Rooting depth projections of global plant functional types and driving factors analysis based on a hybrid modeling framework by Qinggong Han, Bo Liu, Yunuo Liu, Jielin Zhang, Yongxia Ding, Shouzhang Peng

“…In this study, we developed a hybrid model that combines random forest algorithm with ecosystem data simulated by LPJ-GUESS model and environmental variables to predict global rooting depth, based on 1,184 integrated rooting depth observations. …”
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A Correlation Analysis-Based Structural Load Estimation Method for RC Beams Using Machine Vision and Numerical Simulation by Chun Zhang, Yinjie Zhao, Guangyu Wu, Han Wu, Hongli Ding, Jian Yu, Ruoqing Wan

“…Subsequently, a deep neural network (DNN) is trained as a FEM surrogate model to quickly predict the structural strain response by considering material uncertainties. …”
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A Rule-Based Agent for Unmanned Systems with TDGG and VGD for Online Air Target Intention Recognition by Li Chen, Jing Yang, Yuzhen Zhou, Yanxiang Ling, Jialong Zhang

“…Then, a rule-based agent for unmanned systems for online intention recognition is proposed, with no training, no tagging, and no big data support, which is not only for intention recognition and parameter prediction, but also for formation identification of air targets. …”
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Modelling current and future forest fire susceptibility in north-eastern Germany by K. H. Horn, K. H. Horn, S. Vulova, S. Vulova, H. Li, B. Kleinschmit

“…We applied a random forest (RF) machine learning (ML) algorithm to model current and future FFS in the federal state of Brandenburg (Germany) using topographic, climatic, anthropogenic, soil, and vegetation predictors. …”
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Preoperative predictors of thrombosis in children with congenital heart disease by V. A. Lastovka, R. F. Tepaev, O. B. Gordeeva, A. R. Bidzhiev, A. A. Chotchaeva

“…The literature describes in detail the disturbances in the hemostasis system observed after cardiac surgeries performed in conditions of artificial circulation, but there are no indicators that could predict the risk of thrombosis in children. The use of parameters of plasma hemostasis as predictors of thrombosis in the algorithm for diagnosing hemocoagulation disorders in children of the first year of life undergoing surgery for congenital heart defects has been substantiated. …”
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Aircraft Routing and Crew Pairing Solutions: Robust Integrated Model Based on Multi-Agent Reinforcement Learning by Chengjin Ding, Yuzhen Guo, Jianlin Jiang, Wenbin Wei, Weiwei Wu

“…The problem is formulated as a sequential decision-making process and solved via a novel multi-agent reinforcement learning algorithm. Numerical results demonstrate that the novel method outperforms prior methods in the literature in terms of solving speed and can also enhance planning robustness. …”
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Measurement of snowpack density, grain size, and black carbon concentration using time-domain diffuse optics by Connor Andrew Henley, Colin Richard Meyer, Jacob Ian Chalif, Joseph Lee Hollmann, Ramesh Raskar

“…We develop an algorithm that retrieves these properties from measurements at two wavelengths. …”
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Deep learning-based framework for Mycobacterium tuberculosis bacterial growth detection for antimicrobial susceptibility testing by Hoang-Anh T. Vo, Sang Nguyen, Ai-Quynh T. Tran, Han Nguyen, Hai Bich Ho, Philip W. Fowler, Timothy M. Walker, Thuy Thi Nguyen

“…Automated Mycobacterial Growth Detection Algorithm (AMyGDA) is a software package that uses image processing techniques to read plates, but struggles with plates that exhibit low growth or images of low quality. …”
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Resource Optimization Method Based on Spatio-Temporal Modeling in a Complex Cluster Environment for Electric Vehicle Charging Scenarios by Hongwei Wang, Wei Liu, Chenghui Wang, Kao Guo, Zihao Wang

“…To address this, a novel self-organizing prediction method for spatio-temporal resource allocation is proposed. …”
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CPO-VMD Combined With Multiscale Permutation Entropy for Noise Reduction in GNSS Vertical Time Series in Mining Areas by Xu Yang, Xinxin Yao, Xinjian Fang, Xuexiang Yu, Yi Wu, Shicheng Xie

“…Taken together, the CPO-VMD-MPE method proposed in this paper significantly reduces the noise in the time series and provides a better theoretical and methodological reference for deformation analysis and prediction.…”
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Trauma, personality structure and psychopathology: a cartography of psychodynamic constructs by Jürgen Fuchshuber, Victor Blüml, Nestor Kapusta, Henriette Löffler-Stastka, Johanna Alexopoulos, Elisa Renner, Hugo Senra, Human-Friedrich Unterrainer

