Stepwise Multiple Linear Regression Method Research Articles

Evaluation of complex copper ore sorting: Effect of optical filtering on particle recognition

In mixed and multi-component mineral systems, the reflectance spectra of individual minerals interfere with the reflectance/absorbance features of other minerals and random spectra can form. This contradictory case causes difficulty in implementing ore sorting to certain minerals. Hence, filtering out certain wave lengths may prevent this situation which makes it difficult for an ore sorter to perform a selective and efficient separation. The scope of this study is to investigate the feasibility of the optical filtering to enhance the differences in the reflectance features of mineral grains, and to compare the possible separation performances of the ore sorters under the best filtered and unfiltered conditions.Within the experimental studies, a new experimental setup which runs its uniquely coded software was designed. Additionally, an adjustable filter cartridge apparatus was developed enabling to mount the wavelength specific filters in front of the conventional sensors which support universal f-mount type lenses. A representative sample batch consisting of 31 grains of complex copper ore was prepared. Filtered and unfiltered images of each grain in between 450 and 1650 nm wavelength range were acquired carefully with the designed experimental setup. Following the data extraction by imaging studies, each particle was weighed, ground, and analyzed to determine chemical compositions. Thus, the reflectance values and chemical analysis data of each particle with each filter were obtained. Principal component analysis (PCA), partial least square analysis (PLS) and stepwise multiple linear regression (SMLR) methods were used to evaluate the resulting data in order to establish meaningful relationships between dominant chemical contents and reflectance values of each individual particle. Hence, the effect of using optical filters in altering the differences among the reflectance values of complex copper ore grains has been determined. Following the determination of best filters and wave lengths, projected product qualities of a conjectural optical sorting operation integrated with optical filters have been analytically investigated. It was concluded that an alteration in the relationship between % sulphide content and reflectance values was observed over 1500 nm wavelengths in comparison to the unfiltered and other filtered conditions. Evaluation of the overall results showed that up to 73.30% of Au, 96.14% of Ag, and 86.24% of CuFeS2 in feed can be recovered when a long-pass 1500 nm filter was used.

Pedotransfer functions for estimating the field capacity and permanent wilting point in the critical zone of the Loess Plateau, China

Field capacity (FC) and permanent wilting point (PWP) are important physical properties for evaluating the available soil water storage, as well as being used as input variables for related agro-hydrological models. Direct measurements of FC and PWP are time consuming and expensive, and thus, it is necessary to develop related pedotransfer functions (PTFs). In this study, stepwise multiple linear regression (SMLR) and artificial neural network (ANN) methods were used to develop FC and PWP PTFs for the deep layer of the Loess Plateau based on the bulk density (BD),sand, silt, clay, and soil organic carbon (SOC) contents. Soil core drilling was used to obtain undisturbed soil cores from three typical sites on the Loess Plateau, which ranged from the top of the soil profile to the bedrock (0–200 m). The FC and PWP were measured using the centrifugation method at suctions of − 33 and − 1500 kPa, respectively. The results showed that FC and PWP exhibited moderate variation where the coefficients of variation were 11 and 23%, respectively. FC had significant correlations with sand, silt, clay, and SOC (P < 0.01), while there were also significant correlations between all of the variables and PWP. In addition, sand was an important input variable for predicting FC, and clay and BD for predicting PWP. The performance of the SMLR and ANN approaches was similar. In this study, we developed new PTFs for FC and PWP as the first set of PTFs based on data obtained from deep profiles in the Loess Plateau. These PTFs are important for evaluating the soil water conditions in the deep profile in this region.

