Controlling the formation of microstructure at the melt-pool boundaries during directed energy deposition of aluminum alloy with a modified continuous growth restriction factor by Shanshan Xu, Bo Yin, Jiale Wang, Liquan Jin, Yu Yin, Zhenhua Li, David H. StJohn, Petro Pavlenko, Yueling Guo

“…However, existing analytical models fail to consider internal and external factors, particularly the solute concentration and scan speed, leading to low prediction accuracy of the solidified microstructure. …”
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Distribution and clinicopathological characteristics of G-CSF expression in tumor cells and stromal cells in upper tract urothelial carcinoma by Go Kobayashi, Yohei Sekino, Hikaru Nakahara, Kohei Kobatake, Keisuke Goto, Tetsutaro Hayashi, Kazuhiro Sentani, Nobuyuki Hinata

“…A prognostic model was constructed by incorporating the presence or absence of G-CSF expression along with clinicopathologic factors, which allowed for a more accurate prediction of poor prognosis. We further showed that G-CSF expression was associated with a high Ki-67 labeling index and with PD-L1, HER2, and p53 expression in UTUC. …”
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A Dual-Stage Processing Architecture for Unmanned Aerial Vehicle Object Detection and Tracking Using Lightweight Onboard and Ground Server Computations by Odysseas Ntousis, Evangelos Makris, Panayiotis Tsanakas, Christos Pavlatos

“…The UAV transmits selected frames to the ground server, which handles advanced tracking, trajectory prediction, and target repositioning using state-of-the-art deep learning models. …”
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Association of Septic Shock with Mortality in Hospitalized COVID-19 Patients in Wuhan, China by Shaoqiu Chen, Zitong Gao, Ling Hu, Yi Zuo, Yuanyuan Fu, Meilin Wei, Emory Zitello, Gang Huang, Youping Deng

“…Log-rank test was conducted to determine any association with clinical progression. A prediction model was established using random forest. …”
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Use of the LCM Model in the prospective simulation of land use in the Nafoun watershed (Northern Ivory Coast) by Kamagate Anzoumanan, Koffi Ehouman Serge, Koffi Yao Blaise

“…Landsat images from 1986, 2000 and 2023 were used to assess and predict the spatio- temporal distributions of land use change. …”
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Improved Outcome of Severe Acute Pancreatitis in the Intensive Care Unit by Polychronis Pavlidis, Siobhan Crichton, Joanna Lemmich Smith, David Morrison, Simon Atkinson, Duncan Wyncoll, Marlies Ostermann

“…On admission to ICU, the median Acute Physiology and Chronic Health Evaluation (APACHE) II score was 17, the pancreatitis outcome prediction score was 8, and the median Computed Tomography Severity Index (CTSI) was 4. …”
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Magnetic field influence on heat transfer of NEPCM in a porous triangular cavity with a cold fin and partial heat sources: AI analysis combined with ISPH method by Munirah Aali Alotaibi, Weaam Alhejaili, Abdelraheem M. Aly, Samiyah Almalki

“…The ANN model’s training, reflected in a decreasing mean squared error (MSE), demonstrates prediction accuracy, and regression analysis reveals high model reliability, with predictions closely aligning with theoretical Nu̅ values.…”
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Sustainability metrics targeted optimization and electric discharge process modelling by neural networks by Muhammad Sana, Muhammad Asad, Muhammad Umar Farooq, Mehdi Tlija, Rodolfo Haber

“…An artificial neural network (ANN) has been constructed for the better prediction of output responses. Moreover, multi-response optimization through the non-dominated sorting genetic algorithm (NSGA-II) has also been performed. …”
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Deep Ensemble Learning for Human Action Recognition in Still Images by Xiangchun Yu, Zhe Zhang, Lei Wu, Wei Pang, Hechang Chen, Zhezhou Yu, Bin Li

“…Finally, we design the deep ensemble learning based on voting strategy (DELVS) model to pool together multiple deep models with weighted coefficients to obtain a better prediction. More importantly, the model complexity can be reduced by lessening the number of trainable parameters, thereby effectively mitigating overfitting issues of the model in small datasets to some extent. …”
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High-resolution canopy fuel maps based on GEDI: a foundation for wildfire modeling in Germany by Johannes Heisig, Milutin Milenković, Edzer Pebesma

