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Journal articles on the topic 'Multilinear regression (MLR)'

Author: Grafiati

Published: 4 June 2021

Last updated: 3 February 2022

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1

Kilo, Jafar La, and Akram La Kilo. "Kajian HKSA Antimalaria Senyawa Turunan Quinolon-4(1H)-imines Menggunakan Metode MLR-ANN." Jambura Journal of Chemistry 1, no. 1 (2019): 21–26. http://dx.doi.org/10.34312/jambchem.v1i1.2104.

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Quantitatif Structure-Activity Relationship (QSAR) study of 22 antimalarial compounds of Quinolon-4(1H)-imines derivatives has been done using multilinear regression (MLR) and artificial neural network (ANN) methods. The best QSAR model was obtained from ANN analysis indicated by its higher correlation coefficient (r2) compared to MLR method, i.e. 0.931 with most influential descriptors is qC1, qC5, qC11, qN14 and log P.Keywords: Quinolon-4(1H)-imines, Antimalarial, QSAR, MLR-ANNTelah dilakukan kajian analisis Hubungan Kuantitatif Struktur Aktivitas (HKSA) terhadap 22 senyawa antimalaria turun

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Chen, Wei-Bo, and Wen-Cheng Liu. "Water Quality Modeling in Reservoirs Using Multivariate Linear Regression and Two Neural Network Models." Advances in Artificial Neural Systems 2015 (June 9, 2015): 1–12. http://dx.doi.org/10.1155/2015/521721.

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In this study, two artificial neural network models (i.e., a radial basis function neural network, RBFN, and an adaptive neurofuzzy inference system approach, ANFIS) and a multilinear regression (MLR) model were developed to simulate the DO, TP, Chl a, and SD in the Mingder Reservoir of central Taiwan. The input variables of the neural network and the MLR models were determined using linear regression. The performances were evaluated using the RBFN, ANFIS, and MLR models based on statistical errors, including the mean absolute error, the root mean square error, and the correlation coefficient,

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Lin, Jie, and Chris W. Brown. "Near-IR Fiber-Optic Temperature Sensor." Applied Spectroscopy 47, no. 1 (1993): 62–68. http://dx.doi.org/10.1366/0003702934048424.

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A fiber-optic temperature sensor based on the perturbations of near-IR water bands has been developed. These fiber-optic sensors are very simple and readily fabricated. Models for expressing temperature can be developed by linear regression (LR) of the absorbance at one selected wavenumber, by multilinear regression (MLR) of the absorbances at several selected wavenumbers, or by principal component regression (PCR) using entire spectra. The standard errors of prediction for temperature are 0.53 to 1.64°C for the LR model, 0.22 to 0.85°C for the MLR model, and 0.16 to 0.32°C for the PCR model o

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de la Maza, Gabriel, Nicole Williams, Esteban Sáez, Kyle Rollins, and Christian Ledezma. "Liquefaction-Induced Lateral Spread in Lo Rojas, Coronel, Chile: Field Study and Numerical Modeling." Earthquake Spectra 33, no. 1 (2017): 219–40. http://dx.doi.org/10.1193/012015eqs012m.

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This paper describes a detailed field survey conducted at Lo Rojas fishermen port in Coronel, where extensive liquefaction-induced lateral spread was reported for the 2010, Mw 8.8 Maule earthquake. The survey includes SPT and SCPT soundings, as well as the use of surface-based geophysical techniques. The data was used to evaluate a multilinear regression (MLR) lateral-spread expression and to develop a detailed hydro-mechanical finite element model. Results of the MLR equation were over-conservative and proved to be very sensitive to the distance from the site to the energy source. On the othe

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Bui, Moayedi, Gör, Jaafari, and Foong. "Predicting Slope Stability Failure through Machine Learning Paradigms." ISPRS International Journal of Geo-Information 8, no. 9 (2019): 395. http://dx.doi.org/10.3390/ijgi8090395.

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In this study, we employed various machine learning-based techniques in predicting factor of safety against slope failures. Different regression methods namely, multi-layer perceptron (MLP), Gaussian process regression (GPR), multiple linear regression (MLR), simple linear regression (SLR), support vector regression (SVR) were used. Traditional methods of slope analysis (e.g., first established in the first half of the twentieth century) used widely as engineering design tools. Offering more progressive design tools, such as machine learning-based predictive algorithms, they draw the attention

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Roberts, Keith J., Brian A. Colle, Nickitas Georgas, and Stephan B. Munch. "A Regression-Based Approach for Cool-Season Storm Surge Predictions along the New York–New Jersey Coast." Journal of Applied Meteorology and Climatology 54, no. 8 (2015): 1773–91. http://dx.doi.org/10.1175/jamc-d-14-0314.1.

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AbstractA multilinear regression (MLR) approach is developed to predict 3-hourly storm surge during the cool-season months (1 October–31 March 31) between 1979 and 2012 using two different atmospheric reanalysis datasets and water-level observations at three stations along the New York–New Jersey coast (Atlantic City, New Jersey; the Battery in New York City; and Montauk Point, New York). The predictors of the MLR are specified to represent prolonged surface wind stress and a surface sea level pressure minimum for a boxed region near each station. The regression underpredicts relatively large

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Bueso-Bordils, Jose I., Pedro A. Aleman-López, Sara Costa-Piles, et al. "Obtaining Microbiological and Pharmacokinetic Highly Predictive Equations." Current Topics in Medicinal Chemistry 18, no. 11 (2018): 908–16. http://dx.doi.org/10.2174/1568026618666180712092326.

