The optimization path of agricultural industry structure and intelligent transformation by deep learning by Xingchen Pan, Jinyu Chen

“…The method also significantly surpasses traditional algorithms in crop disease identification accuracy, climate change prediction precision, and the quality of synthetic data generation. …”
Get full text

Weighted mixed regression localization method based on three-dimensional Voronoi diagram division by Fenfang LI, Xiaochao DANG, Zhanjun HAO

“…With the development of the wireless communication technology and sensing technology, various technologies based on wireless sensor networks are applied.These technologies are widely used in the fields of intelligent agriculture, intelligent transportation, fire rescue and so on.Node localization technology is one of the basic technologies of wireless sensor networks.Location information is a part of the sensing data, which determines the specific measures to be taken in the next step.Due to the complexity of the three-dimensional (3D) space localization environment, the application of the plane positioning method in 3D space will have some limitations.Aiming at above problems, the weighted hybrid regression location algorithm WMR-SKR based on a 3D Voronoi diagram was studied.The localization algorithm was divided into two stages: offline training and online testing.The 3D space was divided into Voronoi diagrams according to the anchor nodes in the network.In the offline training stage, the sequence composed of the coordinates of the anchor nodes and Voronoi cell vertices was used as the training set for training.In the online test stage, the coordinates of unknown nodes in the network were predicted through the trained localization model.Simulation results show that the WMR-SKR algorithm can effectively reduce the node localization error and improve the node localization speed in 3D space.…”
Get full text

Applicability Analysis of Log Calculation Method for Organic Matter Maturity of Changning Shale Gas Reservoir in Southern Sichuan Basin by QIU Dingguo, YAN Jianping, GUO Wei, LIAO Maojie, QIU Xiaoxue, HUANG Yi

“…The color combination of Rt-AC logging curve is “blue + dark red” mode.③CatBoost algorithm selected GR, AC, CNL and Rt curves as input variables, and the correlation coefficients between the calculated RO values and the measured RO values of maturity wells Ⅰ and Ⅱ were all more than 0.95, which achieved a good prediction effect of organic matter maturity. …”
Get full text

Forecasting Urban Sprawl Dynamics in Islamabad: A Neural Network Approach by Saddam Sarwar, Hafiz Usman Ahmed Khan, Falin Wu, Sarah Hasan, Muhammad Zohaib, Mahzabin Abbasi, Tianyang Hu

“…Utilizing a land change modeler (LCM), forecasts of the future conditions in 2025, 2030, and 2035 are predicted. The artificial neural network (ANN) model embedded in IDRISI software 18.0v based on a well-defined backpropagation (BP) algorithm was used to simulate future urban sprawl considering the historical pattern for 2015–2020. …”
Get full text

A Coupled Least Absolute Shrinkage and Selection Operator–Backpropagation Model for Estimating Evapotranspiration in Xizang Plateau Irrigation Districts with Reduced Meteorological... by Qiang Meng, Jingxia Liu, Fengrui Li, Peng Chen, Junzeng Xu, Yawei Li, Tangzhe Nie, Yu Han

“…Short-term ET_O predictions for the three districts were also conducted using the mean-generating function optimal subset regression algorithm. …”
Get full text

Case-control study combined with machine learning techniques to identify key genetic variations in GSK3B that affect susceptibility to diabetic kidney diseases by Jinfang Song, Yi Xu, Liu Xu, Tingting Yang, Ya Chen, Changjiang Ying, Qian Lu, Tao Wang, Xiaoxing Yin

“…A case-control study was conducted to evaluate the predictive effect of GSK3B genetic polymorphisms on the susceptibility to DKD, with the aim of providing a theoretical basis and laboratory rationale for the prediction of the risk of developing DKD in patients with type 2 diabetes mellitus (T2DM). …”
Get full text

Increased risk of COVID-19-related admissions in patients with active solid organ cancer in the West Midlands region of the UK: a retrospective cohort study by Peter Nightingale, Fahad Mahmood, Akinfemi Akingboye, Nabeel Amiruddin, Olorunseun O Ogunwobi