MODELING OF CARBONIC ANHYDRASE (II) INHIBITORY ACTIVITIES OF SULPHONILAMIDE SCHIFF BASES BY ARTIFICIAL NEURAL NETWORK TRAINED WITH DIFFERENT NUMERICAL TECHNIQUES

Objective: The aim of the present study was to develop robust linear and non-linear Quantitative Structure-Activity Relationship (QSAR) models for exploring the relationship between the structural features of a series of sulphanilamide Schiff bases and their CA (II) inhibition activities.Methods: QSAR modeling of carbonic anhydrase (II) inhibiting activities of a series of sulphanilamide Schiff bases as a function of theoretically derived molecular descriptors calculated by Dragon software was established linearly by stepwise multiple linear regression (SW-MLR) method and non-linearly by artificial neural network (ANN) method, trained with different numerical techniques namely, Scaled conjugate gradient (SCG), quasi-Newton (BFGS), and Levenberg-Marquardt (LM) algorithm. SW-MLR method was also used to select descriptors from large descriptor pool. After the selection of variables, best selected linear model was validated by Y-randomization test. The applicability domain was assessed by the normalized mean Euclidean distance value for each compound. The prediction quality of proposed non-linear QSAR models was tested externally using validation and test set.Results: The low value of R2average = 0.214 from the Y-randomization test and no significant correlation between the selected descriptors indicates that linear model is reliable, and robust. Applicability domain analysis has also revealed that the suggested model has acceptable predictability. To explore non-linear relationship between selected descriptors and the target property, ANN approach trained with three supervised algorithms (BFGS, SCG and LM) was used. Statistical comparison of the quality of models obtained using ANN method trained with above mentioned three algorithms with SW-MLR model shows that ANN with 4-3-1 architecture and trained with LM algorithm has better predictive power as indicated by low RMSEval (0.11), MAPEval (11.95) values and high R2val (0.96) value.Conclusion: The results of this work indicated the ANN trained with fastest Levenberg-Marqardt algorithm is a promising tool for establishing non-linear relationship between selected sulphanilamide Schiffbases and their CA (II) inhibition values.

Using EEG for Predicting User Preferences of Physical Compliance in Human-Robot Cooperation

Using EEG for Predicting User Preferences of Physical Compliance in Human-Robot Cooperation

Multiple linear regression and random forest to predict and map soil properties using data from portable X-ray fluorescence spectrometer (pXRF)

ABSTRACT Determination of soil properties helps in the correct management of soil fertility. The portable X-ray fluorescence spectrometer (pXRF) has been recently adopted to determine total chemical element contents in soils, allowing soil property inferences. However, these studies are still scarce in Brazil and other countries. The objectives of this work were to predict soil properties using pXRF data, comparing stepwise multiple linear regression (SMLR) and random forest (RF) methods, as well as mapping and validating soil properties. 120 soil samples were collected at three depths and submitted to laboratory analyses. pXRF was used in the samples and total element contents were determined. From pXRF data, SMLR and RF were used to predict soil laboratory results, reflecting soil properties, and the models were validated. The best method was used to spatialize soil properties. Using SMLR, models had high values of R² (≥0.8), however the highest accuracy was obtained in RF modeling. Exchangeable Ca, Al, Mg, potential and effective cation exchange capacity, soil organic matter, pH, and base saturation had adequate adjustment and accurate predictions with RF. Eight out of the 10 soil properties predicted by RF using pXRF data had CaO as the most important variable helping predictions, followed by P2O5, Zn and Cr. Maps generated using RF from pXRF data had high accuracy for six soil properties, reaching R2 up to 0.83. pXRF in association with RF can be used to predict soil properties with high accuracy at low cost and time, besides providing variables aiding digital soil mapping.

Controlling factor analysis and prediction of the quality of tight sandstone reservoirs: A case study of the He8 Member in the eastern Sulige Gas Field, Ordos Basin, China