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In this paper, a Multilinear Regression (MLR) analysis has been carried out in order to accurately predict physicochemical properties and biological activities of a group of antibacterial quinolones by means of a set of structural descriptors called topological indices. The aim of this work is to develop prediction equations for these properties after collecting the maximum number of data from the literature on antibacterial quinolones. The five regression functions selected by presenting the best combination of various statistical parameters, subsequently validated by means of internal valida

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Katritzky, Alan R., Yueying Ren, Svetoslav H. Slavov, and Mati Karelson. "A comparative QSAR study of SVM and PPR in the correlation of lithium cation basicities." Collection of Czechoslovak Chemical Communications 74, no. 1 (2009): 217–41. http://dx.doi.org/10.1135/cccc2008191.

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Correlation of gas-phase lithium cation basicities (LCB) of 259 diverse compounds extends the published datasets utilizing multilinear, support vector machine (SVM) and projection pursuit regression (PPR) modeling. The best multiple linear regression (BMLR) method implemented in CODESSA was used to: (i) build multiparameter linear QSPR models and (ii) select set of descriptors for further treatment by the SVM and PPR. The external predictivity and the performance of each of the above methods was estimated and compared to those of the other techniques. The PPR method produced results superior t

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Gupta, Ishank, Deepak Devegowda, Vikram Jayaram, Chandra Rai, and Carl Sondergeld. "Machine learning regressors and their metrics to predict synthetic sonic and mechanical properties." Interpretation 7, no. 3 (2019): SF41—SF55. http://dx.doi.org/10.1190/int-2018-0255.1.

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Planning and optimizing completion design for hydraulic fracturing require a quantifiable understanding of the spatial distribution of the brittleness of the rock and other geomechanical properties. Eventually, the goal is to maximize the stimulated reservoir volume with minimal cost overhead. The compressional and shear velocities ([Formula: see text] and [Formula: see text], respectively) can also be used to calculate Young’s modulus, Poisson’s ratio, and other mechanical properties. In the field, sonic logs are not commonly acquired and operators often resort to regression to predict synthe

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Lestari, Evie Kama, Agus Dwi Ananto, Maulida Septiyana, and Saprizal Hadisaputra. "QSAR treatment of meisoindigo derivatives as a potentbreast anticancer agent." Acta Chimica Asiana 2, no. 2 (2019): 114. http://dx.doi.org/10.29303/aca.v2i2.12.

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A quantitative structure-activity relationship (QSAR) analysis of meisoindigo derivatives as a breast anticancer has been carried out. This study aimed to obtain the best QSAR model in order to design new meisoindigo based compounds with best anticancer activity. The semiempirical PM3 method was used for descriptor calculation. The best QSAR model was built using multilinear regression (MLR) with enter method. It was found that there were 19 new meisoindigo derivativeswith better predictive a potent anticancer agent. The best compound was (E)-2-(1-((3-ethylisoxazol-5-yl)methyl)-2-oxoindolin-3-

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Doucet, J. P., and A. Doucet-Panaye. "Dibenzoylhydrazines as Insect Growth Modulators: Topology-Based QSAR Modelling." Advances in Sciences and Engineering 12, no. 1 (2020): 28–40. http://dx.doi.org/10.32732/ase.2020.12.1.28.

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Dibenzoylhydrazines Xa-(C6H5)a-CO-N-(t-Bu)-NH-CO-(C6H5)b-Yb are efficient insect growth regulators with high activity and selectivity toward lepidopteran and coleopteran pests. For 123 congeneric molecules, a quantitative structure activity relationship model was built in the framework of the QSARINS package using 2D, Topology-based, PaDEL descriptors. Variable selection by GA-MLR allows building an efficient multilinear regression linking pEC50 values to nine structural variables. Robustness and quality of the model were carefully examined at various levels: data-fitting (recall), leave-one (

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Scotti, Luciana, Mariane Balerine Fernandes, Eric Muramatsu, et al. "13C NMR spectral data and molecular descriptors to predict the antioxidant activity of flavonoids." Brazilian Journal of Pharmaceutical Sciences 47, no. 2 (2011): 241–49. http://dx.doi.org/10.1590/s1984-82502011000200005.

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Tissue damage due to oxidative stress is directly linked to development of many, if not all, human morbidity factors and chronic diseases. In this context, the search for dietary natural occurring molecules with antioxidant activity, such as flavonoids, has become essential. In this study, we investigated a set of 41 flavonoids (23 flavones and 18 flavonols) analyzing their structures and biological antioxidant activity. The experimental data were submitted to a QSAR (quantitative structure-activity relationships) study. NMR 13C data were used to perform a Kohonen self-organizing map study, an

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Maya Gopal P S and Bhargavi R. "Selection of Important Features for Optimizing Crop Yield Prediction." International Journal of Agricultural and Environmental Information Systems 10, no. 3 (2019): 54–71. http://dx.doi.org/10.4018/ijaeis.2019070104.

