smart grid systems. • Integrated Intelligence Stack: Combines RL-ENN, T-STFREP, FL-DEO, GNNHSCO, and Q-GAN-ESO into a unified architecture for real-time control, forecasting, decentralized optimization, network routing, and synthetic scenario generation. • Real-Time, Scalable, and Privacy-Preserving: Enables adaptive energy dispatch, federated optimization without compromising data privacy, and graph-based power routing, making it suitable for large-scale, smart grid deployments. • Proven Long-Term Performance: Achieved significant improvements over traditional methods (GA, PSO) with 27.5 % lower NPC, 18.2 % reduction in COE, and 30.2 % increase in battery life, validated using 30 years of meteorological data.…”
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Evaluation of ecological environment quality in China's mining areas by remote sensing: A review by LI Feiyue, LI Jun, XIAO Wu, ZHANG Chengye, WANG Shanshan, YANG Junquan, ZHANG Xiaoping, CHENG Yang

“…Potential research opportunities include expanding accessible indicators by remote sensing, constructing a framework for integrated data collection on the surface and underground, improving the data quality of remote sensing indicators, constructing a new indicator system for evaluation using remote sensing, and developing cloud computing algorithms.…”
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The potential & limitations of monoplotting in cross-view geo-localization conditions by Bradley J. Koskowich, Michael J. Starek, Scott A. King

“…This proposed methodology demonstrates an average 42x improvement in feature matching between CVGL image pairs, which improves on inconsistent baseline methodology by reducing translation errors between 50%–75%.…”
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Deep Learning-Driven Throughput Maximization in Covert Communication for UAV-RIS Cognitive Systems by Van Nhan Vo, Nguyen Quoc Long, Viet-Hung Dang, Tu Dac Ho, Hung Tran, Symeon Chatzinotas, Dinh-Hieu Tran, Surasak Sanguanpong, Chakchai So-In

“…In particular, optimization algorithms are employed to maximize the covert SR throughput under outage probability and security constraints. …”
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Analysis of the Current State of Digitalization İmplementation in the Banking System of Azerbaijan by K. N. Atayev

“…Overall, digitalization has contributed to enhancing the quality, accessibility, and efficiency of banking services in the country, and has facilitated the sector’s transition toward a more innovative and customer-centric operational model. In the future, the key development directions of the banking sector wll be the improvement of digital credit products, the broad implementation of open banking technologies, the development of artificial intelligence-based services, and the issuance of a digital manat. …”
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Optimization of PV parameters under varied environmental conditions: A hybrid secant–Newton-Raphson method by Brahim El Fahmi, Driss Saadaoui, Imade Choulli, Khalid Assalaou, Ismail Abazine, Mustapha Elyaqouti, El hanafi Arjdal, Mohammed Agdam, Yassine El aidi Idrissi

“…This hybrid approach provides significant improvement over purely numerical techniques and metaheuristic algorithms because it provides rapid convergence, reduced computational load, and high accuracy in PV parameter extraction.…”
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Evaluation of agriculture land transformations with socio-economic influences on wheat demand and supply for food sustainability by Danish Raza, Hong Shu, Muhsan Ehsan, Hong Fan, Kamal Abdelrahman, Hasnat Aslam, Abdul Quddoos, Rana Waqar Aslam, Majid Nazeer, Mohammed S. Fnais, Azeem Sardar

“…Third, population dynamics were examined by applying an exponential growth model to forecast population growth and predict food demand. …”
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Synthetic Data Generation and Evaluation Techniques for Classifiers in Data Starved Medical Applications by Wan D. Bae, Shayma Alkobaisi, Matthew Horak, Siddheshwari Bankar, Sartaj Bhuvaji, Sungroul Kim, Choon-Sik Park

“…ML algorithms rely heavily on vast quantities of training data to make accurate predictions. …”
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Supporting self-management with an internet intervention for low back pain in primary care: a RCT (SupportBack 2) by Adam W A Geraghty, Taeko Becque, Lisa C Roberts, Jonathan Hill, Nadine E Foster, Lucy Yardley, Beth Stuart, David A Turner, Gareth Griffiths, Frances Webley, Lorraine Durcan, Alannah Morgan, Stephanie Hughes, Sarah Bathers, Stephanie Butler-Walley, Simon Wathall, Gemma Mansell, Malcolm White, Firoza Davies, Paul Little

“…A cost-effectiveness study estimated cost per point improvement in the Roland–Morris Disability Questionnaire. …”
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The fusion of machine olfactory data and UV–Vis-NIR-MIR spectra enabled accurate prediction of key soil nutrients by Shuyan Liu, Lili Fu, Xiaomeng Xia, Jiamu Wang, Yvhang Cao, Xinming Jiang, Honglei Jia, Zengming Feng, Dongyan Huang

“…Three fusion strategies including series and parallel modes were designed to effectively amalgamate the gathered data and supplemented with machine learning algorithms to predict the content of key soil nutrients. …”
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Estimation and trend analysis of grassland aboveground biomass on the Qinghai-Xizang Plateau based on machine learning by Ruoqi Zhang, Qisheng Feng, Yonghui Zhang, Jingjing Mai, Tiangang Liang

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A semantic segmentation-based automatic pterygium assessment and grading system by Qingbo Ji, Qingbo Ji, Wanyang Liu, Wanyang Liu, Qingfeng Ma, Qingfeng Ma, Lijun Qu, Lin Zhang, Hui He

“…This study aims to develop an automated grading system combining deep learning and image processing techniques for precise pterygium evaluation.MethodsThe proposed system integrates two modules: 1) A semantic segmentation module utilizing an improved TransUnet architecture for pixel-level pterygium localization, trained on annotated slit-lamp microscope images from clinical datasets. 2) A severity assessment module employing enhanced curve fitting algorithms to quantify pterygium invasion depth in critical ocular regions. …”
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Application of Image Computing in Non-Destructive Detection of Chinese Cuisine by Xiaowei Huang, Zexiang Li, Zhihua Li, Jiyong Shi, Ning Zhang, Zhou Qin, Liuzi Du, Tingting Shen, Roujia Zhang

“…This study pioneers a hyperspectral imaging framework enhanced with domain-specific deep learning algorithms (spatial–spectral convolutional networks with attention mechanisms) to address these challenges. …”
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StrideHD: A Binary Hyperdimensional Computing System Utilizing Window Striding for Image Classification by Dehua Liang, Jun Shiomi, Noriyuki Miura, Hiromitsu Awano

“…As an extension, the iterative retraining mode of StrideHD averagely provides 11.33% accuracy improvement to its single-pass mode, which can be accomplished in fewer iterations in comparison with the baseline HD algorithms. …”
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