jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Baohua Yang | Yue Zhu | Mengxuan Wang | Jingming Ning
Source: IEEE Access (article, 2019-01-01)
Field: Chemistry — Analytical Chemistry

A Model for Yellow Tea Polyphenols Content Estimation Based on Multi-Feature Fusion Polyphenols are one of the important ingredients determining the quality of tea, which play an important role in affecting tea quality standards and quality control. At present, NIR spectroscopy technology has been widely used in tea quality detection to achieve good results. However, due to the lack of spatial features, it is difficult to meet the accuracy requirements to comprehensively judge the quality of both inside and outside of tea. With the development of hyperspectral imaging system (HIS), although progress has been made in the estimation of tea texture based on gray level co-occurrence matrix (GLCM) extraction, there are still some obstacles in practical applications. When the resolution is low, the texture features of the image are not significantly different, and a small number of features cannot more fully represent the image features, resulting in lower model accuracy. When the resolution is higher, the increase in the dimension of the feature leads to a more complex model. Therefore, it is necessary to extract multi-scale features from the hyperspectral image while preserving the original information of the hyperspectral image. In this study, a multi-feature fusion method is proposed to improve the accuracy of tea polyphenols content estimation. The process includes multi-scale wavelet decomposition, and feature fusion based on wavelet coefficient features, GLCM texture features and wavelet texture features. Experiments were carried out on five kinds of yellow tea by comparing different models based on different features, including partial least squares regression (PLSR) and support vector regression (SVR). Results indicated that the model based on multi-feature fusion is more accurate than the individual indicators, and models based on SVR perform better than PLSR. Artificial intelligence ; Hyperspectral imaging ; Pattern recognition (psychology) ; Computer science ; Partial least squares regression ; Wavelet ; Feature extraction ; Feature (linguistics) ; Computer vision ; Machine learning Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Tea Polyphenols and Effects
Authors: Luqmon Azeez | Agbaje Lateef | Abideen A. Wahab | Ayoade L. Adejumo | K. Raji
Source: South African Journal of Chemistry (article, 2019-01-01)
Field: Chemistry — Analytical Chemistry

Comparative Effects of Silver Nanoparticles, Sucrose and Sodium Chloride as Osmotic Solutions for Tomato Slices: Antioxidant Activity, Microbial Quality and Modelling with Polynomial Regression Model This study has reported comparative effects of silver nanoparticles (AgNPs), sucrose and sodium chloride as osmotic solutions on antioxidant activity and microbial quality of 10 mm tomato slices. 40 g of tomato slices were dehydrated osmotically (OD) at different temperatures (60,70 and 80 °C) and time (30,60,90,120150 and 180 min). Water loss, solid impregnation, water and solid diffusivities of tomato slices were found to increase with increase in solution temperatures and concentrations with AgNPs having the greatest influence. Antioxidant activities using 2,2-diphenyl-1-picrylhydrazyl increased with increase in solution concentrations but decreased with increase in temperature. Three-way ANOVA (R2 = 0.998) revealed additive statistically significant effects of osmotic agents, concentrations and temperatures on antioxidant activity; F(854) = 67.854, P = 0.00. Polynomial regression analysis with response surface methodology validated experiments such that for each unit increase in concentration and temperature, antioxidant activity increased with good coefficients of determination; sucrose (R2 = 0.87), NaCl, (R2 = 0.89) and AgNPs (R2 = 0.91). Potato dextrose and nutrient agars were used for isolating and identifying microorganisms in OD tomato slices. Tomato slices dehydrated with AgNPs had the highest microbial inhibition of fungi with growth occurring after 7 days, unlike in treatments with sucrose and NaCl where fungal growth appeared after 2 and 5 days, respectively. Aspergillus niger was the most prevalent fungus. It can be concluded that AgNPs may serve as a viable means to dehydrate and preserve tomatoes without loss of antioxidant activity. Keywords: Osmotic dehydration, polynomial regression, response surface, antioxidant activity, three-way ANOVA, silver nanoparticles. Chemistry ; Sodium ; Antioxidant ; Sucrose ; Polynomial regression ; Regression analysis ; Chloride ; Polynomial ; Osmotic pressure ; Food science ; Biochemistry ; Organic chemistry ; Statistics ; Mathematics Heavy Metals in Plants ; Hibiscus Plant Research Studies ; Agricultural and Food Sciences
Authors: Tara Eicher | Andrew Patt | Esko A. Kautto | Raghu Machiraju | Ewy A. Mathé | Yan Zhang
Source: BMC Bioinformatics (article, 2019-12-01)
Field: Chemistry — Spectroscopy