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In agriculture, crop yield prediction is critical. Crop yield depends on various features including geographic, climate and biological. This research article discusses five Feature Selection (FS) algorithms namely Sequential Forward FS, Sequential Backward Elimination FS, Correlation based FS, Random Forest Variable Importance and the Variance Inflation Factor algorithm for feature selection. Data used for the analysis was drawn from secondary sources of the Tamil Nadu state Agriculture Department for a period of 30 years. 75% of data was used for training and 25% data was used for testing. Th

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Lin, Jie, and Chris W. Brown. "Simultaneous Determination of Physical and Chemical Properties of Sodium Chloride Solutions by near Infrared Spectroscopy." Journal of Near Infrared Spectroscopy 1, no. 2 (1993): 109–20. http://dx.doi.org/10.1255/jnirs.14.

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Near infrared (NIR) spectroscopy has been investigated as a new technique for the simultaneous determination of physical and chemical properties of NaCl solutions. The spectra of NaCl solutions (0 to 5 M) were measured with cuvettes in the 1100–2500 nm and 680–1230 nm regions at temperatures between 23.0 and 28.5°C, and with a fibre-optic probe in the 1100–1870 nm region at room temperature (23.0 ± 0.5°C). These spectra were correlated with various properties of NaCl solutions by principal component regression (PCR) and multilinear regression (MLR) models. The properties studied include water

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Kadela-Tomanek, Monika, Maria Jastrzębska, Krzysztof Marciniec, Elwira Chrobak, Ewa Bębenek, and Stanisław Boryczka. "Lipophilicity, Pharmacokinetic Properties, and Molecular Docking Study on SARS-CoV-2 Target for Betulin Triazole Derivatives with Attached 1,4-Quinone." Pharmaceutics 13, no. 6 (2021): 781. http://dx.doi.org/10.3390/pharmaceutics13060781.

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A key parameter in the design of new active compounds is lipophilicity, which influences the solubility and permeability through membranes. Lipophilicity affects the pharmacodynamic and toxicological profiles of compounds. These parameters can be determined experimentally or by using different calculation methods. The aim of the research was to determine the lipophilicity of betulin triazole derivatives with attached 1,4-quinone using thin layer chromatography in a reverse phase system and a computer program to calculate its theoretical model. The physiochemical and pharmacokinetic properties

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16

Maeda, Hisashi, Yukihiro Ozaki, Munehiro Tanaka, Nobuyuki Hayashi, and Takayuki Kojima. "Near Infrared Spectroscopy and Chemometrics Studies of Temperature-Dependent Spectral Variations of Water: Relationship between Spectral Changes and Hydrogen Bonds." Journal of Near Infrared Spectroscopy 3, no. 4 (1995): 191–201. http://dx.doi.org/10.1255/jnirs.69.

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The present study aims to provide new insights into the temperature-dependent spectral variations in the near infrared (NIR) region of the spectrum of water by comparing chemometrics with spectroscopic analysis. Fourier transform (FT)-NIR spectra of water in the 9000–5500 cm−1 region have been measured over a temperature range of 5–85°C. The observed spectral changes have been analysed by both chemometrics, such as multilinear regression (MLR), principal component regression (PCR) and partial least squares (PLS) regression, and spectroscopic data analyses, such as second derivative, difference

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17

Gozalbes, Rafael, Monique Brun-Pascaud, Ramon Garcia-Domenech, et al. "Anti-Toxoplasma Activities of 24 Quinolones and Fluoroquinolones In Vitro: Prediction of Activity by Molecular Topology and Virtual Computational Techniques." Antimicrobial Agents and Chemotherapy 44, no. 10 (2000): 2771–76. http://dx.doi.org/10.1128/aac.44.10.2771-2776.2000.

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ABSTRACT The apicoplast, a plastid-like organelle of Toxoplasma gondii, is thought to be a unique drug target for quinolones. In this study, we assessed the in vitro activity of quinolones againstT. gondii and developed new quantitative structure-activity relationship models able to predict this activity. The anti-Toxoplasma activities of 24 quinolones were examined by means of linear discriminant analysis (LDA) using topological indices as structural descriptors. In parallel, in vitro 50% inhibitory concentrations (IC50s) were determined in tissue culture. A multilinear regression (MLR) analy

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18

D’Archivio, Angelo A., and Andrea Giannitto. "Characterisation of Gas-Chromatographic Poly(Siloxane) Stationary Phases by Theoretical Molecular Descriptors and Prediction of McReynolds Constants." International Journal of Molecular Sciences 20, no. 9 (2019): 2120. http://dx.doi.org/10.3390/ijms20092120.

