jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Sowjanya Gummadi | Prasanna Kumar Chandaka
Source: American Journal of PharmTech Research (article, 2019-02-08)
Field: Chemistry — Analytical Chemistry

Chemometrics Approach to Drug Analysis â€“ An Overview Chemometrics is the use of mathematical and statistical methods to improve the understanding of chemical information and to correlate quality parameters or physical properties to analytical instrument data. It is a data-driven multidisciplinary science that allows maximum collection and extraction of useful information from the analytical data of numerous application areas such as chemistry, biochemistry, medicine, biology and chemical engineering. This review focuses mainly on numerous chemometric models used and their relevant applications in the field of pharmaceutical sciences. Chemometrics ; Drug ; Computer science ; Data science ; Management science ; Medicine ; Pharmacology ; Engineering ; Machine learning Spectroscopy and Chemometric Analyses ; Computational Drug Discovery Methods ; Analytical Chemistry and Chromatography
Authors: Meysam Hassanipour | Shinta Watanabe | Kyosuke Hirayama | H. Li | Hiroyuki Toda | Kentaro Uesugi | Akihisa Takeuchi
Source: Materials Science and Engineering A (article, 2019-02-01)
Field: Materials Science — Materials Chemistry

Assessment of predominant microstructural features controlling 3D short crack growth behavior via a surrogate approach in Ti-6Al-4V Materials science ; Crack closure ; Microstructure ; Shear (geology) ; Electron backscatter diffraction ; Fracture mechanics ; Composite material ; Crack growth resistance curve ; Ultimate tensile strength ; Paris' law Titanium Alloys Microstructure and Properties ; High-Velocity Impact and Material Behavior ; Microstructure and mechanical properties
Authors: Izabela Jasińska
Source: Applied Sciences (article, 2019-09-10)
Field: Materials Science — Polymers and Plastics

The Algorithms of Image Processing and Analysis in the Textile Fabrics Abrasion Assessment The abrasion resistance and susceptibility of textiles to surface damage is an important issue for their utility properties. The currently used test method for abrasion resistance assessment has been based on criteria that define the breakage point of fabrics, visually identified and highly depended on observer perception. Taking under consideration the character of abrasion assessment process the efforts were made to elaborate the new alternative test technique which supports this evaluation. The abrasion resistance tests using instrumental method (based on image analysis tools) parallel with standard method were carried out. There were two steps of analysis. Firstly, the preliminary analysis for selecting the most effective and sensitive algorithm was carried out. Secondly, the final analysis, involving whole range of captured image samples, using chosen algorithm, based on image histogram calculation was done. Summarizing the abrasion resistance tests results obtained using both standard and instrumental methods it was found that the instrumental method gave more complex results during identification of surface changes caused directly by the abrasion process. The instrumental method is more sensitive to surface texture modifications and colour fade and its discrimination threshold is significantly lower than standard methods with qualitative breakage criteria (such as broken threads, loss of pile). Abrasion (mechanical) ; Breakage ; Point (geometry) ; Computer science ; Histogram ; Artificial intelligence ; Image (mathematics) ; Mathematics ; Materials science ; Composite material Textile materials and evaluations ; Industrial Vision Systems and Defect Detection ; Surface Roughness and Optical Measurements
Authors: Sang-Yun Yang | Yonggun Park | Hyunwoo Chung | Hyunbin Kim | Se‐Yeong Park | In-Gyu Choi | Ohkyung Kwon | Hwanmyeong Yeo
Source: Journal of the Korean Wood Science and Technology (article, 2019-01-01)
Field: Chemistry — Analytical Chemistry

