Evaluating the predictive power of combined gene expression dynamics from single cells on antibiotic survival by Razan N. Alnahhas, Virgile Andreani, Mary J. Dunlop

“…We developed a Bayesian inference model to predict how the combination of dual reporter expression levels and growth rate impacts ciprofloxacin survival in Escherichia coli. …”
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Relationship Between 8-iso-prostaglandin-F_2α and Predicted 10-Year Cardiovascular Risk in Hypertensive Patients by Giulio Geraci, Alessandra Sorce, Luca Zanoli, Giuseppe Cuttone, Vincenzo Calabrese, Francesco Pallotti, Valentina Paternò, Pietro Ferrara, Ligia J. Dominguez, Riccardo Polosa, Jacob George, Giuseppe Mulè, Caterina Carollo

“…The aim of this study was to assess the relationship between 8-iso-PGF_2α and 10-year CV risk, as predicted by validated equations in hypertension patients without CV diseases. …”
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Assessment of spatial autocorrelation and scalability in fine-scale wildfire random forest prediction models by Madeleine Pascolini-Campbell, Joshua B. Fisher, Kerry Cawse-Nicholson, Christine M. Lee, Natasha Stavros

“…Here we use high resolution (70 m, every 3–5 days) remote sensing observations of evapotranspiration and evaporative stress index, which represent plant water stress, from Ecosystem Spaceborne Thermal Radiometer on Space Station (ECOSTRESS), as well as topography and weather data, to predict burn severity and occurrence for 8 large wildfires that burned 3715 km2 from 2021 and 2022 in New Mexico, USA. …”
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Classification Prediction of Rockburst in Railway Tunnel Based on Hybrid PSO-BP Neural Network by Min Zhang

“…In order to accurately predict the rockburst intensity level of the railway tunnel, the rock stress coefficient σθ/σc, rock brittleness coefficient σc/σt, and elastic energy index Wet are used as evaluation indexes of rockburst intensity, and a BP neural network rockburst prediction model based on hybrid particle swarm optimization algorithm is proposed. …”
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Aging Analysis and Degradation Prediction of PLL Circuits in 14-nm FinFET Technology by Meng Li, Xin Xu, Xianghui Li, Yunpeng Li, Yiqun Shi, Qingqing Sun, Hao Zhu

“…The quasi-static-approximation (QSA) model built with DC stress test data, was employed for device and circuit degradation predictions, and its limitations and applicability were discussed. …”
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Creep behavior of clayey soil and its model prediction in the Cangzhou land subsidence area by Jianfeng Qi, Yongjie Xie, Chen Li, Haipeng Guo, Yunlong Wang

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Study on the Prediction of the Height of Two Zones in the Overlying Strata under a Strong Shock by Xingping Lai, Bowei Liu, Pengfei Shan, Feng Cui, Yun Zhang, Xudong Zhang, Rui Bai, Xuan Wu

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TEENAGE PREGNANCY PREDICTION INDEX DURING THE ONLINE LEARNING PERIOD OF THE COVID-19 PANDEMIC by Eny Qurniyawati, Santi Martini, Fariani Syahrul, Jayanti Dian Eka Sari, Rahayu Lubis, Nayla Mohamed Gomaa Nasr

“…Aims: To determine the predictive index of risk variables for teen pregnancy throughout the COVID-19 pandemic's online learning period. …”
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Biomarker panels for improved risk prediction and enhanced biological insights in patients with atrial fibrillation by Pascal B. Meyre, Stefanie Aeschbacher, Steffen Blum, Tobias Reichlin, Moa Haller, Nicolas Rodondi, Andreas S. Müller, Alain Bernheim, Jürg Hans Beer, Giorgio Moschovitis, André Ziegler, Bianca Wahrenberger, Elia Rigamonti, Giulio Conte, Philipp Krisai, Leo H. Bonati, Stefan Osswald, Michael Kühne, David Conen

