jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Jun‐Li Xu | Cecilia Riccioli | Ana Herrero‐Langreo | Aoife Gowen
Source: Journal of Spectral Imaging (article, 2020-12-24)
Field: Chemistry — Analytical Chemistry

Deep learning classifiers for near infrared spectral imaging: a tutorial Deep learning (DL) has recently achieved considerable successes in a wide range of applications, such as speech recognition, machine translation and visual recognition. This tutorial provides guidelines and useful strategies to apply DL techniques to address pixel-wise classification of spectral images. A one-dimensional convolutional neural network (1-D CNN) is used to extract features from the spectral domain, which are subsequently used for classification. In contrast to conventional classification methods for spectral images that examine primarily the spectral context, a three-dimensional (3-D) CNN is applied to simultaneously extract spatial and spectral features to enhance classificationaccuracy. This tutorial paper explains, in a stepwise manner, how to develop 1-D CNN and 3-D CNN models to discriminate spectral imaging data in a food authenticity context. The example image data provided consists of three varieties of puffed cereals imaged in the NIR range (943–1643 nm). The tutorial is presented in the MATLAB environment and scripts and dataset used are provided. Starting from spectral image pre-processing (background removal and spectral pre-treatment), the typical steps encountered in development of CNN models are presented. The example dataset provided demonstrates that deep learning approaches can increase classification accuracy compared to conventional approaches, increasing the accuracy of the model tested on an independent image from 92.33 % using partial least squares-discriminant analysis to 99.4 % using 3-CNN model at pixel level. The paper concludes with a discussion on the challenges and suggestions in the application of DL techniques for spectral image classification. Artificial intelligence ; Computer science ; Convolutional neural network ; Context (archaeology) ; Pattern recognition (psychology) ; Pixel ; Deep learning ; Spectral bands ; Range (aeronautics) ; Contextual image classification ; Scripting language ; Linear discriminant analysis ; Image (mathematics) ; Machine learning ; Remote sensing Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Juan Luis de Pablos | Edoardo Menga | Ignacio Romero
Source: Materials (article, 2020-10-02)
Field: Materials Science — Materials Chemistry

A Methodology for the Statistical Calibration of Complex Constitutive Material Models: Application to Temperature-Dependent Elasto-Visco-Plastic Materials The calibration of any sophisticated model, and in particular a constitutive relation, is a complex problem that has a direct impact in the cost of generating experimental data and the accuracy of its prediction capacity. In this work, we address this common situation using a two-stage procedure. In order to evaluate the sensitivity of the model to its parameters, the first step in our approach consists of formulating a meta-model and employing it to identify the most relevant parameters. In the second step, a Bayesian calibration is performed on the most influential parameters of the model in order to obtain an optimal mean value and its associated uncertainty. We claim that this strategy is very efficient for a wide range of applications and can guide the design of experiments, thus reducing test campaigns and computational costs. Moreover, the use of Gaussian processes together with Bayesian calibration effectively combines the information coming from experiments and numerical simulations. The framework described is applied to the calibration of three widely employed material constitutive relations for metals under high strain rates and temperatures, namely, the Johnson-Cook, Zerilli-Armstrong, and Arrhenius models. Calibration ; Constitutive equation ; Sensitivity (control systems) ; Bayesian probability ; Range (aeronautics) ; Computer science ; Gaussian ; Gaussian process ; Bayesian inference ; Point (geometry) ; Applied mathematics ; Algorithm ; Mathematical optimization ; Mathematics ; Materials science ; Statistics ; Artificial intelligence ; Engineering ; Finite element method ; Structural engineering ; Physics ; Electronic engineering High-Velocity Impact and Material Behavior ; Probabilistic and Robust Engineering Design ; Granular flow and fluidized beds
Authors: Yoshiomi Hiranaga | Takanori Mimura | Takao Shimizu | Hiroshi Funakubo | Yasuo Cho
Source: Journal of Applied Physics (article, 2020-12-28)
Field: Materials Science — Materials Chemistry

