检索结果-内蒙古大学图书馆

Titanium Oxide Nanocubes Embedded Molecularly Imprinted Polymer-Based Electrode for Selective Detection of Caffeine in Green Tea

引用

IEEE SENSORS JOURNAL 2020年第12期20卷 6240-6247页

作者： Das, Debangana Chatterjee, Trisita Nandy Roy, Runu Banerjee Tudu, Bipan Hazarika, Ajanto Kumar Sabhapondit, Santanu Bandyopadhyay, Rajib Jadavpur Univ Dept Instrumentat & Elect Engn Kolkata 700098 India Tocklai Tea Res Inst Jorhat 785008 Assam India ITMO Univ Lab Artificial Sensory Syst St Petersburg 197101 Russia

The present study reports the development of a low cost electrode by means of molecularly imprinted polymer (MIP) technique for detection and quantification of caffeine in green tea. The sensing material has been synthesized using the co-polymer of acrylonitrile (AN) and ethylene glycol dimethacrylate (EGDMA) followed by impregnation of TiO2 nanocubes into it. The electrode demonstrated a wide linear range from 5 mu M to 120 mu M with limit of detection (LOD) being 0.6 mu M . The analytical characteristics revealed acceptable selectivity, repeatability, stability and reproducibility of the electrode. Real time application of developed sensor has been ascertained by measuring the caffeine content in different variants of green tea. The partial least square regression (PLSR) and principal component regression (PCR) models have been explored to estimate the predictive ability of the electrode in terms of their caffeine content by correlating the response of the obtained differential pulse voltammetry (DPV) datasets of green tea samples with HPLC data. In case of PLSR technique, an average prediction accuracy of 92.94% is obtained with root mean square error of calibration (RMSEC) value being as low as 0.07. Additionally for PCR, an average prediction accuracy of 93.75% is acquired with RMSEC value being 0.07.

关键词： Electrodes Titanium dioxide Polymers Nanoparticles Sensors Powders X-ray diffraction Molecularly imprinted polymer titanium oxide nanocubes caffeine green tea linear regression models

来源：评论

学校读者我要写书评

暂无评论

Valorization of waste pond ash in cement mortars and prediction of mechanical properties by simple linear regression

引用

JOURNAL OF MATERIAL CYCLES AND WASTE MANAGEMENT 2024年第2期26卷 1147-1168页

作者： Sharma, Sandesh Vyas, Ashok Kumar Malaviya Natl Inst Technol Dept Civil Engn JLN Marg Jaipur 302017 Rajasthan India

Pond ash disposal in open fields is a major environmental concern due to huge land requirements. One of the approaches to utilizing pond ash is by replacing it with river sand in cement mortars. Hence, in the current study, pond ash was used to replace river sand up to 100% by volume. The present study evaluates the mechanical properties using volumetric mix proportions of 1:4 and 1:5 (cement: sand). The pozzolanic activity of pond ash through the strength activity index (SAI) and Frattini test was also evaluated. The compressive strength of the 1:4 mix with 30% pond ash increased by 26% compared to the control mix. Drying shrinkage was found to increase by 35-40% in both mix proportions. Microstructural studies were conducted to support the mechanical properties of mortar results. linear regression models were also developed using experimental data to establish the relationship between mechanical properties. Incorporating up to 50% pond ash in cement mortars increased the mechanical properties of mortars, except for drying shrinkage. Thus, waste pond ash can be valorized as fine aggregate in cement mortars. This study will have direct field application by replacing river sand with up to 60% pond ash, reducing mortars' environmental burden and cost.

关键词： Pond ash Cement mortars Pozzolanic activity Microstructural analysis linear regression models

来源：评论

学校读者我要写书评

暂无评论

Causes of deforestation in southwestern Madagascar: what do we know?

