Application of Overall Equipment Effectiveness for Optimizing Ventilator Reliability in Intensive Care Units and Emergency Departments by Khelood A. Mkalaf, Rami Hikmat Al-Hadeethi, Peter Gibson

“…RCM is an integrated approach to continuous improvement of the maintenance programs because it can predict early medical equipment failure and determine the mean time between failures. …”
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Understanding Groundwater Resource Vulnerability at Bryce Canyon National Park, Utah, Using Applied Geophysics at the Rubys Inn Thrust Fault by Trevor H. Schlossnagle, Kayla D. Smith, Tyler C. Gilkerson

“…The influence of fault zones on groundwater flow parallel and perpendicular to their planes is difficult to predict. Geophysical imaging can yield important information about subsurface fault geometry. …”
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A novel ViT-BILSTM model for physical activity intensity classification in adults using gravity-based acceleration by Lin Wang, Zizhang Luo, Tianle Zhang

“…The model consistently exhibited superior accuracy in predicting sedentary (98.9% ± 1%) compared to light physical activity (98.2% ± 2%) and moderate-to-vigorous physical activity (98.2% ± 3%). …”
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Exploring the textural characteristics of foods preferred by Chinese elderly individuals based on IDDSI levels. by Muxi Chen, Yi Cheng, Wen Hu, Mengyan Wang, Juan Duan, Lei Shi

“…The study provides empirical evidence supporting the IDDSI framework and offers a predictive model that can assist in the development of customized diets, ensuring both safety and nutritional adequacy. …”
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Evaluation of Risk Factors of Venous Thromboembolism in Imam Sadiq Teaching Hospital at Babylon City by Intisar Mahdi Kadhim Almurshedi, Amel Mustafa Kamil, Aqeel Abbas Noaman

“…To evaluate the risk factors of VTE between cases and controls in the hospital Imam Sadiq Teaching in Babylon City and to predict variables that contribute to the risk factors of VTE among the studied samples. …”
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Research on low carbon dispatch technology for wind and solar grid connection in the Gobi Desert and barren land areas by Yanhong Ma, QingQuan Lv, Jianmei Zhang, Chunxiang Yang, Qiang Zhou

“…In particular, the upper-level model maximizes the grid’s potential for new energy consumption by refining the covariance between load forecasts and wind and solar predictions. Concurrently, the lower-level model harmonizes various peak-shaving resources and incorporates a tiered carbon trading cost, thus establishing a multi-objective “source-grid-load-storage” collaborative low-carbon scheduling framework. …”
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Using Milk Urea Nitrogen to Evaluate Diet Formulation and Environmental Impact on Dairy Farms by J.S. Jonker, R.A. Kohn

“…A mathematical model was developed and evaluated with an independent literature data set to integrate MUN and milk composition to predict urinary and fecal excretion, intake, and utilization efficiency for N in lactating dairy cows. …”
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Exploring Early Learning Challenges in Children Utilizing Statistical and Explainable Machine Learning by Mithila Akter Mim, M. R. Khatun, Muhammad Minoar Hossain, Wahidur Rahman, Arslan Munir

“…Furthermore, we explored robust machine learning (ML) models to analyze and predict the learning challenges faced by children. …”
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Investigating Fracture Behavior in Titanium Aluminides: Surface Roughness as an Indicator of Fracture Mechanisms in Ti-48Al-2Cr-2Nb Alloys by Alessia Serena Perna, Lorenzo Savio, Michele Coppola, Fabio Scherillo

“…These findings contribute to understanding fracture behavior in titanium aluminides and provide a predictive framework for assessing structural integrity based on surface characteristics.…”
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Development and validation of a deep learning system for detection of small bowel pathologies in capsule endoscopy: a pilot study in a Singapore institution by Bochao Jiang, Michael Dorosan, Justin Wen Hao Leong, Marcus Eng Hock Ong, Sean Shao Wei Lam, Tiing Leong Ang

“…They serve as a decision support system, partially automating the diagnosis process by providing probability predictions for abnormalities. Methods: We demonstrated the use of deep learning models in CE image analysis, specifically by piloting a bowel preparation model (BPM) and an abnormality detection model (ADM) to determine frame-level view quality and the presence of abnormal findings, respectively. …”
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Examining Prenylated Xanthones as Potential Inhibitors Against Ketohexokinase C Isoform for the Treatment of Fructose-Driven Metabolic Disorders: An Integrated Computational Approa... by Tilal Elsaman, Magdi Awadalla Mohamed