Local <i>C</i>–<i>V</i> mapping for ferroelectrics using scanning nonlinear dielectric microscopy Detailed analysis of local polarization switching will promote the further development of a wide range of applications using ferroelectrics. Here, we propose a local C–V mapping technique using scanning nonlinear dielectric microscopy (SNDM) that enables visualization of dynamic ferroelectric switching behavior in real space. Using this method, C–V butterfly curves characteristic of ferroelectrics can be measured on a scanning probe microscopy platform with nanoscale resolution by virtue of the high capacitance-detection sensitivity of SNDM. This provides real-space mapping of the net switchable polarization, the switching voltage, and the local imprint with a short measurement time (e.g., 10 min or less for 256×256 pixels). Furthermore, the proposed method will be useful for study of the electric-field response of domain walls. In this paper, we present some examples of experiments with LiTaO3 single crystals and HfO2-based ferroelectric thin films and give an overview of what kind of evaluation is possible with the local C–V mapping technique. Dielectric ; Ferroelectricity ; Polarization (electrochemistry) ; Scanning probe microscopy ; Microscopy ; Materials science ; Nonlinear system ; Scanning capacitance microscopy ; Capacitance ; Electric field ; Nanoscopic scale ; Image resolution ; Local field ; Voltage ; Optics ; Piezoresponse force microscopy ; Optoelectronics ; Nanotechnology ; Physics ; Condensed matter physics ; Scanning confocal electron microscopy ; Chemistry ; Electrode Ferroelectric and Piezoelectric Materials ; Ferroelectric and Negative Capacitance Devices ; Advanced Memory and Neural Computing
Authors: Shikai Jin | Mitchell D. Miller | Mingchen Chen | Nicholas P. Schafer | Xingcheng Lin | Xun Chen | G.N. Phillips | Peter G. Wolynes
Source: IUCrJ (article, 2020-10-26)
Field: Materials Science — Materials Chemistry

Molecular-replacement phasing using predicted protein structures from <i>AWSEM-Suite</i> The phase problem in X-ray crystallography arises from the fact that only the intensities, and not the phases, of the diffracting electromagnetic waves are measured directly. Molecular replacement can often estimate the relative phases of reflections starting with those derived from a template structure, which is usually a previously solved structure of a similar protein. The key factor in the success of molecular replacement is finding a good template structure. When no good solved template exists, predicted structures based partially on templates can sometimes be used to generate models for molecular replacement, thereby extending the lower bound of structural and sequence similarity required for successful structure determination. Here, the effectiveness is examined of structures predicted by a state-of-the-art prediction algorithm, the <i>Associative memory, Water-mediated, Structure and Energy Model Suite</i> (<i>AWSEM-Suite</i>), which has been shown to perform well in predicting protein structures in CASP13 when there is no significant sequence similarity to a solved protein or only very low sequence similarity to known templates. The performance of <i>AWSEM-Suite</i> structures in molecular replacement is discussed and the results show that <i>AWSEM-Suite</i> performs well in providing useful phase information, often performing better than <i>I-TASSER-MR</i> and the previous algorithm <i>AWSEM-Template</i>. Template ; Molecular replacement ; Phaser ; Computer science ; Sequence (biology) ; Suite ; Protein structure prediction ; Similarity (geometry) ; Software suite ; Protein structure ; Algorithm ; Phase problem ; Biological system ; Artificial intelligence ; Software ; Chemistry ; Physics ; Biology ; Image (mathematics) Enzyme Structure and Function ; Protein Structure and Dynamics ; Advanced NMR Techniques and Applications
Authors: M Ramachandran | B. A. Modia
Source: Journal of Advanced Research in Fluid Mechanics and Thermal Sciences (article, 2020-04-30)
Field: Materials Science — Biomaterials

Optimization of Molding Process Parameter for Jute Reinforced Poly Lactic Acid Composite Molding process parameters decide the quality of the composite. Optimization of Molding Process Parameter will improve the quality of the composite. In this paper, molding process parameter optimization is carried out for molding Jute Reinforced Polylactic Acid polymeric Composite in the compression molding machine. Response surface methodology with the composite design is used. Curing temperature, curing time, pressure and mold temperature are taken as an input factor and tensile strength, hardness and impact strength are taken as a response. The analysis is evident that that smaller changes in the mold temperature will reduce the mechanical properties of the mold. With molding process parameters of 190 o C curing temperature, 1300 seconds curing time, 80 bar pressure and 190 o C mold temperature gives composite with significantly improved mechanical properties. Mold ; Materials science ; Compression molding ; Composite number ; Composite material ; Curing (chemistry) ; Molding (decorative) ; Polylactic acid ; Ultimate tensile strength ; Transfer molding ; Response surface methodology ; Process variable ; Process (computing) ; Polymer ; Computer science biodegradable polymer synthesis and properties
Authors: Brett Tully
Source: Scientific Reports (article, 2020-06-02)
Field: Chemistry — Spectroscopy

