jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Tran Thuc Binh | Le Thi Phuong Tram | Nguyen Van Hop | Nguyễn Đăng Giáng Châu | Nguyễn Duy Lưu | Nguyễn Thị Quỳnh Trang
Source: Journal of Analytical Methods in Chemistry (article, 2021-07-20)
Field: Chemistry — Analytical Chemistry

Simultaneous Determination of Hydrochlorothiazide and Losartan Potassium in Pharmaceutical Product by UV-Vis Spectrophotometric Method with Kalman Filter Algorithm In this paper, hydrochlorothiazide (HCT) and losartan potassium (LSP) in tablets are simultaneously determined with UV-Vis spectrophotometry and chemometrics without separation. The spectra of standard and sample solutions were recorded in the wavelength from 220 to 300 nm at 1.0 nm intervals. The concentrations of HCT and LSP in the sample solutions were computed with the Kalman filter algorithm written on the Microsoft Excel 2016 and Visual Basic for Applications (VBA) platform. The method validation was determined via the accuracy and repeatability of measurements when analyzing HCT and LSP in the Splozarsin Plus tablet and comparing the mean values of their contents in the sample with those analyzed with HPLC. The proposed method is simple with a low cost compared with the standard HPLC method. Hydrochlorothiazide ; Repeatability ; Kalman filter ; Losartan Potassium ; Chemometrics ; Chromatography ; Chemistry ; Analytical Chemistry (journal) ; Computer science ; Algorithm ; Artificial intelligence ; Losartan ; Angiotensin II Analytical Methods in Pharmaceuticals ; Pesticide Residue Analysis and Safety ; Analytical Chemistry and Sensors
Authors: Ardy Lololau | Tresna Priyana Soemardi | Harry Purnama | O. Polit
Source: International Journal of Technology (article, 2021-12-20)
Field: Materials Science — Polymers and Plastics

Composite Multiaxial Mechanics: Laminate Design Optimization of Taper-Less Wind Turbine Blades with Ramie Fiber-Reinforced Polylactic Acid As the research on composite materials based on natural resources proliferates further, ramie fiber and polylactic acid (PLA), which are fully biodegradable composite materials, are expected to be used for mechanical application due to their exce Materials science ; Composite number ; Composite material ; Structural engineering ; Turbine blade ; Polylactic acid ; Flexural strength ; Turbine ; Mechanical engineering ; Engineering ; Polymer Natural Fiber Reinforced Composites ; Mechanical Engineering and Vibrations Research ; Cellular and Composite Structures
Authors: Cedric J. Gommes | Reiner Zorn | Sebastian Jaksch | Henrich Frielinghaus | Olaf Holderer
Source: The Journal of Chemical Physics (article, 2021-07-13)
Field: Materials Science — Materials Chemistry

Inelastic neutron scattering analysis with time-dependent Gaussian-field models Converting neutron scattering data to real-space time-dependent structures can only be achieved through suitable models, which is particularly challenging for geometrically disordered structures. We address this problem by introducing time-dependent clipped Gaussian field models. General expressions are derived for all space- and time-correlation functions relevant to coherent inelastic neutron scattering for multiphase systems and arbitrary scattering contrasts. Various dynamic models are introduced that enable one to add time-dependence to any given spatial statistics, as captured, e.g., by small-angle scattering. In a first approach, the Gaussian field is decomposed into localized waves that are allowed to fluctuate in time or to move either ballistically or diffusively. In a second approach, a dispersion relation is used to make the spectral components of the field time-dependent. The various models lead to qualitatively different dynamics, which can be discriminated by neutron scattering. The methods of this paper are illustrated with oil/water microemulsion studied by small-angle scattering and neutron spin-echo. All available data-in both film and bulk contrasts, over the entire range of q and τ-are analyzed jointly with a single model. The analysis points to the static large-scale structure of the oil and water domains while the interfaces are subject to thermal fluctuations. The fluctuations have an amplitude of around 60 Å and contribute to 30% of the total interface area. Neutron scattering ; Neutron ; Inelastic scattering ; Scattering ; Small-angle neutron scattering ; Inelastic neutron scattering ; Biological small-angle scattering ; Field (mathematics) ; Quasielastic neutron scattering Block Copolymer Self-Assembly ; Surfactants and Colloidal Systems ; Spectroscopy and Quantum Chemical Studies
Authors: Jai Inder Preet Singh | Sehijpal Singh
Source: Asian Journal of Engineering and Applied Technology (article, 2021-04-18)
Field: Materials Science — Polymers and Plastics

