Causal relationship between blood lipids and diabetic kidney disease：a Mendelian randomization study by Wang Hao-hao, Liu Hao-fei, Miao Shao-bo, Jia Run-ke, Ma Ji-wei

“…The analysis results showed that the genetic prediction of TG （OR=1.428， 95%CI： 1.150-1.774， P=0.001） and TC （OR=0.683， 95%CI： 0.486-0.960， P=0.028） had a causal relationship with DKD. …”
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Indoor Black Carbon Concentrations and their Sources in Residential Environments: Validation of an Input-adaptive Proxy Model by Jiangyue Zhao, Pak Lun Fung, Martha Arbayani Zaidan, Birgit Wehner, Kay Weinhold, Alfred Wiedensohler, Tareq Hussein

“…This proxy model can predict indoor eBC concentrations based on existing indoor databases or in cases where direct measurements of indoor eBC concentrations are not available. …”
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Moral grounds and social norms of safe prosocial behaviour of young people by P. A. Kislyakov, E. A. Shmeleva, M. O. Aleksandrovich

“…The identified relationships allow for the prediction of the level of readiness of the individual to help and take care of the well-being of another person and society, depending on moral norms and norms of prosocial behaviour. …”
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Evaluating the Performance of Aluminum Oxide Nanoparticle-Modified Asphalt Binder and Modelling the Viscoelastic Properties by Using Artificial Neural Networks and Support Vector M... by Mustafa Alas, Sani Isah Abba, Shaban Ismael Albrka Ali, Abdur Rahim, Nur Izzi Md. Yusoff

“…Moreover, based on the statistical performance indicator, coefficient of determination (R2), it was observed that the ANN models for predicting G∗ and δ achieved a prediction accuracy of 0.989 and 0.911 while SVM models were able to achieve 0.984 and 0.929, respectively, considering the training datasets. …”
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Rapid estimation method of lithium battery state of health based on novel health feature by DONG Xiaohong, DONG Jinbo, WANG Mingshen, ZENG Fei, PAN Yi

“…The experimental results show that the proposed method and novel health feature can greatly reduce the calculation volume, and can achieve fast estimation of lithium battery SOH while ensuring prediction accuracy.…”
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Association of serum neurofilament light chain with cognitive impairment: findings from the National Health and Nutrition Examination Survey by Tianjiao Meng, Qinwen Fei, Tian Lv, Shiqin Chen

“…The least absolute shrinkage and selection operator (LASSO) regression was applied for identifying key cognitive impairment factors, which was then included in the establishment of a risk prediction nomogram model, with the receiver operating characteristic (ROC) curve being built to evaluate its discriminatory power for cognitive impairment.ResultsIt was found that there is a strong positive correlation between serum NfL levels and both low total cognitive function (total-CF) OR: 1.028 (95%CI = 1.015–1.041 p < 0.001) and low Digit Symbol Substitution Test (DSST) OR: 1.026 (95%CI = 1.003–1.050, p = 0.027). …”
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Nonlinear Structural Fusion for Multiplex Network by Nianwen Ning, Feiyu Long, Chunchun Wang, Youjie Zhang, Yilin Yang, Bin Wu

“…Experiments on real-world networks demonstrate that MNSF outperforms the state-of-the-art methods in tasks link prediction and shared community detection.…”
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Role of drug-induced sleep endoscopy in evaluation of positional vs non-positional OSA by Ming-Chin Lan, Stanley Yung-Chuan Liu, Ming-Ying Lan, Yun-Chen Huang, Tung-Tsun Huang, Yen-Bin Hsu

“…Multivariate analysis revealed that oropharyngeal lateral wall collapse (OR = 1.90, p = 0.027) was the only anatomical factor significantly predicted non-positional dependency in OSA patients. …”
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Prevalence of perinatal post-traumatic stress disorder (PTSD) in low-income and middle-income countries: a systematic review and meta-analysis by Charles Opondo, Holly Jenkins, Fiona Alderdice, Gracia Fellmeth, Zoe Daskalopoulou

“…Pooled prevalence estimates were calculated with 95% CIs and prediction intervals (PI) using random-effects meta-analyses. …”
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A high-throughput ResNet CNN approach for automated grapevine leaf hair quantification by Nagarjun Malagol, Tanuj Rao, Anna Werner, Reinhard Töpfer, Ludger Hausmann

“…This approach achieved an overall model prediction accuracy of 95.41%. As final validation, 10,120 input images from a segregating F1 biparental population were used to evaluate the algorithm performance. …”
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Simple methods for estimating the maximum 24-hour urinary potassium excretion in kidney failure without replacement therapy patients by Danyang Zhang, Yukun Wang, Shimin Jiang, Wenge Li

