Space alternating variational estimation based sparse Bayesian learning for complex‐value sparse signal recovery using adaptive Laplace priors by Zonglong Bai, Liming Shi, Jinwei Sun, Mads Græsbøll Christensen

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International competencies of nurses with advanced practice in anesthesia nursing: An integrative review by Kathrin Julia Pann, Verena-Katrin Buchner, Roland Eßl-Maurer, Tobias Bacher, Manela Glarcher, Andre Ewers

“…Eight qualitative, ten quantitative, and one mixed methods study, as well as seven scientific reports could be identified. …”
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Integrating Remote Sensing and AI for precision Monitoring of Soil and Vegetation Contamination by M. Spiralski, A. Miszczak, G. Siebielec, Ż. Piasecka, R. Trojnacki, P. Kwaśnik, J. Kotlarz, K. A. Kubiak-Siwinska, M. Kacprzak, S. Marciniak, K. A. Rotchimmel, K. P. Beben, J. Szymanski

“…Addressing the needs of end-users, the research focuses on the development of reliable methods to assess environmental contaminants that impact soil quality. …”
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The biological function and prognostic significance of ferroptosis-related genes in clear cell renal cell carcinoma by Huizhen Ye, Xiwen Wu, Gehao Liang

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Enhancing Maritime Data Integration for Platform Services With Sequence-to-Sequence Models and Statistical Refinement by Hyoseong Hwang, Richard Wong, Ducsun Lim, Jonggu Kang, Inwhee Joe

“…Experimental results demonstrate that the sequence-to-sequence model with statistical refinement outperformed single-step and discriminative methods in handling class imbalance and variations when mapping ship DSLs to a unified platform data model. …”
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Integration of Machine Learning and Wavelet Algorithms for Processing Probing Signals: An Example of Oil Wells by Zukhra Abdiakhmetova, Zhanerke Temirbekova

“…These signals can be obscured by noise or exhibit complex, non-stationary behavior, making them difficult to detect and analyze using conventional Fourier-based methods. Moreover, standard regression-based approaches for interpreting induction logging data may fail to capture intricate signal variations, limiting their effectiveness in real-time decision-making. …”
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Bayesian variable selection with graphical structure learning: Applications in integrative genomics. by Suprateek Kundu, Yichen Cheng, Minsuk Shin, Ganiraju Manyam, Bani K Mallick, Veerabhadran Baladandayuthapani

“…Our methods are motivated by and applied to a glioblastoma multiforme (GBM) dataset from The Cancer Genome Atlas to predict patient survival times integrating gene expression, copy number and methylation data. …”
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Addressing process-induced porosity variations in multiscale composite materials analysis using aggregated projection clustering and Halton sequence RVE sampling by Hamidreza Dehghani, Henri Perrin, Elias Belouettar-Mathis, Borek Patzák, Salim Belouettar

“…In such cases, porosity significantly decreases as we approach the consolidation surfaces, leading to substantial variations in material behavior in those areas. To address this, we propose an unsupervised machine learning approach integrated with micro-computed tomography (μCT) image processing and Asymptotic Homogenization (AH) for accurate and robust consideration of real microstructure as the basis for an upscaling process. …”
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Multi-objective mathematical programs to minimize the makespan, the patients' flow time, and doctors' workloads variation using dispatching rules and genetic algorithm by Jerbi Badreddine, Kanoun Salma, Kamoun Hichem

“…The problem considers a parallel machine scheduling model that integrates simultaneously the following most known objectives in healthcare systems: minimization of the makespan, the patients' total flow times, and the doctors' workloads variations. …”
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Croatia’s Economic Integration in EU’s Regional Supply Chains: Panel Data Quantile Regression by Davor Mance, Dora Šekimić, Borna Debelić

