Assessing Urban Land Parcel Dynamics Driven by Bus Rapid Transit (BRT) as an Exclusive Transit Route by Rana Tahir Mehmood, Muhammad Zaly Shah, Mehdi Moeinaddini, Muhammad Mashhood Arif, Ramine Chuhdary, Mufeeza Tahira

“…This study applies the C5.0 decision tree algorithm, a non-parametric model that creates a decision tree with leaf nodes that predict the relationship. …”
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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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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

“…Model accuracy ranged between 69 % (<span class="inline-formula">RF_test</span>) and 71 % (leave one year out, LOYO), showing a moderately high model reliability for predicting FFS. The model results underscore the importance of anthropogenic parameters and vegetation parameters in modelling FFS on a regional level. …”
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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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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 introduce a model that predicts the time-dependent reflectance of a dry snowpack as a function of its density, grain size, and black carbon content. …”
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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

“…Computed tomography (CT) is the imaging method of choice for evaluating the canine nasal cavity, being invaluable in determining disease extent, guiding sampling, and planning treatment. While predictions of pathology type can be made, there is significant overlap between CT changes noted in neoplastic, inflammatory, and infectious nasal disease. …”
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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

“…The final multivariate model (BMI, age, CPL diameter) yielded an 85% accuracy in predicting CPL detectability by TAUS. TAUS could be a cost-effective and patient-friendly imaging method for the surveillance of CPL in selected patients.…”
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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 positive and negative impacts of various features predicting PD and MSA were clarified, with larger fourth ventricular and smaller brainstem volumes being most significant. …”
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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

“…The fragmentation of magnetized filaments on 200 pc scales or less occurs when they exceed an average critical line mass, as predicted by theory. On larger scales, however, kiloparsec filaments form out of the cold neutral medium, and fragmentation follows local variations in the critical line mass along spiral arms or at the boundaries of superbubbles.…”
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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

“…Benefits from this model are seen in accurate bottomhole pressure and reservoir characteristic predictions, which are of major importance for safety and economic reasons during UBD and follow-up completion operations.…”
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Data-Driven Approach for Passenger Mobility Pattern Recognition Using Spatiotemporal Embedding by Chao Yu, Haiying Li, Xinyue Xu, Jun Liu, Jianrui Miao, Yitang Wang, Qi Sun

“…Urban mobility pattern recognition has great potential in revealing human travel mechanism, discovering passenger travel purpose, and predicting and managing traffic demand. This paper aims to propose a data-driven method to identify metro passenger mobility patterns based on Automatic Fare Collection (AFC) data and geo-based data. …”
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Identifying ferroptosis-related genes in lung adenocarcinoma using random walk with restart in the PPI network by Can Liu, Peng He, Ru Qiao, Xiaoyan Yang, Changsong Ding, Fuyuan He

“…In this study, we employed the random walk with restart (RWR) algorithm on the LUAD protein-protein interaction (PPI) network to predict ferroptosis-related target genes. …”
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In Situ Monitoring and Numerical Experiments on Vertical Deformation Profiles of Large-Scale Underground Caverns in Giant Hydropower Stations by Hao Wu, Jian Liu, Xiaogang Wang, Lipeng Liu, Zhenhua Tian

“…After fitting the complete VDP curve with a Levenberg-Marquardt algorithm, we verify its validity by comparing predicted data with in situ monitoring data. …”
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Power System Reliability Assessment with Quantification of Demand Response Uncertainty Based on Advanced Sigmoid Cloud Model by Bo Hu, Yue Sun, Wei Huang, Changzheng Shao, Tao Niu, Xin Cheng, Kaigui Xie

“…However, the price elasticity curve of the DR resources is influenced by consumers&#x0027; behavioral uncertainty and therefore is difficult to predict. Consequently, additional risk may be introduced to composite power system reliability. …”
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Digital Health Technologies for Optimising Treatment and Rehabilitation Following Surgery: Device-Based Measurement of Sling Posture and Adherence by Joss Langford, Ahmed Barakat, Engy Daghash, Harvinder Singh, Alex V. Rowlands

“…Results: We found that upper arm angle and posture type during sling wear can be predicted from a sling sensor alone (R² = 0.79, <i>p</i> < 0.001 and Cohen’s kappa = 0.886, respectively). …”
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LSAF-LSTM-Based Self-Adaptive Multi-Sensor Fusion for Robust UAV State Estimation in Challenging Environments by Mahammad Irfan, Sagar Dalai, Petar Trslic, James Riordan, Gerard Dooly

“…Validated on an in-house integrated UAV platform and evaluated against high-precision RTK ground truth, the algorithm incorporates deep learning-predicted fusion weights into an optimization-based odometry pipeline. …”
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Determining IFI44 as a key lupus nephritis’s biomarker through bioinformatics and immunohistochemistry by Yue Tan, Xueyao Wang, Deyou Zhang, Jiahui Wang, Shuxian Wang, Jinyu Yu, Hao Wu

“…The levels of IFI44 positively correlate with serum creatinine and the Systemic Lupus Erythematosus Disease Activity Index (SLEDAI) and inversely with serum complement C3 and initial estimated glomerular filtration rate (eGFR).Conclusion IFI44 is identified as a promising biomarker for LN, offering potential to refine the assessment of disease progression and predict clinical outcomes. This facilitates the development of more personalized treatment strategies for LN patients.…”
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