Advances in Hemodynamic Analysis in Cardiovascular Diseases Investigation of Energetic Characteristics of Adult and Pediatric Sputnik Left Ventricular Assist Devices during Mock Ci... by Alexander A. Pugovkin, Aleksandr G. Markov, Sergey V. Selishchev, Leonie Korn, Marian Walter, Steffen Leonhardt, Leo A. Bockeria, Olga L. Bockeria, Dmitry V. Telyshev

“…Finally, we show that the implementation of control algorithms using the modulation of the RBP speed in order to open the aortic valve and unload the LV more efficiently is necessary and will be content of further research.…”
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Evaluation of the Capability of Horizontal ATR-FTMIR and UV-Visible Spectroscopy in the Discrimination of Virgin Olive Oils from the Moroccan Region of Beni Mellal-Khenifra by Aimen El Orche, Mustapha Bouatia, Siham Yanisse, Houda Labjar, Mouad Mouhsin, Mohamed Bouha, Mustapha Oubenali, Mohamed Mbarki

“…To develop a rapid analysis tool capable of authenticating the geographical origin of virgin olive oils from five geographical areas of the Moroccan region of Beni Mellal-Khenifra, UV-Visible and ATR-FTMIR spectral data were processed by chemometric algorithms. PCA was applied on the spectral data set to represent the data in a very small space, and then discrimination methods were applied on the principal components synthesized by the PCA. …”
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Machine learning-based prediction of the mechanical properties of β titanium shape memory alloys by Naoki Nohira, Taichi Ichisawa, Masaki Tahara, Itsuo Kumazawa, Hideki Hosoda

“…Key features, including Mo equivalent, bond order, and d-orbital energy level, were selected for the models through Pearson correlation maps and subset selection methods. Four ML algorithms—Linear Regression (LIN), Support Vector Regression (SVR), Random Forest Regression (RFR), and Gradient Boosting Regression (GBR)—were employed and evaluated using metrics like mean absolute error (MAE), mean squared error (MSE), and coefficient of determination (R2). …”
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RL-ADN: A high-performance Deep Reinforcement Learning environment for optimal Energy Storage Systems dispatch in active distribution networks by Shengren Hou, Shuyi Gao, Weijie Xia, Edgar Mauricio Salazar Duque, Peter Palensky, Pedro P. Vergara

“…The effectiveness of RL-ADN is demonstrated using distribution networks with size varying, showing marked performance improvements in the adaptability of DRL algorithms for ESS dispatch tasks. Furthermore, RL-ADN achieves a tenfold increase in computational efficiency during training, making it highly suitable for large-scale network applications. …”
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Multimodal fusion model for diagnosing mild cognitive impairment in unilateral middle cerebral artery steno-occlusive disease by Ziyi Yuan, Zhaodi Huang, Chaojun Li, Shengrong Li, Qingguo Ren, Xiaona Xia, Qingjun Jiang, Daoqiang Zhang, Qi Zhu, Xiangshui Meng, Xiangshui Meng

“…ObjectivesTo propose a multimodal functional brain network (FBN) and structural brain network (SBN) topological feature fusion technique based on resting-state functional magnetic resonance imaging (rs-fMRI), diffusion tensor imaging (DTI), 3D-T1-weighted imaging (3D-T1WI), and demographic characteristics to diagnose mild cognitive impairment (MCI) in patients with unilateral middle cerebral artery (MCA) steno-occlusive disease.MethodsThe performances of different algorithms on the MCI dataset were evaluated using 5-fold cross-validation. …”
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Advanced Machine Learning and Deep Learning Approaches for Estimating the Remaining Life of EV Batteries—A Review by Daniel H. de la Iglesia, Carlos Chinchilla Corbacho, Jorge Zakour Dib, Vidal Alonso-Secades, Alfonso J. López Rivero

“…In addition, we discuss the ethical implications of DL in RUL estimation, addressing concerns about privacy and algorithmic bias. By synthesizing current knowledge, identifying key research directions, and suggesting methodological improvements, this review serves as a central guide for researchers and practitioners in the rapidly evolving field of EV battery management. …”
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Personalized treatment strategies for breast adenoid cystic carcinoma: A machine learning approach by Sakhr Alshwayyat, Mahmoud Bashar Abu Al Hawa, Mustafa Alshwayyat, Tala Abdulsalam Alshwayyat, Siya sawan, Ghaith Heilat, Hanan M. Hammouri, Sara Mheid, Batool Al Shweiat, Hamdah Hanifa

“…To identify the prognostic variables, we conducted Cox regression analysis and constructed prognostic models using five Machine Learning (ML) algorithms to predict the 5-year survival. A validation method incorporating the area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to validate the accuracy and reliability of ML models. …”
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Artificial intelligence assisted risk prediction in organ transplantation: a UK Live-Donor Kidney Transplant Outcome Prediction tool by Hatem Ali, Arun Shroff, Tibor Fülöp, Miklos Z. Molnar, Adnan Sharif, Bernard Burke, Sunil Shroff, David Briggs, Nithya Krishnan

“…We set out to apply artificial intelligence (AI) algorithms to create a highly predictive risk stratification indicator, applicable to the UK’s transplant selection process.Methodology: Pre-transplant characteristics from 12,661 live-donor kidney transplants (performed between 2007 and 2022) from the United Kingdom Transplant Registry database were analyzed. …”
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Fault diagnosis of a CNC hobbing cutter through machine learning using three axis vibration data by Nagesh Tambake, Bhagyesh Deshmukh, Sujit Pardeshi, Sachin Salunkhe, Robert Cep, Emad Abouel Nasr

