Future of Alzheimer's detection: Advancing diagnostic accuracy through the integration of qEEG and artificial intelligence by Sahar Rezaei, Farzan Asadirad, Alireza Motamedi, Mohammadsadegh Kamran, Farzaneh Parsa, Haniyeh Samimi, Parna Ghannadikhosh, Mahdi Zahmatyar, Seyed Ali Hosseinzadeh, Hossein Arabi

“…Through systematic analysis of 11 key studies across multiple international databases, we evaluated various AI architectures, including machine learning algorithms and deep learning networks, applied to qEEG data for AD detection. …”
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Modern advancements of energy storage systems integrated with hybrid renewable energy sources for water pumping application by Marwa M. Ahmed, Haneen M. Bawayan, Mohamed A. Enany, Mahmoud M. Elymany, Ahmed A. Shaier

“…The study concludes by identifying gaps in existing research and proposing future directions, such as integrating hydrogen generation, advanced AI algorithms, and innovative energy storage techniques to further enhance the feasibility and impact of HREWPS.…”
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Decentralized Energy Swapping for Sustainable Wireless Sensor Networks Using Blockchain Technology by Umar Draz, Tariq Ali, Sana Yasin, Mohammad Hijji, Muhammad Ayaz, EL-Hadi M. Aggoune

“…The system is built using NS-3 to simulate node behavior, energy usage, and network dynamics, while Python manages the blockchain architecture, cryptographic security, and trading algorithms. Sensor nodes checked their power levels and broadcast requests when energy fell under a predefined threshold. …”
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Identification of Reference Gene for Quantitative Gene Expression in Early-Term and Late-Term Cultured Canine Fibroblasts Derived from Ear Skin by Sang-Yun Lee, Yeon-Woo Jeong, Yong-Ho Choe, Seong-Ju Oh, Rubel Miah, Won-Jae Lee, Sung-Lim Lee, Eun-Yeong Bok, Dae-Sung Yoo, Young-Bum Son

“…Using three widely used algorithms, geNorm, Normfinder, and Bestkeeper, we identified HPRT1, YWHAZ, and GUSB as the most stable reference genes for both early- and late-passage fibroblasts. …”
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For Precision Animal Husbandry: Precise Detection of Specific Body Parts of Sika Deer Based on Improved YOLO11 by Jinfan Wei, Haotian Gong, Lan Luo, Lingyun Ni, Zhipeng Li, Juanjuan Fan, Tianli Hu, Ye Mu, Yu Sun, He Gong

“…This work provides strong algorithmic support for achieving non-contact intelligent monitoring of sika deer, assisting in automated management (deer antler collection and preparation), and improving animal welfare, demonstrating the application potential of deep learning technology in modern precision animal husbandry.…”
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Measuring the Intracluster Light Fraction with Machine Learning by Louisa Canepa, Sarah Brough, Francois Lanusse, Mireia Montes, Nina Hatch

“…However, only small samples have been studied to date due to its very low surface brightness and the heavy manual involvement required for the majority of measurement algorithms. Upcoming large imaging surveys such as the Vera C. …”
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Improving chlorophyll-a estimation using Sentinel-2 data: a comparative analysis of augmented datasets by Jinmyeong Lee, Do Hyuck Kwon, Heewon Jeong, Gibeom Nam, Euiho Hwang, Jin Hwi Kim, Kyung Hwa Cho, Hyo Gyeom Kim

“…Models trained on the augmented datasets, GEND and ND-SMOGN, successfully addressed this underestimation issue for the sample with the highest Chl-a concentration. Among the six algorithms, multilayer perceptron with attention mechanism exploited the highest performance across all indicators with coefficient of determination (R2) and root mean square error (RMSE) values of 0.93 and 2.76. …”
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Analysis of shared pathogenic mechanisms and drug targets in myocardial infarction and gastric cancer based on transcriptomics and machine learning by Junyang Ma, Junyang Ma, Shufu Hou, Xinxin Gu, Peng Guo, Jiankang Zhu

“…The random forest and Lasso algorithms were used to identify genes with diagnostic value, leading to nomogram construction. …”
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Method for prediction magnetic silencing of uncertain energy-saturated extended technical objects in prolate spheroidal coordinate system by B. I. Kuznetsov, A. S. Kutsenko, T. B. Nikitina, I. V. Bovdui, K. V. Chunikhin, V. V. Kolomiets

“…Nonlinear minimax optimization problems solutions calculated based on particle swarm nonlinear optimization algorithms. Results. Results of prediction extended technical objects far magnetic field magnitude based on extended technical objects spatial prolate spheroidal harmonics of the magnetic field model in the prolate spheroidal coordinate system using near field measurements with consideration of extended technical objects magnetic characteristics uncertainty. …”
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MODERN ANALYSIS METHODS USE IN ORDER TO ESTABLISH THE GEOGRAPHIC ORIGIN OF FOOD PRODUCTS by L. A. Oganesyants, A. L. Panasyuk, E. I. Kuzmina, D. A. Sviridov

“…The advantages of an integrated research approach, which includes the creation of data array of various indicators values and its in-depth analysis using chemometric algorithms and mathematical modeling methods, are shown.…”
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MicroRNA-1912 regulates cholesterol homeostasis by targeting PCSK9 by Chan Joo Lee, Myeongjune Go, Sae-Bom Jeon, Sun-Ho Lee, Dongkook Min, So Hee Park, Seunghyun Lee, Sahng Wook Park