“…Among these, hit <b>8</b> emerged as the best performer, achieving a binding free energy of −61.30 kcal/mol, 100% predicted oral absorption, enhanced metabolic stability, and stable molecular dynamics. …”
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Evaluation of the Accumulation Conditions and Favorable Areas of Shale Gas in the Upper Palaeozoic Marine-Continental Transitional Facies in the Daning-Jixian Area, Ordos Basin by Xu Zeng, Wei Wang, Qian Cao, Shangwen Zhou, Guodong Dong, Aiming Wang, Zhixin Chen, Hua Mei

“…Favorable areas are predicted based on these factors.…”
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Wind, Water Level, and Fluid Mud Thresholds in Lake Apopka, Florida by Earl J. Hayter, Ashish J. Mehta, John M. Jaeger, Arnoldo Valle-Levinson, Andrew J. Manning, Carola Forlini

“…The rise, which is considered significant when fluid mud occupies the 0.2 m high benthic boundary layer (BBL), occurs when the threshold wind exceeds about 9 m s⁻¹ corresponding to a 4% cumulative probability of occurrence. Predictive modeling suggests that in 2 m water depth the required wind would be about 14 m s⁻¹ with a low probability of 2%. …”
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Galaxy evolution in the post-merger regime. III -- The triggering of active galactic nuclei peaks immediately after coalescence by Sara Ellison, Leonardo Ferreira, Robert Bickley, Tess Grindlay, Samir Salim, Shoshannah Byrne-Mamahit, Shobita Satyapal, David R. Patton, Jillian M. Scudder

“…The Multi-Model Merger Identifier (MUMMI) machine vision pipeline has been demonstrated to provide reliable predictions of time post-merger (T_PM) for galaxies selected from the Ultraviolet Near Infrared and Optical Northern Survey (UNIONS) up to T_PM=1.76 Gyr after coalescence. …”
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Deep Learning Based Dual Channel Banana Grading System Using Convolution Neural Network by Raghavendra S, Souvik Ganguli, P. Thirumarai Selvan, Mitali Madhusmita Nayak, Sushovan Chaudhury, Randell U. Espina, Isaac Ofori

“…Via a combination of CNN and MLP applied to data collected using RGB and hyperspectral imaging, the multi-input model reliably recognizes bananas with an accuracy level of 98.4 percent as well as an F1-score of 0.97. The AI algorithm predicted the size (large, medium, and microscopic) and perspective (front or rear half) of banana classes with 99 percent accuracy. …”
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Prostate Cancer Detection from MRI Using Efficient Feature Extraction with Transfer Learning by Rafiqul Islam, Al Imran, Md. Fazle Rabbi

“…The random forest model seeks to identify patterns in the feature space and produce precise predictions on the presence or absence of prostate cancer. …”
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Impact of Dataset Size on 3D CNN Performance in Intracranial Hemorrhage Classification by Chun-Chao Huang, Hsin-Fan Chiang, Cheng-Chih Hsieh, Bo-Rui Zhu, Wen-Jie Wu, Jin-Siang Shaw

“…<b>Background:</b> This study aimed to evaluate the effect of sample size on the development of a three-dimensional convolutional neural network (3DCNN) model for predicting the binary classification of three types of intracranial hemorrhage (ICH): intraparenchymal, subarachnoid, and subdural (IPH, SAH, SDH, respectively). …”
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Archaeological Site Detection: Latest Results from a Deep Learning Based Europe Wide Hillfort Search by Jürgen Landauer, Simon Maddison, Giacomo Fontana, Axel G. Posluschny

“…While automation significantly reduces manual workload, human verification remains critical for refining AI predictions and addressing false positives. This study also applies different expert validation workflows, emphasizing their efficiency and adaptability to regional differences. …”
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Molecular Modeling Studies of Substituted 2,4,5-Trisubstituted Triazolinones Aryl and Nonaryl Derivatives as Angiotensin II AT1 Receptor Antagonists by Mukesh C. Sharma, D. V. Kohli, Smita Sharma

“…Multiple linear regression (MLR) methodology coupled with feature selection method namely simulated annealing, was applied to derive Group based QSAR models which were further validated for statistical significance and predictive ability by internal and external validation. …”
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The Relationship between Landing Error Scoring System Performance and Injury in Female Collegiate Athletes by Peter Lisman, Joshua N. Wilder, Joshua Berenbach, Enric Jiao, Bethany Hansberger

“…A Receiver Operating Characteristic curve determined the optimal cutpoint for the total LESS score for predicting injury. Pearson’s Chi squared statistics examined the association between injury and LESS total scores >5. …”
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