“…We identify 5 biomarkers including D-dimer, growth differentiation factor 15 (GDF-15), interleukin-6 (IL-6), N-terminal pro-B-type natriuretic peptide (NT-proBNP), and high-sensitivity troponin T (hsTropT) that independently predict cardiovascular death, stroke, myocardial infarction, and systemic embolism, significantly enhancing predictive accuracy. …”
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Prediction method of surface deformation around soft base dump based on viscoelastic theory by Dong WANG, Li YIN, Lanzhu CAO, Yiming FU, Liguo ZHANG, Chunhui ZHANG, Chunjian DING

“…A series of quantitative data is obtained through calculations and predictions of surface deformation on layered viscoelastic substrates under pile load actions in the discharging yard. …”
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Optimizing corn yield prediction: Integrating multi-temporal UAS data and machine learning by Huihui Zhang, Yuting Zhou, Shengfang Ma, Kevin Yemoto

“…The integration of VNIR and LWIR imagery improves yield prediction accuracy, particularly in water-stressed conditions, highlighting the importance of advanced sensing technologies and complex models such as RF and GB. …”
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Multi‐trait multi‐environment genomic prediction of preliminary yield trial in pulse crop by Rica Amor Saludares, Sikiru Adeniyi Atanda, Lisa Piche, Hannah Worral, Francoise Dariva, Kevin McPhee, Nonoy Bandillo

“…Multi‐trait multi‐environment enabled genomic prediction (MTME‐GP) offers a valuable alternative to predict missing phenotypes of selection candidates for multiple traits and diverse environments. …”
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MODIFIABLE AND NON-MODIFIABLE RISK FACTORS IN PREDICTING THE RECURRENCE OF ATRIAL FIBRILLATION IN PATIENTS WITH ARTERIAL HYPERTENSION by M. S. Arakelyan, N. G. Poteshkina, P. A. Mogutova

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Advancements in predicting soil liquefaction susceptibility: a comprehensive analysis of ensemble and deep learning approaches by Divesh Ranjan Kumar, Warit Wipulanusat

“…The BI-LSTM model has the highest accuracy, with 0.9791 in training and 0.8889 in testing, indicating strong predictive ability and good generalizability. LSTM follows closely with training and testing accuracies of 0.9433 and 0.8750, respectively, offering consistent performance. …”
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Comparison of hemodynamic effects and negative predictive value of normal adenosine gated myocardial perfusion scan with or without caffeine abstinence by Maseeh uz Zaman, Nosheen Fatima, Areeba Zaman, Unaiza Zaman, Rabia Tahseen

“…The aim of this study was to compare the hemodynamic changes and negative predictive value (NPV) of normal MPIs with adenosine stress performed with or without caffeine abstinence. …”
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CS03 | Khorana risk score and genomic profiling for prediction of venous thromboembolism in ovarian cancer

“…Figure 1. Evaluation of the predictive role of genomic mutations in patients with ovarian cancer. a. …”
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Compression-compression fatigue life prediction model of T300/69 laminates under edge impact by ZHANG Peng, LIU Jianhui, WEI Yaobing

“…Therefore, it is of practical engineering significance to establish a fatigue life prediction model for low-velocity impact at the edge. …”
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Contact fatigue limit prediction method for heavy-duty gears considering hardness gradient characteristics by Boyu Zhang, Yongyong He, Zhengwei Wang

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Evaluating the feasibility of using crystalline patterns induced by PBF-LB to predict strength enhancing orientations by José David Pérez-Ruiz, Luis Norberto López de Lacalle, Wilmer Velilla-Díaz, Jaime A. Mesa, Gaizka Gómez, Heriberto Maury, Gorka Urbikain, Haizea Gonzalez

“…A distinctive feature of the PBF-LB process is its capacity to develop crystalline patterns, which can be utilized to predict strength-enhancing orientations of the produced components. …”
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Biomarkers for intensive care unit-acquired weakness: a systematic review for prediction, diagnosis and prognosis by Jiamei Song, Ting Deng, Qingmei Yu, Xun Luo, Yanmei Miao, Leiyu Xie, Yongming Mei, Peng Xie, Shaolin Chen

“…Biomarkers offer potential for diagnosing, predicting, and prognosticating ICU-AW, but a comprehensive synthesis of the available evidence is still lacking. …”
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