The He8 Member is the main producing zone in the Permian rocks of the eastern Sulige Gas Field in the Ordos Basin. It is characterized by low(10%≤Φ<15%) to ultralow(<10%) porosity and ultralow permeability(K < 1mD). To realize efficient exploration and development in this gas field, it is necessary to study the genesis of tight sandstone reservoirs and clarify the factors controlling reservoir development, in order to establish effective methods for reservoir quality prediction. The composition, pore structure, diagenetic type and strength of sandstone reservoirs, as well as their authigenic mineral contents and types, were analyzed. The techniques including casting thin sections, SEM, X-ray diffraction, high-pressure mercury intrusion, porosity-permeability tests and fluid inclusion homogenization temperature tests were used, in order to reconstruct the diagenetic and pore evolution history of the sandstone reservoirs. The effects of 12 sedimentary and diagenetic factors on porosity and permeability were analyzed using the stepwise multiple linear regression method, and a prediction model of reservoir quality (including both porosity and permeability) was constructed. The results show that the reservoir rock is dominated by litharenite, which accounts for 69.76%, followed by sublitharenite, which accounts for 26.15%. The reservoirs are characterized by low to ultralow porosity (porosity ranges from 0.29 to 16.6%, with an average of 7.51%), ultralow permeability (horizontal permeability ranges from 0.0065 mD to 5.21 mD, with most values being less than 0.4 mD). Displacement pressure is high (which ranges from 0.48 to 4.2 MPa, with an average of 1.48 MPa). Sandstone reservoirs are reformed by moderate compaction, moderate to strong cementation and weak dissolution. Cementation mainly occurs as quartz overgrowths, authigenic quartz, ferrocalcite, nonferrous calcite and clay minerals. Clay minerals are dominated by grain-coating chlorite, kaolinite and illite. Dissolution has little influence on reservoir quality. Reservoir porosity is mainly controlled by the contents of kaolinite, siliceous cement, illite, chlorite, and feldspar, as well as the degree of compaction. On the other hand, reservoir permeability is mainly controlled by the amount of siliceous cement, quartz, illite, and kaolinite, as well as the degree of compaction. The porosity and permeability were predicted using the equation established by multiple linear stepwise regression analysis, and good results were achieved. In this paper, the factors that influence the quality of the sandstone reservoir of the He8 Member in the eastern Sulige Gas Field were clarified, and a corresponding prediction model of reservoir quality was constructed. This model provides a new concept and method for quantitatively predicting the quality of tight sandstone reservoirs in other areas.

Molecular docking, QSAR and ADMET studies of withanolide analogs against breast cancer.

Withanolides are a group of pharmacologically active compounds present in most prodigal amounts in roots and leaves of Withania somnifera (Indian ginseng), one of the most important medicinal plants of Indian traditional practice of medicine. Withanolides are steroidal lactones (highly oxygenated C-28 phytochemicals) and have been reported to exhibit immunomodulatory, anticancer and other activities. In the present study, a quantitative structure activity relationship (QSAR) model was developed by a forward stepwise multiple linear regression method to predict the activity of withanolide analogs against human breast cancer. The most effective QSAR model for anticancer activity against the SK-Br-3 cell showed the best correlation with activity (r2=0.93 and rCV2 =0.90). Similarly, cross-validation regression coefficient (rCV2=0.85) of the best QSAR model against the MCF7/BUS cells showed a high correlation (r2=0.91). In particular, compounds CID_73621, CID_435144, CID_301751 and CID_3372729 have a marked antiproliferative activity against the MCF7/BUS cells, while 2,3-dihydrowithaferin A-3-beta-O-sulfate, withanolide 5, withanolide A, withaferin A, CID_10413139, CID_11294368, CID_53477765, CID_135887, CID_301751 and CID_3372729 have a high activity against the Sk-Br-3 cells compared to standard drugs 5-fluorouracil (5-FU) and camptothecin. Molecular docking was performed to study the binding conformations and different bonding behaviors, in order to reveal the plausible mechanism of action behind higher accumulation of active withanolide analogs with β-tubulin. The results of the present study may help in the designing of lead compound with improved activity.