“…We aim to quantify the risk of hospitalisation in patients with active cancer and use a machine learning algorithm (MLA) and traditional statistics to predict clinical outcomes and mortality.Design Retrospective cohort study.Setting A single UK district general hospital.Participants Data on total hospital admissions between March 2018 and June 2020, all active cancer diagnoses between March 2019 and June 2020 and clinical parameters of COVID-19-positive admissions between March 2020 and June 2020 were collected. 526 COVID-19 admissions without an active cancer diagnosis were compared with 87 COVID-19 admissions with an active cancer diagnosis.Primary and secondary outcome measures 30-day and 90-day post-COVID-19 survival.Results In total, 613 patients were enrolled with male to female ratio of 1:6 and median age of 77 years. …”
Get full text

Identification of the intestinal type gastric adenocarcinoma transcriptomic markers using bioinformatic and gene expression analysis by V. V. Volkomorov, E. S. Grigor’eva, G. S. Krasnov, N. V. Litvyakov, N. A. Lisitsyn, M. I. Voevoda, A. V. Belkovets, S. G. Afanas’ev, N. V. Cherdyntseva

“…These markers can be used for early tumor diagnosis and prognosis as well as for prediction of therapeutic response, estimation of tumor volume or to assess disease recurrence through monitoring. …”
Get full text

Vis/NIR Spectroscopy and Vis/NIR Hyperspectral Imaging for Non-Destructive Monitoring of Apricot Fruit Internal Quality with Machine Learning by Tiziana Amoriello, Roberto Ciorba, Gaia Ruggiero, Francesca Masciola, Daniela Scutaru, Roberto Ciccoritti

“…In recent years, machine learning techniques, such as artificial neural networks (ANNs), have been successfully applied to more efficiently extract valuable information from spectral data and to accurately predict quality traits. In this study, prediction models were developed based on a multilayer perceptron artificial neural network (ANN-MLP) combined with the Levenberg–Marquardt learning algorithm. …”
Get full text

Cetacean feeding modelling using machine learning: A case study of the Central-Eastern Mediterranean Sea by Carla Cherubini, Giulia Cipriano, Leonardo Saccotelli, Giovanni Dimauro, Giovanni Coppini, Roberto Carlucci, Carmelo Fanizza, Rosalia Maglietta

“…Behavioural data from April 2016 to October 2023, coupled with 20 environmental variables from Copernicus Marine Service and EMODnet-bathymetry datasets, were used to build Cetacean Feeding Models (CFMs) for the target species using Random Forest and RUSBoost algorithms. Multiple subsets of environmental predictors—physiographic, physical, inorganic, and bio-chemical—were employed to develop and evaluate ML models tailored to feeding prediction. …”
Get full text

Quantifying Uncertainties in Solar Wind Forecasting due to Incomplete Solar Magnetic Field Information by Stephan G. Heinemann, Jens Pomoell, Ronald M. Caplan, Mathew J. Owens, Shaela Jones, Lisa Upton, Bibhuti Kumar Jha, Charles N. Arge

“…Solar wind forecasting plays a crucial role in space weather prediction, yet significant uncertainties persist duet to incomplete magnetic field observations of the Sun. …”
Get full text

Construction and validation of HBV-ACLF bacterial infection diagnosis model based on machine learning by Neng Wang, Shuai Tao, Liang Chen

“…We utilized six machine learning algorithms—Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Logistic Regression (LR), K-Nearest Neighbors (KNN), Random Forest (RF), and Decision Tree (DT)—to construct predictive models. …”
Get full text

Low-Carbon Slag Concrete Design Optimization Method Considering the Coupled Effects of Formwork Stripping, Strength Progress, and Carbonation Durability by Li-Na Zhang, Seung-Jun Kwon, Xiao-Yong Wang

“…Through the formulation of constraints for optimization using a genetic algorithm, the appropriate mix proportions for each design scenario are obtained. …”
Get full text

Machine learning-enhanced discovery of tsRNA-mRNA regulatory networks: identifying novel diagnostic biomarkers and therapeutic targets in breast cancer by Zhongling Ma, Rui Wang, Ming Yuan, Bo Wang, Li Li, Tianfu Zhao, Xinhan Zhao