Toffee – a highly efficient, lossless file format for DIA-MS The closed nature of vendor file formats in mass spectrometry is a significant barrier to progress in developing robust bioinformatics software. In response, the community has developed the open mzML format, implemented in XML and based on controlled vocabularies. Widely adopted, mzML is an important step forward; however, it suffers from two challenges that are particularly apparent as the field moves to high-throughput proteomics: large increase in file size, and a largely sequential I/O access pattern. Described here is 'toffee', an open, random I/O format backed by HDF5, with lossless compression that gives file sizes similar to the original vendor format and can be reconverted back to mzML without penalty. It is shown that mzML and toffee are equivalent when processing data using OpenSWATH algorithms, in additional to novel applications that are enabled by new data access patterns. For instance, a peptide-centric deep-learning pipeline for peptide identification is proposed. Documentation and examples are available at https://toffee.readthedocs.io, and all code is MIT licensed at https://bitbucket.org/cmriprocan/toffee. Computer science ; File format ; Pipeline (software) ; XML ; XML framework ; Vendor ; Software ; Database ; Operating system Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Beth A. Caine | Maddalena Bronzato | Torquil Fraser | Nathan J. Kidley | Christophe Dardonville | Paul L. A. Popelier
Source: Communications Chemistry (article, 2020-02-12)
Field: Chemistry — Organic Chemistry

Aqueous pKa prediction for tautomerizable compounds using equilibrium bond lengths The accurate prediction of aqueous pK<sub>a</sub> values for tautomerizable compounds is a formidable task, even for the most established in silico tools. Empirical approaches often fall short due to a lack of pre-existing knowledge of dominant tautomeric forms. In a rigorous first-principles approach, calculations for low-energy tautomers must be performed in protonated and deprotonated forms, often both in gas and solvent phases, thus representing a significant computational task. Here we report an alternative approach, predicting pK<sub>a</sub> values for herbicide/therapeutic derivatives of 1,3-cyclohexanedione and 1,3-cyclopentanedione to within just 0.24 units. A model, using a single ab initio bond length from one protonation state, is as accurate as other more complex regression approaches using more input features, and outperforms the program Marvin. Our approach can be used for other tautomerizable species, to predict trends across congeneric series and to correct experimental pK<sub>a</sub> values. Tautomer ; Protonation ; Deprotonation ; Chemistry ; Ab initio ; Aqueous solution ; Computational chemistry ; Computer science ; In silico ; Biological system ; Physical chemistry ; Stereochemistry ; Organic chemistry Free Radicals and Antioxidants ; Chemistry and Chemical Engineering ; Chemical Reaction Mechanisms
Authors: Kritamorn Jitrangsri | Amornrut Chaidedgumjorn | Malaï Satiraphan
Source: Pharmaceutical Sciences Asia (article, 2020-01-01)
Field: Chemistry — Inorganic Chemistry

