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Inhibition of carbonaceous matters adsorbing gold using a green and efficient chlorinating agent TCCA: Inhibition behavior, kinetics and isotherms, inhibition mechanism

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COLLOIDS AND SURFACES A-PHYSICOCHEMICAL AND ENGINEERING ASPECTS 2023年 675卷

作者： Niu, Huiqun Yang, Hongying Zhao, Rongxin Tong, Linlin Cristiani, Pierangela Northeastern Univ Key Lab Ecol Met Multimet Mineral Minist Educ Shenyang 110819 Peoples R China Northeastern Univ Sch Met Shenyang 110819 Peoples R China Shandong Gold Min Ind Jiaojia Gold Mine Laizhou 264100 Peoples R China Sustainable Energy & Energy Sources Dept Via Rubattino 54 I-20134 Milan Italy

Refractory carbonaceous gold ore contains carbonaceous matters that seriously interfere with gold leaching. Therefore, this paper presented an in-depth experimental investigation on the inhibition gold-adsorbing behavior using Trichloroisocyanuric acid (TCCA). Various factors affecting the inhibition were analyzed. Moreover, the kinetics and isotherms associated with the adsorption were established to describe the gold adsorption of carbonaceous matters after TCCA treatment. A variety of analytical techniques were used to clarify the inhibition mechanism. The results showed the average gold adsorption percentage of elemental carbon decreased from 89.79 % to 9.33 % at pH 3.0, TCCA volume 15.17 mL, TCCA concentration 0.104 molL-1, 35 degree celsius and 3 h. The average adsorption percentage of humic acid decreased from 56.19 % to 3.13 % at pH 5.0, TCCA volume 5.10 mL, TCCA concentration 0.012 molL-1, 35 degree celsius and 4.5 h. The gold-adsorption behavior of the treated elemental carbon conformed to the pseudo-second-order and Langmuir model, accompanied by an activation energy of 9.42 kJmol(-1). And the adsorption process of the treated humic acid could be explained by the pseudo-first-order and Langmuir model with an activation energy of 40.11 kJmol(-1). TCCA molecules and their hydrolysis products covered the elemental carbon surface, resulting in a reduction in the size of the porous structure, which further affected the number and activity of surface-active sites. Treated with TCCA, the surface area of humic acid reduced from 42.84 m(2)g(-1) to 9.96 m(2)g(-1). Furthermore, spectroscopic analysis showed that the chemical groups of humic acid were destroyed, suggesting a sharp decrease in chemisorption capability.

关键词： Carbonaceous matters Inhibiting adsorption multiple linear regression model Kinetics and isotherms Inhibition mechanism

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Research on exchange rate forecast based on MLR-ELM model

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INTERNATIONAL JOURNAL OF modelLING IDENTIFICATION AND CONTROL 2023年第3期43卷 249-257页

作者： Peng, Yi He, Kang Yu, Qing Chen, Yanan Shenzhen Polytech Sch Econ Shenzhen Peoples R China Changsha Univ Sch Econ & Management Changsha Peoples R China Guangzhou City Univ Technol Management Coll Guangzhou Peoples R China

This paper introduces a new model to predict the exchange rate. The model is a combination model of the multiple linear regression model (MLR) and the extreme learning machine model (ELM). The RMB-USD exchange rate is the object of prediction. Firstly, the sample data are pre-processed and divided into a training set and a test set;then a linear regression equation is created for the training set. The predicted values of the MLR model and other selected independent variables are the input data of ELM, which is determined by the training set. Secondly, the test set data are tested with parameter set obtained from the training set, and the optimal parameters of MLR-ELM model are determined by the performance of the training set and the test set. Finally, the exchange rate is predicted. The simulation results suggest that MLR-ELM model have a better prediction than the multiple linear regression model.

关键词： exchange rate forecast multiple linear regression model MLR extreme learning machine model ELM

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Assessing digital transformation readiness: a comprehensive study of local clinics in Northwest Vietnam

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International Journal of Information Technology (Singapore) 2025年第3期17卷 1607-1617页

作者： Duong, An Hoai Nguyen, Thu Duc Duong, Giang Huong Tran, Thuy Thi Business School Griffith University Nathan Campus 170 Kessels Road Nathan 4111 QLD Australia Faculty of Business Administration Thai Nguyen University of Economics and Business Administration Thai Nguyen Viet Nam Department of Planning and Finance Thai Nguyen University of Economics and Business Administration Thai Nguyen Viet Nam Faculty of Biotechnology and Food Technology Thai Nguyen University of Agriculture and Forestry Thai Nguyen Viet Nam

