Anticipating epidemic transitions with imperfect data. by Tobias S Brett, Eamon B O'Dea, Éric Marty, Paige B Miller, Andrew W Park, John M Drake, Pejman Rohani

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Novel Insights from Comprehensive Bioinformatics Analysis Utilizing Large-Scale Human Transcriptomes and Experimental Validation: The Role of Autophagy in Periodontitis by Liu F, Zhu Z, Zou H, Huang Z, Xiao S, Li Z

“…Subsequently, a comprehensive analysis of immune cell infiltrate utilizing the CIBERSORT algorithm was performed. Finally, leveraging the DSigDB database, potential candidate drugs for periodontitis treatment targeting autophagy were predicted.Results: A total of 79 genes have been identified as DEARGs in periodontitis. …”
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Relationship Between Sepsis Phenotypes and Treatment Characteristics of Patients with Viral and Bacterial Pneumonia by I. A. Ruslyakova, E. Z. Shamsutdinova, L. B. Gaikovaya

“…New subgroups of patients with severe community-acquired pneumonia (SCAP) are hardly predicted by the use of clinical covariates; clusterization may significantly improve diagnostic approaches and facilitate the adaptation of specific treatment modalities to patient’s individual characteristics.The aim of the study. …”
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Single-cell and bulk transcriptome analyses reveal elevated amino acid metabolism promoting tumor-directed immune evasion in colorectal cancer by Tianyue Sun, Yan Chen, Ying-Xuan Chen

“…Additionally, LASSO and Cox regression analyses were conducted to construct an AA metabolism-related risk score for predicting prognosis and drug sensitivity across multiple bulk transcriptome cohorts.ResultsThis study identified a link between elevated amino acid metabolism in CRC epithelial cells and resistance to PD-1 blockade therapy. …”
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Simulation and Modelling of C+L+S Multiband Optical Transmission for the OCATA Time Domain Digital Twin by Prasunika Khare, Nelson Costa, Marc Ruiz, Antonio Napoli, Jaume Comellas, Joao Pedro, Luis Velasco

“…Once datasets were generated using the adaptive step size RK4IP method, two ML modelling approaches were considered to be integrated in the OCATA DT, where models predict optical signal propagation in the time domain. …”
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Artificial Intelligence ECG Diastolic Dysfunction and Survival in Cardiac Intensive Care Unit Patients by Jacob C. Jentzer, Eunjung Lee, Zachi Attia, Dustin Hillerson, Garvan C. Kane, Francisco Lopez‐Jimenez, Peter A. Noseworthy, Paul A. Friedman, Jae K. Oh

“…An artificial intelligence enhanced ECG (AIECG) algorithm can predict LVDD and mortality in general populations but has not been examined in cardiac intensive care units. …”
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Market and cadastral data comparison for the real estate market value forecasting by M. B. Laskin, P. A. Cherkesova

“…The authors propose a method for estimating the most likely movement of the market value for a pre-selected real estate object that has passed cadastral registration and has a cadastral value entered in the register and predicting the market value in the future period.Results. …”
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Stepwise autonomous orbit determination of large LEO constellations by GNSS observations with partial inter-satellite ranging by Yuanxi Yang, Xiaoyong Song

“…The difference of the adaptive stepwise OD algorithm is that the covariance matrix of the predicted orbit parameters based on the dynamic model is modified by an adaptive factor. …”
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Research on Non-Random Vibration Analysis of Concrete Pump Truck Boom Based on Dynamic Excitation by Weixin Zhou, Wubin Xu, Bing Li, Yuanbin Xiao, Xianyu Liu, Hanwen Zhang, Bo Xu

“…The technique can reliably predict the dynamic displacement boundary and control the casting position deviation within a predefined range by accurately predicting the dynamic displacement range of the pump truck’s boom end and efficiently constructing the displacement envelope under uncertain dynamic excitation. …”
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Full-chain comprehensive assessment and multi-scenario simulation of geological disaster vulnerability based on the VSD framework: a case study of Yunnan province in China by Li Xu, Shucheng Tan, Runyang Li

“…Thus, scientifically assessing and predicting geological disasters and formulating disaster prevention and mitigation policies are of critical importance for promoting regional sustainable development. …”
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Multi-objective optimization of sustainable cement-zeolite improved sand based on life cycle assessment and artificial intelligence [version 1; peer review: 1 approved, 2 approved... by Hossein MolaAbasi, Satinder Kaur Brar, Amin Tanhadoust, Sepideh Nasrollahpour, Omolbanin Ataee, Moncef L. Nehdi