Effect of ethanol percentage upon various extraction methods of peanut based on antioxidant activity with trans-resveratrol and total phenolic contents The aim of this study was to determine the effect of ethanol percentage in the extraction solvent on the constituents of peanut extracts prepared from three extraction methods including Solid-Liquid Extraction (SLE), Ultrasound-Assisted Extraction (UAE) and Microwave-Assisted Extraction (MAE). Evaluation was performed through antioxidant tests together with trans-resveratrol and total phenolic contents. The ethanol content was set at 20 and 80%v/v. Although extraction with 80%v/v ethanol gave higher percentage yield of the extract, it provided lower resveratrol amount and total phenolic content in all extraction techniques. Lower ethanol content mostly showed positive influence on radical scavenging antioxidant capacity of the extract (DPPH and ABTS assay). Moreover, with DPPH and ABTS assay, trans-resveratrol and total phenolic contents demonstrated strong and moderate correlation with antioxidant activity, respectively. On the contrary, solvent with higher percentage of ethanol in SLE and UAE caused higher reducing power extracts with Ferric Reducing Antioxidant Power (FRAP) assay. This implied that, different ethanol composition in SLE and UAE extracted different types of compounds that possessed different mechanisms of antioxidant activity. Concerning extraction methods, UAE was the most effective extraction method which provided the highest antioxidant activity of the extract. According to this study, the percentage of ethanol and extraction methods had significant influence on the composition of the extracts assessed through antioxidant activities as well as trans-resveratrol and total phenolic contents. Resveratrol ; Extraction (chemistry) ; Chemistry ; Antioxidant ; Food science ; Ethanol ; Chromatography ; Organic chemistry ; Biochemistry Coconut Research and Applications ; Food Chemistry and Fat Analysis ; Phytochemicals and Antioxidant Activities
Authors: Xufeng Jing | Youhuang Ke | Ying Tian | Haiyong Gan | Yingwei He | Chenxia Li | Zhi Hong
Source: IEEE Access (article, 2020-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Manipulation of Terahertz Wave Based on Three-Layer Transmissive Pancharatnam-Berry Phase Metasurface In order to improve the transmitted efficiency of metasurfaces, the three-layer unit cell structure with coupling characteristics between layers was proposed. Using these Pancharatnam-Berry phase element particles with three-layer structure, we constructed encoded metasurfaces with different sequences to control the transmitted scattered waves. However, the manipulation of continuous transmission angle requires the continuous change of encoding metasurface period. Since the size of encoding particles in the coded metasurfaces cannot be designed to be infinitesimally small, it is impossible to obtain the continuously changing period of coded metasurfaces. In order to obtain the continuous manipulation of transmission scattering angles, we introduced the principle of Fourier convolution operation in digital signal processing on encoding metasurface sequences. By performing the addition and subtraction operation between two different encoding metasurface sequences, a new encoding metasurface sequence can be obtained with different scattering angle. The transmission scattering angles can be obtained continuously, and the terahertz wave can be manipulated freely. Moreover, by using the proposed three-layer highly efficient Pancharatnam-Berry phase encoding meta-atoms, these coded particles with different rotation angles can be precisely arranged to build the generators of the orbital angular momentum beam with different topological charges. Optics ; Physics ; Scattering ; Geometric phase ; Terahertz radiation ; Phase (matter) ; Transmission (telecommunications) ; Computer science ; Telecommunications Metamaterials and Metasurfaces Applications ; Orbital Angular Momentum in Optics ; Advanced Antenna and Metasurface Technologies
Authors: Te Ma | Tetsuya Inagaki | Satoru Tsuchikawa
Source: Holzforschung (article, 2020-10-21)
Field: Chemistry — Analytical Chemistry