Challenges in proteogenomics: a comparison of analysis methods with the case study of the DREAM proteogenomics sub-challenge In addition to benchmarking aforementioned machine learning approaches for predicting protein levels from transcript levels, we discuss challenges and potential solutions in state-of-the-art proteogenomic analyses. Proteogenomics ; Computational biology ; Proteomics ; Biology ; Proteome ; DNA microarray ; Genomics ; Bioinformatics ; Gene ; Gene expression ; Genome ; Genetics Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Gene expression and cancer classification
Authors: Hayam M. Lotfy | Sara El-Hanboushy | Yasmin M. Fayez | M. A. Abdelkawy
Source: Future Journal of Pharmaceutical Sciences (article, 2019-09-02)
Field: Chemistry — Analytical Chemistry

Spectral analysis of overlapped absorption bands of binary mixtures—an application on combination of pseudoephedrine sulphate and loratadine mixture Simple, specific, accurate, and precise spectrophotometric methods are progressed and validated for concurrent analysis of pseudoephedrine sulphate (PSE) and loratadine (LOR) in their combined dosage form depending on spectral analysis procedures. In this binary mixture, pseudoephedrine (PSE) could be determined by using its resolved spectrum of zero-order absorption at 256.8 nm after subtraction of the spectrum of LOR, and also it could be determined in existence of the spectrum of LOR by different methods including absorption correction method (AC) at 256.8 nm and 280 nm, dual wavelength method (DW) at 254 nm and 273 nm, induced dual-wavelength method (IDW) at 230 nm and 263 nm, and ratio difference method (RD) at 256.8 nm and 270 nm. Loratadine (LOR) in the binary mixture could be determined either by direct analysis at 280 nm without any contribution from the spectrum of PSE or through its recovered spectrum of zero-order absorption via constant multiplication method (CM) using plateau region (277–326 nm). Also, concurrent determination for PSE and LOR in their overlapped binary mixture could be achieved by applying induced amplitude modulation (IAM) method. Specificity of the proposed spectrophotometric methods was examined by the analysis of prepared mixtures in laboratory and was applied successfully for pharmaceutical dosage form analysis which has the cited drugs without additive contribution. The proposed spectrophotometric methods were also validated as per the guidelines of ICH. Statistical comparison was performed between the obtained results with those from the official methods of the cited drugs, using one-way ANOVA, F test, and Student’s t test, and the results exhibit insignificant difference concerning precision and accuracy. The previously proposed spectrophotometric methods could be easily used accurately and precisely for simultaneous determination of the studied binary mixture with simple manipulation procedures. Loratadine ; Pseudoephedrine ; Chemistry ; Absorption (acoustics) ; Analytical Chemistry (journal) ; Absorption spectroscopy ; Binary number ; Wavelength ; Chromatography ; Mathematics ; Ephedrine ; Optics ; Physics Analytical Methods in Pharmaceuticals ; Analytical Chemistry and Sensors ; Antibiotics Pharmacokinetics and Efficacy
Authors: Ryo Murakami | Hironori Kageyama | Kazuki Nakamura | Hiromi Tanaka | Hiroshi Shinotsuka | Hideki Yoshikawa | Kazuhiro Yoshihara
Source: e-Journal of Surface Science and Nanotechnology (article, 2019-07-12)
Field: Materials Science — Surfaces, Coatings and Films

Background Estimation in X-ray Photoelectron Spectroscopy Data Using an Active Shirley Method with Automated Selection of the Analytical Range In this study, we introduce a novel algorithm that can recognize the concavo-convex shapes of X-ray photoelectron spectroscopy (XPS) data and estimate the optimum background (BG) in XPS spectra with fine structures near the endpoints. In this algorithm, the active Shirley method was improved by incorporating a function for automatically selecting the analytical range. This autoselection function first investigates all the candidates for the initial endpoints. These estimates are then used to decide the BG shape according to the Shirley method. In order to exclude false-positive candidates caused by the recognition of noise peaks as small XPS peaks, the function evaluates the concavo-convex shape of the XPS spectrum after the long-period noise is removed using a smoothing process. The proposed algorithm was demonstrated to successfully estimate the optimal spectral BG from an XPS spectrum with a poor signal-to-noise ratio of about 40%. X-ray photoelectron spectroscopy ; Smoothing ; Noise (video) ; Function (biology) ; Computer science ; Range (aeronautics) ; Signal-to-noise ratio (imaging) ; Spectral line ; Algorithm ; Biological system ; Analytical Chemistry (journal) ; Artificial intelligence ; Materials science ; Chemistry ; Physics ; Nuclear magnetic resonance ; Computer vision ; Telecommunications Electron and X-Ray Spectroscopy Techniques ; Nuclear Physics and Applications ; X-ray Spectroscopy and Fluorescence Analysis
Authors: Kavita Shah | Hyunjin Kim
Source: IUBMB Life (review, 2019-02-22)
Field: Chemistry — Spectroscopy