Local clinics are pivotal in delivering primary healthcare, especially in economically disadvantaged areas like Vietnam’s Northwest. However, these regions face notable deficits in healthcare infrastructure. Digital transformation offers a promising solution. This study assesses the digital transformation readiness of 75 local clinics in Northwest Vietnam and investigates the impact of influential factors on this readiness. The study design involved collecting responses from clinic heads or designated representatives through a web-based survey. The sample size comprised 75 local clinics in Northwest Vietnam. multiple linear regressions were utilised to examine the impact of influential factors on the clinics’ digital transformation readiness. Findings indicate a significant readiness gap among the surveyed clinics, with observed scores falling below the maximum achievable score of 290. Most clinics scored between 63.5 and 116, highlighting substantial room for improvement in digital preparedness. The study unveiled significant relationships between digital readiness and clinic attributes. Negative correlations included clinic head age and reliance on e-wallets. Positive associations included seniority, social media engagement, and clinic characteristics like education and technology use. The regression results highlight positive associations with clinic head seniority, clinic social accounts, personnel using smart devices, and online patient record integration. Conversely, negative associations were noted with clinic head age and e-wallet usage. The findings stress targeted support for older clinic leaders in digital adaptation, highlight experienced leadership’s role, note distractions from financial technologies, emphasise social media’s digital readiness impact, and stress technological adoption’s importance, plus digital record-keeping benefits for clinics and patient care. © Bharati Vidyapeeth's Institute of Computer Applications and Management 2024.

关键词： Local clinics multiple linear regression model Readiness for digital transformation Web-based surveys

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Covid-19's Influence on the Sale of Chinese Commercial Residential Housing——Evaluation Analysis Based on Multi Variable linear regression model

Covid-19's Influence on the Sale of Chinese Commercial Resid...

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作者： Jiaming Yang Lei Chang School of Letters and Science University of California School of Big Data Changzhou University

In January 8th, 2023, Chinese government officially terminated its quarantine policies after the publication of "The Overall Plan of Implementing Category B Management Measures to Covid-19 As a Category B Infectious Disease", since then,Chinese society entered into a brand new phase of the recovery of economic ***, in January 17th, 2023, the vice prime minister He Liu made a speech about his optimistic opinions about future Chinese Housing Market in the annual meeting of Davos Forum. This paper chooses the sale of Chinese commercial residential housing as the research object and acquires annual data of Chinese Housing Market since 1998 from Huibo terminal platform and Qianzhan database as the experimental data. This paper uses STATA to model experimental data and conducts research of the sale of Chinese commercial residential housing through the method of linear regression analysis. Bases on the analysis of the experimental data, this paper finds out the conclusion that covid-19 causes significant impacts toward the sale of Chinese commercial residential housing. Bases on the fitting result derived from the fitting analysis of the sale of Chinese commercial residential housing from 2022 to 2024 in the experimental model, it points out that there is going to be significant recovery in Chinese housing market from 2023 to 2024.

关键词： China sale area of commercial housing Covid-19 sale of chinese commercial residential housing multiple linear regression model

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Bayesian Estimation of Fault Slip Distribution for Slow Slip Events Based on an Efficient Hybrid Optimal Directional Gibbs Sampler and Its Application to the Guerrero 2006 Event

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MATHEMATICAL GEOSCIENCES 2023年第6期55卷 859-886页

作者： Montesinos-Lopez, J. Cricelio Capella, Antonio Christen, J. Andres Tago, Josue Ctr Invest Matemat AC Guanajuato Mexico Univ Nacl Autonoma Mexico Inst Matemat Mexico City DF Mexico Univ Nacl Autonoma Mexico Fac Ingn Mexico City DF Mexico

An efficient Bayesian approach is proposed to infer fault slip from geodetic data in a Slow Slip Event (SSE). The physical model of the slip process reduces to a multiple linear regression with constraints. Assuming a Gaussian model for the geodetic data and considering a multivariate truncated normal prior distribution for the unknown fault slip, the resulting posterior distribution is also a multivariate truncated normal. A prior slip distribution having a detailed correlation structure to impose natural coherence in the fault slip is proposed. Regarding the posterior, an ad hoc algorithm based on a Hybrid Optimal Directional Gibbs sampler is proposed that allows to sample efficiently from the resulting high-dimensional posterior slip distribution without supercomputing resources. A synthetic fault slip example illustrates the flexibility and accuracy of the proposed approach. This methodology is also applied to a real data set for the 2006 Guerrero, Mexico, SSE, where the objective is to recover the fault slip on a known interface that produces displacements observed at ground geodetic stations. As a by-product, our approach further allows us to estimate the Moment Magnitude for the 2006 Guerrero SSE with uncertainty quantification.

