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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An efficient privacy-preserving multilevel fusion-based feature engineering framework for UAV-enabled land cover classification using remote sensing images by S. Nagadevi, G. Abirami, R. Brindha, T. Prabhakara Rao, Gyanendra Prasad Joshi, Woong Cho

“…Nevertheless, networked UAVs are vulnerable to malicious attacks, and therefore intrusion detection systems (IDSs) are logically derived to address the vulnerabilities and/or attacks. Deep learning (DL) methods are essential for processing security problems in UAV networks. …”
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Improving the Universal Performance of Land Cover Semantic Segmentation Through Training Data Refinement and Multi-Dataset Fusion via Redundant Models by Jae Young Chang, Kwan-Young Oh, Kwang-Jae Lee

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Data and Knowledge Dual-Driven Creep Life Prediction for Austenitic Heat-Resistance Steel by Xiaochang Xie, Mutong Liu, Ping Yang, Zenan Yang, Chengbo Pan, Chenchong Wang, Xiaolu Wei

“…The artificial intelligence method can skip the complex mechanism and directly establish the mathematical correlation between the composition/process and the target performance. …”
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In Silico tool for predicting, designing and scanning IL-2 inducing peptides by Naman Kumar Mehta, Anjali Lathwal, Rajesh Kumar, Dilraj Kaur, Gajendra P. S. Raghava

“…Initially, we developed alignment-based methods, which demonstrated high precision but limited coverage. …”
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Music-stylized hierarchical dance synthesis with user control by Yanbo Cheng, Yichen Jiang, Yingying Wang

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Skin Microbiome alterations in heroin users revealed by full-length 16S rRNA sequencing by Ruiyang Tao, Xiang Wang, Xiaoyuan Zhen, Ruocheng Xia, Kaiqin Chen, Han Zhang, Yu Deng, Suhua Zhang

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The medial prefrontal cortex encodes procedural rules as sequential neuronal activity dynamics by Shuntaro Ohno, Masanori Nomoto, Kaoru Inokuchi

“…To investigate this, we recorded neuronal activities in the medial prefrontal cortex of mice during rule learning using Ca2+ imaging. We utilized a method based on convolutional negative matrix factorization, iSeq, to automatically detect temporal neuronal sequences in the recorded data. …”
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Unveiling patient profiles associated with elevated Lp(a) through an unbiased clustering analysis by Miguel Saraiva, Jonatas Garcez, Beatriz Tavares da Silva, Inês Poças Ferreira, José Carlos Oliveira, Isabel Palma

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Assessment of plant diversity index in degraded desert grassland using UAV hyperspectral multimodal data and Encoder-CNN by Zhaohui Tang, Chuanzhong Xuan, Tao Zhang, Xinyu Gao, Suhui Liu, Mengqin Zhang

“…To this end, this study proposed a novel method for assessing plant diversity index in degraded desert grassland based on multimodal UAV hyperspectral data and Encoder-CNN. …”
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Fluorescence Guided Raman Spectroscopy enables the training of robust support vector machines for the detection of tumour marker proteins by Johannes Reifenrath, Benjamin Gardner, Alexander Gigler, Friederike Liesche-Starnecker, Suzy Eldershaw, Nick Stone, Jürgen Schlegel

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Weighting Variables for Transportation Assets Condition Indices Using Subjective Data Framework by Abdallah B. Al-Hamdan, Yazan Ibrahim Alatoom, Inya Nlenanya, Omar Smadi

“…The motivation for this study lies in addressing the limitations of existing expert-based weighting methods for condition indices, which often lack transparency and consistency; this research aims to provide a data-driven framework that enhances accuracy and reliability in infrastructure asset management. …”
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Radiation enteritis associated with temporal sequencing of total neoadjuvant therapy in locally advanced rectal cancer: a preliminary study by Chen-ying Ma, Yi Fu, Lou Liu, Jie Chen, Shu-yue Li, Lu Zhang, Ju-ying Zhou

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GeaGrow: a mobile tool for soil nutrient prediction and fertilizer optimization using artificial neural networks by Olusegun Folorunso, Oluwafolake Ojo, Mutiu Busari, Muftau Adebayo, Joshua Adejumobi, Daniel Folorunso, Femi Ayo, Orobosade Alabi, Olusola Olabanjo

“…The two sets of data were pre-processed and normalized using Python, and an ANN was employed to predict soil properties such as NPK, Organic Carbon, Soil Textural Composition and pH levels through regressive analysis while building a composite model for Soil Texture Classification based on the predicted soil composition. …”
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Development and validation of risk stratification and shared decision-making tool for catheter ablation for atrial fibrillation in patients with heart failure: a multicentre cohort... by Xiaodong Peng, Liu He, Jue Wang, Nan Li, Jing Cui, Shijun Xia, Song Zuo, Chao Jiang, Jinzhu Hu, Kui Hong, Zhuheng Li, Peng Zhang, Ning Zhou, Caihua Sang, Deyong Long, Xin Du, Jianzeng Dong, Changsheng Ma

“…Interpretation: This machine learning-based tool shows promise in facilitating shared decision-making for patients with AF and HF by identifying those most likely to benefit from RFCA following risk stratification. …”
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AmpHGT: expanding prediction of antimicrobial activity in peptides containing non-canonical amino acids using multi-view constrained heterogeneous graph transformer by Yongcheng He, Xu Song, Hongping Wan, Xinghong Zhao

“…Results A novel deep learning model, termed AmpHGT, was developed based on heterogeneous graphs’ representation of peptides. …”
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FruitsMultiNet: A deep neural network approach to identify fruits through multi-scale feature fusion using mobile interface by Tasauf Mim, Md Mahbubur Rahman, Jahanur Biswas, Ahmad Shafkat, Khandaker Mohammad Mohi Uddin

“…The proposed research combines MobileNet and VGG16 to build a transfer learning (TL) principles-based framework named FruitsMultiNet. …”
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A Lightweight Dual-Stream Network with an Adaptive Strategy for Efficient Micro-Expression Recognition by Xinyu Liu, Ju Zhou, Feng Chen, Shigang Li, Hanpu Wang, Yingjuan Jia, Yuhao Shan

“…Firstly, a motion magnification network based on transfer learning is employed to magnify the motion states of facial muscles in MEs. …”
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Exploration of the relationships between the information and communication technology (ICT) and the education system in Morocco by Abdelkarim Taam, Amine Amar, Brahim Hmedna, Khalid Benabbes, El Menzhi Kaoutar, Rachid Daoudi, Adil El Makrani

“…Consequently, countries have adapted several methods of teaching and learning and made continuous reforms for a better quality of education. …”
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CFRANet: Cross-Modal Frequency-Responsive Attention Network for Thermal Power Plant Detection in Multispectral High-Resolution Remote Sensing Images by Qinxue He, Bo Cheng, Xiaoping Zhang, Yaocan Gan

“…However, detecting TPPs remains a challenging task due to their complex and irregular composition. Many traditional approaches focus on detecting compact, small-scale objects, while existing composite object detection methods are mostly part-based, limiting their ability to capture the structural and textural characteristics of composite targets like TPPs. …”
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