“…This study aimed to explore miRNA candidates for PCSK9 regulation and to validate the most potent miRNA for this regulation in vivo. Bioinformatic algorithms identified miRNAs regulating PCSK9, with miR-224 and miR-1912 showing a high probability of targeting PCSK9. …”
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ICAFormer: An Image Dehazing Transformer Based on Interactive Channel Attention by Yanfei Chen, Tong Yue, Pei An, Hanyu Hong, Tao Liu, Yangkai Liu, Yihui Zhou

“…To address the limitations of traditional dehazing algorithms—particularly in global feature association and local detail preservation—this study proposes a novel Transformer-based dehazing model enhanced by an interactive channel attention mechanism. …”
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Fundus camera-based precision monitoring of blood vitamin A level for Wagyu cattle using deep learning by Nanding Li, Naoshi Kondo, Yuichi Ogawa, Keiichiro Shiraga, Mizuki Shibasaki, Daniele Pinna, Moriyuki Fukushima, Shinichi Nagaoka, Tateshi Fujiura, Xuehong De, Tetsuhito Suzuki

“…This study developed a handheld camera system capable of capturing cattle fundus images and predicting vitamin A levels in real time using deep learning. 4000 fundus images from 50 Japanese Black cattle were used to train and test the prediction algorithms, and the model achieved an average 87%, 83%, and 80% accuracy for three levels of vitamin A deficiency classification (particularly 87% for severe level), demonstrating the effectiveness of camera system in vitamin A deficiency prediction, especially for screening and early warning. …”
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Development of Quantitative Structure–Anti-Inflammatory Relationships of Alkaloids by Cristian Rojas, Doménica Muñoz, Ivanna Cordero, Belén Tenesaca, Davide Ballabio

“…When using molecular descriptors, genetic algorithms-variable subset selection (GAs-VSS) was used for supervised feature selection. …”
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Integrated artificial intelligence approach for well-log fluid identification in dual-medium tight sandstone gas reservoirs by Wurong Wang, Wurong Wang, Linbo Qu, Linbo Qu, Dali Yue, Dali Yue, Wei Li, Wei Li, Junlong Liu, Wujun Jin, Jialin Fu, Jialin Fu, Jiarui Zhang, Jiarui Zhang, Dongxia Chen, Dongxia Chen, Qiaochu Wang, Qiaochu Wang, Sha Li, Sha Li

“…To address the limitations of conventional machine learning algorithms, which have low accuracy due to data inhomogeneity and weak fluid logging responses, this study introduces a novel method for fluid logging evaluation in dual-medium tight sandstone gas reservoirs.MethodsThe method integrates core, thin section, and scanning electron microscope observations, taking into account the effect of fractures.ResultsReservoirs are divided into three types: fractured reservoirs (FR), porous reservoirs (PR), and microfracture-pore composite reservoirs (MPCR), highlighting the distinct fluid logging responses of each type. …”
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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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Eyes on nature: Embedded vision cameras for terrestrial biodiversity monitoring by Kevin F. A. Darras, Marcel Balle, Wenxiu Xu, Yang Yan, Vincent G. Zakka, Manuel Toledo‐Hernández, Dong Sheng, Wei Lin, Boyu Zhang, Zhenzhong Lan, Li Fupeng, Thomas C. Wanger

“…Our camera uses interchangeable lenses to resolve barely visible and remote targets, as well as customisable algorithms for blob detection, region‐of‐interest classification and object detection to automatically identify them. …”
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Listener Acoustic Personalization Challenge - LAP24: Head-Related Transfer Function Upsampling by Aidan O. T. Hogg, Roberto Barumerli, Rapolas Daugintis, Katarina C. Poole, Fabian Brinkmann, Lorenzo Picinali, Michele Geronazzo

“…The submissions to Task 2 employed both algorithmic and machine learning-based approaches, which were evaluated on three key spatial audio objective metrics, including the log-spectral distortion (LSD), interaural time difference (ITD), and the interaural level difference (ILD). …”
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Comprehensive Review on the Control of Heat Pumps for Energy Flexibility in Distribution Networks by Gustavo L. Aschidamini, Mina Pavlovic, Bradley A. Reinholz, Malcolm S. Metcalfe, Taco Niet, Mariana Resener

“…From a grid impact assessment perspective, studies have focused primarily on RBCs for providing energy flexibility through HP operation, without addressing more advanced methods such as real-time optimization using MPC or RL-based algorithms. Incorporating these advanced control strategies could help identify key limitations, including the impact of varying user participation levels and the cost-benefit trade-offs associated with their implementation.…”
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Leveraging AI for early cholera detection and response: transforming public health surveillance in Nigeria by Adamu Muhammad Ibrahim, Mohamed Mustaf Ahmed, Shuaibu Saidu Musa, Usman Abubakar Haruna, Mohammed Raihanatu Hamid, Olalekan John Okesanya, Aishat Muhammad Saleh, Don Eliso Lucero-Prisno III

“…AI technologies, including predictive modeling and ML algorithms such as random forests and convolutional neural networks (CNNs), can analyze diverse data sources—such as meteorological, environmental, and health records—to detect patterns and predict outbreaks. …”
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