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Retention in gas–liquid chromatography is mainly governed by the extent of intermolecular interactions between the solute and the stationary phase. While molecular descriptors of computational origin are commonly used to encode the effect of the solute structure in quantitative structure–retention relationship (QSRR) approaches, characterisation of stationary phases is historically based on empirical scales, the McReynolds system of phase constants being one of the most popular. In this work, poly(siloxane) stationary phases, which occupy a dominant position in modern gas–liquid chromatography

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Jiang, Han, Yajie Zou, Shen Zhang, Jinjun Tang, and Yinhai Wang. "Short-Term Speed Prediction Using Remote Microwave Sensor Data: Machine Learning versus Statistical Model." Mathematical Problems in Engineering 2016 (2016): 1–13. http://dx.doi.org/10.1155/2016/9236156.

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Recently, a number of short-term speed prediction approaches have been developed, in which most algorithms are based on machine learning and statistical theory. This paper examined the multistep ahead prediction performance of eight different models using the 2-minute travel speed data collected from three Remote Traffic Microwave Sensors located on a southbound segment of 4th ring road in Beijing City. Specifically, we consider five machine learning methods: Back Propagation Neural Network (BPNN), nonlinear autoregressive model with exogenous inputs neural network (NARXNN), support vector mac

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Hadanau, R. "A QSAR Modeling on Aurone Derivatives as Antimalarial Agents." Asian Journal of Chemistry 32, no. 11 (2020): 2839–45. http://dx.doi.org/10.14233/ajchem.2020.22846.

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A quantitative structure activity relationship (QSAR) analysis was performed on several compound and aurone derivatives (1-16) and 17-21 compounds were used as internal and external tests, respectively. Studies have investigated aurone derivatives; however, for aurone compounds, QSAR analysis has not been conducted. The semi-empirical PM3 method of HyperChem for Windows 8.0 was used to optimise the aurone derivative structures to acquire descriptors. For 15 influential descriptors, the multilinear regression MLR analysis was conducted by employing the backward method, and four new QSAR models

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Gozalbes, Rafael, Monique Brun-Pascaud, Ramon García-Domenech, et al. "Prediction of Quinolone Activity against Mycobacterium avium by Molecular Topology and Virtual Computational Screening." Antimicrobial Agents and Chemotherapy 44, no. 10 (2000): 2764–70. http://dx.doi.org/10.1128/aac.44.10.2764-2770.2000.

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ABSTRACT We conducted a quantitative structure-activity relationship study using a database of 158 quinolones previously tested againstMycobacterium avium-M. intracellulare complex in order to develop a model capable of predicting the activity of new quinolones against the M. avium-M. intracellulare complex in vitro. Topological indices were used as structural descriptors and were related to anti-M. avium-M. intracellulare complex activity by using the linear discriminant analysis (LDA) statistical technique. The discriminant equation thus obtained correctly classified 137 of the 158 quinolone

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Shen, Shijing, Yong Pan, Xianke Ji, Yuqing Ni, and Juncheng Jiang. "Prediction of the Auto-Ignition Temperatures of Binary Miscible Liquid Mixtures from Molecular Structures." International Journal of Molecular Sciences 20, no. 9 (2019): 2084. http://dx.doi.org/10.3390/ijms20092084.

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A quantitative structure-property relationship (QSPR) study is performed to predict the auto-ignition temperatures (AITs) of binary liquid mixtures based on their molecular structures. The Simplex Representation of Molecular Structure (SiRMS) methodology was employed to describe the structure characteristics of a series of 132 binary miscible liquid mixtures. The most rigorous “compounds out” strategy was employed to divide the dataset into the training set and test set. The genetic algorithm (GA) combined with multiple linear regression (MLR) was used to select the best subset of SiRMS descri

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Jović, Ozren, and Tomislav Šmuc. "Combined Machine Learning and Molecular Modelling Workflow for the Recognition of Potentially Novel Fungicides." Molecules 25, no. 9 (2020): 2198. http://dx.doi.org/10.3390/molecules25092198.

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Novel machine learning and molecular modelling filtering procedures for drug repurposing have been carried out for the recognition of the novel fungicide targets of Cyp51 and Erg2. Classification and regression approaches on molecular descriptors have been performed using stepwise multilinear regression (FS-MLR), uninformative-variable elimination partial-least square regression, and a non-linear method called Forward Stepwise Limited Correlation Random Forest (FS-LM-RF). Altogether, 112 prediction models from two different approaches have been built for the descriptor recognition of fungicide

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Zhou, Jinfeng, Rongwu Wang, Xiongying Wu, and Bugao Xu. "Fiber-Content Measurement of Wool–Cashmere Blends Using Near-Infrared Spectroscopy." Applied Spectroscopy 71, no. 10 (2017): 2367–76. http://dx.doi.org/10.1177/0003702817713480.

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Cashmere and wool are two protein fibers with analogous geometrical attributes, but distinct physical properties. Due to its scarcity and unique features, cashmere is a much more expensive fiber than wool. In the textile production, cashmere is often intentionally blended with fine wool in order to reduce the material cost. To identify the fiber contents of a wool–cashmere blend is important to quality control and product classification. The goal of this study is to develop a reliable method for estimating fiber contents in wool–cashmere blends based on near-infrared (NIR) spectroscopy. In thi

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Nourani, Vahid, Huseyin Gokcekus, and Gebre Gelete. "Estimation of Suspended Sediment Load Using Artificial Intelligence-Based Ensemble Model." Complexity 2021 (February 17, 2021): 1–19. http://dx.doi.org/10.1155/2021/6633760.

