Triple-effect correction for Cell Painting data with contrastive and domain-adversarial learning by Chengwei Yan, Yu Zhang, Jiuxin Feng, Heyang Hua, Zhihan Ruan, Zhen Li, Siyu Li, Chaoyang Yan, Pingjing Li, Jian Liu, Shengquan Chen

“…However, CP data contains three types of technical effects, referred to as triple effects, including batch effects, gradient-influenced row and column effects (well-position effects). …”
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RNA from LPS-stirnulated macrophages induces the release of tumour necrosis factor-α and interleukin-1 by resident macrophages by R. A. Ribeiro, F. L. De Lucca, C. A. Flores, F. Q. Cunha, S. H. Ferreira

“…The effect of exogenous RNA on many cellular functions has been studied in a variety of eukaryotic cells but there are few reports on macrophages. …”
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Improving fluoroprobe sensor performance through machine learning by D. Lafer, A. Sukenik, T. Zohary, O. Tal

“…Accurate assessment of phytoplankton abundance and community structure is critical for understanding the health and functioning of lake ecosystems. To monitor phytoplankton dynamics efficiently, fluorescence sensors offer rapid and high-throughput estimates of chlorophyll-a concentrations, a widely used proxy for phytoplankton biomass. …”
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Machine Learning-Based Classification and Statistical Analysis of Liver Cancer: A Comprehensive Study of Model Performance and Clinical Significance by Pratyush Kumar MAHARANA, Tapan Kumar BEHERA, Pradeep Kumar NAIK

“…It performs numerous functions that are essential for metabolism, digestion, detoxification, and nutrient storage. …”
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Straightness monitoring of scraper conveyor based on CUDA-accelerated dynamic programming and optimized panoramic stitching by LI Bo, SHI Shouyi, ZHANG Jianjun, XIA Rui, WANG Xuewen, CUI Weixiu, NI Qiang

“…Kernel functions for energy map computation and seamline optimization were defined, enabling the seamless fusion of the two images along the seamline to complete panoramic stitching. …”
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Snow Leopard and Himalayan Wolf: Food Habits and Prey Selection in the Central Himalayas, Nepal. by Madhu Chetri, Morten Odden, Per Wegge

“…Top carnivores play an important role in maintaining energy flow and functioning of the ecosystem, and a clear understanding of their diets and foraging strategies is essential for developing effective conservation strategies. …”
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Gyro-System for Guidance with Magnetically Suspended Gyroscope, Using Control Laws Based on Dynamic Inversion by Romulus Lungu, Constantin-Adrian Mihai, Alexandru-Nicolae Tudosie

“…For this purpose, a differential geometry method, based on the use of the output vector’s gradient with respect to the nonlinear state functions, i.e., based on Lie derivatives, is used. …”
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Study of the Stress State of Solid Cylinders with Inhomogeneous Structure Under Various Boundary Conditions at the Ends by Oleksandr Ya. Grygorenko, Liliia S. Rozhok, Nataliia P. Boreiko, Lesia V. Kharytonova

“…The solution of the problem is based on the application of the method of spline-approximation of functions in the direction of the longitudinal coordinate and the numerical method of discrete orthogonalization along the radial coordinate. …”

Intervention of machine learning in bladder cancer research using multi-omics datasets: systematic review on biomarker identification by Blessy Kiruba, P. S. Athul Narayan, Badhari Raj, S. Rohieth Raj, Sam George Mathew, Sudhakaran Sajitha Lulu, Vino Sundararajan

“…Integrated models combining computational techniques with large multi-omics datasets have gained significant attention, enabling the identification of significant BC biomarkers that include genes coding for diverse cellular functions, differentially expressed genes, proteins, and metabolites. …”
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Partitioning the phenotypic and genetic variances of reaction norms by de Villemereuil, Pierre, Chevin, Luis-Miguel

“…We show that the additive components can be expressed, and further decomposed according to the relative contributions from each parameter, using what we describe as the reaction norm gradient. This allows for a very general framework applicable from the character-state to curve-parameter approaches, including polynomial functions, or arbitrary non-linear models. …”
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Prevalence and characteristics of probable major depression and bipolar disorder within UK biobank: cross-sectional study of 172,751 participants. by Daniel J Smith, Barbara I Nicholl, Breda Cullen, Daniel Martin, Zia Ul-Haq, Jonathan Evans, Jason M R Gill, Beverly Roberts, John Gallacher, Daniel Mackay, Matthew Hotopf, Ian Deary, Nick Craddock, Jill P Pell