Synthesis, crystal structure and chromotropism study of copper complexes containing tridentate and pseudo halide ligands; amide linkage isomerism

Two mononuclear complexes of [CuL(N3)]ClO4, 1 and [CuL(SCN)]ClO4, 2, with tridentate ligand of N,N-dimethyl,N-3-propylamideethylenediamine, L, were synthesized and characterized by elemental analyses, molar conductance measurements, UV–Vis and FT-IR spectroscopy techniques. The crystal structure of 1 has been identified by single-crystal X-ray diffraction analyses and confirmed that the copper(II) ion has a distorted square pyramidal environment. The chromotropism of the complexes were studied using spectral analysis. The solvatochromism of the complexes were analyzed by multi-parametric equation using SPSS/PC software. The stepwise multiple linear regression method revealed that the donor power of the solvent acting the most important role in the observed positive solvatochromism of the compounds. The complexes demonstrated halochromism in aqueous solution. The pH effects on the visible absorption spectra of the complexes were studied that functions as pH-induced “off–on–off” switches owing to protonation and deprotonation of amide moiety at room temperature. The complexes exhibited noticeable ionochromism and demonstrated high-sensitive and selective towards CN− and N3− anions in presence of other halides and pseudo-halides.

Solvato- and thermochromism study in oxalato-bridged dinuclear copper(II) complexes of bidentate diamine ligands

Two new oxalato complexes of the formula [Cu2(L)2(µ-ox)(MeOH)2](ClO4)2 (1) and [Cu2(L)2(µ-ox)](NO3)2 (2), where ox=oxalato and L=N,N′-dibenzylethane-1,2-diamine, were prepared and characterized by elemental analysis, IR and UV–vis spectroscopies and molar conductance measurements. The crystal structure of compound 1 was determined by single-crystal X-ray analysis. The compounds are solvatochromic and their solvatochromism was studied with different solvent parameter models using the stepwise multiple linear regression (SMLR) method with SPSS/PC software. It was demonstrated that the donor power of the solvent plays the most important role in the observed positive solvatochromism of the compounds. The complexes show irreversible thermochromism in solution due to the substitution of the weakly coordinated counter ions and coordinated solvents by solvent molecules.

Development of QSBR models for anoxic biodegradability of polycyclic aromatic hydrocarbons by using SMLR and BP-ANN

Abstract In the present study, quantitative structure-biodegradability relationship (QSBR) models were developed for the anoxic Andrews model parameters of polycyclic aromatic hydrocarbons (PAHs). The molecular geometries of 20 PAHs were studied using density functional theory. Stepwise multiple linear regression (SMLR) and backpropagation artificial neural network (BP-ANN) methods were applied to establish the QSBR model between the anoxic biodegradability (q max ) and 5 molecular descriptors. Results of the regression analysis indicated that both the accuracy and predictive ability of the BP-ANN model were better than those of SMLR model. After analyzing the sensitivity of variables, the key molecular structure descriptor influencing anoxic biodegradability of PAHs were screened to be E HOMO and Freq. The present study demonstrates the value of QSBR not only as a predictive tool but also as a framework for understanding the mechanisms governing biodegradation at the molecular level.

Factors determining co-operative small enterprises access to co-operative grant scheme in South Africa

This paper investigates factors determining co-operative small enterprises access to the co-operative grant incentive scheme in South Africa. The raw data used in this study were extracted from the Cooperative Incentive Scheme (CIS) database over the sample financial period FY 2010/11 to FY 2014/15. The amount approved was modelled as the dependent variable, while the turnover prior to application, number of employees, number of members, number of males, number of females, number of youth, number of the disabled, and purpose of application for additional capital were the exploratory variables in the model. Statistical Package for Social Sciences (SPSS) version 24 for Windows was used to perform data processing and statistical analysis using the multiple linear regression method for the overall model and stepwise multiple linear regression method at sectoral level. Estimated results indicate that turnover prior to application, the number of members, males, females and youth had a significant impact on the amount approved for the applications submitted by firms in the agricultural and manufacturing sectors during the sample financial years under review. The paper concludes that the department of small business development should focus on implementing strategies that promote access to the CIS grant funding targeting SMEs co-operatives in the agriculture and manufacturing sectors located mainly in the rural areas of South Africa. Keywords: small and medium enterprises, co-operative, grant, incentive, South Africa. JEL Classification: L26, H81

Composition of the Essential Oils and Volatile Fractions of Artemisia absinthium by Three Different Extraction Methods: Hydrodistillation, Solvent-Free Microwave Extraction and Headspace Solid-Phase Microextraction Combined with a Novel QSRR Evaluation