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Suspended sediment modeling is an important subject for decision-makers at the catchment level. Accurate and reliable modeling of suspended sediment load (SSL) is important for planning, managing, and designing of water resource structures and river systems. The objective of this study was to develop artificial intelligence- (AI-) based ensemble methods for modeling SSL in Katar catchment, Ethiopia. In this paper, three single AI-based models, that is, support vector machine (SVM), adaptive neurofuzzy inference system (ANFIS), feed-forward neural network (FFNN), and one conventional multilinea

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Cartes, J. E., T. Brey, J. C. Sorbe, and F. Maynou. "Comparing productionbiomass ratios of benthos and suprabenthos in macrofaunal marine crustaceans." Canadian Journal of Fisheries and Aquatic Sciences 59, no. 10 (2002): 1616–25. http://dx.doi.org/10.1139/f02-130.

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Using available data from the literature, we compared the productionbiomass ratios (P/B) between the suprabenthic (= hyperbenthic) and the benthic (infaunaepifauna) species within the group of the macrofaunal marine crustaceans. This data set consists of 91 P/B estimates (26 for suprabenthos and 65 for infaunaepifauna) for 49 different species. Suprabenthic crustacean P/B was significantly higher than P/B of benthic crustacean (post-hoc Scheffé test; one-way analysis of covariance, ANCOVA; p < 103) and also of other (noncrustacean) benthic invertebrate (p < 104). Predictive multilin

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Pan, Yong, Xianke Ji, Li Ding, and Juncheng Jiang. "Prediction of Lower Flammability Limits for Binary Hydrocarbon Gases by Quantitative Structure—Property Relationship Approach." Molecules 24, no. 4 (2019): 748. http://dx.doi.org/10.3390/molecules24040748.

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The lower flammability limit (LFL) is one of the most important parameters for evaluating the fire and explosion hazards of flammable gases or vapors. This study proposed quantitative structure−property relationship (QSPR) models to predict the LFL of binary hydrocarbon gases from their molecular structures. Twelve different mixing rules were employed to derive mixture descriptors for describing the structures characteristics of a series of 181 binary hydrocarbon mixtures. Genetic algorithm (GA)-based multiple linear regression (MLR) was used to select the most statistically effective mixture

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Zaki, Magdi E. A., Sami A. Al-Hussain, Vijay H. Masand, et al. "Identification of Anti-SARS-CoV-2 Compounds from Food Using QSAR-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation Analysis." Pharmaceuticals 14, no. 4 (2021): 357. http://dx.doi.org/10.3390/ph14040357.

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Due to the genetic similarity between SARS-CoV-2 and SARS-CoV, the present work endeavored to derive a balanced Quantitative Structure−Activity Relationship (QSAR) model, molecular docking, and molecular dynamics (MD) simulation studies to identify novel molecules having inhibitory potential against the main protease (Mpro) of SARS-CoV-2. The QSAR analysis developed on multivariate GA–MLR (Genetic Algorithm–Multilinear Regression) model with acceptable statistical performance (R2 = 0.898, Q2loo = 0.859, etc.). QSAR analysis attributed the good correlation with different types of atoms like non

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Asmara, Anjar Purba, Reni Silvia Nasution, and Rosi Minarty. "QSAR Modeling of Compounds Derived from 1,2,3-Triazolopiperidine as DPP-4 Enzyme Inhibitors Using Semiempirical AM1." JKPK (Jurnal Kimia dan Pendidikan Kimia) 5, no. 1 (2020): 70. http://dx.doi.org/10.20961/jkpk.v5i1.28358.

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<p>This study aims to model the derived compounds of 1,2,3-triazolopiperidine using semiempirical method AM1 and determine the further derivation with the better IC<sub>50</sub> values against DPP-4 enzyme theoretically. This research employed ChemDraw Pro 12 software for for 2D structural drawing, Hyperchem 8.0 for 3D modelling, and MLR statistical analysis for modeling QSAR equations. The semiempirical method was likely to be the appropriate platform to apply because the correlation coefficient of H<sup>1 </sup>NMR chemical shift between theoretical and actual

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Chayawan, Chayawan, Cosimo Toma, Emilio Benfenati, and Ana Y. Caballero Alfonso. "Towards an Understanding of the Mode of Action of Human Aromatase Activity for Azoles through Quantum Chemical Descriptors-Based Regression and Structure Activity Relationship Modeling Analysis." Molecules 25, no. 3 (2020): 739. http://dx.doi.org/10.3390/molecules25030739.

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Aromatase is an enzyme member of the cytochrome P450 superfamily coded by the CYP19A1 gene. Its main action is the conversion of androgens into estrogens, transforming androstenedione into estrone and testosterone into estradiol. This enzyme is present in several tissues and it has a key role in the maintenance of the balance of androgens and estrogens, and therefore in the regulation of the endocrine system. With regard to chemical safety and human health, azoles, which are used as agrochemicals and pharmaceuticals, are potential endocrine disruptors due to their agonist or antagonist interac

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Ferguson Aikins, Emmanuel, and Usha Ramanathan. "Key factors of carbon footprint in the UK food supply chains: a new perspective of life cycle assessment." International Journal of Operations & Production Management 40, no. 7/8 (2020): 945–70. http://dx.doi.org/10.1108/ijopm-06-2019-0478.

