Analytical screening of polymorphic variants of 20S proteasome genes when planning a study of pathogenetic effects of modification of NFKB1 post-translational processing by A. V. Meyer, M. V. Ulyanova, D. O. Imekina, A. D. Padyukova, T. A. Tolochko, E. A. Astafieva, M. B. Lavryashina

“…Determination of genes that encode proteins of the multisubunit proteasome complex prospective for research purposes, was carried out on the basis of information retrieved from eLIBRARY and PubMed. …”
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Multi-omics characterization of diabetic nephropathy in the db/db mouse model of type 2 diabetes by Liping Wang, Ran Zhou, Guanghui Li, Xiaodan Zhang, Yan Li, Yinchen Shen, Junwei Fang

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Detection of breast cancer using machine learning and explainable artificial intelligence by Tharunya Arravalli, Krishnaraj Chadaga, H Muralikrishna, Niranjana Sampathila, D. Cenitta, Rajagopala Chadaga, K. S. Swathi

“…The stacked ensemble model, which combines the strengths of different models, obtained an F1-score performance of 83%. The research emphasized the results obtained by explainers such as SHAP (SHapley Additive exPlanations), LIME (Local Interpretable Model-agnostic Explanations), ELI5 (Explain Like I’m Five), Anchor and QLattice (Quantum Lattice) to decipher the findings. …”
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Development and evaluation of machine learning training strategies for neonatal mortality prediction using multicountry data by Gabriel Ferreira dos Santos Silva, Roberta Moreira Wichmann, Francisco Costa da Silva Junior, Alexandre Dias Porto Chiavegatto Filho

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An explainable AI-based approach for predicting undergraduate students academic performance by Fatema Tuz Johora, Md Nahid Hasan, Aditya Rajbongshi, Md Ashrafuzzaman, Farzana Akter

“…Two eXplainable Artificial Intelligence (XAI) algorithms, namely SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-agnostic Explanations), were integrated to provide a comprehensible prediction of the best model and determine the significant factors. …”
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Development of an Intelligent System for the Recommendation of the Most Suitable Routes for Pedestrians by M. H. Zali, M. Argany, M. A. Mostafavi, M. A. Mostafavi

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A Novel Graph Reinforcement Learning-Based Approach for Dynamic Reconfiguration of Active Distribution Networks with Integrated Renewable Energy by Hua Zhan, Changxu Jiang, Zhen Lin

“…Traditional mathematical optimization algorithms tend to encounter issues like slow computational speed and difficulties in solving large-scale models, while heuristic algorithms are prone to fall into local optima. …”
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Development of Engineering Models of Nanosatellites for Student Training by V. Е. Evchik, A. A. Spiridonov, D. V. Ushakov, V. S. Baranova, I. A. Shalatonin, V. A. Saechnikov

“…It has reduced development costs, flexible equipment reconfiguration, and easier access to the simulator's internal architecture for demonstration purposes.The developed complexes allow students to practically study the ultra-small satellite components design and ground stations, methods for receiving and processing telemetry and scientific information, attitude determination and control algorithms. The complexes allow to conduct of research in the development of individual onboard systems and special-purpose equipment of the nanosatellite and their testing in the loop. …”
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Machine Learning Approaches to Predict Patient’s Length of Stay in Emergency Department by Mohammad A. Shbool, Omar S. Arabeyyat, Ammar Al-Bazi, Abeer Al-Hyari, Arwa Salem, Thana’ Abu-Hmaid, Malak Ali

“…Therefore, patients’ length of stay in EDs across waiting time duration is categorized as (low, medium, and high) using supervised machine learning (ML) approaches. Unsupervised algorithms have been applied to classify the patient’s length of stay in local EDs in the Kingdom of Jordan. …”
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Interpretable artificial intelligence (AI) for cervical cancer risk analysis leveraging stacking ensemble and expert knowledge by Priyanka Roy, Mahmudul Hasan, Md Rashedul Islam, Md Palash Uddin

“…The research integrates global and local XAI techniques, including individual feature contributions and tree-based explanations, to interpret model decisions. …”
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Sem-SLAM: Semantic-Integrated SLAM Approach for 3D Reconstruction by Shuqi Liu, Yufeng Zhuang, Chenxu Zhang, Qifei Li, Jiayu Hou

“…Under the upsurge of research on the integration of Simultaneous Localization and Mapping (SLAM) and neural implicit representation, existing methods exhibit obvious limitations in terms of environmental semantic parsing and scene understanding capabilities. …”
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2TSS: Two-Tier Semantic Segmentation Framework With Enhancement for Hotspot Detection of Solar Photovoltaic Thermal Images by Nurul Huda Ishak, Iza Sazanita Isa, Muhammad Khusairi Osman, Mohd Shawal Jadin, Kamarulazhar Daud, Mohd Zulhamdy Ab Hamid

“…The first tier of segmentation distinguishes between solar PV modules and the background, whilst the second tier enhances the hotspot localization region. This research enhances comprehension of multi-tier segmentation architectures in deep learning, focusing on optimizing performance for solar energy systems through comparative analysis of semantic models. …”
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Climate seasonality and predictability during the middle stone age and implications for technological diversification in early Homo sapiens by Lucy Timbrell, James Clark, Gonzalo Linares-Matás, Solène Boisard, Eslem Ben Arous, James Blinkhorn, Matt Grove, Eleanor M. L. Scerri

“…We utilise a set of standardised bioclimatic simulations, as well as a time series decomposition algorithm, to determine the nature and extent of regional differences in terms of environmental productivity, seasonality and predictability at MSA sites through time. …”
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Two-Stage Deep Learning Framework for Individual Tree Crown Detection and Delineation in Mixed-Wood Forests Using High-Resolution Light Detection and Ranging Data by Qian Li, Baoxin Hu, Jiali Shang, Tarmo K. Remmel

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Optimization of microwave components using machine learning and rapid sensitivity analysis by Slawomir Koziel, Anna Pietrenko-Dabrowska

“…On the other hand, the most widely used nature-inspired algorithms require large numbers of system simulations to yield a satisfactory design. …”
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Remote sensing semantic segmentation based on multimodal feature alignment and fusion by B. Chang, T. Balz

“…The overarching algorithmic framework is analogous to that of the Unet model. …”
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The role of explainable AI in enhancing breast cancer diagnosis using machine learning and deep learning models by Zulfikar Ali Ansari, Manish Madhava Tripathi, Rafeeq Ahmed

“…This work presents a thorough assessment of XAI approaches classified by data kinds (imaging, genomic, and clinical), a comparative analysis of LIME (Local Interpretable Model-agnostic Explanations), SHAP (SHapley Additive exPlanations), and Grad-CAM, and highlights important issues and future directions of research. …”
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A novel method for asynchronous source localisation based on time of arrival measurements by Huijie Zhu, Sheng Liu, Zhiqiang Yao, Moses Chukwuka Okonkwo, Zheng Peng

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Augmented UWB-ZUPT-SLAM Utilizing Multisensor Fusion by Chi-Shih Jao, Danmeng Wang, Changwei Chen, Eudald Sangenis, Joe Grasso, Solmaz S. Kia, Andrei M. Shkel

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Indirect determination of hemoglobin A2 reference intervals in Pakistani infants using data mining by Muhammad Shariq Shaikh, Sibtain Ahmed, Saba Farrukh, Shahnawaz Bayunus

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