“…Various machine learning algorithms, including Decision Trees, Efficient Linear models, Neural Networks, and Ensemble methods, were evaluated for their classification accuracy. …”
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Integrating Information Gain and Chi-Square for Enhanced Malware Detection Performance by Fauzi Adi Rafrastara, Wildanil Ghozi, Ramadhan Rakhmat Sani, Lekso Budi Handoko, Abdussalam Abdussalam, Elkaf Rahmawan Pramudya, Faizal M. Abdollah

“…Recent studies have shown that this challenge can be addressed by employing machine learning algorithms for detection. Some studies have also implemented various feature selection methods to optimize detection efficiency. …”
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A joint three-plane physics-constrained deep learning based polynomial fitting approach for MR electrical properties tomography by Kyu-Jin Jung, Thierry G. Meerbothe, Chuanjiang Cui, Mina Park, Cornelis A.T. van den Berg, Stefano Mandija, Dong-Hyun Kim

“…To estimate tissue electrical properties, various reconstruction algorithms have been proposed. However, physics-based reconstructions are prone to various artifacts such as noise amplification and boundary artifact. …”
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Environmental exposures related to gut microbiota among children with asthma: a pioneer study in Taiwan by Aji Kusumaning Asri, Tsunglin Liu, Hui-Ju Tsai, Jiu-Yao Wang, Chih-Da Wu

“…Air pollution was estimated using an ensemble learning model that combined regression and machine-learning algorithms, while greenspace was quantified using the normalized difference vegetation index (NDVI) and green land-cover data. …”
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A Novel and Automated Approach to Detect Sea- and Land-Based Aquaculture Facilities by Maxim Veroli, Marco Martinoli, Arianna Martini, Riccardo Napolitano, Domitilla Pulcini, Nicolò Tonachella, Fabrizio Capoccioni

“…The results demonstrate that the approach proposed can identify, characterize, and geolocate sea- and land-based aquaculture structures without performing any post-processing procedure, by directly applying customized deep learning and artificial intelligence algorithms.…”
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UEF-HOCUrdu: Unified Embeddings Ensemble Framework for Hate and Offensive Text Classification in Urdu by Kifayat Ullah, Muhammad Aslam, Muhammad Usman Ghani Khan, Faten S. Alamri, Amjad Rehman Khan

“…For this purpose, an extensive comparison of different learning algorithms were conducted. As a result, the most efficient models, namely FastText, XLM-RoBERTa, ULMFiT, and XGBoost were incorporated in the proposed ensemble approach to achieve the best results in both classification and mitigation of NLP issues. …”
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An Efficient CNN Model for COVID-19 Disease Detection Based on X-Ray Image Classification by Aijaz Ahmad Reshi, Furqan Rustam, Arif Mehmood, Abdulaziz Alhossan, Ziyad Alrabiah, Ajaz Ahmad, Hessa Alsuwailem, Gyu Sang Choi

“…To further prove that the proposed model outperforms other models, a comparative analysis has been done with some of the machine learning algorithms. The proposed model has outperformed all the models generally and specifically when the model testing was done using an independent testing set.…”
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Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes by S. Ubbiali, C. Kühnlein, C. Schär, L. Schlemmer, T. C. Schulthess, T. C. Schulthess, M. Staneker, H. Wernli

“…<p>We explore the domain-specific Python library GT4Py (GridTools for Python) for implementing a representative physical parametrization scheme and the related tangent-linear and adjoint algorithms from the Integrated Forecasting System (IFS) of ECMWF. …”
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Ancient and contemporary shellfish cultivation practices bolster bivalve communities and diversity‐biomass relationships by Kieran D. Cox, Hailey L. Davies, Ben Millard‐Martin, Morgan Black, Margot Hessing‐Lewis, Nicole F. Smith, Francis Juanes, Sarah E. Dudas

“…We examined these data using a combination of diversity indices, structural complexity metrics, non‐parametric multivariate statistics and supervised machine learning algorithms. We show that both cultivation methods create distinct biological communities, with community composition proportional to how each cultivation practice alters the habitats' substrate, sediment and physical complexity. …”
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Deep Reinforcemnet Learning for Robust Beamforming in Integrated Sensing, Communication and Power Transmission Systems by Chenfei Xie, Yue Xiu, Songjie Yang, Qilong Miao, Lu Chen, Yong Gao, Zhongpei Zhang

“…Our results demonstrate that DRL-based algorithms significantly improve resource allocation, power management, and information transmission, particularly in dynamic and uncertain environments with imperfect CSI.…”
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Implementation of a Smart Home Intruder Detection System using a Vibrometer and ESP 32 CAM by Samuel Owoeye, Folasade Durodola, Adekunle Oyelami, Racheal Oladejo, Samuel Obasuyi, Ademola Qasim, Joshua Ogundairo

“…The ATMega328P contributes to the system's intelligence by supporting motion detection algorithms, which, in turn, trigger automated alerts and activate lighting or alarm systems in response to detected movement. …”
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SSVEP Enhancement in Mixed Reality Environment for Brain&#x2013;Computer Interfaces by Jieyu Wu, Feng He, Xiaolin Xiao, Runyuan Gao, Lin Meng, Xiuyun Liu, Minpeng Xu, Dong Ming

“…The proposed SA-xTRCA significantly outperformed the other four traditional algorithms. The online average information transfer rate (ITR) achieved 57.58 &#x00B1; 5.31 bits/min. …”
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