Demonstration of the applicability of visible and near-infrared spatially resolved spectroscopy for rapid and nondestructive wood classification Abstract Although visible and near-infrared (Vis-NIR) spectroscopy can rapidly and nondestructively identify wood species, the conventional spectrometer approach relies on the aggregate light absorption due to the chemical composition of wood and light scattering originating from the physical structure of wood. Hence, much of the work in this area is still limited to further spectral pretreatments, such as baseline correction and standard normal variate to reduce the light scattering effects. However, it should be emphasized that the light scattering rather than absorption in wood is dominant, and this must be effectively utilized to achieve highly accurate and robust wood classification. Here a novel method based on spatially resolved diffuse reflectance (wavelength range: 600–1000 nm) was demonstrated to classify 15 kinds of wood. A portable Vis-NIR spectral measurement system was designed according to previous simulations and experimental results. To simplify spectral data analysis (i.e., against overfitting), support vector machine (SVM) model was constructed for wood sample classification using principal component analysis (PCA) scores. The classification accuracies of 98.6% for five-fold cross-validation and 91.2% for test set validation were achieved. This study offers enhanced classification accuracy and robustness over other conventional nondestructive approaches for such various kinds of wood and sheds light on utilizing visible and short-wave NIR light scattering for wood classification. Overfitting ; Near-infrared spectroscopy ; Spectroscopy ; Principal component analysis ; Spectrometer ; Diffuse reflectance infrared fourier transform ; Light scattering ; Materials science ; Scattering ; Nondestructive testing ; Support vector machine ; Optics ; Biological system ; Artificial intelligence ; Computer science ; Chemistry ; Artificial neural network ; Physics Spectroscopy and Chemometric Analyses ; Wood and Agarwood Research ; Industrial Vision Systems and Defect Detection
Authors: Tianhao Liu | Meihui Jiang | Dongdong Zhang | Haisen Zhao | Feng Shuang
Source: IEEE Access (article, 2020-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Effect of Symmetrical Voltage Sag on Induction Motor Considering Phase-Angle Factors Based on a New 2-D Multi-Slice Time-Stepping Finite Element Method Voltage sag is one of the most common power quality disturbance in industry, which causes huge inrush current and inrush torque of induction motors, and has serious impacts on the safe and stable operation of induction motor. To further study the detailed transient characteristics of induction motors during sag events, an improved 2-D multi-slice field-circuit-motion coupling time-stepping finite element method (FEM) is proposed. Then, taking a 5.5 kW, a 55 kW and a 135 kW induction motors as examples, the influence of phase-angle jumps and initial point-on-wave on the stator current peak, torque peak, speed loss and critical clearing time of the induction motor are discussed by using the proposed model. The simulation results show that stator current peak and torque peak increase obviously, while speed and critical clearing time decrease apparently, when considering the phase angle jump. And different initial points have little influence on these operation indicators. Finally, the proposed method is verified by comparing the measured and calculation data of the 5.5 kW three-phase squirrel-cage motor, respectively. The results show that the proposed method can reach higher precision with considering nonlinear characteristics. Inrush current ; Control theory (sociology) ; Induction motor ; Stator ; Voltage sag ; Squirrel-cage rotor ; Torque ; Finite element method ; Transient (computer programming) ; Rotor (electric) ; Voltage ; Computer science ; Engineering ; Physics ; Electrical engineering ; Power quality ; Structural engineering Magnetic Properties and Applications ; Electric Motor Design and Analysis ; Machine Fault Diagnosis Techniques
Authors: Wenjing Xia | Tao Xu
Source: ACS Omega (article, 2020-08-14)
Field: Materials Science — Materials Chemistry

Thermal Characteristics, Kinetic Models, and Volatile Constituents during the Energy Conversion of Bituminous SARA Fractions in Air To understand the thermal characteristics, nonisothermal kinetic models, and volatile constituents during the energy conversion of bituminous materials at the fraction level, differential scanning calorimetry-mass spectrometry tests were performed on bituminous four fractions, including saturates, aromatics, resins, and asphaltenes (SARA). Then, three-dimensional (3D) nonisothermal kinetic models of SARA fractions were established and volatile constituents of SARA fractions were discussed. Results indicate that when the heating rate is increased, the decomposition temperature ranges in each stage increase and the initial decomposition, peak, and burn-out temperatures of each SARA fraction all shift to high temperatures. Also, the whole energy conversion processes of SARA fractions are mainly exothermic reactions. Additionally, the energy conversion mechanism in each stage of saturates and aromatics accords with different nonisothermal kinetic models. However, the energy conversion mechanisms of resins and asphaltenes are similar and both accord with the 3D diffusion models. Further, the established nonisothermal kinetic models in each decomposition stage of SARA fractions are feasible to describe the energy conversion processes of SARA fractions. The released small molecular volatiles from saturates and aromatics increase when the heating rate is increased, but the macromolecular volatiles are decreased. The opposite is true for resins, but all volatiles emitted from asphaltenes are increased. Finally, the heating rate has little influence on the constituents of emitted gaseous products from SARA fractions but shows an effect on the release amount of volatiles from SARA fractions. The main common volatiles of SARA fractions are CO<sub>2</sub>, H<sub>2</sub>O, methanol, hydrazine, propyne, acetaldehyde, and propane. This study contributes to further reveal the energy conversion mechanisms of bituminous materials. Kinetic energy ; Asphalt ; Thermal ; Environmental science ; Chemistry ; Environmental chemistry ; Materials science ; Chemical engineering ; Thermodynamics ; Engineering ; Physics ; Composite material Thermal and Kinetic Analysis ; Asphalt Pavement Performance Evaluation ; Polymer Nanocomposites and Properties