“…This study examines Croatia’s integration into EU RVCs and its economic impact. <i>Methods</i>: Using panel data from the UNCTAD–Eora database (2000–2019), this study applies panel data quantile regression (PDQR) to analyse Croatia’s trade relationships with EU Member States. …”
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Reliability of an Integrated Ultrasound and Stereophotogrammetric System for Lower Limb Anatomical Characterisation by Frederick Greatrex, Erica Montefiori, Thomas Grupp, Josef Kozak, Claudia Mazzà

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The rising burden of diabetes and state-wise variations in India: insights from the Global Burden of Disease Study 1990–2021 and projections to 2031 by Shubham Chauhan, Mahalaqua Nazli Khatib, Suhas Ballal, Pooja Bansal, Kiran Bhopte, Abhay M. Gaidhane, Balvir S. Tomar, Ayash Ashraf, M. Ravi Kumar, Ashish Singh Chauhan, Muhammed Shabil, Diptismita Jena, Ganesh Bushi, Prakasini Satapathy, Lara Jain, Vaibhav Jaiswal, Manvi Pant

“…BackgroundDiabetes is a major public health concern in India, contributing significantly to morbidity and mortality. With variations in disease burden across states, a detailed understanding of trends in incidence, prevalence, and Disability Adjusted Life Years (DALYs) is essential for targeted interventions.MethodsThis study utilized Global Burden of Disease (GBD) data from 1990 to 2021 to examine trends in diabetes across Indian states. …”
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Bridging the gap between technology and nursing education: Assessing student perspectives on Blackboard integration by Petelyne P. Pangket, Evalynn M. Rondilla, Jerold C. Alcantara, Dolores I. Cabansag, Hamdan Mohammad Albaqawi, Sarah Nawasreh, Lea L. Dando, Jonalee M. Valdez, Jane Rachelle D. Baroquillo, Laila Lafi Alharbi, Latifa Awad Alshammari

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ADTnorm: robust integration of single-cell protein measurement across CITE-seq datasets by Ye Zheng, Daniel P. Caron, Ju Yeong Kim, Seong-Hwan Jun, Yuan Tian, Florian Mair, Kenneth D. Stuart, Peter A. Sims, Raphael Gottardo

“…Here, we present ADTnorm, a normalization and integration method designed explicitly for ADT abundance. …”
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Bearing Fault Diagnosis under Transient Conditions: Using Variational Mode Decomposition and the Symmetrized Dot Pattern-Based Convolutional Neural Network Model by Jide Jia, Jianmin Mei, Chuang Sun, Fengjuan Yang

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Title not available by Flinth, Axel, de Gournay, Frédéric, Weiss, Pierre

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Integration of unpaired single cell omics data by deep transfer graph convolutional network. by Yulong Kan, Yunjing Qi, Zhongxiao Zhang, Xikeng Liang, Weihao Wang, Shuilin Jin

“…Here, we present a robust deep transfer model based graph convolutional network, scTGCN, which achieves versatile performance in preserving biological variation, while achieving integration hundreds of thousands cells in minutes with low memory consumption. …”
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A review on multi-omics integration for aiding study design of large scale TCGA cancer datasets by Eonyong Han, Hwijun Kwon, Inuk Jung

“…Abstract Background Rapid advancements in high-throughput sequencing technologies allow for detailed and accurate measurement of omics features within their biological context. The integration of different omics types creates heterogeneous datasets, presenting challenges in analysis due to variations in measurement units, sample numbers, and features. …”
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Fractal–Fractional Synergy in Geo-Energy Systems: A Multiscale Framework for Stress Field Characterization and Fracture Network Evolution Modeling by Qiqiang Ren, Tianhao Gao, Rongtao Jiang, Jin Wang, Mengping Li, Jianwei Feng, He Du

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A hybrid deep learning-based approach for optimal genotype by environment selection by Zahra Khalilzadeh, Motahareh Kashanian, Saeed Khaki, Lizhi Wang

“…By applying the Generalized Ensemble Method (GEM), we combined the CNN-based models and optimized their weights to improve overall predictive performance. …”
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