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PurposeThe purpose of this paper is to empirically identify key factors of UK food supply chains (SCs) that significantly contribute to CO2 emissions (CO2e) taking into account the life cycle assessment (LCA). The UK food supply chain includes imports from other countries.Design/methodology/approachThis research develops a conceptual framework from extant literature. Secondary data obtained from ONS and FAOSTAT covering from 1990 to 2014 are analysed using Multilinear Regression (MLR) and Stochastic Frontier Analysis (SFA) to identify the factors relating to CO2 emissions significance, and the

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Monteiro dos Santos, Djacinto, Luciana Varanda Rizzo, Samara Carbone, Patrick Schlag, and Paulo Artaxo. "Physical and chemical properties of urban aerosols in São Paulo, Brazil: links between composition and size distribution of submicron particles." Atmospheric Chemistry and Physics 21, no. 11 (2021): 8761–73. http://dx.doi.org/10.5194/acp-21-8761-2021.

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Abstract. In this work, the relationships between size and composition of submicron particles (PM1) were analyzed at an urban site in the Metropolitan Area of São Paulo (MASP), a megacity with about 21 million inhabitants. The measurements were carried out from 20 December 2016 to 15 March 2017. The chemical composition was measured with an Aerodyne Aerosol Chemical Speciation Monitor and size distribution with a TSI Scanning Mobility Particle Sizer 3082. PM1 mass concentrations in the MASP had an average mass concentration of 11.4 µg m−3. Organic aerosol (OA) dominated the PM1 composition (56

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Pazmiño, Andrea, Sophie Godin-Beekmann, Alain Hauchecorne, et al. "Multiple symptoms of total ozone recovery inside the Antarctic vortex during austral spring." Atmospheric Chemistry and Physics 18, no. 10 (2018): 7557–72. http://dx.doi.org/10.5194/acp-18-7557-2018.

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Abstract. The long-term evolution of total ozone column inside the Antarctic polar vortex is investigated over the 1980–2017 period. Trend analyses are performed using a multilinear regression (MLR) model based on various proxies for the evaluation of ozone interannual variability (heat flux, quasi-biennial oscillation, solar flux, Antarctic oscillation and aerosols). Annual total ozone column measurements corresponding to the mean monthly values inside the vortex in September and during the period of maximum ozone depletion from 15 September to 15 October are used. Total ozone columns from th

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USMAN, Abdullahi Garba, Selin IŞIK, Sani Isah ABBA, and Filiz MERİÇLİ. "Artificial intelligence–based models for the qualitative and quantitative prediction of a phytochemical compound using HPLC method." TURKISH JOURNAL OF CHEMISTRY 44, no. 5 (2020): 1339–51. http://dx.doi.org/10.3906/kim-2003-6.

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Isoquercitrin is a flavonoid chemical compound that can be extracted from different plant species such as Mangifera indica (mango), Rheum nobile, Annona squamosal, Camellia sinensis (tea), and coriander (Coriandrum sativum L.). It possesses various biological activities such as the prevention of thromboembolism and has anticancer, antiinflammatory, and antifatigue activities. Therefore, there is a critical need to elucidate and predict the qualitative and quantitative properties of this phytochemical compound using the high performance liquid chromatography (HPLC) technique. In this paper, thr

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Oliveira, R. A., R. Näsi, O. Niemeläinen, et al. "ASSESSMENT OF RGB AND HYPERSPECTRAL UAV REMOTE SENSING FOR GRASS QUANTITY AND QUALITY ESTIMATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 4, 2019): 489–94. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-489-2019.

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<p><strong>Abstract.</strong> The information on the grass quantity and quality is needed for several times in a growing season for making optimal decisions about the harvesting time and the fertiliser rate, especially in northern countries, where grass swards quality declines and yield increases rapidly in the primary growth. We studied the potential of UAV-based photogrammetry and spectral imaging in grass quality and quantity estimation. To study this, a trial site with large variation in the quantity and quality parameters was established by using different nitrogen ferti

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Ealo, Marina, Andrés Alastuey, Noemí Pérez, Anna Ripoll, Xavier Querol, and Marco Pandolfi. "Impact of aerosol particle sources on optical properties in urban, regional and remote areas in the north-western Mediterranean." Atmospheric Chemistry and Physics 18, no. 2 (2018): 1149–69. http://dx.doi.org/10.5194/acp-18-1149-2018.

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Abstract. Further research is needed to reduce the existing uncertainties on the effect that specific aerosol particle sources have on light extinction and consequently on climate. This study presents a new approach that aims to quantify the mass scattering and absorption efficiencies (MSEs and MAEs) of different aerosol sources at urban (Barcelona – BCN), regional (Montseny – MSY) and remote (Montsec – MSA) background sites in the north-western (NW) Mediterranean. An analysis of source apportionment to the measured multi-wavelength light scattering (σsp) and absorption (σap) coefficients was

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Bacher, Ulrike, Susanne Schnittger, Wolfgang Kern, et al. "The Detection of Multilineage Dysplasia (MLD) Has No Influence on Prognosis in NPM1 Mutated Acute Myeloid Leukemia (AML) with Normal Karyotype." Blood 112, no. 11 (2008): 2518. http://dx.doi.org/10.1182/blood.v112.11.2518.2518.

