AIoT Monitoring for Early Identification of Diseases in Grapevines: Complete Study by Mihaela Hnatiuc, Domnica Alpetri, Sorin-Robertino Sintea, Bogdan Hnatiuc, Gabriel Margarit Raicu, Mirel Paun, Ionica Dina

“…This study explores the application of the Artificial Intelligence of Things (AIoT) in viticulture for the early detection of grapevine diseases. By integrating Internet of Things (IoT) sensors with machine learning algorithms, the system is designed to detect potential grapevine pathogens in real time. …”
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ThermOptCobra: Thermodynamically optimal construction and analysis of metabolic networks for reliable phenotype predictions by Pavan Kumar S, Nirav Pravinbhai Bhatt

“…We present ThermOptCOBRA, a comprehensive solution consisting of four algorithms for optimal model construction and analysis that integrate thermodynamic constraints to address TICs. …”
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Deep multi-view feature fusion with data augmentation for improved diabetic retinopathy classification by Boualleg Yaakoub, Daouadi Kheir Eddine, Guehairia Oussama, Djeddi Chawki, Cheddad Abbas, Siddiqi Imran, Bouderah Brahim

“…Diabetic retinopathy (DR) is a leading cause of blindness worldwide, necessitating early detection to prevent severe visual impairment. Despite numerous proposed classification techniques, challenges persist due to the high parameter count of deep learning algorithms, imbalanced datasets, and limited performance. …”
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Identification of Changing Lower Limb Neuromuscular Activation in Parkinson’s Disease during Treadmill Gait with and without Levodopa Using a Nonlinear Analysis Index by Amir Pourmoghaddam, Marius Dettmer, Daniel P. O’Connor, William H. Paloski, Charles S. Layne

“…A previously introduced algorithm (SYNERGOS) that provides a single index value based on simultaneous multiple muscle activations (MMA) has been shown to be effective in detecting changes in EMG activation due to modifications of walking speeds in healthy adults. …”
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A human-on-the-loop approach for labelling seismic recordings from landslide site via a multi-class deep-learning based classification model by Jiaxin Jiang, David Murray, Vladimir Stankovic, Lina Stankovic, Clement Hibert, Stella Pytharouli, Jean-Philippe Malet

“…Recent advances in machine learning have introduced algorithms for classifying seismic events associated with landslides, such as earthquakes, rockfalls, and smaller quakes. …”
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Automated Implementation of the Edinburgh Visual Gait Score (EVGS) by Ishaasamyuktha Somasundaram, Albert Tu, Ramiro Olleac, Natalie Baddour, Edward D. Lemaire

“…The system uses OpenPose for pose estimation and new algorithms for automatic gait event detection, stride segmentation, and computation of the 17 EVGS parameters across the sagittal and coronal planes. …”
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Advancing ECG Signal Classification With a Fuzzy Classifier Approach by Jan Rabcan, Vitaly Levashenko, Elena Zaitseva, Miroslav Kvassay

“…Over the years, numerous methods and algorithms have been developed to classify ECG signals with reliable accuracy. …”
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Strong parameter hierarchy in the interstellar phosphorus chemical network by Marina Fernández-Ruz, Marina Fernández-Ruz, Izaskun Jiménez-Serra, Mario Castro, Mario Castro, Marta Ruiz-Bermejo, Jacobo Aguirre, Jacobo Aguirre

“…In this study, we introduce the Fisher Information Spectral Reduction (FISR) algorithm, a novel and computationally efficient method to reduce the complexity of such sloppy models. …”
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Predicting Protein Interactions Using a Deep Learning Method-Stacked Sparse Autoencoder Combined with a Probabilistic Classification Vector Machine by Yanbin Wang, Zhuhong You, Liping Li, Li Cheng, Xi Zhou, Libo Zhang, Xiao Li, Tonghai Jiang

“…This method was developed based on a deep learning algorithm-stacked sparse autoencoder (SSAE) combined with a Legendre moment (LM) feature extraction technique. …”
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Physics-informed deep generative learning for quantitative assessment of the retina by Emmeline E. Brown, Andrew A. Guy, Natalie A. Holroyd, Paul W. Sweeney, Lucie Gourmet, Hannah Coleman, Claire Walsh, Athina E. Markaki, Rebecca Shipley, Ranjan Rajendram, Simon Walker-Samuel

