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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A novel mitochondrial quality regulation gene signature for anticipating prognosis, TME, and therapeutic response in LUAD by multi-omics analysis and experimental verification by Lijun Zeng, Sixuan Wu, Zhimin Li, Yuanbin Tang, Yeru Tan, Renji Liang, Yuehua Li

“…Utilizing the LASSO algorithm and multivariate COX regression, a predictive risk model was created. …”
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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

“…The methodology is based on a mixed approach: econometric testing, Fourier analysis, stochastic simulations, and AI-algorithm tuning, which together provide dynamic testing, calibration, and forecasting capabilities of the model. …”
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Risk analysis of the association between EASIX and all-cause mortality in critical ill patients with atrial fibrillation: a retrospective study from MIMIC-IV database by Yu Xia, Anfeng Liang, Mei Wang, Jianlin Zhang

“…The AUC showed that the performance of EASIX in predicting both short-term and long-term all-cause mortality was comparable to the SOFA and higher than the CHA₂DS₂–VASc score. …”
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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

“…Diagnostic performance assessments showed that Cer(d18:1/16:0) had superior accuracy in detecting ACS compared to other ceramides tested. The Boruta algorithm identified 8 significant variables related to ACS. …”
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Statistics and behavior of clinically significant extra-pulmonary vein atrial fibrillation sources: machine-learning-enhanced electrographic flow mapping in persistent atrial fibri... by Peter Ruppersberg, Steven Castellano, Philip Haeusser, Kostiantyn Ahapov, Melissa H. Kong, Stefan G. Spitzer, Stefan G. Spitzer, Georg Nölker, Andreas Rillig, Tamas Szili-Torok

“…These findings, supported by the FLOW-AF trial, underscore the usefulness of clinical outcome-based machine learning to improve the efficacy of algorithm based medical diagnostics.…”
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AFF3 is a Prognostic Biomarker Correlated with Immune Infiltrates in Triple-Negative Breast Cancer by Jing Chen, Bing Tan, Wei Zhuang, Tenghua Yu, Jianglong Li, Chongwu He

“…Conclusions: In TNBC, low AFF3 expression might be predictive of poor survival. AFF3 might provide additional insight into therapeutics in TNBC.…”
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Visualising fibre path and generating G-code for melt electrowriting of tubular scaffolds using Grasshopper software by Kelly L. O’Neill, Taite McLoughlin, Georgia Van der Linden, Ignacio Lopez Buson, Naomi C. Paxton, Mary Polites, Paul D. Dalton

“…This visual prototyping platform through Rhinoceros and Grasshopper offers a new method in predicting fibre paths and incorporating scaffold design parameters, meeting the need for diverse tubular scaffolds in different fields. …”
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Understanding the evolutionary processes and causes of groundwater drought using an interpretable machine learning model by Zhiyuan Gan, Xianjun Xie, Chunli Su, Weili Ge, Hongjie Pan, Liangping Yang

“…We employed machine learning models and the Shapley Additive Explanation (SHAP), a game theory-based interpretability method, to understand and predict the evolution of groundwater drought by evaluating eight models with SHAP analysis in the West Liao River Plain (WLRP), with a semi-arid climate. …”
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Impact of Climate Change on the Distributional Potential of the Endemic Species Tamarix dubia Bunge and Conservation Implications for the Irano‐Turanian Region by Habibollah Ijbari, Jamil Vaezi, Maryam Behroozian, Hamid Ejtehadi

“…Under both future scenarios, we predicted a decrease in the suitable habitat range of T. dubia in the period 2041–2060. …”
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IDI diesel engine performance and exhaust emission analysis using biodiesel with an artificial neural network (ANN) by K. Prasada Rao, T. Victor Babu, G. Anuradha, B.V. Appa Rao

“…For the ANN modeling standard back propagation algorithm was found to be the optimum choice for training the model. …”
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A Real-Time Safety-Based Optimal Velocity Model by Awad Abdelhalim, Montasir Abbas