Soft Independent Modeling of Class Analogy for Classifying Lumber Species Using Their Near-infrared Spectra This paper examines the classification of five coniferous species, including larch (Larix kaempferi), red pine (Pinus densiflora), Korean pine (Pinus koraiensis), cedar (Cryptomeria japonica), and cypress (Chamaecyparis obtusa), using near−infrared (NIR) spectra. Fifty lumber samples were collected for each species. After air−drying the lumber, the NIR spectra (wavelength = 780−2500 nm) were acquired on the wide face of the lumber samples. Soft independent modeling of class analogy (SIMCA) was performed to classify the five species using their NIR spectra. Three types of spectra (raw, standard normal variated, and Savitzky−Golay 2nd derivative) were used to compare the classification reliability of the SIMCA models. The SIMCA model based on Savitzky−Golay 2nd derivatives preprocessing was determined as the best classification model in this study. The accuracy, minimum precision, and minimum recall of the best model (PCA models using Savitzky−Golay 2nd derivative preprocessed spectra) were evaluated as 73.00%, 98.54% (Korean pine), and 67.50% (Korean pine), respectively. Cryptomeria ; Larix kaempferi ; Chamaecyparis ; Cypress ; Larch ; Pinus densiflora ; Pinus koraiensis ; Mathematics ; Pattern recognition (psychology) ; Artificial intelligence ; Chemistry ; Japonica ; Botany ; Computer science ; Biology Spectroscopy and Chemometric Analyses ; Wood and Agarwood Research ; Industrial Vision Systems and Defect Detection
Authors: Zhipeng Ma | Lijun Yang | Haoran Bian | Muhammad Shoaib Bhutta | Pengfei Xu
Source: IEEE Access (article, 2019-01-01)
Field: Materials Science — Materials Chemistry

An Improved IPM for Life Estimation of XLPE Under DC Stress Accounting for Space-Charge Effects Inverse power model (IPM) is often used in the engineering field to estimate the electrical life of cross-linked polyethylene (XLPE) cable insulation and describe the relationship between applied voltage and insulation failure time. The voltage tolerance index n in IPM is also used as an important factor to select appropriate AC cable thickness and pre-evaluation test voltage. However, under the influence of DC electric field, space charge accumulation changes the internal field strength of XLPE. As a result, the actual electric field strength is quite different from the applied value. Hence, the existing IPM model exhibits a large error in evaluating the electrical life of DC cables. In this paper, an improved IPM is proposed. The correction parameters α and β are introduced into the cumulative loss parameter C and voltage tolerance index n of the existing IPM to quantify the effect of space charge on distorting the electric field in electrical insulation life. Correlation between applied field strength (E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">a</sub> ), maximum endurance field strength (E <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">rm</sub> ) and insulation failure time t of several XLPE with different thicknesses is obtained from DC voltage withstand test and pulsed electro acoustic test. In addition, the validity of the improved IPM is preliminarily verified. α and β predicted by using the space charge characteristic parameter matrix [P] is proposed to efficiently obtain the actual parameters. According to experimental analysis, the improved IPM with a certain thickness is predicted by using the neural network fitting method. Space charge ; Electric field ; Voltage ; Field (mathematics) ; Electrical engineering ; Materials science ; Electronic engineering ; Computer science ; Reliability engineering ; Physics ; Mathematics ; Engineering High voltage insulation and dielectric phenomena ; Electrical Fault Detection and Protection ; Electrostatic Discharge in Electronics
Authors: Nathan D. Wright | P.M. Collins | R. Talon | Elliot R Nelson | L. Koekemoer | Mingda Ye | Radosław P. Nowak | Joseph Newman | Jia Tsing Ng | Nick Mitrovich | Helton Wiggers | F. von Delft
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2019-12-20)
Field: Materials Science — Materials Chemistry

The Low-Cost, Semi-Automated Shifter Microscope Stage Transforms Speed and Robustness of Manual Protein Crystal Harvesting Abstract Despite the tremendous success of x-ray cryocrystallography over recent decades, the transfer of crystals from the drops where they grow to diffractometer sample mounts, remains a manual process in almost all laboratories. Here we describe the Shifter, a semi-automated microscope stage that offers an accessible and scalable approach to crystal mounting that exploits on the strengths of both humans and machines. The Shifter control software manoeuvres sample drops beneath a hole in a clear protective cover, for human mounting under a microscope. By allowing complete removal of film seals the tedium of cutting or removing the seal is eliminated. The control software also automatically captures experimental annotations for uploading to the user’s data repository, removing the overhead of manual documentation. The Shifter facilitates mounting rates of 100-240 crystals per hour, in a more controlled process than manual mounting, which greatly extends the lifetime of drops and thus allows for a dramatic increase in the number of crystals retrievable from any given drop, without loss of X-ray diffraction quality. In 2015 the first in a series of three Shifter devices was deployed as part of the XChem fragment screening facility at Diamond Light Source (DLS), where they have since facilitated the mounting of over 100,000 crystals. The Shifter was engineered to be simple, allowing for a low-cost device to be commercialised and thus potentially transformative as many research initiatives as possible. Synopsis A motorised X/Y microscope stage is presented that combines human fine motor control with machine automation and automated experiment documentation, to transform productivity in protein crystal harvesting. Microscope ; Computer science ; Software ; Automation ; Computer hardware ; Materials science ; Engineering drawing ; Engineering ; Mechanical engineering ; Optics ; Operating system ; Physics Enzyme Structure and Function ; Biochemical and Molecular Research ; Genetics, Bioinformatics, and Biomedical Research
Authors: Yoko Yamabe‐Mitarai | S. Kuroda | Norie Motohashi | Hiroaki Matsumoto | Gorō Miyamoto | Elango Chandiran | Yoshinori Yoshida | Yoshio Itsumi
Source: MATERIALS TRANSACTIONS (article, 2019-04-11)
Field: Materials Science — Materials Chemistry