引用

FOREST POLICY AND ECONOMICS 2004年第1期6卷 33-48页

作者： Casse, T Milhoj, A Ranaivoson, S Randriamanarivo, JR Roskilde Univ Ctr DK-4000 Roskilde Denmark Univ Copenhagen Inst Econ & Stat Copenhagen Denmark Ctr Natl Resch Environm Antananarivo Madagascar

Causes of deforestation are discussed in the case of southwestern Madagascar. The article has two objectives. First, the idea is to discuss the usual linear regression approach to determine causes of deforestation. Secondly, the intention is to determine the causes of deforestation in our case study. Distinction is made between direct causes (agriculture, wood collection, and pasture land) and indirect causes (migration, export prices, property rights, and government policies). In outlining the strategies of the peasants, the article ends up with an estimation of the value of agricultural land vs. an estimation of benefits derived from utilisation of non-timber forest products from primary forest or scrub (value of medical plants and roots used as staple food). (C) 2002 Elsevier Science B.V. All rights reserved.

关键词： causes of deforestation linear regression models peasant strategies value of medical plants and roots Madagascar

来源：评论

学校读者我要写书评

暂无评论

Modeling Fecal Indicator Bacteria Concentrations in Natural Surface Waters: A Review

引用

CRITICAL REVIEWS IN ENVIRONMENTAL SCIENCE AND TECHNOLOGY 2014年第21期44卷 2380-2453页

作者： de Brauwere, Anouk Ouattara, Nouho Koffi Servais, Pierre Catholic Univ Louvain Inst Mech Mat & Civil Engn IMMC B-1348 Louvain La Neuve Belgium Catholic Univ Louvain Georges Lemaitre Ctr Earth & Climate Res TECLIM B-1348 Louvain La Neuve Belgium Vrije Univ Brussel Brussels Belgium Univ Libre Bruxelles Brussels Belgium

Microbiological quality of waters must be assessed to ensure that no health risk due to pathogenic microorganisms is associated with its use. As it is impossible to measure the abundance of all possible pathogens, it is general practice to quantify the abundance only of one or a few fecal indicator bacteria (FIB), organisms which are selected to be indicative of fecal pollution and can therefore serve as general indicators of microbiological water quality. Yet, even by focusing on this limited number of indicator organisms, it is still unfeasible to experimentally monitor their levels at the high spatiotemporal resolution often needed in real applications. Therefore, direct FIB measurements are increasingly combined with the use of models. The aim of this review is to present and evaluate the wide variety of models used so far in the scientific literature to simulate and predict FIB concentrations in natural surface waters. First, the distinction is made between regression-based and mechanistic models. While the first are particularly useful in operational contexts and indeed can produce reliable short-term predictions, they do not allow an in-depth understanding of the processes. Because the sources and processes are not modeled explicitly, they cannot be used to test the effect of changes in these internal and external forcings, e. g., to evaluate the impact of different management options. These questions can only be addressed by the use of mechanistic models, which are often based on rather complex computational methods. These models explicitly consider the effect on FIB concentrations due to horizontal transport, external sources, decay, and/or sediment-related processes. It is not possible to make statements about "best" practices, given the broad range of study domains and questions. Instead, we attempted to compile the modeling approaches published so far in a comprehensive and transparent way, hoping that the resulting overview would help to better understa

关键词： fecal indicator bacteria concentration microbiological water quality models linear regression models mechanistic models mortality sediment attachment

来源：评论

学校读者我要写书评

暂无评论

Shrinkage and LASSO strategies in high-dimensional heteroscedastic models

引用

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 2016年第15期45卷 4454-4470页

作者： Nkurunziza, Severien Al-Momani, Marwan Lin, Eric Yu Yin Univ Windsor Dept Math & Stat Windsor ON N9B 3P4 Canada

In this paper, we consider the estimation problem of the parameter vector in the linear regression model with heteroscedastic errors. First, under heteroscedastic errors, we study the performance of shrinkage-type estimators and their performance as compared to theunrestricted and restricted least squares estimators. In order to accommodate the heteroscedastic structure, we generalize an identity which is useful in deriving the risk function. Thanks to the established identity, we prove that shrinkage estimators dominate the unrestricted estimator. Finally, we explore the performance of high-dimensional heteroscedastic regression estimator as compared to classical LASSO and shrinkage estimators.