“…We developed and validated two new models to assess the upper limit of dietary potassium consumption in this high-risk cohort, using the maximum 24-hour urinary potassium excretion as a proxy.Methods The data of 145 kidney failure without replacement therapy patients with hyperkalemia was gathered. The prediction models were developed using multilayer perceptron and stepwise multiple linear regression utilizing a stochastic sample of 102 (70%) patients. …”
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SACNN‐IDS: A self‐attention convolutional neural network for intrusion detection in industrial internet of things by Mimonah Al Qathrady, Safi Ullah, Mohammed S. Alshehri, Jawad Ahmad, Sultan Almakdi, Samar M. Alqhtani, Muazzam A. Khan, Baraq Ghaleb

“…The proposed architecture has a self‐attention layer to calculate the input attention and convolutional neural network (CNN) layers to process the assigned attention features for prediction. The performance evaluation of the proposed SACNN architecture has been done with the Edge‐IIoTset and X‐IIoTID datasets. …”
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Rainfall-Groundwater Table Fluctuations Impact on Root Zone Soil Water Simulated in Upflow for Crop Production Planning in Obio Akpa Watershed, Nigeria by Ikpe Udom, Samuel Nta, Godwin Usoh, Matthew Kamai, Boniface Ugwuishiwu

“… The non-predictability of rainfall-groundwater table relationships in the ungauged Obio Akpa watershed has rubbished remedial measures against seasonal crop losses.    …”
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Machine learning-based interpretation of non-contrast feature tracking strain analysis and T1/T2 mapping for assessing myocardial viability by Amir GhaffariJolfayi, Alireza Salmanipour, Kiyan Heshmat-Ghahdarijani, MohammadHossein MozafaryBazargany, Amir Azimi, Pirouz Pirouzi, Ali Mohammadzadeh

“…The integration of T1/T2 mapping and strain analysis significantly enhanced myocardial viability prediction, positioning these non-contrast techniques as promising alternatives to LGE-CMR. …”
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Study of the coefficient of friction and forward slip in cold rolling of stainless steel AISI 430 in Sendzimir mills by André C.M. Miranda, Carlos L. Neto, Wilian da S. Labiapari, Pedro Henrique R. Pereira, Paulo R. Cetlin, Ariel R. Arias

“…Forward slip is also an important variable to predict skidding and an investigation of forward slip behavior is proposed in this paper. …”
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Short-term solar irradiance forecasting using deep learning models by Syed Saad Ahmed, Chang Wei Bin, Nisar Humaira, Riaz Hannan Naseem, Yeap Kim Ho, Zaber Nursaida Mohamad

“…In this paper, short-term solar forecasting models are proposed using deep learning to reliably predict the amount of solar irradiance for optimal power generation. …”
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A recurrence model for non-puerperal mastitis patients based on machine learning. by Gaosha Li, Qian Yu, Feng Dong, Zhaoxia Wu, Xijing Fan, Lingling Zhang, Ying Yu

“…<h4>Results</h4>The logistic regression model emerged as the optimal model for predicting recurrence of NPM with machine learning, primarily utilizing three variables: FIB, bacterial infection, and CD4+ T cell count. …”
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In silico identification of chilli genome encoded MicroRNAs targeting the 16S rRNA and secA genes of “Candidatus phytoplasma trifolii” by Vineeta Pandey, Aarshi Srivastava, Ramwant Gupta, Haitham E. M. Zaki, Haitham E. M. Zaki, Muhammad Shafiq Shahid, Rajarshi K. Gaur

“…P. trifolii”) through plant miRNA prediction algorithms. Mature chilli miRNAs (CA-miRNAs) were collected and used to hybridise the 16S rRNA and secA genes. …”
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Uncertainty analysis of linear and non-linear regression models in the modeling of water quality in the Caspian Sea basin: Application of Monte-Carlo method by Sahar Heidari Masteali, Mahmoud Bayat, Pete Bettinger, Mansour Ghorbanpour

“…The assessment of uncertainty in water quality prediction models is crucial for understanding the reliability of these models. …”
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Subseasonal forecasts of heat waves in West African cities by C. G. Ngoungue Langue, C. G. Ngoungue Langue, C. Lavaysse, C. Lavaysse, C. Flamant

“…In this perspective, the present study addresses the predictability of heat waves at subseasonal timescales in West African cities over the period 2001–2020. …”
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