A strategy for multivariate calibration based on modified single-index signal regression: Capturing explicit non-linearity and improving prediction accuracy

In this paper, a modified single-index signal regression (mSISR) method is proposed to construct a nonlinear and practical model with high-accuracy. The mSISR method defines the optimal penalty tuning parameter in P-spline signal regression (PSR) as initial tuning parameter and chooses the number of cycles based on minimizing root mean squared error of cross-validation (RMSECV). mSISR is superior to single-index signal regression (SISR) in terms of accuracy, computation time and convergency. And it can provide the character of the non-linearity between spectra and responses in a more precise manner than SISR. Two spectra data sets from basic research experiments, including plant chlorophyll nondestructive measurement and human blood glucose noninvasive measurement, are employed to illustrate the advantages of mSISR. The results indicate that the mSISR method (i) obtains the smooth and helpful regression coefficient vector, (ii) explicitly exhibits the type and amount of the non-linearity, (iii) can take advantage of nonlinear features of the signals to improve prediction performance and (iv) has distinct adaptability for the complex spectra model by comparing with other calibration methods. It is validated that mSISR is a promising nonlinear modeling strategy for multivariate calibration.     

Well/Ill Posedness for the Euler-Korteweg-Poisson System and Related Problems

We consider a general Euler-Korteweg-Poisson system in R ³, supplemented with the space periodic boundary conditions, where the quantum hydrodynamics equations and the classical fluid dynamics equations with capillarity are recovered as particular examples. We show that the system admits infinitely many global-in-time weak solutions for any sufficiently smooth initial data including the case of a vanishing initial density - the vacuum zones. Moreover, there is a vast family of initial data, for which the Cauchy problem possesses infinitely many dissipative weak solutions, i.e. the weak solutions satisfying the energy inequality. Finally, we establish the weak-strong uniqueness property in a class of solutions without vacuum. In this paper we show that, even in presence of a dispersive tensor, we have the same phenomena found by De Lellis and Székelyhidi.     

Determination of phenolic compounds and authentication of PDO Lambrusco wines by HPLC-DAD and chemometric techniques

This work proposes a fast and simple method for detection and quantification of phenolic compounds in PDO Lambrusco wines using HPLC-DAD and chemometric techniques. Samples belonging to three different varieties of Lambrusco (Grasparossa, Salamino and Sorbara) were analyzed to provide a methodology appropriate for routine analysis. Given the high complexity of the sample and the coelution among chromatographic peaks, the use of chemometric techniques to extract the information of the individual eluting compounds was needed. Multivariate curve resolution-alternating least squares (MCR-ALS) allowed the resolution of the chromatographic peaks obtained and the use of this information for the quantification of the phenolic analytes in the presence of interferences. Use of multiset analysis and local rank/selectivity information was proven to be crucial for the correct resolution and quantification of compounds. The quantitative data provided by MCR-ALS about the phenolic targets and additional compounds present in the samples analyzed provided wine composition profiles, which were afterwards used to distinguish among wine varieties. Principal component analysis applied to the wine profiles allowed characterizing the wines according to their varieties.     

Extension and application of multivariate curve resolution-alternating least squares to four-way quadrilinear data-obtained in the investigation of pollution patterns on Yamuna River,India—A case study

This study focuses on the development and extension of Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) to the analysis of four-way datasets. The proposed extension of the MCR-ALS method with non-negativity and the newly developed quadrilinear constraints can be exploited to summarize and manage huge multidimensional datasets and resolve their four way component profiles. In this study, its application is demonstrated by analyzing a four-way data set obtained in a long term environmental monitoring study (15 sampling sites × 9 variables × 12 months × 7 years) belonging to the Yamuna River, one of the most polluted rivers of India and the largest tributary of the Ganges river. MCR-ALS resolved pollution profiles described appropriately the major observed changes on pH, organic pollution, bacteriological pollution and temperature, along with their spatial and temporal distribution patterns for the studied stretch of Yamuna River. Results obtained by MCR-ALS have also been compared with those obtained by another multi-way method, PARAFAC. The methodology used in this study is completely general and it can be applied to other multi-way datasets.     