关键词： Asymptotic distribution risk Heteroscedastic models HHR estimator LASSO Least squares estimator linear regression models Shrinkage strategies 62J07 62F30

来源：评论

学校读者我要写书评

暂无评论

A regression model describing the effect of pH, NaCl and temperature on D values of Bacillus stearothermophilus spores

引用

EUROPEAN FOOD RESEARCH AND TECHNOLOGY 2003年第6期216卷 535-538页

作者： Tejadillos, S Armero, C Periago, PM Martínez, A CSIC Inst Agroquim & Tecnol Alimentos Valencia 46100 Spain Univ Valencia Fac Math Dept Stat & Operat Res Valencia Spain

A new microbiological predictive model was developed, relating pH, NaCl concentration and temperature (T) with the decimal reduction coefficient D as dependent variable, using data previously reported by [1]. The model was obtained by multiple linear regression using only three predictor variables (T-2, pH(2) and NaCl), easily computed from the basic variables pH, NaCl concentration and temperature (T). The fitted model is robust, stable and satisfies all the basic hypotheses of the regression models. It also provides simplicity when compared with previously published models based on multiple linear regression tools.

关键词： predictive microbiology Bacillus stearothermophilus mathematical modelling linear regression models

来源：评论

学校读者我要写书评

暂无评论

Prediction of the aqueous solubility of diverse compounds by 2D-QSPR

引用

JOURNAL OF MOLECULAR LIQUIDS 2020年 302卷 112572-112572页

作者： Fioressi, Silvina E. Bacelo, Daniel E. Aranda, Jose F. Duchowicz, Pablo R. Univ Belgrano Fac Ciencias Exactas & Nat CONICET Villanueva 1324 RA-1426 Buenos Aires DF Argentina UNLP Inst Invest Fisicoquim Teor & Aplicadas INIFTA CONICET Diag 113 & 64CC 16Sucursal 4 RA-1900 La Plata Argentina

Non conformational QSPR models were built for the aqueous solubility (mol/L) at 25 degrees C of 5610 structurally heterogeneous compounds, including pesticides, drugs and solvents, among others, with a wide range of aqueous solubility. The experimental database was taken from the WATERNT module for solubility estimation of the EPI Suite program. A large set of 23,723 conformation-independent molecular descriptors was explored to obtain trustworthy but simple multivariable linear regression models. It is found that four selected molecular descriptors improve the predictive capacity of the WATERNT program, thus achieving satisfactory predictions for the water solubility through an alternative methodology. (C) 2020 Elsevier B.V. All rights reserved.

关键词： Quantitative structure-property relationships Aqueous solubility Conformation-independent molecular descriptors linear regression models

来源：评论

学校读者我要写书评

暂无评论

Usage of output-dependent data scaling in modeling and prediction of air pollution daily concentration values (PM₁₀) in the city of Konya

引用

NEURAL COMPUTING & APPLICATIONS 2012年第8期21卷 2153-2162页

作者： Polat, Kemal Durduran, S. Savas Abant Izzet Baysal Univ Elect & Elect Engn Dept TR-14280 Bolu Turkey Selcuk Univ Fac Engn & Architecture Dept Geomat Engn TR-42035 Konya Turkey

