Method for predicting the reliability of applied software at the early stages of their development by S. M. Borovikov, S. S. Dick, N. K. Fomenko

“…The model is based on generalized statistical data taken from domestic and foreign printing on the expected number of errors in the developed application software, depending on the number of lines of computer program code, the duration of its testing, the qualifications and experience of testers. …”
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Efficient spectrally-resolved electron transport for thermal property prediction by Jackson R. Harter, Shuxiang Zhou, Sebastian Schunert, Andrea Jokisaari, P. Alex Greaney

“…Predicting thermal conductivity from the transport of electrons is a complex challenge which must be addressed for the design and production of nano- and microscale devices. …”
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Identifying long-term conditions in New Zealand general practice using structured and unstructured data: a cross-sectional study by Vanessa Selak, Katrina Poppe, Sue Wells, Yeunhyang Catherine Choi, Allan Ronald Moffitt, Claris Yee Seung Chung, Jane Ullmer

“…Programmatic text classification was developed and assessed against gold-standard clinician ratings, using sensitivity, specificity, positive predictive value (PPV) and F1-score.Results A quarter of general practitioner classifications contained either unrecognised Read codes or consisted of free-text only. …”
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Identification and characterization of new structured RNA classes in plants by Maximilian Sack, Maren Reinhardt, Rica Burgardt, Philipp Berg, Julia Bauer, Andreas Wachter, Zasha Weinberg

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Long non-coding RNA Malat1 modulates CXCR4 expression to regulate the interaction between induced neural stem cells and microglia following closed head injury by Qin Dong, Pengyu Chen, Wenqiao Qiu, Zhijun Yang, Yanteng Li, Yuhui Zhou, Lili Guo, Dan Zou, Ruxiang Xu, Mou Gao

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Prediction of the Radiative Properties of Triangular-Grating Surfaces from Electromagnetic Theory by Taoufik Ghabara

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A general two-group constants estimator for 17x17 PWR assembly configurations using artificial neural networks by Gökhan Pediz, M. Alim Kırışık

“…In this study, a preliminary general two-group constants predictor using artificial neural networks (ANNs) for pressurized water reactor (PWR) based assembly designs is established. …”
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Predicted thresholds for RMP ELM suppression access in double-null configurations by P. Lunia, A.V. Dudkovskaia, N.C. Logan, N. Leuthold, B.C. Lyons, C. Paz-Soldan, M.W. Shafer

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Feature selection for helpfulness prediction of online product reviews: An empirical study. by Jiahua Du, Jia Rong, Sandra Michalska, Hua Wang, Yanchun Zhang

“…Also, the current works tend to concentrate on domain- and/or platform-dependent feature curation, lacking wider generalization. Moreover, the issue of result comparability and reproducibility occurs due to frequent data and source code unavailability. …”
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Implementation and Validation of Online Tidal Analysis by Abdul Basith, Ghani Yanuargo Dondiarta

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Characteristics of motor resonance predict the pattern of flash-lag effects for biological motion. by Klaus Kessler, Lucy Gordon, Kari Cessford, Martin Lages

“…Our results suggest that predictive coding within the sensorimotor system alone cannot explain the FLE. …”
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Expression Significance and Relationship of Serum miR-542-3p and lncRNA TUG1 in STBI Patients and Their Predictive Value for Prognosis by Zhang X, Chen D, Zhu C, Zhou X, Liu H, Zhu G

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Comparison of DKRZ Database and LARS-WG Model in Three Parameters of Minimum Temperature, Maximum Temperature and Precipitation (Case study: Qazvin plain) by Fatemeh Borzoo, Hadi Ramezani Etedali, Abbas Kaviani

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Identifying those at risk: predicting patient factors associated with worse EGS outcomes by Adil H Haider, Maryam Pyar Ali Lakhdir, Zainab Samad, Noreen Afzal, Asma Altaf Hussain Merchant, Komal Abdul Rahim, Namra Qadeer Shaikh, Saad bin Zafar Mahmood, Saqib Kamran Bakhshi, Mushyada Ali

“…Background Comorbidity has a detrimental impact on Emergency General Surgery (EGS) outcomes. In lesser-developed countries with inconsistent documentation of comorbid conditions, undiagnosed and progressively worsening comorbidities can worsen EGS outcomes. …”
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A Multiscale CNN-Based Intrinsic Permeability Prediction in Deformable Porous Media by Yousef Heider, Fadi Aldakheel, Wolfgang Ehlers

“…The methodology involves four steps: (1) constructing a dataset of CT images from Bentheim sandstone at varying volumetric strain levels; (2) conducting pore-scale flow simulations using the lattice Boltzmann method (LBM) to obtain permeability data; (3) training the CNN model with processed CT images as inputs and permeability tensors as outputs; and (4) employing techniques like data augmentation to enhance model generalization. Examples demonstrate the CNN’s ability to accurately predict the permeability tensor in connection with the deformation state through the porosity parameter. …”
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Harnessing pre-trained models for accurate prediction of protein-ligand binding affinity by Jiashan Li, Xinqi Gong

“…Results Our model demonstrates a significantly higher correlation coefficient in binding affinity predictions. Extensive evaluation on the PDBBind v2019 refined set, CASF, and Merck FEP benchmarks confirms the model’s robustness and strong generalization across diverse datasets. …”
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Lactate-related lncRNAs assessment model predicts the prognosis of pancreatic ductal adenocarcinoma by Jing Sun, Tao Zhang, Shuai Zhu

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Using confidence, decision time, and confidence entropy to predict accuracy for online and real eyewitnesses by Adele Quigley-McBride, Rachel Leigh Greenspan

“…In general, including multiple reflector variables better predicted decisions than any reflector variable alone, but there were diminishing returns associated with each additional variable. …”
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A compositional model for effort‐aware Just‐In‐Time defect prediction on android apps by Kunsong Zhao, Zhou Xu, Meng Yan, Lei Xue, Wei Li, Gemma Catolino

“…To meet the new requirements from users, the apps encounter frequent updates, which involves a large quantity of code commits. Previous studies proposed to apply Just‐in‐Time (JIT) defect prediction for apps to timely identify whether the new code commits can introduce defects into apps, aiming to assure their quality. …”
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Fungi-Kcr: a language model for predicting lysine crotonylation in pathogenic fungal proteins by Yong-Zi Chen, Yong-Zi Chen, Xiaofeng Wang, Zhuo-Zhi Wang, Haixin Li, Haixin Li

“…Moreover, our results indicate that a general predictive model performs better than species-specific models. …”
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