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Abstract Acute myeloid leukemia with mutated nucleophosmin (AML NPM1mut) represents about one-third of all adult AML and shows distinctive biological and clinical features. For this reason, AML NPM1mut is planned to be included as a separate category in the revised WHO classification. A yet controversial issue, however, is whether AML NPM1mut with or without multilineage dysplasia (MLD) may differ biologically and clinically, as the presence of MLD might confer a negative prognostic impact. A further feature that was suggested to be typical for NPM1 mutated AML is “cup-like” morphology of blas

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Mumpuni, Esti, Agus Purwanggana, Esti Mulatsari, and Yafi Lakstian. "Desain Senyawa Turunan Kuersetin sebagai Inhibitor Pertumbuhan Candida Albicans Menggunakan Analisis QSAR." Talenta Conference Series: Tropical Medicine (TM) 1, no. 3 (2018): 056–60. http://dx.doi.org/10.32734/tm.v1i3.262.

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Candida albicans adalah sejenis jamur oportunistik yang patogen bagi manusia dan terlibat dalam proses Oral Candidiasis (OC). Candida albicans merupakan spesies yang paling umum diisolasi dalam kasus klinis infeksi jamur invasif. Candida albicans hidup secara komensal di usus, faringeal oral, saluran kemih dan kulit. Senyawa alam seperti flavonoid, telah banyak dikembangkan untuk menghambat pertumbuhan Candida albicans salah satu diantaranya adalah kuersetin yang memiliki nilai MIC 197 µg/mL dalam menghambat pertumbuhan Candida albicans. Upaya peningkatan daya penghambatan kuersetin dalam pros

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Tobiasson, Magnus, Donal McLornan, Mohsen Karimi, et al. "Mutations in Histone Modulators Are Associated with Prolonged Survival during Azacitidine Therapy." Blood 126, no. 23 (2015): 2839. http://dx.doi.org/10.1182/blood.v126.23.2839.2839.

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Abstract Early therapeutic decision-making is crucial in patients with higher-risk MDS where median survival is only around one year. Azacitidine prolongs survival for these patients (Fenaux et al, Lancet Oncology 2009) but clinically relevant biomarkers remain to be identified. We evaluated retrospectively, the impact of clinical parameters and mutational profiles in 134 consecutive patients treated with a median number of 7 cycles of Azacitidine (range 1-45), in accordance to European guidelines. The vast majority (n=114) had higher-risk disease i.e. MDS with IPSS int-2 or high, AML with mul

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Sözer, M., H. Haykiri-Acma, and S. Yaman. "Prediction of Calorific Value of Coal by Multilinear Regression and Analysis of Variance." Journal of Energy Resources Technology 144, no. 1 (2021). http://dx.doi.org/10.1115/1.4050880.

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Abstract The higher heating value (HHV) of 84 coal samples including hard coals, lignites, and anthracites from Russia, Colombia, South Africa, Turkey, and Ukrania was predicted by multilinear regression (MLR) method based on proximate and ultimate analysis data. The prediction accuracy of the correlation equations was tested by Analysis of variance method. The significance of the predictive parameters was studied considering R2, adj. R2, standard error, F-values, and p-values. Although relationships between HHV and any of the single parameters were almost irregular, MLR provided a reasonable

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Abdulsalam, Jibril, Abiodun Ismail Lawal, Ramadimetja Lizah Setsepu, Moshood Onifade, and Samson Bada. "Application of gene expression programming, artificial neural network and multilinear regression in predicting hydrochar physicochemical properties." Bioresources and Bioprocessing 7, no. 1 (2020). http://dx.doi.org/10.1186/s40643-020-00350-6.

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AbstractGlobally, the provision of energy is becoming an absolute necessity. Biomass resources are abundant and have been described as a potential alternative source of energy. However, it is important to assess the fuel characteristics of the various available biomass sources. Soft computing techniques are presented in this study to predict the mass yield (MY), energy yield (EY), and higher heating value (HHV) of hydrothermally carbonized biomass using Gene Expression Programming (GEP), multiple-input single output-artificial neural network (MISO-ANN), and Multilinear regression (MLR). The th

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"Corrigenda for vol. 77, Pages 1185-1197." Journal of Applied Physiology 78, no. 3 (1995): 1209. http://dx.doi.org/10.1152/jappl.1995.78.3.-r1209.

