Developing an Empirical Relationship to Predict the Wear Characteristics of Ni-Based Hardfaced Deposits on Nuclear Grade 316LN Austenitic Stainless Steel by S. Gnanasekaran, Samson Jerold Samuel Chelladurai, G. Padmanaban, Ramesh Arthanari, V. Balasubramanian

“…Hence, in this investigation, an effort has been made to develop empirical relationship to predict weight loss of laser hardfaced Ni-based alloy surface incorporating laser parameters using statistical tools such as design of experiments (DoE) and analysis of variance (ANOVA). …”
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Real-Time HIL Simulation of Nonlinear Generalized Model Predictive-Based High-Order SMC for Permanent Magnet Synchronous Machine Drive by Hafidh Djouadi, Kamel Ouari, Youcef Belkhier, Hocine Lehouche

“…Recent attention has turned to employing predictive control techniques for nonlinear multivariable systems, offering an intriguing avenue for research. …”
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Characterisation of EfbA from the Endodontic Pathogen Enterococcus faecalis and Prediction of Immunodominant EfbA Epitope Peptides: An In-vitro and In-silico Study by Dev Arora, AS Smiline Girija, J Vijayashree Priyadharsini

“…The prediction of T-cell epitopes was carried out with the help of the EpiDOCK server, and B-cell predictions were made using the Kolaskar and Tongaonkar tool. …”
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Association of genomic predictions for fertility traits with reproductive outcomes in dairy cows under 2 estrus detection and timed artificial insemination programs by D.B. Melo, R.G.S. Bruno, R.S. Bisinotto, F.S. Lima

“…ABSTRACT: Genomic prediction of daughter pregnancy rate (GDPR) and cow conception rate (GCCR) are fertility traits developed to help improve selection for reproductive performance. …”
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Validity assessment of the POLARS score tool in the prediction of post rectal cancer surgery LARS score in a population-based Swedish cohort by Asif Johar, Pernilla Lagergren, Boglarka Rethy, Caroline Nordenvall, Emil Pieniowski, Gabriella Jansson-Palmer, Mirna Abraham-Nordling

“…Other methods to predict the risk of LARS need to be developed.…”
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A Simplified Analysis Model for Predicting the Crack Width and Deflection of Reinforced UHPC Shallow T-Shaped Beams Under Four-Point Bending by Zhe Zhang, Yichuan Wang, Binchen Yuan, Ping Zhu

“…To predict the mid-span deflection and crack width of reinforced ultra-high-performance concrete (R-UHPC) shallow T-shaped beams, a simplified analysis model comprising a bilinear curve with several characterization points is proposed in this paper. …”
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IoT-based prediction model for aquaponic fish pond water quality using multiscale feature fusion with convolutional autoencoder and GRU networks by Suma Christal Mary Sundararajan, Yamini Bhavani Shankar, Sinthia Panneer Selvam, Nalini Manogaran, Koteeswaran Seerangan, Deepa Natesan, Shitharth Selvarajan

Subjects: “…Water quality prediction…”
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Nomogram prediction of overall survival in breast cancer patients post-surgery: integrating SEER database and multi-center evidence from China by Yufen Zheng, Yuan Yuan, Minya Jin, Chunlong Wu

“…Calibration curves demonstrated good agreement between predicted and observed outcomes in all validation cohorts. …”
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Serum Concentrations of Transforming Growth Factor-Beta 1 in Predicting the Occurrence of Diabetic Retinopathy in Juvenile Patients with Type 1 Diabetes Mellitus by Katarzyna Zorena, Ewa Malinowska, Dorota Raczyńska, Małgorzata Myśliwiec, Krystyna Raczyńska

“…In the present study, we have decided to evaluate if serum transforming growth factor-beta 1 (TGF-β1) concentrations may have diagnostic value in predicting the occurrence of diabetic retinopathy (DR) in juvenile patients with type 1 diabetes mellitus (T1DM). …”
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Design and Fabrication of a High Performance Microfluidic Chip for Blood Plasma Separation: Modelling and Prediction of System Behaviour via CFD Method by Hossein Amini, Amin Sokhansanj, Mohammad Akrami, Ismaeil Haririan

“…A model with high accuracy using the COMSOL Multiphysics software was created to predict the capillary forces and chip model validation. …”
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Study on the prediction model of non-suicidal self-injury behavior risk during hospitalization for adolescent inpatients with depression based on medical data by Yanyan Zhang, Huirong Guo, Yali Wang, Junru Wang, Yuming Ren