关键词： multiple linear regression model Slow slip events Mexico subduction zone Multivariate truncated normal distribution Bayesian uncertainty quantification Markov chain Monte Carlo

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Analyzing geomorphological and topographical controls for the heterogeneous glacier mass balance in the Sikkim Himalayas

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Journal of Mountain Science 2023年第7期20卷 1854-1864页

作者： GUHA Supratim TIWARI Reet Kamal Geomatics Engineering Laboratory Department of Civil EngineeringIndian Institute of Technology RoparPunjab-140001India

Glacier response patterns at the catchment scale are highly heterogeneous and defined by a complex interplay of various dynamics and surface *** studies have explained heterogeneous responses in qualitative ways but quantitative assessment is lacking yet where an intrazone homogeneous climate assumption can be ***,in the current study,the reason for heterogeneous mass balance has been explained in quantitative methods using a multiple linear regression model in the Sikkim Himalayan *** first,the topographical parameters are selected from previously published studies,then the most significant topographical and geomorphological parameters are selected with backward stepwise subset selection ***,the contributions of selected parameters are calculated by least square *** results show that,the magnitude of mass balance lies between-0.003±0.24 to-1.029±0.24 m.w.e.a^(-1) between 2000 and 2020 in the Sikkim Himalaya ***,the study shows that,out of the terminus type of the glacier,glacier area,debris cover,ice-mixed debris,slope,aspect,mean elevation,and snout elevation of the glaciers,only the terminus type and mean elevation of the glacier are significantly altering the glacier mass balance in the Sikkim Himalayan ***,the mass loss is approximately 0.40 m.w.e.a^(-1) higher in the lake-terminating glaciers compared to the land-terminating glaciers in the same elevation *** the other hand,a thousand meters mean elevation drop is associated with 0.179 m.w.e.a-1of mass loss despite the terminus type of the *** the current study,the model using the terminus type of the glaciers and the mean elevation of the glaciers explains 76% of fluctuation of mass balance in the Sikkim Himalayan region.

关键词： Glacier mass balance Glacier terminus Topographical parameter Sikkim Himalaya multiple linear regression model

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Marcinkiewicz-Zygmund type strong law of large numbers for weighted sums of random variables with infinite moment and its applications

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JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION 2023年第11期93卷 1694-1715页

作者： Wu, Yi Wang, Xuejun Chizhou Univ Ctr Appl Math Sch Big Data & Artificial Intelligence Chizhou Peoples R China Anhui Univ Sch Big Data & Stat Hefei Peoples R China Anhui Univ Sch Big Data & Stat Hefei 230601 Peoples R China

In this work, the Marcinkiewicz-Zygmund type strong law of large numbers for weighted sums of widely orthant dependent random variables is established under mild conditions including infinite variance. As applications, some new results such as the Cesaro strong law of large numbers, the strong consistency of the least squares estimator in multiple linear regression models, and the strong consistency of the wavelet estimator in nonparametric regression models are presented. Simulation studies are also provided to support the theoretical results.

关键词： Strong law of large numbers widely orthant dependent infinite moment consistency least squares estimator multiple linear regression model wavelet estimator nonparametric regression model

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The Application of the Insulin to C-Peptide Molar Ratio (ICPR) in Primary Screening for Insulin Antibodies in Type 2 Diabetes Mellitus Patients: A Further Quantitative Study on the Relationship Between ICPR and Insulin Antibodies

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DIABETES METABOLIC SYNDROME AND OBESITY 2023年 16卷 1121-1132页

作者： Hua, Kai-Fang Jing, Bo-Yang Wu, Yan-Hui Xiamen Univ Dept Endocrinol Xiangan Hosp Xiamen Fujian Peoples R China Xiamen Univ Sch Med Xiamen Fujian Peoples R China Kunming Med Univ Hai Yuan Coll Kunming Yunnan Peoples R China Xiamen Univ Natl Metab Management Ctr Xiangan Hosp Xiamen Fujian Peoples R China

