A BERT-Based Classification Model: The Case of Russian Fairy Tales by Валерий Дмитриевич Соловьев, Марина Ивановна Солнышкина, Andrey Ten, Николай Аркадиевич Прокопьев

“…Evaluation of the models performance is conducted based on the loss function, prediction accuracy, precision and recall. Results: We validated BERT’s potential for Russian text classification and ability to enhance the performance and quality of the existing NLP models. …”
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Construction and application of a digital twin model for multi-objectiveoptimization of intelligent tape conveyor system by Wei CHEN, Jingzhao LI, Qing SHI, Jichao LIU, Huashun LI

“…In this conceptual model, an Online Sequential Extreme Learning Machine (OS-ELM) is applied within the virtual component to construct a near real-time model predicting sweeping force, using physical feedback data as input parameters. …”
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Activation of three targets by a TAL effector confers susceptibility to bacterial blight of cotton by Brendan W. Mormile, Yan Yan, Taran Bauer, Li Wang, Rachel C. Rivero, Sara C. D. Carpenter, Catherine Danmaigona Clement, Kevin L. Cox, Lin Zhang, Xiyu Ma, Terry A. Wheeler, Jane K. Dever, Ping He, Adam J. Bogdanove, Libo Shan

“…Transcriptome profiling coupled with TALE-binding element prediction identify a pectin lyase gene as an additional Tal7b target, quantitatively contributing to Xcm virulence alongside GhSWEET14a/b. …”
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Assessing how pro-environmental perspectives impact participation in rooftop organic agriculture in urban neighborhoods by Mohammad Enamul Hoque, Abdullah Al Mamun, Perengki Susanto

“…Strong intentions could promote and predict the adoption of organic food production in rooftop gardens. …”
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Towards a decision support system for post bariatric hypoglycaemia: development of forecasting algorithms in unrestricted daily-life conditions by Francesco Prendin, Olivia Streicher, Giacomo Cappon, Eva Rolfes, David Herzig, Lia Bally, Andrea Facchinetti

“…In this study, the run-to-run rAR yielded most satisfactory results with accurate PBH event predictive capacity and few false alarms, thereby indicating potential for the development of DSS for people with PBH.…”
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Deep-Learning-Driven Insights into Nitrogen Leaching for Sustainable Land Use and Agricultural Practices by Caixia Hu, Jie Li, Yaxu Pang, Lan Luo, Fang Liu, Wenhao Wu, Yan Xu, Houyu Li, Bingcang Tan, Guilong Zhang

“…However, the performance improved significantly after integrating the four models with Bayesian optimization (all models had R² > 0.56), which realized quantitative prediction capabilities for nitrate leaching loss concentrations. …”
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Efficiency and heat transport processes of low-temperature aquifer thermal energy storage systems: new insights from global sensitivity analyses by Luka Tas, Niels Hartog, Martin Bloemendal, David Simpson, Tanguy Robert, Robin Thibaut, Le Zhang, Thomas Hermans

“…Insensitive parameters can be fixed to average values without compromising on prediction accuracy. It also demonstrates the insignificance of seasonal soil temperature fluctuations on storage in unconfined shallow aquifers and it clarifies the thermal energy exchange dynamics directly above the storage volume. …”
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Structure and dynamics analysis of brain functional hypernetworks based on the null models by Chen Cheng, Yao Li, Chunyan Wang, Yanli Yang, Hao Guo

“…Brain functional hypernetworks that can characterize the complex and multivariate interactions among multiple brain regions have been widely used in the diagnosis and prediction of brain diseases. However, there are few studies on the structure and dynamics of brain functional hypernetworks. …”
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Deciphering the multifaceted mechanism of Shuang Huang Lian in treating upper respiratory tract infections: A metabolomics-based network pharmacology approach by Gang Xu, Akshay Suresh Patil, Ruhan Wei, Dan Liu, Aimin Zhou, Yan Xu

“…Key cheminformatics and bioinformatics platforms and databases, including ADMETlab, SEA, PASS, Super-Pred, SwissTargetPrediction, PharmMapper, and GeneCards, were used to predict the drug-like properties of active SHL components and identify protein targets shared between the active SHL components and the URTI-related disease genes. …”
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cfDNA as a surrogate marker for COVID-19 severity in patients with influenza-like symptoms with and without SARS-CoV-2 infections in general practice: a study protocol for a prospe... by Dorothea Dehnen, Elmo Neuberger, Jürgen in der Schmitten, Ekaterini Giagkou, Perikles Simon, Suzan Botzenhardt

“…Laboratory values of SARS-CoV-2 patients such as lymphocyte counts or C-reactive protein (CRP) do not allow a prediction of the actual course of the disease. To identify a possible predictive marker for the differentiation and prognosis of illness with influenza-like symptoms with and without SARS-CoV-2 infections in general practice, we will analyse the concentrations of cell-free DNA (cfDNA) levels, laboratory and clinical parameters, temperature, oxygen saturation, breathing rate and concomitant symptoms in patients with flu-like symptoms with and without a SARS-CoV-2 infection.Methods and analysis This is a single-centre, two-arm, parallel longitudinal cohort study with a total of 44 patients. 22 patients with flu-like symptoms without a SARS-CoV-2 infection and 22 patients with flu-like symptoms with a SARS-CoV-2 infection will be recruited. …”
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Multifield Coupling Mechanism of Unloading Deformation and Fracture of Composite Coal-Rock by Zhen Yang, Yan Li, Xin Li, Jiayu Zhuang, Hao Li, Xue Wang, Yuning Wang