“…This study proposes a multi-objective optimization approach using back-propagation neural network (BPNN) to predict the mechanical strength, along with an adaptive geometry estimation-based multi-objective evolutionary algorithm (AGE-MOEA) to identify the best parameters for cement-zeolite-improved sand, filling a long-lasting research gap. …”
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Increasing Systemic Resilience to Socioeconomic Challenges: Modeling the Dynamics of Liquidity Flows and Systemic Risks Using Navier–Stokes Equations by Davit Gondauri, Nino Chedia, Vakhtang Tsintsadze

“…In addition, the cyclical components obtained by Fourier analysis are harmoniously related to economic cycles and increase the accuracy of the model's predictions. The scientific significance of the study lies in the fact that it creates a mathematically balanced framework for a multifactorial analysis of the behavior of the financial system, which makes it possible not only to predict crises, but also to plan countercyclical policies and increase systemic stability. …”
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Cer(d18:1/16:0) as a biomarkers for acute coronary syndrome in Chinese populations by Liang Zhang, Yang Zhang, YaoDong Ding, Tong Jin, Yi Song, Lin Li, XiaoFang Wang, Yong Zeng

“…The objective of this study was to investigate the association between serum ceramide levels and Acute coronary syndrome, as well as evaluate their potential for predicting ACS in Chinese population. Data of 1327 patients with suspected or known coronary artery disease from Beijing anzhen Hospital and Handan First hospital were collected. …”
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Individual patient variability with the application of the kidney failure risk equation in advanced chronic kidney disease. by Christopher McCudden, Ayub Akbari, Christine A White, Mohan Biyani, Swapnil Hiremath, Pierre Antoine Brown, Navdeep Tangri, Scott Brimble, Greg Knoll, Peter G Blake, Manish M Sood

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Numerical Simulation of Earthquake Impacts on Marine Structures: A Comprehensive Review by Adel Kabi, Jersson X. Leon-Medina, Francesc Pozo

“…Furthermore, integrating laboratory and field data into unified frameworks will significantly improve the precision and practicality of these models, offering robust tools for predicting earthquake and wave impacts on marine environments.…”
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Quantum machine learning regression optimisation for full-scale sewage sludge anaerobic digestion by Yomna Mohamed, Ahmed Elghadban, Hei I Lei, Amelie Andrea Shih, Po-Heng Lee

“…Combining a variational quantum circuit with a classical optimiser, this approach predicts biogas production from operational data of 18 full-scale mesophilic AD sites in the UK. …”
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The Use of General Inverse Problem Platform (GRIPP) as a Robust Backtracking Solution by Nikolas Gomes Silveira de Souza, Jader Lugon, Alexandre Macedo Fernandes, Ramiro Joaquim de Jesus Neves, Antônio José da Silva Neto

“…The optimization yielded a solution with a mean error of 0.019 degrees between predicted and observed tracer locations. This demonstrates the potential of GRIPP and GenSA for solving practical environmental problems in coastal regions. …”
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Machine learning-based multiphysics model for corrosion fatigue crack propagation in aluminum alloy by Hongkun Wang, Zhenshuang Wu, Dongmei Jiang, Haitao Wang, En-Hou Han

“…The present study predicted the corrosion fatigue crack growth rate of 7075-T7651 aluminum alloy under cyclic sinusoidal loading in an aqueous solution. …”
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Robust Representation Learning Based on Deep Mutual Information for Scene Classification Against Adversarial Perturbations by Linjuan Li, Gang Xie, Haoxue Zhang, Xinlin Xie, Heng Li

“…However, deep learning models used for scene classification are highly vulnerable to adversarial samples, resulting in incorrect predictions and posing significant risks. While most current methods focus on improving adversarial robustness, they face a trade-off that compromises accuracy on clean, unperturbed images. …”
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Application of a GA-BP Neural Network in Accurately Characterizing the Diffusion Range of Groundwater Pollutants by Jiayun JI, Xiao XIAO, Pinlu YANG, Yang LIU, Yahong ZHOU

“…To overcome this, two neural network models—GA-BP and standard BP—were applied to predict Mn2+ concentrations at unsampled locations. …”
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