The significant others: Global search for direct kinase substrates using chemical approaches Protein kinases function as key signaling hubs in the intricate network of biochemical signaling processes in the living cell. More than two-thirds of the human proteome is estimated to be phosphorylated at ~960,000 phosphosites, which makes it challenging to identify the direct contribution of any desired kinase in generating this phosphoproteome. In this review, we discuss some of the methods that have been developed over the years for global identification of kinase substrates. The methods are essentially categorized into two classes, namely, (i) direct tagging of kinase substrates and (ii) indirect phosphoproteomics-based approaches. We discuss the advantages and limitations entailed to each of the method introduced, with a special emphasis on the analog-sensitive (as) kinase approach method. © 2019 IUBMB Life, 71(6):721-737, 2019. Phosphoproteomics ; Kinase ; Computational biology ; Proteome ; Identification (biology) ; Function (biology) ; MAP kinase kinase kinase ; Computer science ; Biology ; Cell biology ; Proteomics ; Protein kinase A ; Biochemistry ; Protein phosphorylation ; Gene Advanced Proteomics Techniques and Applications ; Ubiquitin and proteasome pathways ; Protein Degradation and Inhibitors
Authors: N. Shesh | Sudhir Srivastava | Jianmin Pan | Xiaoyong Wu | P. Somesh | Chongkham S. Mekmaysy | Lynn DeLeeuw | Jonathan B. Chaires | Nichola C. Garbett
Source: PLoS ONE (article, 2019-08-20)
Field: Chemistry — Physical and Theoretical Chemistry

Multi-group diagnostic classification of high-dimensional data using differential scanning calorimetry plasma thermograms The thermoanalytical technique differential scanning calorimetry (DSC) has been applied to characterize protein denaturation patterns (thermograms) in blood plasma samples and relate these to a subject's health status. The analysis and classification of thermograms is challenging because of the high-dimensionality of the dataset. There are various methods for group classification using high-dimensional data sets; however, the impact of using high-dimensional data sets for cancer classification has been poorly understood. In the present article, we proposed a statistical approach for data reduction and a parametric method (PM) for modeling of high-dimensional data sets for two- and three- group classification using DSC and demographic data. We compared the PM to the non-parametric classification method K-nearest neighbors (KNN) and the semi-parametric classification method KNN with dynamic time warping (DTW). We evaluated the performance of these methods for multiple two-group classifications: (i) normal versus cervical cancer, (ii) normal versus lung cancer, (iii) normal versus cancer (cervical + lung), (iv) lung cancer versus cervical cancer as well as for three-group classification: normal versus cervical cancer versus lung cancer. In general, performance for two-group classification was high whereas three-group classification was more challenging, with all three methods predicting normal samples more accurately than cancer samples. Moreover, specificity of the PM method was mostly higher or the same as KNN and DTW-KNN with lower sensitivity. The performance of KNN and DTW-KNN decreased with the inclusion of demographic data, whereas similar performance was observed for the PM which could be explained by the fact that the PM uses fewer parameters as compared to KNN and DTW-KNN methods and is thus less susceptible to the risk of overfitting. More importantly the accuracy of the PM can be increased by using a greater number of quantile data points and by the inclusion of additional demographic and clinical data, providing a substantial advantage over KNN and DTW-KNN methods. Lung cancer ; Cervical cancer ; Pattern recognition (psychology) ; Parametric statistics ; Artificial intelligence ; Cancer ; Mathematics ; Statistics ; Internal medicine ; Medicine ; Computer science thermodynamics and calorimetric analyses ; Physiological and biochemical adaptations ; Computational Drug Discovery Methods
Authors: Mauro Santoyo-Mora | Agustin Sancen-Plaza | Alejandro Espinosa Calderón | Alejandro Israel Barranco Gutiérrez | Juan Prado-Olivarez
Source: Journal of Sensors (article, 2019-04-07)
Field: Chemistry — Analytical Chemistry