“…A cross-sectional network between personality organization [IPO-16], hypomentalizing [RFQ-6], attachment [ECR-RD8]), primary affective traits [BANPS-GL], depression, anxiety and somatization symptoms [BSI-18], addiction [WHO-ASSIST] and childhood trauma [CTQ] was estimated via the EBICglasso and relimp algorithm. Regularized partial correlation edge weights, node centrality, predictability, bridge centrality, relative importance and stability coefficients were analyzed. …”
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A Novel Machine Learning Model for the Automated Diagnosis of Nasal Pathology in Canine Patients by Andreea Istrate, Radu Constantinescu, Lithicka Anandavel, Shraddha Rajeshkumar Tandel, Simon Dye, Charlotte Dye

“…The machine learning algorithm showed reasonable accuracy (86%) in classifying the diagnosis from an isolated scan slice but high accuracy (99%) when aggregating over slices taken from a full scan. …”
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Transabdominal ultrasound for the characterization and follow-up of cystic pancreatic lesions by Julian Seelig, Maria Heni, Max Seitzinger, Kien Vu Trung, Jürgen Feisthammel, Marcus Hollenbach, Robert Henker, Albrecht Hoffmeister, Jonas Rosendahl, Valentin Blank, Thomas Karlas

“…Cross-method morphological assessments were analysed, and a patient-specific algorithm for selecting the appropriate monitoring method was developed. …”
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Design and validation of a CFD model for energy-efficient Ni-Co-Mn cathode calcination process by Jaeseop Jo, Minyoung Hwang, Jungeui Lee, Joo Hyun Park

“…The primary objective is to quantitatively predict and optimize energy consumption in high-temperature solid-state synthesis processes. …”
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Brain structural features with functional priori to classify Parkinson’s disease and multiple system atrophy using diagnostic MRI by Kai Zhou, Jie Li, Rui Huang, Jiali Yu, Rong Li, Wei Liao, Fengmei Lu, Xiaofei Hu, Huafu Chen, Qing Gao

“…The structure constrained super-resolution network (SCSRN) algorithm was employed to reconstruct clinical 2D MRI data for 56 PD and 58 MSA patients. …”
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Filamentary Hierarchies and Superbubbles. I. Characterizing Filament Properties across a Simulated Spiral Galaxy by Rachel Pillsworth, Erica Roscoe, Ralph E. Pudritz, Eric W. Koch

“…By adapting the FilFinder algorithm of E. W. Koch & E. W. Rosolowsky, we extract over 500 filaments ranging up to 10 kpc in scale, to derive the probability distribution functions for filament masses and lengths, magnetic field orientations, and the gravitational stability and fragmentation patterns of filaments. …”
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Real-Time Interpretation Model of Reservoir Characteristics While Underbalanced Drilling Based on UKF by Miao He, Yihang Zhang, Mingbiao Xu, Jun Li, Jianjian Song

“…This study presents a novel interpretation model for reservoir characteristics while underbalanced drilling (UBD), by incorporating an unscented Kalman filter (UKF) algorithm in a three-phase variable mass flow model of oil, gas, and liquid. …”
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Pathogen-specific epitopes as epidemiological tools for defining the magnitude of Mycobacterium leprae transmission in areas endemic for leprosy. by Marcia V S B Martins, Marjorie M da S Guimarães, John S Spencer, Mariana A V B Hacker, Luciana S Costa, Fernanda M Carvalho, Annemieke Geluk, Jolien J van der Ploeg-van Schip, Maria A A Pontes, Heitor S Gonçalves, Janvier P de Morais, Tereza J P G Bandeira, Maria C V Pessolani, Patrick J Brennan, Geraldo M B Pereira

“…The data generated indicate that an IFN-γ assay based on these peptides applied individually or as a pool can be used as a new tool for predicting the magnitude of M. leprae transmission in a given population.…”
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An efficient method for network security situation assessment by Xiaoling Tao, Kaichuan Kong, Feng Zhao, Siyan Cheng, Sufang Wang

“…Then, the back propagation neural network algorithm is adopted to perform network security situation assessment. …”
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Real-Time Caterpillar Detection and Tracking in Orchard Using YOLO-NAS Plus SORT by Sumesh Nair, Guo-Fong Hong, Chia-Wei Hsu, Chun-Yu Lin, Shean-Jen Chen

“…With an inference time of just 0.2 milliseconds, SORT enabled real-time tracking and accurately predicted caterpillar positions under wind interference, further improving reliability. …”
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