Effect of Forging Temperature on Microstructure Evolution and Tensile Properties of Ti-17 Alloys In this study, the microstructure, tensile strength, elongation, and reduction of area of near-β Ti alloys (Ti-17) were investigated after being subjected to solution and aging treatments. Ti-17 was forged at temperatures between 700 and 850°C followed by air cooling. Then, the forged Ti-17 was subjected to solution treatment at 800°C for 4 h followed by water quenching and aging treatment at 620°C for 8 h followed by air cooling. Tensile tests were performed at room temperature, 450°C, and 600°C. The change in microstructure at different forging temperatures was exhibited by only the volume fraction and morphology of the grain boundary (GB) α phase. That is, a granular GB α phase was formed in the samples forged at 700 and 750°C. Moreover, a film-like GB α phase was formed in the samples forged at 800 and 850°C. The tensile strength was the same for all the tested samples, indicating that the microstructure has little effect on the tensile strength. The elongation and reduction of area increased with decreasing volume fraction in the GB α phase. It is considered that the film-like morphology slightly improves ductility. Materials science ; Microstructure ; Ultimate tensile strength ; Volume fraction ; Forging ; Elongation ; Ductility (Earth science) ; Phase (matter) ; Quenching (fluorescence) ; Metallurgy ; Composite material ; Grain boundary ; Creep Titanium Alloys Microstructure and Properties ; Intermetallics and Advanced Alloy Properties ; Metallurgy and Material Forming
Authors: N. Pankajkumar-Patel | E. Peris-García | M.J. Ruiz-Ángel | Samuel Carda‐Broch | M.C. García‐Álvarez‐Coque
Source: Journal of Chromatography A (review, 2019-01-19)
Field: Chemistry — Spectroscopy

Modulation of retention and selectivity in oil-in-water microemulsion liquid chromatography: A review Chemistry ; Microemulsion ; Pulmonary surfactant ; Reagent ; Chromatography ; Selectivity ; Yield (engineering) ; Elution ; Aqueous solution ; Phase (matter) ; Organic chemistry Analytical Chemistry and Chromatography ; Surfactants and Colloidal Systems ; Microfluidic and Capillary Electrophoresis Applications
Authors: Thomas Matson | Max Farfel | Nathan Levin | Elizabeth A. Holm | Chen Wang
Source: Microscopy and Microanalysis (article, 2019-08-01)
Field: Materials Science — Materials Chemistry

Machine Learning and Computer Vision for the Classification of Carbon Nanotube and Nanofiber Structures from Transmission Electron Microscopy Data Transmission electron microscopy ; Carbon nanotube ; Nanofiber ; Carbon nanofiber ; Materials science ; Nanotechnology ; Electron microscope ; Artificial intelligence ; Computer science ; Optics ; Physics Carbon Nanotubes in Composites ; Nanotechnology research and applications ; Graphene and Nanomaterials Applications
Authors: Ya‐Qiong Zhao | Feng Qin | Fei Xu | Jinxing Ma | Zhenyu Sun | Yuli Song | Longlian Zhao | Junhui Li | Haiguang Wang
Source: Journal of Spectroscopy (article, 2019-07-24)
Field: Chemistry — Analytical Chemistry

