Over-activation and dysfunction of platelet-NK cell aggregates in HIV-infected individuals by Meiju Deng, Ruojia Biao, Meiqing Jiang, Jiantao Fu, Hongxin Zhao, Juan Du

Get full text

Machine learning and artificial intelligence in type 2 diabetes prediction: a comprehensive 33-year bibliometric and literature analysis by Mahreen Kiran, Ying Xie, Nasreen Anjum, Graham Ball, Barbara Pierscionek, Duncan Russell

“…Ensemble methods (e.g., Random Forest, Gradient Boosting) and deep learning models (e.g., Convolutional Neural Networks) dominate recent advancements. …”
Get full text

Research on Multiscale Atmospheric Chaos Based on Infrared Remote-Sensing and Reanalysis Data by Zhong Wang, Shengli Sun, Wenjun Xu, Rui Chen, Yijun Ma, Gaorui Liu

“…Among quantitative methods, the Wolf method is used to calculate the Largest Lyapunov Exponents, while the G–P method is used to calculate the correlation dimensions. …”
Get full text

The microbial landscape action on development destructive erysipelas forms by L. A. Vasilevskaya

“…Of our studies indicate that the microflora of the primary cells in destructive forms of the erysipelas changed both quantitatively and qualitatively. Detected microbial pathogens in bacteriological studies of soft tissue exudates allowed installing criteria for forecasting the development of purulent complications. …”
Get full text

Application of K-Nearest Neighbor Classification for Static Webcams Visibility Observation by David Sládek

“…This versatile method holds potential for adoption by meteorological services worldwide.…”
Get full text

Predictive analysis of heart disease using quantum-assisted machine learning by Mehroush Banday, Sherin Zafar, Parul Agarwal, M. Afshar Alam, Siddhartha Sankar Biswas, Imran Hussain, K. M. Abubeker

“…Techniques for QML have the potential to forecast cardiac disease and help in early detection. …”
Get full text

Predicting tennis match outcomes mid-game using machine learning on psychological and physical data by Boyuan Li, Zihui Deng, Gaurav Gupta, Jinger Li, Yixuan Miao

“…The data source is from Wimbledon and US Open games from 2017 to 2022, a total of 1592 games, and utilize 363 games of 2023 to evaluate their forecasting ability. We first obtained weights through information entropy and defined psychological momentum, and then 3 best classifiers, random forest, CatBoost, and Logistic Regression, were detected to assess the features. …”
Get full text

Aphid Species in Citrus Orchards in Crete: Key Vectors of Citrus Tristeza Virus and Automated Monitoring Innovations for Alate Aphids by Matthaios M. Mathioudakis, Kyriaki Varikou, Antonia Karagianni, Panagiota Psirofonia, Nikolaos Tektonidis, Despoina Kapantaidaki, Vasiliki Evangelou, Leonidas Economou, Beata Hasiów-Jaroszewska, Ilyas Potamitis

“…<i>Toxoptera aurantii, Myzus persicae</i>, and <i>A. craccivora</i> were present in low numbers, and <i>A. citricidus</i> was not detected. Due to the absence of CTV detection in aphids and citrus trees from the pilot orchards, a complementary survey was conducted in CTV-infected fields. …”
Get full text

Application of Acoustic Emission Technique in Landslide Monitoring and Early Warning: A Review by Jialing Song, Jiajin Leng, Jian Li, Hui Wei, Shangru Li, Feiyue Wang

“…Traditional monitoring approaches, such as geodetic, geotechnical, and geophysical methods, have limitations in providing early warning capabilities due to their inability to detect precursory subsurface deformations. …”
Get full text

Predictors of severe forms of rotaviral infection in children by K. D. Ermolenko, A. I. Konev, K. Yu. Ermolenko, Yu. V. Lobzin

“…Comparison of the frequency of occurrence of signs in the groups was performed using the Pearson χ2 test and Fisher’s exact method. The forecasting model was developed using discriminant analysis of the statistical package Statistica for Windows.Results. …”
Get full text

