Identification, Cloning, and Expression of A Major Thermolabile Hemolysin Gene from Vibrio alginolyticus ATCC17749 by Raj Kamal Vibhuti, Avijit Pramanik

“…Vibrio alginolyticus, an opportunistic pathogen in humans, obtains iron from various iron-containing compounds, including hemin, a heme derivative. This process may be an important virulence-associated adaptation for evolution into a human pathogen. …”
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Online Adaptive Error Compensation SVM-Based Sliding Mode Control of an Unmanned Aerial Vehicle by Kaijia Xue, Congqing Wang, Zhiyu Li, Hanxin Chen

“…As modeling errors and noises both exist in the process of flight, the offline SVM one-time mode cannot predict the uncertainties and noises accurately. …”
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Cancer Discrimination Using Fourier Transform Near-Infrared Spectroscopy with Chemometric Models by Hui Chen, Zan Lin, Chao Tan

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A Comparative Study of Loan Approval Prediction Using Machine Learning Methods by Vahid Sinap

“…Loan prediction plays an important role in the process of evaluating loan applications by financial institutions. …”
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Spatial Characteristics and Driving Mechanisms of Carbon Neutrality Progress in Tourism Attractions in the Qinghai–Tibet Plateau Based on Remote Sensing Methods by Bing Xia

“…The carbon neutrality process in natural tourism attractions is marginally superior to that in cultural tourism attractions. …”
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Role of the Plenum of Russian Supreme Court in the judicial practice formation by Yu. S. Pestereva, I. G. Ragozina, E. I. Chekmezova

“…The authors draw attention to the problem of evaluative features used in the process of law enforcement when interpreting the norms of the Special Part of the Criminal Code of the Russian Federation. …”
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Machine Learning-Based Non-Invasive Prediction of Metabolic Dysfunction-Associated Steatohepatitis in Obese Patients: A Retrospective Study by Jie Chen, Bo Zhang, Yong Cheng, Yuanchen Jia, Biao Zhou

“…Various ML models, including K-nearest neighbors, linear support vector machine, radial basis function support vector machine, Gaussian process, random forest, multilayer perceptron, adaptive boosting, and naïve Bayes, were developed through cross-validation and hyperparameter tuning. …”
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Drainage Density Mapping Using ArcGIS in the Liwiec Watershed by Stoica Paula, Giurma Ion, Zaborilă Anca, Giurma-Handley Catrinel-Raluca

“…It is associated with hydrologic processes like infiltration, soil saturation, and runoff. …”
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Spoofing’s Selection and Compensation in the Global Navigation Satellite System Consumer Navigation Equipment with Multi-Channel Antenna System by H. Kh. Saad, M. A. Loban

“…Compensation of spoofing signals is carried out in the spatial domain by estimating the correlation matrix of processes at the outputs of the antenna system channels by the corresponding countdown of code channel signals after matched filtering and forming of a weight vector while minimizing the output power of spoofing signals by directly inverting the estimate of the correlation matrix and carrying out weight processing of the adopted implementation. …”
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Approximate Schur Complement Preconditioners for Half-Quadratic Image Restoration With Zero Boundary Conditions by Chaojie Wang, Shuen Sun, Jie Chen, Biling Liu

“…In order to accelerate this process, we have proposed a preconditioning method based on approximations of the Schur complement and the blurring matrix. …”
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Deep learning for compressed sensing based sparse channel estimation in FDD massive MIMO systems by Yuan HUANG, Yigang HE, Yuting WU, Tongtong CHENG, Yongbo SUI, Shuguang NING

“…For FDD massive multi-input multi-output (MIMO) downlink system, a novel deep learning method for compressed sensing based sparse channel estimation was proposed, which was called convolutional compressed sensing network (ConCSNet).In the ConCSNet, the convolutional neural network was utilized to solve the inverse transformation process from measurement vector y to signal h and solve the underdetermined optimization problem through data-driven method without sparsity.Simulation results show that the algorithm can recover the channel state information in massive MIMO Systems with unknown sparsity more quickly and accurately.…”
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Research of Forming Trajectory of Multi-branches Rose Curve of Double Eccentric Sets Transmission for Orbital Forming Press Head by Gong Xiaotao, Geng Pei