The present work is mainly focused on relative abilities of three different extraction techniques, namely hydrodistillation (HD), solvent-free microwave extraction (SFME) and headspace solid-phase microextraction (HS-SPME) to separate the essential oils and volatile fractions from stems, leaves and fruits of Artemisia absinthium L., in combination with analysis by GC and GC-MS. By means of the HD method, 16, 21 and 31 components were identified in the stem, leaf and fruit oils, representing 99.9%, 98.5% and 98.0% of the total oil components, respectively; by the SFME method, 27, 23 and 20 components were identified, constituting 98.4%, 100.0% and 100.0% of the oils, respectively. The HS-SPME method revealed even more constituents, namely 37, 37 and 31 volatile fractions from the stem, leaf and fruit of A. absinthium, representing 99.5%, 98.5% and 95.4% of the total chemical profiles. β-Thujone, 1,8-cineole, cis-chrysanthenol, sabinene and α-phellandrene were identified as major compounds in all of the oils and volatiles. Furthermore, a quantitative structure-retention relationship (QSRR) study was performed using stepwise multiple linear regression (SW-MLR) method. A model, with high statistical significance (R2 = 0.952, Q2LOO =0.932, Q2LGO =0.930, F = 104.4), was found to be appropriate for predicting the retention indices of the essential oils and volatile components.

RELATIONS BETWEEN SOIL CHEMICAL PROPERTIES AND CADMIUM CONTENT IN GREEN MASS OF SILAGE MAIZE

UDK 631.41:633.15; 633.15:546.48 (497.6)&#x0D; Cadmium content in soil is an important factor which determines the content of this heavy metal in plants. However, many other factors including soil pH, content of organic matter, other trace minerals in soil which could reduce or enhance cadmium uptake by roots of plants as well as anthropogenic routes of cadmium contamination (mining, superphosphates and industry) can have an influence on the cadmium concentrations in plant tissue. A three years study was conducted to evaluate cadmium content in green mass of silage maize in certain areas of Central Bosnia region. A multiple linear regression (MLR) model was developed to predict maize tissues cadmium concentration as function of different factors such as soil cadmium content, pH of soil, organic matter in soil as well as phosphorus, potassium, zinc and iron content in soil. The results indicate huge variability of cadmium content in soil (maximum value was more than 3fold greater than the minimum value) and green mass of maize (maximum to minimum ratio greater than 100). Cadmium concentration in all investigated samples of maize was below maximum tolerable levels in ruminant nutrition. Using a stepwise multiple linear regression method, a significant model emerged (F2.14 = 55.193, p&lt;0.001; R2 = 0.887). Significant variables were phosphorus (Beta = 0.813, p&lt;0.001) and potassium (Beta = -0.401, p&lt;0.005) content in soil. Soil pH, organic matter, cadmium, zinc and iron were not significant in this model. Insignificant correlation between soil and plant cadmium content (r=0.374, p=0.07) indicates that the presence of cadmium in the soil may not be the main determinant of its content in plants.

Syntheses, crystal structures and solvatochromic properties of dinuclear oxalato-bridged copper(II) complexes

Three dinuclear copper(II) complexes, [Cu2(L1)2(μ-ox)](ClO4)2⋅2(CH3CN), [Cu2(L2)2(μ-ox)](ClO4)2⋅H2O, and [Cu2(L3)2(μ-ox)](ClO4)2 where ox = oxalato; L = N,N-dimethyl,N′-benzylethane-1,2-diamine, L1, N,N-diethyl,N′-benzylethane-1,2-diamine, L2, N,N-diisoprophyl,N′-benzylethane-1,2-diamine, L3, were prepared and characterized by elemental analyses, spectral (IR, UV–Vis) data and molar conductance measurements. The crystal structures of [Cu2(L1)2(μ-ox)](ClO4)2⋅2(CH3CN) and [Cu2(L3)2(μ-ox)](ClO4)2 have been determined by single-crystal X-ray analysis. Solvatochromic behaviors were investigated in various solvents, showing positive solvatochromism. The effect of steric hindrance around the copper ion imposed by N-alkyl groups of the diamine chelates on the solvatochromism property of the complexes is discussed. Solvatochromism was also studied with different solvent parameter models using stepwise multiple linear regression method.