“…Then, we analyze the driver behavior to predict the shape of the underlying TTC-based desired velocity function. …”
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Phenotyping sarcoidosis: a single institution retrospective analysis by Francesco Rocco Bertuccio, Francesco Rocco Bertuccio, Davide Piloni, Davide Piloni, Marianna Russo, Marianna Russo, Fady Tousa, Fady Tousa, Mariachiara Crescenzi, Mariachiara Crescenzi, Paola Putignano, Paola Putignano, Nicola Baio, Nicola Baio, Ida Maragò, Angelo Guido Corsico, Angelo Guido Corsico, Giulia Maria Stella, Giulia Maria Stella

“…For instance, finding a relationship between symptom burden, race, gender, HRQoL, and pulmonary function could have therapeutic ramifications, influence clinical practice, and aid in selecting patients for specific clinical studies.MethodsA comprehensive statistical evaluation was conducted using the JMP partitioning algorithm which explores all potential divisions to identify the most predictive variables.ResultsWith our analysis, we tried to categorize patients from a single Institution respiratory unit to delineate clinical phenotypes in sarcoidosis.ConclusionsLarger studies using appropriate methodology should surely be carried out to address this issue and help clarify the varying contributions of genetics, socioeconomic status, environmental exposures, and other sociodemographic factors to illness severity and phenotypic presentation. …”
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Optimization of grading rings for 1000 kV dry-type air-core shunt reactor based on hybrid RBFNN–Kriging surrogate model by Yiqin Liu, Liang Xie, Dongyang Li, Yunpeng Liu, Kexin Liu, Gang Liu

“…First, the sparrow search algorithm is used to optimize the hyperparameters of the RBFNN. …”
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Bamboo bio composite: A renewable and sustainable sound absorber for acoustic comfort in indoor settings by Hassan Irvani, Hassan Asilian Mahabadi, Ali Khavanin, Ali Safari Variani, Mohammad Javad SheikhMozafari

“…Furthermore, the impedance tube results exhibited noteworthy concordance with the predictions of the JCA model. Conclusively, the findings of this research underscore the potential of natural bamboo fiber-based composites as promising sound absorbers for effective sound control in indoor environments.…”
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Knowledge-guided self-learning control strategy for mixed vehicle platoons with delays by Jingyao Wang, Huinian Wang, Jian Song, Xingyu Chen, Jinghua Guo, Keqiang Li, Xunrui Li, Bowen Huang

“…This helps autonomous vehicles predict traditional vehicles’ trajectories. Secondly, to tackle delayed current state information, the study incorporates previous control instructions into the state representation of the soft actor-critic algorithm. …”
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A strategy for out-of-roundness damage wheels identification in railway vehicles based on sparse autoencoders by Jorge Magalhães, Tomás Jorge, Rúben Silva, António Guedes, Diogo Ribeiro, Andreia Meixedo, Araliya Mosleh, Cecília Vale, Pedro Montenegro, Alexandre Cury

“…Abstract Wayside monitoring is a promising cost-effective alternative to predict damage in the rolling stock. The main goal of this work is to present an unsupervised methodology to identify out-of-roundness (OOR) damage wheels, such as wheel flats and polygonal wheels. …”
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A damage model that can be coupled with constitutive behavior prior to necking for SGAFC 780 steel by Seong Jin Lee, Taek Jin Jang, Hyunho Shin, Yongwon Ju, Sangho Bae, Jong-Bong Kim

“…They also predicted damage contours that reasonably correspond to the moments and locations of cracks observed during the tensile fracture tests. …”
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UAV-Based SAR-Imaging of Objects From Arbitrary Trajectories Using Weighted Backprojection by Alexander Grathwohl, Julian Kanz, Christina Bonfert, Christian Waldschmidt

“…Both the distance between radar and targets as well as the viewing angle of the radar change significantly during flight. A common imaging algorithm for close-range and nonlinear flightpaths is therefore backprojection (BP), since it respects the nonlinear flightpath. …”
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