“…The formation process of multi- branches rose curve trajectory motion are analyzed,the branch numbers of multi- branches rose curve and the law of the its trajectory are studied.…”
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Assessing the ability of output gap estimates to forecast inflation in emerging countries by Nwabisa Florence Ndzama

“…We further find some indications of a better inflation forecasting ability of the output gap in countries with inflation targeting, suggesting that the improved transparency related to inflation targeting might support the inflation forecasting process.…”
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Advancing patient care: Machine learning models for predicting grade 3+ toxicities in gynecologic cancer patients treated with HDR brachytherapy. by Andres Portocarrero-Bonifaz, Salman Syed, Maxwell Kassel, Grant W McKenzie, Vishwa M Shah, Bryce M Forry, Jeremy T Gaskins, Keith T Sowards, Thulasi Babitha Avula, Adrianna Masters, Jose G Schneider, Scott R Silva

“…The training process involved sequential feature selection (SFS) when appropriate, followed by hyperparameter tuning. …”
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Using A One-Class SVM To Optimize Transit Detection by Jakob Roche

“…As machine learning algorithms become increasingly accessible, a growing number of organizations and researchers are using these technologies to automate the process of exoplanet detection. These mainly utilize Convolutional Neural Networks (CNNs) to detect periodic dips in lightcurve data. …”
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Study on Height Measurement for Polyethylene Terephthalate (PET) Materials Based on Residual Networks by Chongwei Liao, Weixin Zhang, Yujie Peng, Changjun Liu

“…In industrial production, high-power microwaves are commonly used for heating and drying processes; however, their application in measurement is relatively limited. …”
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Calculation of Transient Stability Limit Based on Convolutional Neural Network by Qihe LOU, Rongsheng LI, Jie TAN, Tiejiang YUAN

“…Then certain key features of the transmission interface are selected as the input layer vector of the neural network. And next the nonlinear mapping relationship between the key features of the system and the transient stability limit of interface power transmission is constructed after multiple rounds of training processes. …”
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Venation Skeleton-Based Modeling Plant Leaf Wilting by Shenglian Lu, Chunjiang Zhao, Xinyu Guo

“…The proposed method includes five principal processes. Firstly, a three-dimensional leaf skeleton is constructed from a leaf image, and the leaf skeleton is further used to generate a detailed mesh for the leaf surface. …”
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RESEARCH ON THE FITTING CLEARANCE BETWEEN FLANGE BORE AND SHAFT CONSIDERING MULTI-ERRORS COUPLING by NI WeiHua, JIANG XiaoHui

“…The mating state between a flange bore and a shaft and the position error for a flange shaft in a bore has an important influence on the assembly accuracy of precision products.In view of the fact that three-dimensional cylindricity was usually ignored in existing researches,a contact method was developed,which was based on equal vector judgment criterion and measured profile data of the parts.It can effectively determine the actual fitting clearance between bore and shaft taking threedimensional cylindricity errors into account.The effects of the cylindricity error and the number of lobes on the fitting clearance were analyzed in detail.The results indicate that the cylindricity error has significant influence on the actual fitting clearance.By the principal of error composition and neutralization,the actual fitting clearance between a flange bore and shaft was obtained considering the coupling of dimension errors,three-dimensional cylindricity errors and perpendicular errors.It is effective to preanalyze the position accuracy for a flange shaft in a flange bore.Then it can provide guidance for subsequent assembly processes to increase assembly efficiency and improve assembly accuracy of precision products before they are assembled.…”
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Technological priorities for the development of Russia’s industrial sector in the context of deep digital penetration by O. E. Pudovkina

“…Industry 4.0 dictates certain requirements for the modernisation of processes and production facilities. This is especially true for industry, which has a relatively high share of the country’s gross domestic product The outline of the future strategic development of the industry sector in an environment of external change is therefore of particular relevance. …”
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