Incorporating phylogenetic metrics of biodiversity to refine Lyme disease risk models by Shannon Summers, Grace Shaw, Andrea Swei

“…Abstract Biodiversity has been linked to reduced disease transmission through the dilution effect process. Traditional ecological measures of biological diversity, such as species richness, are most commonly used to test for the dilution effect. …”
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Crop Model Ensemble Averaging: A Large But Underappreciated Uncertainty Source for Global Crop Yield Projections Under Climate Change by Xiaomeng Yin, Guoyong Leng, Jiali Qiu, Xiaoyong Liao, Shengzhi Huang, Jian Peng

“…Here, we use seven ensemble averaging methods including simple average, regression, Support Vector Regressor, Bayesian model average (BMA), Random Forest (RF), Artificial neural network (ANN) and Long‐short term memory to derive the ensemble mean of eight process‐based crop models for global maize yield projections. …”
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A Novel Magnetic Flux Leakage Method Incorporating TMR Sensors for Detecting Zinc Dross Defects on the Surface of Hot-Dip Galvanized Sheets by Bo Wang, San Zhang, Jie Wang, Liqin Jing, Feilong Mao

“…Zinc dross, the most common surface defect in the hot-dip galvanizing process, significantly affects the sheet’s service performance. …”
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An Intelligent Passenger Flow Prediction Method for Pricing Strategy and Hotel Operations by Tianyang Wang

“…Predicting the future demand of a hotel is a key step in the process of hotel revenue management. Hotel passenger flow prediction plays an important role in guiding the formulation of hotel pricing and operating strategies. …”
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Research progress and considerations for thalassemia gene therapy by GAO Xinjie, LIU Yan, WANG Dawei

“…This article summarizes the marketed products and research progress in clinical trials, aiming to analyze the respective advantages and limitations of these two approaches, and discusses the effectiveness and safety of current gene therapies for β-thalassemia, as well as the future directions for associated technologies, including ex vivo HSC expansion with maintenance of stemness and vector-mediated in vivo gene modification. In terms of clinical translational medicine, this article provides in-depth insights into promising solutions for contemporary challenges confronted in clinical trials, including process development challenges, clinical trial conduct, regulatory approval processes, commercialization and payment systems.…”
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Developmental and Functional Hair Cell-Like Cells Induced by Atoh1 Overexpression in the Adult Mammalian Cochlea In Vitro by Lingyi Kong, Yuan Xin, Fanglu Chi, Jie Chen, Juanmei Yang

“…In this study, we used a three-dimensional cochlear culture system and an adenoviral-mediated delivery vector to overexpress Atoh1 in adult mouse cochleae. …”
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Machine learning detection of Gaussian steering in continuous-variable systems under data imbalance by Jie Guo, Taotao Yan, Jinchuan Hou, Xiaofei Qi, Kan He

“…Rapid detection of Gaussian steering is a significant challenge in quantum information process. In this paper, we employ a combination of machine learning methods, including Support Vector Machine (SVM), Backpropagation Neural Network (BPNN) and Meta-Weight-Net Neural Network (MWN) to speed up the detection. …”
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An Iterative Pixel-Based Dimensional Voting Model for High Spatial-Resolution Image Classification by Muhamad Asyraf Mohd Pouzi, Haza Nuzly Abdull Hamed, Muhammad Razib Othman, Hishammuddin Asmuni, Mohd Adham Isa, Husni Ruslai

“…Pixel-DMV outperformed conventional methods, including Support Vector Machine (SVM), Random Forest (RF), and Maximum Likelihood (ML) classifications. …”
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Impacts of Policies on Tourism-Oriented Rural Spaces: A Case Study of Minority Villages in Yanbian Prefecture by Yu Zhang, Wenxin Xiong, Li Dong

“…This study utilizes the PMC index model, the coupled coordination degree model, and the vector autoregressive model to analyze the implementation effects of rural tourism policies and to establish an index system for rural spatial construction. …”
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Optimization of carbon peak path in Fujian Province based on sparrow search algorithm by CAI Huang, LIN Xiaoyu*, CAI Zhiling, ZHONG Yiwen, ZHONG Fenglin