This paper presents the combination of a data preprocessing called output-dependent data scaling (ODDS) and adaptive network-based fuzzy inference system (ANFIS) to predict the air pollution daily levels including particulate matter (PM10) concentration values belonging to the city of Konya in Turkey. Also, we have used the regression models including least square regression, partial least square regression, and multivariate linear regression as prediction models in addition to ANFIS model. Data transformation or normalization methods should be used to increase the performance of used prediction models and are used prior to prediction algorithms. In this study, we have used the output-dependent data scaling method as data transformation method and combined it with ANFIS and regression models. PM10 concentration dataset has been taken from Air Quality Statistics database of Turkish Statistical Institute. In PM10 concentration dataset, the mean values belonging to seasons of winter period have been used with the aim of watching the air pollution changes between dates of December, 1, 2003 and December, 30, 2005 in the city of Konya. In the forecasting of PM10 concentration in Konya province, temperature (A degrees C), humidity (%), pressure (kPa), and wind velocity (km/h) attributes have been used. The experimental results demonstrated that the ODDS method has obtained very promising results in the prediction of PM10 concentration values.

关键词： Output-dependent data scaling PM10 Prediction Adaptive network-based fuzzy inference system linear regression models Air pollution

来源：评论

学校读者我要写书评

暂无评论

Predicting the absorption of chemical vapours

引用

ADVANCED DRUG DELIVERY REVIEWS 2013年第2期65卷 306-314页

作者： Rauma, Matias Boman, Anders Johanson, Gunnar Karolinska Inst Inst Environm Med Unit Work Environm Toxicol S-17177 Stockholm Sweden Karolinska Inst Inst Environm Med Unit Occupat & Environm Dermatol S-17177 Stockholm Sweden

The focus of this review is on the systemic absorption of vapours via skin, including experimental data as well as regression and pharmacokinetic models. Dermal contribution ratios (DCR), i.e. amount absorbed through skin relative to total intake (skin and inhalation) at specified conditions, could be identified or calculated from published data for 33 chemical vapours. The ratios vary from similar to 0.0002 (vinyl chloride) to similar to 0.8 (2-butoxyethanol), with hydrophilic chemicals having a higher ratio than lipophilic ones. Multiple regression analysis of these data suggests that the DCR is largely explained by the octanol:water partition coefficient, vapour pressure and molecular weight (R-2 = 0.69). Several physiologically-based pharmacokinetic models were identified;however, all describe the absorption of single substances. Regarding predictive models, only two models were found. In conclusion, dermal uptake of chemical vapours needs more attention, as such exposures are common, data are scarce and few predictive models exist. (C) 2012 Elsevier B.V. All rights reserved.

关键词： linear regression models Predictive models PBPK model Organic solvents Dermal to inhalation ratio Dermal contribution ratio DIR DCR

来源：评论

学校读者我要写书评

暂无评论

Increasing diversity: Natural language measures for software fault prediction

引用

JOURNAL OF SYSTEMS AND SOFTWARE 2009年第11期82卷 1793-1803页

作者： Binkley, David Feild, Henry Lawrie, Dawn Pighin, Maurizio Loyola Coll Baltimore MD 21210 USA Univ Massachusetts Amherst MA 01003 USA Univ Udine Dept Math & Comp Sci I-33100 Udine Italy

While challenging, the ability to predict faulty modules of a program is valuable to a software project because it can reduce the cost of software development, as well as software maintenance and evolution. Three language-processing based measures are introduced and applied to the problem of fault prediction. The first measure is based on the usage of natural language in a program's identifiers. The second measure concerns the conciseness and consistency of identifiers. The third measure, referred to as the QALP score, makes use of techniques from information retrieval to judge software quality. The QALP score has been shown to correlate with human judgments of software quality. Two case studies consider the language processing measures applicability to fault prediction using two programs (one open source, one proprietary). linear mixed-effects regression models are used to identify relationships between defects and the measures. Results, while complex, show that language processing measures improve fault prediction, especially when used in combination. Overall, the models explain one-third and two-thirds of the faults in the two case studies. Consistent with other uses of language processing, the value of the three measures increases with the size of the program module considered. (C) 2009 Elsevier Inc. All rights reserved.

关键词： Information retrieval Code comprehension Fault prediction linear regression models Empirical software engineering

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：