Meteorological factors and normalized difference vegetation index drivers of scrub typhus incidence in Shandong Province based on a 16-year time-frequency analysis by Zhisong Ni, Shufen Li, Rui Xi, Kemeng Liang, Sihao Song, Chuanlong Cheng, Hui Zuo, Liang Lu, Xiujun Li

Get full text

Extraction of Significant Wave Height from Spreading First-Order Bragg Peaks of Shipborne High-Frequency Surface Wave Radar with a Single Antenna by Xinbo Zhang, Junhao Xie, Guowei Yao, Chenghui Cao

“…Simulations and field experiments validate the feasibility and accuracy of the method across various scenarios, with a detection range of up to 120 km without auxiliary measurements. …”
Get full text

Bacterial Infections Transmitted by Ticks in Barnaul: Epidemiological and Epizootological Situation, Diagnostic Problems by T. A. Chekanova, A V. Rakov, K. Petremgvdlishvili, A. V. Timonin, N. V. Lukyanenko, T. V. Safyanova, S. V. Shirokostup, N. Ya. Lukyanenko, U. V. Kalinina, I. G. Pashchenko

“…The difficulty of diagnostic of tick-borne rickettsiosis without rash is aggravated by the shortage of reagent kits, primarily for the detection of specific antibodies. The landscape confinement of Dermacentor and Ixodes ticks should take into account when organizing long-term stationary observation sites for monitoring and forecasting the epidemiological and epizootological situation. …”
Get full text

Translation of single channel electro encephalic signals into limb motion by A.B.R. Lara, Oscar E. Ruiz, L.O. Araujo Junior, F.P. Bhering

“…The advantages of this method are: (a) lower hardware expense and (b) lower computing load. …”
Get full text

Solar Flare Prediction Using Long Short-term Memory (LSTM) and Decomposition-LSTM with Sliding Window Pattern Recognition by Zeinab Hassani, Davud Mohammadpur, Hossein Safari

“…A sliding window technique is employed to detect temporal quasi-patterns in both irregular and regularized flare time series. …”
Get full text

Machine learning for predicting earthquake magnitudes in the Central Himalaya by Ram Krishna Tiwari, Rudra Prasad Poudel, Harihar Paudyal

“… Human intervention cannot halt natural disasters like earthquakes, but machine learning application expertise can be utilized to detect patterns in data and increase understanding and predictive power. …”
Get full text

Multiclass Supervised Learning Approach for SAR-COV2 Severity and Scope Prediction: SC2SSP Framework by Shaik Khasim Saheb, B. Narayanan, T.V. Narayana Rao

“…The performance metrics like accuracy, precision, fscore and sensitivity are analyzing the proposed method performance. The proposed SC2SSP approach attains 3.101% and 7.12% higher accuracy; 24.13% and 13.04% higher precision compared with existing methods, like the Detection of COVID-19 from Chest X-ray Images Using Convolutional Neural Networks (Resnet50), Deep learning for automated recognition of covid-19 from chest X-ray images (VGGNet), respectively. …”
Get full text

Online Analysis of Nonlinear Vibration Characteristics of Milling Chatter by WU Shi, WANG Yang-yang, LIU Xian-li, XU Hong, LI Ｒong-yi

“…The characteristics of phase difference and chaotic characteristics can be used as an effective method for the identification of chatter.…”
Get full text

Hybridisation of artificial neural network with particle swarm optimisation for water level prediction by Sarah J. Mohammed, Salah L. Zubaidi

“…This study applies an artificial neural network (ANN) integrated with the particle swarm optimisation algorithm (PSO-ANN) for simulating monthly WL of the Tigris River in Alkut City, Iraq. Data pre-treatment methods are utilised for improving raw data quality and detect the optimal predictors. …”
Get full text

Investigating Safe and Economic Adjustment of Power Balance in Smart Grids Based on Integration of Renewable Energy by Hongyan Zhang

“…The findings indicate that the interruptions in voltage, frequency, and power have been mitigated due to the dynamic simulations using the proposed method. The calculations were predicated on an integration of solar and wind energy, with twenty percent of the energy derived from wind. …”
Get full text