“…In response to the urgent global challenge of carbon emission reduction, reliable pathways to carbon peaking are of significant importance for the implementation of carbon reduction in China. However, the process of carbon dioxide emissions involves numerous influencing factors, and the combinations of their change rates are diverse. …”
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Modification and Characteristics of Biofunctional Properties of Collagen-Containing Xerogels for Medical Purposes: Results of the Experimental Study by Petr S. Eremin, Elena A. Rozhkova, Pavel A. Markov

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A CGAN-based adversarial attack method for data-driven state estimation by Qi Wang, Jing Zhang, Jianxiong Hu, Shutan Wu, Shiyi Hou, Yi Tang

“…Simulation results demonstrate that the proposed method could compromise the state estimation process while evading bad data detection, all with reduced attack costs. …”
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Improving rainfall forecasting using deep learning data fusing model approach for observed and climate change data by Farhan Amir Fardush Sham, Ahmed El-Shafie, Wan Zurina Binti Wan Jaafar, S. Adarsh, Mohsen Sherif, Ali Najah Ahmed

“…The performance of several advanced machine learning models was assessed, with the Efficient Linear Support Vector Machine (ELSVM) showing the highest accuracy in daily rainfall forecasting, yielding an R² value of 0.3868, indicating its ability to effectively capture the variability in rainfall. …”
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Significant Progress in the Study of African Freshwater Snails Over the Past 260 Years by Matabaro Ziganira, Colleen T. Downs

“…Research progress concerning African freshwater snails was reviewed using a systematic review process. Since 1757, the number of publications produced has increased, particularly in the last decade. …”
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Therapeutic limitations of oncolytic VSVd51-mediated miR-199a-5p delivery in triple negative breast cancer models by Guillaume St-Cyr, Lauren Daniel, Hugo Giguère, Rayanna Birtch, Carolina S. Ilkow, Lee-Hwa Tai

“…Abstract Triple-negative breast cancer (TNBC) metastasis is driven, in part, by the epithelial-to-mesenchymal transition (EMT), a process critical for cancer cell migration and invasion. …”
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Vehicle Lane Change Multistep Trajectory Prediction Based on Data and CNN_BiLSTM Model by Shijie Gao, Zhimin Zhao, Xinjian Liu, Yanli Jiao, Chunyang Song, Jiandong Zhao

“…Considering the interaction between vehicles in the driving process, the information of predicted vehicle, and surrounding vehicles is taken as the input of the model. …”
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Advancing Financial Forecasts: Stock Price Prediction Based on Time Series and Machine Learning Techniques by Cheng-Ying Yang, Min-Shiang Hwang, Yu-Wei Tseng, Chou-Chen Yang, Victor R. L. Shen

“…Thus, this study aims to examine the problem of stock price prediction with time series and proposes an effective way to filter out the datasets, which consists of three key steps: First, a time series model with long-short-term memory (LSTM) was used to identify the possible problems and solve them in the process of stock price prediction. Second, the results of LSTM were adopted to influence the stock trend prediction by a variety of machine learning techniques, including random forest, support vector machine, light gradient boosting machine (LightGBM). …”
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MapReduce based big data framework using associative Kruskal poly Kernel classifier for diabetic disease prediction by R. Ramani, S. Edwin Raja, D. Dhinakaran, S. Jagan, G. Prabaharan

“…Recent trendy applications of Artificial Intelligence are Machine Learning (ML) algorithms, which have been extensively utilized for processes like pattern recognition, object classification, effective prediction of disease etc. …”
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Classification of cervical vertebral maturation stages with machine learning models: leveraging datasets with high inter- and intra-observer agreement by Potjanee Kanchanapiboon, Pitipat Tunksook, Prinya Tunksook, Panrasee Ritthipravat, Supatchai Boonpratham, Yodhathai Satravaha, Chaiyapol Chaweewannakorn, Supakit Peanchitlertkajorn

“…Additionally, landmarks annotation of the second to fourth cervical vertebrae and patients’ information underwent a feature selection process. These datasets were used to train various ML models and identify the top-performing model for each dataset. …”
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serologic markers of Epstein-Barr virus reactivation in the conditions of viral encephalitis in young patients by O. V. Goleva, E. A. Murina, Z. A. Osipova

“…The reactivation of Epstein-Barr virus on the background of some basic disease revealed during the development of encephalitis of various etiology could act as a co-factor to trigger the process of demyelinazation of central nervous system tissues. …”
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