Identification of <i>Tilletia foetida</i>, <i>Ustilago tritici</i>, and <i>Urocystis tritici</i> Based on Near-Infrared Spectroscopy Identifying plant pathogens for disease diagnosis and disease control strategy making is of great significance. In this study, based on near-infrared spectroscopy, a method for identifying three kinds of pathogens causing wheat smuts, including Tilletia foetida , Ustilago tritici , and Urocystis tritici , was investigated. Based on the acquired near-infrared spectral data of the teliospore samples of the three pathogens, pathogen identification models were built in different spectral regions using distinguished partial least squares (DPLS), backpropagation neural network (BPNN), and support vector machine (SVM). Satisfactory identification results were achieved using the DPLS, BPNN, and SVM models built in each of the 22 spectral regions. By contrast, the modeling effects of DPLS and SVM were better than those of BPNN. The modeling ratio of the training set to the testing set affected the identification results of the BPNN models more than those obtained using the DPLS and SVM models. In this study, a rapid, accurate, and nondestructive method was provided for plant pathogen identification, and some basis was provided for disease diagnosis, pathogen monitoring, and disease control. Moreover, some methodological references and supports were provided for identification of quarantine wheat smut fungi in plant quarantine. Identification (biology) ; Plant disease ; Support vector machine ; Artificial intelligence ; Biology ; Pattern recognition (psychology) ; Biological system ; Computational biology ; Botany ; Computer science ; Biotechnology Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Plant Pathogens and Fungal Diseases
Authors: Alexandre Boulle | Jérôme Kieffer
Source: Journal of Applied Crystallography (article, 2019-07-24)
Field: Materials Science — Materials Chemistry

High-performance Python for crystallographic computing The Python programming language, combined with the numerical computing library NumPy and the scientific computing library SciPy , has become the de facto standard for scientific computing in a variety of fields. This popularity is mainly due to the ease with which a Python program can be written and executed (easy syntax, dynamical typing, no compilation etc. ), coupled with the existence of a large number of specialized third-party libraries that aim to lift all the limitations of the raw Python language. NumPy introduces vector programming, improving execution speeds, whereas SciPy brings a wealth of highly optimized and reliable scientific functions. There are cases, however, where vector programming alone is not sufficient to reach optimal performance. This issue is addressed with dedicated compilers that aim to translate Python code into native and statically typed code with support for the multi-core architectures of modern processors. In the present article it is shown how these approaches can be efficiently used to tackle different problems, with increasing complexity, that are relevant to crystallography: the 2D Laue function, scattering from a strained 2D crystal, scattering from 3D nanocrystals and, finally, diffraction from films and multilayers. For each case, detailed implementations and explanations of the functioning of the algorithms are provided. Different Python compilers (namely NumExpr , Numba , Pythran and Cython ) are used to improve performance and are benchmarked against state-of-the-art NumPy implementations. All examples are also provided as commented and didactic Python ( Jupyter ) notebooks that can be used as starting points for crystallographers curious to enter the Python ecosystem or wishing to accelerate their existing codes. Python (programming language) ; Computer science ; Programming language ; Compiler ; Implementation ; Computational science ; Theoretical computer science Enzyme Structure and Function ; Machine Learning in Materials Science ; X-ray Diffraction in Crystallography
Authors: Zhe Feng | Chengqiao Ding | Weihao Li | Di Cui
Source: International journal of agricultural and biological engineering (article, 2019-01-01)
Field: Chemistry — Analytical Chemistry

Detection of blood spots in eggs by hyperspectral transmittance imaging Blood spots are one of undesired inclusions in eggs, whose detection success is highly dependent on shell color. This research reports a method for detecting blood spots in light brown-shelled eggs on the basis of hyperspectral transmittance images. The normalized spectra of intact eggs and their shells were acquired. Five feature wavelengths of intact eggs selected by the successive projections algorithm and 3 absorption peak locations of eggshells were regarded as characteristic bands. The k-nearest neighbor (kNN) and support vector machine (SVM) algorithms were adopted to develop detection models. The latter achieved better performance. The overall classification accuracy increased to 100% by merging normalized spectra of intact eggs at 5 feature wavelengths with 3 absorption peaks of eggshells as input variables of SVM-based model. Moreover, a practical SVM-based model with 96.43% overall classification accuracy was established by replacing inputs with normalized spectra of intact eggs at characteristic bands. Keywords: hyperspectral transmittance imaging, non-destructive detection, blood-spot, egg DOI: 10.25165/j.ijabe.20191206.5376 Citation: Feng Z, Ding C Q, Li W H, Cui D. Detection of blood spots in eggs by hyperspectral transmittance imaging. Int J Agric & Biol Eng, 2019; 12(6): 209–214. Hyperspectral imaging ; Spots ; Transmittance ; Support vector machine ; Wavelength ; Eggshell ; Feature (linguistics) ; Artificial intelligence ; Absorption (acoustics) ; Spectral line ; Pattern recognition (psychology) ; Optics ; Materials science ; Analytical Chemistry (journal) ; Mathematics ; Chemistry ; Computer science ; Physics ; Biology ; Chromatography ; Botany ; Ecology Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality
Authors: Joscelyn Sarsby | Lynn McLean | Victoria M. Harman | Robert J. Beynon
Source: Rapid Communications in Mass Spectrometry (article, 2019-11-23)
Field: Chemistry — Spectroscopy