Purpose: This study aimed to further quantify the relationship between insulin antibodies (IAs) and the 2-hour insulin to C-peptide molar ratio (2h-ICPR) using a multiple linear regression model in T2DM patients. Methods: A total of 274 T2DM patients from April 2019 to December 2022 in Xiang'an Hospital of Xiamen University were included in this study. multiple linear model Fitting was conducted on the candidate independent variables (age, BMI, HbA1c, and 2h-ICPR) for the multiple linear regression. The linear relationship between insulin antibodies (IAs) and the significant independent variables was presented by making multiple linear regression equations. Results: The total demographic characteristics of the included patients were as follows: age (51.92 +/- 13.10 years), BMI (24.94 +/- 3.99 kg/m(2)), HbA1c (9.70 +/- 2.39%), 2h-ICPR (0.12 +/- 0.11), and IAs (0.37 +/- 1.12COI). linear relationships of independent variables: age (r=0.163, p=0.007), 2h-ICPR (r=0.259, p=0.001), BMI (r=0.007, p=0.907) and 2h-ICPR (r=0.092, p=0.129). multiple linear regression: age (unstandardized beta=0.014, 95% CI: 0.004-0.024, p=0.004), 2h-ICPR (unstandardized beta=2.758, 95% CI: 1.555-3.962, p <= 0.001). The regression equation: IAs = 0:712 + 0:014 * age + 2:758 * 2h - ICPRoP<0:001). Conclusion: The quantitative relationship between 2h-ICPR and insulin antibodies was IAs = -0:712 + 0:014 * age + 2:758 * 2h - ICPR. 2h-ICPR can be a preliminary screening indicator for insulin antibody testing in patients with type 2 diabetes.

关键词： insulin insulin antibodies C-peptide multiple linear regression model

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regression models in Lubricant Oil Quality Assessment 1

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24th International Conference on Computational Science and Its Applications (ICCSA)

作者： Aleixo, Sandra M. Enguica, Ricardo Sedas, Francisco Ferreira, Paulo Silva, Andre ISEL Inst Super Engn Lisboa IPL Inst Politecn Lisboa Dept Math Rua Conselheiro EmIdio Navarro 1 P-1959007 Lisbon Portugal Univ Lisbon Fac Ciencias CEAUL Ctr Estat & Aplicac Bloco C6Piso 4 P-1749016 Lisbon Portugal Inst Super Tecn CEMAT Ciencias Ctr Matemat Computac & Estocast Ave Rovisco Pais P-1049001 Lisbon Portugal Galp Qual & Tech Prod Care Ave India 8 P-1349065 Lisbon Portugal

ISBN: (数字)9783031651540

ISBN: (纸本)9783031651533;9783031651540

After a suitable data analysis, we adjust two types of regression models to support decision-making when monitoring lubricants in an industrial environment. The target variable is the remaining useful life of a lubricant, as it is an essential process in preventing damage to associated equipment. The main objective of this work is to predict at an early stage how long will an oil load still perform correctly. The first model is a multiple linear regression, adjusting coefficients using cross-validation on several subgroups of the data set. Though the performance of this model is satisfactory, the corresponding adjustment is compromised by the fact that the observations are not independent, as they are grouped taking into account the oil loads to which they belonged. For this reason, a second type of regression was adjusted: a linear regression model with mixed effects. After adjusting the models, a Python algorithm was created to determine an optimal interval regarding the oil service hours after which the lubricant should be replaced.

关键词： Predictive maintenance Lubricants Predictor selection Correlation multiple linear regression model Mixed effects linear regression Stepwise selection methods Optimal range

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EVALUATION OF SATELLITE-BASED modelS FOR SURFACE SOIL MOISTURE ESTIMATION USING SENTINEL-1 DATA: A CASE STUDY

EVALUATION OF SATELLITE-BASED MODELS FOR SURFACE SOIL MOISTU...

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IEEE International Geoscience and Remote Sensing Symposium (IGARSS)

作者： Gatagat, Pooja Ajay Bharat, Tadikonda Venkata Dey, Arindam Indian Inst Technol Guwahati Ctr Disaster Management & Res CDMR Gauhati 781039 Assam India

ISBN: (纸本)9798350360332;9798350360325

To comprehend natural disasters such as floods, droughts, and landslides, assessment of soil moisture variation over time becomes essential, especially in the Himalayan region of India, where risks induced due to these disasters are prominent. The present research focuses on the evaluation of the sensitivity of Sentinel-1 backscatter to the soil moisture variation in a uniform grassland area within the IIT Guwahati campus. Further, the radar-based indices and models such as Normalized Radar Backscatter Soil Moisture Index (NBMI), and multiple linear regression (MLR) models are employed to perform a correlation analysis between predicted soil moisture and in-situ soil moisture observations acquired through a probe. The backscatter obtained from the VV channel has shown higher sensitivity toward observed soil moisture. Furthermore, the Water Cloud model (WCM) based semi-empirical regression model performed better than the other two models.

关键词： Soil moisture estimation multiple linear regression model Synthetic Aperture Radar NBMI Microwave remote sensing

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