Classification of Kiwifruit Grades Based on Fruit Shape Using a Single Camera

This study aims to demonstrate the feasibility for classifying kiwifruit into shape grades by adding a single camera to current Chinese sorting lines equipped with weight sensors. Image processing methods are employed to calculate fruit length, maximum diameter of the equatorial section, and projected area. A stepwise multiple linear regression method is applied to select significant variables for predicting minimum diameter of the equatorial section and volume and to establish corresponding estimation models. Results show that length, maximum diameter of the equatorial section and weight are selected to predict the minimum diameter of the equatorial section, with the coefficient of determination of only 0.82 when compared to manual measurements. Weight and length are then selected to estimate the volume, which is in good agreement with the measured one with the coefficient of determination of 0.98. Fruit classification based on the estimated minimum diameter of the equatorial section achieves a low success rate of 84.6%, which is significantly improved using a linear combination of the length/maximum diameter of the equatorial section and projected area/length ratios, reaching 98.3%. Thus, it is possible for Chinese kiwifruit sorting lines to reach international standards of grading kiwifruit on fruit shape classification by adding a single camera.

Structure and chromotropism properties of an unsymmetrical alkoxo-bridged nickel(II) cubane-like complex

A new tetranuclear cubane-like complex, [Ni4(L)4Cl4(H2O)3(EtOH)]·(H2O), has been synthesized from the reaction of a metal salt with the bidentate ligand 2-hydroxymethylpyridine (LH), and its crystal structure, spectroscopic and chromotropic properties have been studied. The complex has a [Ni4O4] core comprising a distorted cubane arrangement, of which four nickel(II) ions were bridged by μ3-alkoxo moieties. Each nickel(II) was coordinated to three μ3-alkoxo oxygens, one pyridine nitrogen and one chloride. The peripheral ligation was completed by an oxygen atom of water or ethanol ligand, which participated in intramolecular hydrogen bonding. Chromotropism properties of the complex including solvato-, thermo-, and ionochromism were investigated. The complex displayed strong ionochromism and shows high-sensitive and selective activity toward CN− and SCN− anions in the presence of other halides and pseudo-halides. The solvatochromic property of the complex was analyzed by a multi-parametric equation using SPSS/PC software. The stepwise multiple linear regression method demonstrated that the acceptor power of the solvent plays the most important role in the observed negative solvatochromism of the compound. It shows reversible thermochromism in solution due to loss of the weakly coordinated water and ethanol from the nickel(II) units.

Linear solvation energy relationship for the adsorption of synthetic organic compounds on single-walled carbon nanotubes in water

The linear solvation energy relationship (LSER) was applied to predict the adsorption coefficient (K) of synthetic organic compounds (SOCs) on single-walled carbon nanotubes (SWCNTs). A total of 40 log K values were used to develop and validate the LSER model. The adsorption data for 34 SOCs were collected from 13 published articles and the other six were obtained in our experiment. The optimal model composed of four descriptors was developed by a stepwise multiple linear regression (MLR) method. The adjusted r2 (r2adj) and root mean square error (RMSE) were 0.84 and 0.49, respectively, indicating good fitness. The leave-one-out cross-validation Q2 () was 0.79, suggesting the robustness of the model was satisfactory. The external Q2 () and RMSE (RMSEext) were 0.72 and 0.50, respectively, showing the model’s strong predictive ability. Hydrogen bond donating interaction (bB) and cavity formation and dispersion interactions (vV) stood out as the two most influential factors controlling the adsorption of SOCs onto SWCNTs. The equilibrium concentration would affect the fitness and predictive ability of the model, while the coefficients varied slightly.