“…Random forest algorithm was employed to develop a diagnostic model. …”
Get full text

Assessment of the Maize Crop Water Stress Index (CWSI) Using Drone-Acquired Data Across Different Phenological Stages by Mpho Kapari, Mbulisi Sibanda, James Magidi, Tafadzwanashe Mabhaudhi, Sylvester Mpandeli, Luxon Nhamo

“…This study used a unmanned aerial vehicle (UAV) to remotely collect data, to use in combination with the random forest regression algorithm to detect the maize CWSI in smallholder croplands. …”
Get full text

Relationship of transforming growth factor β1 with diabetic retinopathy in type 2 diabetes by A.S. Hudz, V.A. Serhiyenko, I.V. Kudryl, V.G. Guryanov, M.I. Kovtun, S.V. Ziablitsev

“…A three-factor classification model was created on the identified features, which included a system of equations that predicted PDR with 100% accuracy. The overall prediction accuracy of the model was 88.2 % (95% CI 80.4–93.8 %). …”
Get full text

Evaluation of four clinical decision rules in children with minor head trauma: NEXUS II, PECARN, CHALICE, and CATCH by Majid Zamani, Farhad Heydari, Farzin Feyzollahi, Mehrdad Esmaillian, Amir Bahador Boroumand

“…Background: Clinical decision rules could potentially help emergency department (ED) trauma triage, allowing clinicians to prioritize treatment for the most severely injured patients.Objectives: This study evaluated and compared the diagnostic accuracy of the National Emergency X-radiography Utilization Study II (NEXUS II), the Pediatric Emergency Care Applied Research Network (PECARN), the Canadian Assessment of Tomography for Childhood Head Injury (CATCH), and the Children’s Head Injury Algorithm for the Prediction of Important Clinical Events (CHALICE) in identifying intracranial injury (ICI) in children with minor head trauma.Methods: This prospective, cross-sectional, descriptive-comparative study was conducted on children with mild head trauma who presented to the ED. …”
Get full text

H-NMR metabolomics identifies three distinct metabolic profiles differentially associated with cardiometabolic risk in patients with obesity in the Di@bet.es cohort by Enrique Ozcariz, Montse Guardiola, Núria Amigó, Sergio Valdés, Wasima Oualla-Bachiri, Pere Rehues, Gemma Rojo-Martinez, Josep Ribalta

“…Materials and methods Serum samples of a subset of the Di@bet.es cohort consisting of 1387 individuals with obesity were analyzed by H-NMR. A K-means algorithm was deployed to define different H-NMR metabolomics-based clusters. …”
Get full text

Reliability evaluation and multi-objective optimization of combustion chamber’s key components of marine engine by Lei Hu, Wentong Wang, Xu Wang, Jianguo Yang, Yonghua Yu, Chunyang Mei

“…Constrained multi-objective optimization of reliability is conducted through contrastive analysis of different optimization algorithms. The research shows that the multi-objective particle swarm optimization algorithm achieves the best performance, the maximum temperatures of the piston, cylinder head, and liner decrease by 3.90 %, 5.66 %, and 6.52 %, the maximum thermo-mechanical coupling stresses reduced by 9.41 %, 7.83 %, and 4.97 % respectively, and creep-fatigue life enhancements reach 3.84 % and 12.67 % for the piston and cylinder head. …”
Get full text

Diagnostic accuracy of an app-guided, self-administered test for influenza among individuals presenting to general practice with influenza-like illness: study protocol by Nigel Stocks, Matthew Thompson, Barry Lutz, Mark Rieder, Monica Zigman Suchsland, Victoria Lyon, Monique Chilver, Philip Su, Shawna Cooper, Chunjong Park, Libby Rose Lavitt, Alex Mariakakis, Shwetak Patel, Chelsey Graham, Cynthia LeRouge

“…Secondary analyses will include accuracy of the enhanced test strip image, accuracy of an automatic test strip reader algorithm and validation of prediction rules for influenza based on self-reported symptoms. …”
Get full text