Nondestructive Quantification of the Ripening Process in Banana (<i>Musa AAB Simmonds</i>) Using Multispectral Imaging The ripening process in bananas causes the waste of a significant part of the production of this fruit. The aim of this research is to find a new technique useful for identifying, registering, and quantifying the ripening process of a banana ( Musa AAB Simmonds ) at the seventh stage of the growing process. This quantification is proposed with a nondestructive technique based on processing multispectral images. This experiment used a set of multispectral imagery registered in a range of 270-1000 nm (from UV to IR) with the aid of a monochromatic camera and a set of 10 optical filters. Multispectral images were analyzed with three different techniques: Fourier fractal analysis, Hotelling transform, and homogeneity texture analysis based on cooccurrence matrix. First, a characteristic index was computed for each technique for a daily set of multispectral imagery. These indexes are slope index, for Fourier fractals; the average of the computed eigenvalues, with Hotelling transform; and the texture homogeneity value. These indexes were evaluated using the behavior of the resulting graphs for a seven-day period, being preferred those graphs with a tendency of decreasing values. Finally, the repeatability of each technique was evaluated by reproducing similar values for each day during the evaluation period. These three methods will be compared in this article in order to select the one with the best performance for measuring the ripening process in bananas. The obtained results show that it is possible to effectively isolate the brown spots from the banana peel with the Hotelling transform by using only 2 optical filters: visible (410-690 nm) and Near-IR (820-910 nm). With the resulting spectral image fusion it was possible to effectively describe the evolution of the brown spots present in the ripening process through the texture homogeneity criteria. Multispectral image ; Ripening ; Banana peel ; Mathematics ; Artificial intelligence ; Nondestructive testing ; Fractal analysis ; Fractal ; Fourier transform ; Computer science ; Homogeneity (statistics) ; Pattern recognition (psychology) ; Remote sensing ; Computer vision ; Fractal dimension ; Statistics ; Geography ; Physics ; Chemistry ; Food science Spectroscopy and Chemometric Analyses ; Banana Cultivation and Research ; Smart Agriculture and AI
Authors: Dejiang Liu | Jian Shen | Hongsheng Yang | Qiang Niu | Qingxi Guo
Source: EURASIP Journal on Image and Video Processing (article, 2019-01-25)
Field: Chemistry — Analytical Chemistry

Recognition and localization of actinidia arguta based on image recognition In the process of picking, actinidia arguta has difficulty in image recognition and occlusion problems, and there are few studies on kiwifruit recognition. Based on this, this study uses the color model to perform image basic processing and uses frequency domain enhancement to process the image. Simultaneously, in the frequency domain of the image, this study applied filtering to the original image of kiwifruit orchard, used homomorphic filtering to enhance the image of actinidia arguta orchard, highlighted the characteristics of actinidia arguta trunk, and reduced the influence of background noise on the recognition of actinidia arguta trunk. In addition, this study used a binocular stereo vision system for fruit location recognition to improve recognition accuracy. Finally, the effectiveness of the research method is verified by experimental research. The results show that the proposed algorithm performs well and can provide theoretical references for subsequent related research. Artificial intelligence ; Computer science ; Computer vision ; Biometrics ; Image processing ; Pattern recognition (psychology) ; Process (computing) ; Noise (video) ; Actinidia ; Image (mathematics) ; Biology ; Botany Spectroscopy and Chemometric Analyses ; Remote Sensing and Land Use ; Smart Agriculture and AI
Authors: Kristina Navickaitė | C.R.H. Bahl | Kurt Engelbrecht
Source: Frontiers in Energy Research (article, 2019-07-23)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Nature—Inspired Flow Patterns for Active Magnetic Regenerators Assessed Using a 1D AMR Model A novel flow structure of a solid active magnetic regenerator is proposed in this paper. The numerical performances of two nature-inspired flow geometries, based on double corrugated tubes with an elliptical cross-section, are compared to the performance of conventional flow structures for Active Magnetic Regeneration (AMR) applications, namely, packed spheres and a cylindrical micro-channel matrix. The numerical performance of all the geometries is analysed in terms of cooling power and coefficient of performance. Regenerators with various porosities and two different hydraulic diameters of the flow channels are evaluated varying utilisation at fixed temperature spans between the hot and cold reservoirs. The selection of the regenerator geometry is based on two actual AMR machines. The numerical results demonstrate that a suitably optimized AMR geometry with a double corrugated flow pattern provides the same or higher efficiency at higher porosity compared to conventional AMR flow geometries. These findings suggest that the magnetocaloric material used to construct AMR beds can be exploited more efficiently and at a lower investment cost of an AMR device when suitable double corrugated flow pattern is used. Magnetic refrigeration ; Regenerative heat exchanger ; Flow (mathematics) ; Materials science ; Mechanics ; Stack (abstract data type) ; Porosity ; Mechanical engineering ; Heat exchanger ; Magnetic field ; Computer science ; Engineering ; Composite material ; Physics Magnetic and transport properties of perovskites and related materials ; Magnetic Bearings and Levitation Dynamics ; Physics of Superconductivity and Magnetism
Authors: Diksha Priya Lotun | Charlotte Cochard | Fabio Rocha Jimenez Vieira | Juliana Bernardes
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2019-05-24)
Field: Materials Science — Materials Chemistry