Dinuclear copper(II) complexes with bridging oximato group: Synthesis, crystal structure and solvatochromism property

The synthesis, structure, and solvatochromism properties of two new complexes with empirical formula [Cu2L2]X2, are described, where HL stands for 2-(N,N-diisopropyl-2-aminoethyl)imino-3-butanone oximato and X is perchlorate or tetraphenylborate anion. The complexes were characterized by elemental analyses, molar conductance and spectral studies. The binuclear complex [Cu2L2](BPh4)2 was analyzed by X-ray crystallography. In complexes the copper centers are bridged through the oximato NO groups forming a dimer containing a crystallographic twofold symmetry axis. The complexes are solvatochromic and their solvatochromism were investigated by visible spectroscopy. The solvent-dependent absorption maxima, λmax, was analyzed using stepwise multiple linear regression (SMLR) method to find the best model explaining the observed positive solvatochromism. The analysis demonstrated that among different solvent parameters, donor number (DN) is a dominant factor responsible for the shift in the d-d absorption band of the complexes to the higher wavelength with increasing its values.

Synthesis, characterization and solvatochromism study of mixed-chelate copper(II) complexes: A combined experimental and density functional theoretical study

The mixed-chelate copper(II) complexes [Cu(Ph-acac)(diamine)]X, where Ph-acac is 1-phenyl-1,3-butanedione, diamine is N,N-dimethyl,N′-benzyl-1,2-diaminoethane and X=ClO4−, PF6− and BF4−) have been synthesized and characterized spectroscopically (by IR and UV–Vis) and structurally (by single-crystal X-ray diffraction). The X-ray structure of [Cu(Ph-acac)(diamine)]ClO4 demonstrated that the central copper atom is placed in a square planar geometry made by Ph-acac and diamine chelates. Solvatochromism behavior of the compounds was studied in 14 organic solvents, which showed a positive trend with increasing donor power of the solvents. Multi-parametric equation has been utilized to explain the solvent effect on the d–d transition of the complexes using SPSS/PC software. The stepwise multiple linear regression (SMLR) method demonstrated that the donor power of the solvent plays the most important role in the solvatochromism of the compounds. To study the electronic structure of the complex and to confirm the mechanism of the observed solvatochromism, a computation analysis was accomplished on [Cu(Ph-acac)(diamine)]+ by the density functional theory (DFT) and time-dependent DFT calculations. DFT computational results buttressed the experimental observations and indicated that the solvatochromism phenomenon is due to coordination of the solvent molecules on the above and below of the molecular plane, which causes change in geometry of the complex from square planer to octahedron. In this process the d–d transition band of the complex moves to the red with increasing the DN of the solvent.

Towards Retrieving Soil Hydraulic Properties by Hyperspectral Remote Sensing

In this study, we developed spectrotransfer functions (STFs) that relate soil hydraulic properties (SHPs) to spectral reflectance values to estimate hydraulic parameters of the Mualem–van Genuchten (MvG) model. We investigated the general potential of airborne as well as space‐borne remote sensors to retrieve MvG hydraulic parameters of a bare soil agricultural field. Based on the ASD full spectrum (Scenario I), simple spectral signatures were generated mimicking the hyperspectral EnMAP sensor (Scenario II), and the multispectral Sentinel‐2 sensor (Scenario III). A stepwise multiple linear regression method was used for each scenario to derive STFs. We further tested laboratory‐ and soil‐map‐based HYPRES and Rosetta pedotransfer functions (PTFs) to parameterize MvG parameters and thus provide soil water characteristics and hydraulic conductivity functions in the region. The best results were obtained for Scenarios I and II, with similar R2 values for shape parameters α* and n and the lognormal saturated hydraulic conductivity (Ks*). The R2 values were highest for Ks* in Scenarios I and II (0.58 and 0.57, respectively). The R2 values for α* and n were 0.30 and 0.34 in Scenario I and 0.39 and 0.31 in Scenario II, respectively. In all scenarios, the lowest R2 values were obtained for saturated water content (θs), with values around 0.10 for Scenarios I and II and almost zero in Scenario III. Compared with HYPRES and Rosetta PTFs, the spectral approach performed reasonably well in terms of predicting soil water retention characteristics and unsaturated hydraulic conductivity. These findings suggest that spectral reflectance data provide a promising indirect and quick method for large‐scale parameter estimation.