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Pages 1185–1197: S. Kano, C.J. Lanteri, A.W. Duncan, and P.D. Sly. “Influence of nonlinearities on estimates of respiratory mechanics using multilinear regression analysis.” Page 1187, Equations 4,5 and 6 and related information in the surrounding paragraphs were not printed correctly. The Respiratory mechanics section should read as follows: Respiratory mechanics. To evaluate the effect of nonlinearities on estimates of respiratory mechanics and to estimate overdistension using MLR analysis, respiratory mechanics were calculated with three different models: fitting the equation of motion of a

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Adebunmi, Kayode O., Temilola M. Adepoju, Gafari A. Adepoju, and Akeem O. Bisiriyu. "Hybrid Based Artificial Intellegence Short –Term Load Forecasting." Journal of Engineering Research and Reports, May 10, 2021, 75–87. http://dx.doi.org/10.9734/jerr/2021/v20i617330.

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Electrical power load forecasting, which forms a key element in the power industry's electricity preparation, is used for providing required data for day-to-day system management activities and power utility unit participation. Since the statistical method is a linear model, and the load and meteorological parameters have a nonlinear relationship, the statistical method for load forecasting involves a great calculation time for parameter recognition. Using this tool for load forecasting often results in a major mistake in prediction. Due to the disadvantages of the statistical method of load f

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Zamri, Nur Farrah Najwa, Abdul Halim Abdul Majid, Houcine Meddour, and Noor-Asma Jamaluddin. "The Influence of Feedback Conversation on Employee Performance in Malaysian’s Telecommunication Company." Journal of Business and Social Review in Emerging Economies 7, no. 3 (2021). http://dx.doi.org/10.26710/jbsee.v7i3.1731.

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Purpose: Feedback conversation is the process of conveying information in the performance appraisal process. It helps employees to develop the right and appropriate behavior in order to achieve the targeted outcome. This study investigates the influence of feedback conversation (i.e., feedback frequency, the credibility of the feedback provider, receptive capability, organizational culture, and national culture) on employees’ performance in Malaysian-based telecommunication companies. Design/Methodology/Approach: The study utilized a descriptive quantitative approach, in which a 5-point

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Baath, Gurjinder S., K. Colton Flynn, Prasanna H. Gowda, Vijaya Gopal Kakani, and Brian K. Northup. "Detecting Biophysical Characteristics and Nitrogen Status of Finger Millet at Hyperspectral and Multispectral Resolutions." Frontiers in Agronomy 2 (January 20, 2021). http://dx.doi.org/10.3389/fagro.2020.604598.

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Finger millet (Eleusine coracana Gaertn L.) is an important grain crop for small farmers in many countries. Reliable estimates of crop parameters, such as crop growth and nitrogen (N) content, through remote sensing techniques can improve in-season management of finger millet. This study investigated the relationships of hyperspectral reflectance with canopy height, green canopy cover, leaf area index (LAI), and N concentrations of finger millet using an optimal waveband selection procedure with partial least square regression (PLSR). Predictive performance of 13 vegetation indices (VIs) compu

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Keprate, Arvind, R. M. Chandima Ratnayake, and Shankar Sankararaman. "Comparison of Various Surrogate Models to Predict Stress Intensity Factor of a Crack Propagating in Offshore Piping." Journal of Offshore Mechanics and Arctic Engineering 139, no. 6 (2017). http://dx.doi.org/10.1115/1.4037290.

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This paper examines the applicability of the different surrogate-models (SMs) to predict the stress intensity factor (SIF) of a crack propagating in topside piping, as an inexpensive alternative to the finite element methods (FEM). Six different SMs, namely, multilinear regression (MLR), polynomial regression (PR) of order two, three, and four (with interaction), Gaussian process regression (GPR), neural networks (NN), relevance vector regression (RVR), and support vector regression (SVR) have been tested. Seventy data points (consisting of load (L), crack depth (a), half crack length (c) and

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Wahyu Ardhia, Rediana, and Lidia Mayangsari. "A Study of Factors Influencing Indonesian Consumers’ Purchase Intention towards Its Local Fashion Brands." KnE Social Sciences, March 23, 2020. http://dx.doi.org/10.18502/kss.v4i6.6669.

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The rise of Indonesian local fashion brands could be seen from the phenomenon that is happening in the last few years. Kapferer and Schuiling (2016), mentioned that companies have the tendency to focus on the expansion of global brands that then affect to the disadvantage of local brands. While it is quite the contrary of what happens in Indonesia based on Deloitte (2016) findings that most Indonesians are still preferred to buy local fashion brands instead of global fashion brands, the only Indonesian category that prefers to buy global fashion brands are people with monthly income above IDR

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Guillemant, Julie, Marion Lacoue-Nègre, Alexandra Berlioz-Barbier, et al. "Towards a new pseudo-quantitative approach to evaluate the ionization response of nitrogen compounds in complex matrices." Scientific Reports 11, no. 1 (2021). http://dx.doi.org/10.1038/s41598-021-85854-7.

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AbstractUltra high-resolution mass spectrometry (FT-ICR MS) coupled to electrospray ionization (ESI) provides unprecedented molecular characterization of complex matrices such as petroleum products. However, ESI faces major ionization competition phenomena that prevent the absolute quantification of the compounds of interest. On the other hand, comprehensive two-dimensional gas chromatography (GC × GC) coupled to specific detectors (HRMS or NCD) is able to quantify the main families identified in these complex matrices. In this paper, this innovative dual approach has been used to evaluate the

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