“…Outcomes were compared on age, gender, ethnicity, socioeconomic status, educational attainment, functioning, self-reported health status, current depressive symptoms, neuroticism score, smoking status and alcohol use.…”
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Medium-term results of transcatheter implantation of MedLab-CT aortic valve prosthesis by V. V. Bazylev, A. B. Voevodin, A. S. Shalygina

“…The mechanical stability of the valve was tested on the pulse duplicator with a load equivalent to 10 years of functioning in the aortic position. The study included 69 patients who underwent implantation of the MedLab-CT prosthesis. …”
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Method for Evaluating Urban Building Renewal Potential Based on Multimachine Learning Integration: A Case Study of Longgang and Longhua Districts in Shenzhen by Dengkuo Sun, Yuefeng Lu, Yong Qin, Miao Lu, Zhenqi Song, Ziqi Ding

“…With the continuous advancement of urbanization, urban renewal has become a vital means of enhancing urban functionality and improving living environments. Traditional urban renewal research primarily focuses on the macro level, analyzing regions or units, with limited studies targeting individual buildings. …”
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Forecasting Wind Power Generation Using Artificial Neural Network: “Pawan Danawi”—A Case Study from Sri Lanka by Amila T. Peiris, Jeevani Jayasinghe, Upaka Rathnayake

“…This paper develops artificial neural network (ANN) models to forecast wind power generation in “Pawan Danawi”, a functioning wind farm in Sri Lanka. Wind speed, wind direction, and ambient temperature of the area were used as the independent variable matrices of the developed ANN models, while the generated wind power was used as the dependent variable. …”
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Enhancing pipa tuning stability with piezoelectric materials: An adaptive system for real-time performance adjustment. by Kou Yawen

“…The NFIS utilised Gaussian membership functions to categorise sensor inputs into linguistic terms (e.g., "High Voltage," "Medium Temperature"), and a comprehensive rule base of 40 rules was established for adaptive tuning. …”
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Fungal planktonic community related to salinity and temperature in an oligotrophic sea by Ashwag A. Asseri, Alexandra Coello-Camba, Susana Agustí

“…These findings underscore the importance of further research to better understand the role of marine fungi in ecosystem functioning.…”
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The Link between Galaxy Structure Properties and Star Formation in Local Galaxies by Zhimin Zhou, Wenwen Wang

“…Structural components and color properties are examined as functions of deviations from the star formation main sequence (ΔSFR _MS ) and H i gas deficiency (Δ f _H I ). …”
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Optimization of Multi-Source Remote Sensing Soil Salinity Estimation Based on Different Salinization Degrees by Huifang Chen, Jingwei Wu, Chi Xu

“…Specifically, this study integrated in situ hyperspectral data and satellite multispectral data using spectral response functions. Subsequently, machine learning methods such as random forest (RF), extreme gradient boosting (XGBoost), support vector machine (SVM), and multiple linear regression (MLR) were employed, in combination with sensitive spectral indices, to develop a multi-source remote sensing soil salinity estimation model optimized for different salinization degrees (mild or lower salinization vs. moderate or higher salinization). …”
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Application of Open-Source, Low-Code Machine-Learning Library in Python to Diagnose Parkinson's Disease Using Voice Signal Features by Daniel Hilário da Silva, Caio Tonus Ribeiro, Leandro Rodrigues da Silva Souza, Adriano Alves Pereira

“…We leveraged the PyCaret Python library's ML algorithms and functions, which were introduced in this article, to demonstrate their simplicity and effectiveness in dealing with real-world data. …”
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Cheating Detection in Online Exams Using Deep Learning and Machine Learning by Bahaddin Erdem, Murat Karabatak

“…As a result of this study, it has been shown that the application of the most appropriate layer functions and parameter selection that will increase performance can be effective in estimating complex problems and target values that cannot be solved using classical mathematical models. …”
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