Monitoring recombinant protein expression in bacteria by rapid evaporative ionisation mass spectrometry REIMS has considerable potential as a near-instantaneous monitoring tool for protein production in a biotechnology environment. Mass spectrometry ; Recombinant DNA ; Heterologous ; Escherichia coli ; Chemistry ; Bacteria ; Plasmid ; Heterologous expression ; Chromatography ; Biology ; Biochemistry ; DNA Mass Spectrometry Techniques and Applications ; Ion-surface interactions and analysis ; Advanced Proteomics Techniques and Applications
Authors: Edoardo Mainini | Paolo Piovano | Bernd Schmidt | Ulisse Stefanelli
Source: Journal of Statistical Physics (article, 2019-07-24)
Field: Materials Science — Materials Chemistry

$$N^{3/4}$$ Law in the Cubic Lattice We investigate the Edge-Isoperimetric Problem (EIP) for sets with <i>n</i> elements of the cubic lattice by emphasizing its relation with the emergence of the Wulff shape in the crystallization problem. Minimizers <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mi>M</mml:mi> <mml:mi>n</mml:mi></mml:msub> </mml:math> of the edge perimeter are shown to deviate from a corresponding cubic Wulff configuration with respect to their symmetric difference by at most <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mi>O</mml:mi> <mml:mo>(</mml:mo> <mml:msup><mml:mi>n</mml:mi> <mml:mrow><mml:mn>3</mml:mn> <mml:mo>/</mml:mo> <mml:mn>4</mml:mn></mml:mrow> </mml:msup> <mml:mo>)</mml:mo></mml:mrow> </mml:math> elements. The exponent 3 / 4 is optimal. This extends to the cubic lattice analogous results that have already been established for the triangular, the hexagonal, and the square lattice in two space dimensions. Lattice (music) ; Cubic crystal system ; Reciprocal lattice ; Exponent ; Square lattice ; Perimeter ; Crystallization ; Lattice constant Quasicrystal Structures and Properties ; Mathematical Approximation and Integration ; Nonlinear Partial Differential Equations
Authors: Angelo Maiorino | Antongiulio Mauro | Manuel Gesù Del Duca | Adrián Mota-Babiloni | Ciro Aprea
Source: Energies (article, 2019-11-19)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Looking for Energy Losses of a Rotary Permanent Magnet Magnetic Refrigerator to Optimize Its Performances In this paper, an extensive study on the energy losses of a magnetic refrigerator prototype developed at University of Salerno, named ‘8MAG’, is carried out with the aim to improve the performance of such a system. The design details of ‘8MAG’ evidences both mechanical and thermal losses, which are mainly attributed to the eddy currents generation into the support of the regenerators (magnetocaloric wheel) and the parasitic heat load of the rotary valve. The latter component is fundamental since it imparts the direction of the heat transfer fluid distribution through the regenerators and it serves as a drive shaft for the magnetic assembly. The energy losses concerning eddy currents and parasitic heat load are evaluated by two uncoupled models, which are validated by experimental data obtained with different operating conditions. Then, the achievable coefficient of performance (COP) improvements of ‘8MAG’ are estimated, showing that reducing eddy currents generation (by changing the material of the magnetocaloric wheel) and the parasitic heat load (enhancing the insulation of the rotary valve) can lead to increase the COP from 2.5 to 2.8 (+12.0%) and 3.0 (+20%), respectively, and to 3.3 (+32%), combining both improvements, with an hot source temperature of 22 °C and 2 K of temperature span. Magnetic refrigeration ; Refrigerator car ; Magnet ; Cooling load ; Mechanical engineering ; Coefficient of performance ; Eddy current ; Materials science ; Heat transfer coefficient ; Nuclear engineering ; Automotive engineering ; Mechanics ; Heat transfer ; Electrical engineering ; Engineering ; Magnetic field ; Heat pump ; Physics ; Heat exchanger ; Air conditioning ; Magnetization Magnetic and transport properties of perovskites and related materials ; Advanced Thermoelectric Materials and Devices ; Advanced Thermodynamics and Statistical Mechanics