“…The multiphysics coupling model is used to study the characteristics of coal and rock unloading under complex conditions, providing a theoretical basis and new method for the prediction and forecast of coal and rock mining dynamic disasters.…”
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Konsep Decision Tree Reptree untuk Melakukan Optimasi Rule dalam Fuzzy Inference System Tsukamoto by Tundo Tundo, Shofwatul 'Uyun

“…Proof carried out in this research is one of them by using a comparison of decision trees J48 and Random Tree with the aim to find out the optimization of rules formed using the Tsukamoto system's fuzzy inference method, after calculating that the REPTree decision tree has a more average Forecasting Error Rate (AFER) error tree small of 23.17% with a truth value of 76.83%, while J48 has an error rate of 24.96%, with a truth value of 75.04%, while Random Tree has an error rate of 36.51%, with a truth value of 63, 49% in the case of prediction of palm oil production at PT Tapiana Nadenggan. …”
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Analysis of borehole strain anomalies before the 2017 Jiuzhaigou <i>M</i>_s&thinsp;7.0 earthquake based on a graph neural network by C. Li, C. Li, C. Qin, C. Qin, J. Zhang, J. Zhang, Y. Duan, Y. Duan, C. Chi, C. Chi

“…We obtained 1-year data from four stations near the epicenter as the training dataset and data from 1 January to 10 August 2017 as the test dataset. For the prediction results of the variational mode decomposition–graph WaveNet model, the anomalous days were extracted using statistical methods, and the results of anomalous-day accumulation at multiple stations showed that an increase in the number of anomalous days occurred 15–32 d before the earthquake. …”
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Risk of Dementia and Its Associated Factors Among the Patients With Coronary Artery Disease Attending a Tertiary Cardiac Hospital of Dhaka City: A Cross‐Sectional Study by Fardina Rahman Omi, Lingkan Barua, Palash Chandra Banik, Syed Mosfiqur Rahman, Mithila Faruque

“…Furthermore, no dementia risk prediction tool has yet been applied to estimate the risk in any population in Bangladesh. …”
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Transcranial brain atlas based on photon measurement density function in a triple-parameter standard channel space by Lijiang Wei, Yang Zhao, Farui Liu, Yuanyuan Chen, Yilong Xu, Zheng Li, Chaozhe Zhu

“…The PMDF-TBA contains group-averaged sensitivities of channels to gray matter and brain regions as defined in 3 atlases: Brodmann, AAL2, and LPBA40. We evaluated the prediction ability of PMDF-TBA for sensitivity of unseen individuals. …”
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A two-stage deep learning-based hybrid model for daily wind speed forecasting by Shahab S. Band, Rasoul Ameri, Sultan Noman Qasem, Saeid Mehdizadeh, Brij B. Gupta, Hao-Ting Pai, Danyal Shahmirzadi, Ely Salwana, Amir Mosavi

“…This study finds that the novel hybrid models exhibit superior performance to standalone GB and LSTM models, opening the pathway to alternative WS prediction techniques.…”
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Exploring <i>RNF213</i> in Ischemic Stroke and Moyamoya Disease: From Cellular Models to Clinical Insights by Benjamin Y. Q. Tan, Charlene H. P. Kok, Megan B. J. Ng, Shaun Loong, Eric Jou, Leonard L. L. Yeo, Weiping Han, Christopher D. Anderson, Chiea Chuen Khor, Poh San Lai

“…Additionally, we address the gene’s implications for disease prediction, risk assessment, and cascade screening. …”
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Metastable Helium Lidar for Thermosphere and Lower Exosphere Measurements: Instrument Description and Initial Results by Ruocan Zhao, Zhenwei Liu, Xianghui Xue, Hang Zhou, Zhaofeng Wang, Yingyu Liu, Jiangtao Li, Dongsong Sun, Jiaxin Lan, Tingdi Chen, Dongfeng Zhao, Xiankang Dou

“…This is a promising tool to help study the coupling of neutral and ionized atmosphere in this height range and further providing observation basis for space weather prediction.…”
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Risk Factors Associated with Leishmaniasis in the Most Affected Provinces by Leishmania infantum in Morocco by Maryam Hakkour, Asmae Hmamouch, Mohamed Mahmoud El Alem, Abdelhakim Bouyahya, Abdelaali Balahbib, Abdelhak EL Khazraji, Hajiba Fellah, Abderrahim Sadak, Faiza Sebti

“…Our study revealed that the risk factor associated with cutaneous and visceral leishmaniasis in northern Morocco could help in the establishment of a prediction program.…”
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Downregulation of LPAR1 Promotes Invasive Behavior in Papillary Thyroid Carcinoma Cells by Zahra Bokaii Hosseini, Fatemeh Rajabi, Reza Morovatshoar, Mahshad Ashrafpour, Panteha Behboodi, Dorsa Zareie, Mohammad Natami

“…Additionally, miR-221-5p was predicted to target LPAR1 in PTC. Furthermore, our experimental data demonstrated that LPAR1 was under-expressed in the PTC cell line compared to the nonmalignant one ( P  < .01). …”
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