“…Purpose: To develop a predictive model for identifying risk factors of non-suicidal self-injury (NSSI) during hospitalization in adolescents. …”
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Evaluation of Arterial Stiffness for Predicting Future Cardiovascular Events in Patients with ST Segment Elevation and Non-ST Segment Elevation Myocardial Infarction by Oguz Akkus, Durmus Yildiray Sahin, Abdi Bozkurt, Kamil Nas, Kazım Serhan Ozcan, Miklós Illyés, Ferenc Molnár, Serafettin Demir, Mücahit Tüfenk, Esmeray Acarturk

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Development and Validation of a Nomogram Model for Predicting the Risk of Readmission in Patients with Heart Failure with Reduced Ejection Fraction within 1 Year by Yue Hu, Xiaotong Wang, Shengjue Xiao, Chunyan Huan, Huimin Wu, Tao Xu, Minjia Guo, Hong Zhu, Defeng Pan

“…In this study, we aimed to build a simple predictive model to predict the risk of heart failure (HF) readmission in patients with HFrEF within one year of discharge from the hospital. …”
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Prediction-based prompt levothyroxine replacement to prevent a hypothyroid state after immune-related adverse events involving the thyroid gland by Ichiro Yamauchi, Takuro Hakata, Taku Sugawa, Daisuke Kosugi, Haruka Fujita, Kentaro Okamoto, Yohei Ueda, Toshihito Fujii, Daisuke Taura, Norio Harada, Nobuya Inagaki

“…The Toxic-Hypo group developed severe hypothyroidism and required larger levothyroxine (LT4) doses than the Hypo group (75 vs. 25 μg/day; p = 0.007). We predicted that patients with positive TgAbs who developed severe thyrotoxicosis within 4 weeks after the first ICI administration would develop subsequent hypothyroidism. …”
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D-MGDCN-CLSTM: A Traffic Prediction Model Based on Multi-Graph Gated Convolution and Convolutional Long–Short-Term Memory by Linliang Zhang, Shuyun Xu, Shuo Li, Lihu Pan, Su Gong

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AICpred: Machine Learning-Based Prediction of Potential Anti-Inflammatory Compounds Targeting TLR4-MyD88 Binding Mechanism by Lucindah N. Fry-Nartey, Cyril Akafia, Ursula S. Nkonu, Spencer B. Baiden, Ignatus Nunana Dorvi, Kwasi Agyenkwa-Mawuli, Odame Agyapong, Claude Fiifi Hayford, Michael D. Wilson, Whelton A. Miller, Samuel K. Kwofie

“…Studies that employ machine learning (ML) in the prediction of potential inhibitors of TLR4 are limited. …”
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Characterization and Machine Learning-Driven Property Prediction of a Novel Hybrid Hydrogel Bioink Considering Extrusion-Based 3D Bioprinting by Rokeya Sarah, Kory Schimmelpfennig, Riley Rohauer, Christopher L. Lewis, Shah M. Limon, Ahasan Habib

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Intraoperative haemodynamic optimisation using the Hypotension Prediction Index and its impact on tissular perfusion: a protocol for a randomised controlled trial by Javier Ripollés-Melchor, Ane Abad-motos, Juan Victor Lorente, Ignacio Jimenez, Alejandra Becerra, Wilbert Wesselink, Francesca Reguant, Irene Mojarro, Maria de los Angeles Fuentes, Elizabeth Agudelo, Francisco Herrero-Machancoses, Paula Callejo, Joan Bosch, Manuel Ignacio Monge

“…Introduction Intraoperative arterial hypotension is associated with poor postoperative outcomes. The Hypotension Prediction Index (HPI) developed using machine learning techniques, allows the prediction of arterial hypotension analysing the arterial pressure waveform. …”
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Predictive Modeling of Total Real and Reactive Power Losses in Contingency Systems Using Function-Fitting Neural Networks with Graphical User Interface by Alfredo Bonini Neto, Alexandre de Queiroz, Giovana Gonçalves da Silva, André Gifalli, André Nunes de Souza, Enio Garbelini

“…Additionally, a Graphical User Interface (GUI) was implemented to facilitate user interaction, allowing for easy visualization of power-loss predictions and real-time adjustments.…”
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A New Artificial Neural Network Model for the Prediction of the Effect of Molar Ratios on Compressive Strength of Fly Ash-Slag Geopolymer Mortar by Shaise K. John, Alessio Cascardi, Yashida Nadir, Maria Antonietta Aiello, K. Girija

“…In this study, an Artificial Neural Network (ANN) model has been applied to predict the effect of molar ratios on the 28-day compressive strength of fly ash-slag geopolymer mortar. …”
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