“…We present here a novel algorithmic approach that generates highly realistic digital models of human retinal blood vessels, based on established biophysical principles, including fully-connected arterial and venous trees with a single inlet and outlet. …”
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A Study on the Extraction of Satellite Image Information for Two Types of Coastal Fishery Facility Fish Cages and Rafts Influenced by Clouds and Vessels by Ao Chen, Jialu Yu, Junbo Zhang, Gangyi Yu, Rong Wan

“…The MROIC model enhances spectral information by constructing ratio bands alongside principal component analysis, subsequently employing rule sets, edge detection algorithms, and comprehensive algorithmic merging techniques. …”
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Control chart for geometrically distributed data based on Bayesian fast double bootstrap by Muhammad Yahya Matdoan, Muhammad Mashuri, Muhammad Ahsan

“…However, these estimators may struggle to detect significant process shifts, particularly in the presence of large deviations. …”
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Relationship between depression and coronary artery disease in an open female and male population of a middle-urbanized city of Western Siberia by E. V. Akimova, V. V. Gafarov, E. I. Gakova, A. M. Akimov, M. M. Kayumova

“…To determine the severity of depression, the algorithms of the WHO program MONICA-Psychosocial were used. …”
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Real-Time Posture Correction of Squat Exercise: A Deep Learning Approach for Performance Analysis and Error Correction by Prashant Rao, C. S. Asha, P. Raghavendra Rao

“…Detected keypoints are then used to classify squat types and evaluate squat performance using a Bi-CGRU model. …”
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Scoping Review: The Effectiveness of Interprofessional Virtual Reality Simulation by Nebras Alghanaim, Jo Hart, Gabrielle Finn

“…Finally, the modified Kirkpatrick's model for evaluating the effectiveness of educational outcomes was detected in 42% of the studies at level 3, ie, change in behaviours, the highest level captured in the review. …”
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Screening for More than 1,000 Pesticides and Environmental Contaminants in Cannabis by GC/Q-TOF by Philip L. Wylie, Jessica Westland, Mei Wang, Mohamed M. Radwan, Chandrani G. Majumdar, Mahmoud A. ElSohly

“…Twenty-one confiscated cannabis samples were analyzed and ten were found to have no detectable pesticides. The remaining 11 samples had at least one pesticide and one sample had seven detectable residues. …”
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Use of four next-generation sequencing platforms to determine HIV-1 coreceptor tropism. by John Archer, Jan Weber, Kenneth Henry, Dane Winner, Richard Gibson, Lawrence Lee, Ellen Paxinos, Eric J Arts, David L Robertson, Larry Mimms, Miguel E Quiñones-Mateu

“…Identification of non-R5 viruses was comparable among the four platforms, with minor differences attributable to the algorithms used to infer HIV-1 tropism. All NGS platforms showed similar concordance with virologic response to the maraviroc-based regimen (75% to 80% range depending on the algorithm used), compared to Trofile (80%) and population sequencing (70%). …”
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Extra-Tidal Members and Dynamics of the Open Cluster NGC 6705 by Chen Zhou, Xinhua Gao

“…In this study, we utilized Gaia-DR3 astrometric data combined with the density-based spatial clustering of applications with noise (DBSCAN) algorithm to thoroughly investigate the dynamics and extra-tidal members of the open cluster NGC 6705. …”
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FMCW Radar-Aided Navigation for Unmanned Aircraft Approach and Landing in AAM Scenarios: System Requirements and Processing Pipeline by Paolo Veneruso, Luca Manica, Enrico Miccio, Roberto Opromolla, Carlo Tiana, Giacomo Gentile, Giancarmine Fasano

“…The radar is designed to detect high-reflectivity targets placed in the landing area and uses a matching algorithm to associate these detections with their known positions, enabling reliable corrections to the aircraft navigation state. …”
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Hierarchical genetic structure in an evolving species complex: Insights from genome wide ddRAD data in Sebastes mentella. by Atal Saha, Matthew Kent, Lorenz Hauser, Daniel P Drinan, Einar E Nielsen, Jon-Ivar Westgaard, Sigbjørn Lien, Torild Johansen

“…Additional sub-structuring was detected within the 'shallow' and 'deep' pelagic ecotypes. …”
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