Comparative assessment of computational methods for the determination of solvation free energies in alcohol‐based molecules

The determination of differences in solvation free energies between related drug molecules remains an important challenge in computational drug optimization, when fast and accurate calculation of differences in binding free energy are required. In this study, we have evaluated the performance of five commonly used polarized continuum model (PCM) methodologies in the determination of solvation free energies for 53 typical alcohol and alkane small molecules. In addition, the performance of these PCM methods, of a thermodynamic integration (TI) protocol and of the Poisson–Boltzmann (PB) and generalized Born (GB) methods, were tested in the determination of solvation free energies changes for 28 common alkane‐alcohol transformations, by the substitution of an hydrogen atom for a hydroxyl substituent. The results show that the solvation model D (SMD) performs better among the PCM‐based approaches in estimating solvation free energies for alcohol molecules, and solvation free energy changes for alkane‐alcohol transformations, with an average error below 1 kcal/mol for both quantities. However, for the determination of solvation free energy changes on alkane‐alcohol transformation, PB and TI yielded better results. TI was particularly accurate in the treatment of hydroxyl groups additions to aromatic rings (0.53 kcal/mol), a common transformation when optimizing drug‐binding in computer‐aided drug design. © 2013 Wiley Periodicals, Inc.     

Integrating open‐source software applications to build molecular dynamics systems

Three open‐source applications, NanoEngineer‐1, packmol, and mis2lmp are integrated using an open‐source file format to quickly create molecular dynamics (MD) cells for simulation. The three software applications collectively make up the open‐source software (OSS) suite known as MD Studio (MDS). The software is validated through software engineering practices and is verified through simulation of the diglycidyl ether of bisphenol‐a and isophorone diamine (DGEBA/IPD) system. Multiple simulations are run using the MDS software to create MD cells, and the data generated are used to calculate density, bulk modulus, and glass transition temperature of the DGEBA/IPD system. Simulation results compare well with published experimental and numerical results. The MDS software prototype confirms that OSS applications can be analyzed against real‐world research requirements and integrated to create a new capability. © 2014 Wiley Periodicals, Inc.     

有机化学教学中的“三融合、二反思、四进阶”创新教学模式*

为培养出新时代创新人才,构建的“三融合、二反思、四进阶”教学模式有效提升了学生们科技创新能力。依据有机化学特点,创设科学发现情境,通过核心知识点网融合(挑战度)、理论实践交叉融合(高阶性)和化学思政融合(课程思政)“三融合”策略,不断激发学生们学习兴趣;通过教师反思、学生反思的“二反思”过程不断优化教学过程,改善教学效果;最终使具有不同知识层次的学生通过“四进阶”教学策略逐步提升科创能力(创新性)。     

Multivariate statistical analysis approach to assess groundwater quality in two selected mandals of Vizianagaram district,Andhra Pradesh,India

Groundwater quality is the major concern all over the world. Natural processes and manmade activities are the prime reasons for the contamination of available water resources. It is crucial to assess the quality of groundwater in areas surrounded by various industries. The present study was carried out to assess the groundwater quality during pre-monsoon and post monsoon seasons of 2016, in two mandals of Vizianagaram district of Andhra Pradesh via multivariate statistical analysis and water quality index method. The present work gains importance in light of the construction of proposed international airport at Bhohapuram and the existence of various industries in Pusapatirega mandal. A total of thirty-seven villages, eighteen from Bhogapuram mandal and seventeen from Pusapatirega mandal were selected for the present study. Factor analysis, linear regression analysis, correlation matrix analysis and cluster analysis tools were used to emphasize the parameters influencing quality of water in the chosen study area. From the analysis reports, it was found that the groundwater of the two mandals under investigation was strongly influenced by EC, TDS, total hardness(TH), Ca⁺², Mg⁺² and K⁺. During the two seasons under study, the water quality index value was found to be greater than 100 indicating that the water is unfit for human consumption. Concentration of Ca⁺², Mg⁺² and K⁺ were found to be beyond the permissible limits prescribed by BIS (2012). Dissolution of calcium and magnesium bearing minerals, mixing of industrial and household wastes may be the reasons for elevated concentration levels of these parameters.