2dSS: a web server for protein secondary structure visualization 2dSS is a web-server for visualising and comparing secondary structure predictions. It provides two main functionalities: 2D-alignment and compare predictions. The “2D-alignment” has been designed to visualise conserved secondary structure elements in a multiple sequence alignment (MSA). From this we can study the secondary structure content of homologous proteins (a protein family) and highlight its structural patterns. The “compare predictions” has been designed to compare the output of several secondary structure prediction tools, and check their accuracy when compared with real secondary structure elements extracted from 3D-structure. 2dSS provides a comprehensive representation of protein secondary structure elements, and it can be used to visualise and compare secondary structures of any prediction tool. Availability http://genome.lcqb.upmc.fr/2dss/ Protein secondary structure ; Visualization ; Computer science ; Web server ; Secondary development ; Representation (politics) ; Sequence alignment ; Computational biology ; Sequence (biology) ; Protein structure ; Structural alignment ; Bioinformatics ; Data mining ; Biology ; World Wide Web ; The Internet ; Peptide sequence ; Software ; Genetics Enzyme Structure and Function ; Protein Structure and Dynamics ; Genomics and Phylogenetic Studies
Authors: Dong Wang | Ren-Yuan Hong | Mengyao Guo | Yi Liu | Nianhang Chen | Xun Li | Kong De
Source: Molecules (article, 2019-11-05)
Field: Chemistry — Organic Chemistry

Novel C7-Substituted Coumarins as Selective Monoamine Oxidase Inhibitors: Discovery, Synthesis and Theoretical Simulation There is a continued need to develop new selective human monoamine oxidase (<i>h</i>MAO) inhibitors that could be beneficial for the treatment of neurological diseases. However, <i>h</i>MAOs are closely related with high sequence identity and structural similarity, which hinders the development of selective MAO inhibitors. "Three-Dimensional Biologically Relevant Spectrum (BRS-3D)" method developed by our group has demonstrated its effectiveness in subtype selectivity studies of receptor and enzyme ligands. Here, we report a series of novel C7-substituted coumarins, either synthesized or commercially purchased, which were identified as selective <i>h</i>MAO inhibitors. Most of the compounds demonstrated strong activities with IC<sub>50</sub> values (half-inhibitory concentration) ranging from sub-micromolar to nanomolar. Compounds, <b>FR1</b> and <b>SP1</b>, were identified as the most selective <i>h</i>MAO-A inhibitors, with IC<sub>50</sub> values of 1.5 nM (selectivity index (SI) < -2.82) and 19 nM (SI < -2.42), respectively. <b>FR4</b> and <b>FR5</b> showed the most potent <i>h</i>MAO-B inhibitory activity, with IC<sub>50</sub> of 18 nM and 15 nM (SI > 2.74 and SI > 2.82). Docking calculations and molecular dynamic simulations were performed to elucidate the selectivity preference and SAR profiles. Monoamine oxidase ; Chemistry ; Computational biology ; Monoamine oxidase B ; Combinatorial chemistry ; Coumarin ; Drug discovery ; Stereochemistry ; Biochemistry ; Enzyme ; Biology ; Organic chemistry Synthesis and Biological Evaluation ; Synthesis of Organic Compounds ; Synthesis and biological activity