“…Error analysis pointed towards a mixture of biases in model predictions and validation data, as well as underestimation of model prediction standard errors. …”
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Exploring a high-level programming model for the NWP domain using ECMWF microphysics schemes by S. Ubbiali, C. Kühnlein, C. Schär, L. Schlemmer, T. C. Schulthess, T. C. Schulthess, M. Staneker, H. Wernli

“…In order to verify GT4Py for numerical weather prediction (NWP) systems, we put additional emphasis on the implementation and validation of the tangent-linear and adjoint model versions which are employed in data assimilation. …”
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Feature Selection in Cancer Classification: Utilizing Explainable Artificial Intelligence to Uncover Influential Genes in Machine Learning Models by Matheus Dalmolin, Karolayne S. Azevedo, Luísa C. de Souza, Caroline B. de Farias, Martina Lichtenfels, Marcelo A. C. Fernandes

“…To mitigate these challenges, the SHAP (Shapley Additive Explanations) method was applied to generate a list of features, aiming to understand which characteristics influenced the models’ decision-making processes and, consequently, the prediction results for the five tumor types. The SHAP analysis identified 119, 80, and 10 genes for the RF, XGB, and DT models, respectively, totaling 209 genes, resulting in 172 unique genes. …”
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Quantification of Rear-End Crash Risk and Analysis of Its Influencing Factors Based on a New Surrogate Safety Measure by Qiangqiang Shangguan, Ting Fu, Junhua Wang, Rui Jiang, Shou’en Fang

“…This study provides a new surrogate safety measure that can better identify rear-end crash risks in a more reliable way and can be applied to real-time crash risk prediction in driver assistance systems. In addition, the results of this study can be used to provide a theoretical basis for the formulation of traffic management strategies to improve driving safety.…”
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Identification of Hydraulic Connection Points between Different Confined Aquifers in the Liyazhuang Coal Mine by Zhenghe Liu, Peiyun Zhao, Lusheng Yang, Jingui Zhao, Hailong Ye, Jun Yang, Rujun Mo

“…Determining the source of water inrush can facilitate its prediction and guide decisions regarding measures for prevention and control. …”
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Selective Ensemble Learning Method for Belief-Rule-Base Classification System Based on PAES by Wanling Liu, Weikun Wu, Yingming Wang, Yanggeng Fu, Yanqing Lin

“…This drastically decreases the prediction speed and increases the storage requirements for BRB systems. …”
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Psychological and Behavioral Insights From Social Media Users: Natural Language Processing–Based Quantitative Study on Mental Well-Being by Xingwei Yang, Guang Li

“…ConclusionsThe developed framework offers practical applications, such as accelerating hospital diagnoses, improving prediction accuracy, facilitating timely referrals, and providing actionable insights for early interventions in mental health treatment plans.…”
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Atom-Driven and Knowledge-Based Hydrolysis Metabolite Assessment for Environmental Organic Chemicals by Zhe Liu, Yufan Lin, Qi He, Lingjie Dai, Qinyan Tan, Binyan Jin, Philip W. Lee, Xiaoming Zhang, Li Zhang

“…For an external test set of 75 chemicals, the global hydrolysis site prediction model achieved an accuracy of 93%. Additionally, among 99 experimental hydrolysis products, our model successfully predicted 90, with a hit rate of 90%. …”
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Deteksi Cepat Kadar Alkohol Pada Minuman Kopi dengan Metode Dielektrik dan Jaringan Syaraf Tiruan by Sucipto Sucipto, Yuyun Rohmawati, Dyah Ayu Widyaningrum, Danang Triagus Setiyawan

“…The back propagation algorithm was used to connect the input of bioelectric properties and output of prediction of alcohol content and pH in liqueur coffee. …”
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Perceived costs and benefits of companion dog keeping based on a convenience sample of dog owners by Laura Gillet, Borbála Turcsán, Eniko Kubinyi

“…On average, positive statements were rated significantly higher (2.06) than negative ones (−0.66), supporting the prediction from social exchange theory that dog owners in a voluntary sample tend to perceive more advantages than disadvantages in dog ownership. …”
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Using Deep Learning to Identify High-Risk Patients with Heart Failure with Reduced Ejection Fraction by Zhibo Wang, Xin Chen, Xi Tan, Lingfeng Yang, Kartik Kannapur, Justin L. Vincent, Garin N. Kessler, Boshu Ru, Mei Yang

“…An AUC of 0.861 was attained for prediction of 90-day readmission in patients aged 18-64. …”
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