Mechanical and Biodegradation Behaviour of Jute/ Polylactic Acid Green Composites Global warming, diminution of fossil fuels, escalating oil price’s are the major reasons which forces the researchers to develop green products for the sustainable development. In this research work, green composites have been developed with jute fibers as reinforcement and poly lactic acid as matrix material using compression moulding technique. All composites were developed with maintaining the reinforcement as 30% fiber volume fraction. The influence of curing temperature with the range of 160°C, 170°C and 180°C was investigated for various mechanical properties of developed composites and degradation behaviour of developed composites were analysed using soil burial test. Results acquired from the tests specify that the tensile and flexural strength decreases with upsurge in curing temperature. Morphology study using scanning electron microscopy is further justified the findings obtained from mechanical tests. Biodegradation study was done on the all the three different composites under the soil burial conditions for 9 months and results indicate that composites developed at 160°C degrade faster as compared to others. This study also gives an optimum curing temperature for the development of jute/PLA composites. Polylactic acid ; Composite material ; Materials science ; Ultimate tensile strength ; Curing (chemistry) ; Flexural strength ; Biodegradation ; Scanning electron microscope ; Polymer Natural Fiber Reinforced Composites ; biodegradable polymer synthesis and properties ; Nanocomposite Films for Food Packaging
Authors: Lívia Ribeiro de Souza | Abir Al‐Tabbaa
Source: Lab on a Chip (article, 2021-01-01)
Field: Chemistry — Organic Chemistry

High throughput production of microcapsules using microfluidics for self-healing of cementitious materials Capsule-based self-healing of cementitious materials is an effective way of healing cracks, significantly extending the life of structures, without imposing changes due to the incorporation of capsules into products during mixing. The methodologies currently being used for the development of capsules with a liquid core as a healing agent yield a wide range of sizes and shell thicknesses for the microcapsules, preventing a detailed assessment and optimisation of the microcapsule size and its effects. Uniquely, microfluidic technology offers precise control over the size and shell thickness through the formation of double emulsions. The drawback is that only small quantities of material can be typically produced. Here, by using paralleled junctions in a microfluidic device, high throughput production of materials was achieved, focusing for the first time on self-healing of cementitious materials. A microfluidic chip was assembled with 4 channels in parallel and selected hydrophobicity for the formation of the double emulsions. A coefficient of variation below 2.5% was observed for the 4 junctions, demonstrating the formation of monodisperse capsules. The control over the size and shell thickness by adjusting the flow rates was demonstrated, yielding capsules with an outer diameter of 615-630 μm and a shell thickness varying between 50 and 127 μm. By using triethanolamine as a surfactant, capsules with an aqueous core were produced. Furthermore, by selecting PEA, an acrylate with low tensile strength, the capsules embedded in the cement paste were successfully triggered to release the healing agent by crack formation. Capsules were successfully produced continuously for 7 h, with inner and outer diameters of 500 ± 31 μm and 656 ± 9 μm at a production rate of ∼13 g h<sup>-1</sup> and a yield of around 80%. With these results and considering up to 6 chips in parallel, the production rate could be up to 1.5 kg per day. This demonstrates the huge potential of the microfluidic device with unique features to produce sufficiently large quantities of microcapsules for laboratory-scale assessment of self-healing performance. Materials science ; Microfluidics ; Microfiber ; Composite material ; Ultimate tensile strength ; Dispersity ; Triethanolamine ; Mixing (physics) ; Seal (emblem) ; Cementitious ; Self-healing ; Nanotechnology ; Emulsion ; Acrylate ; Cement ; Chemical engineering ; Polymer ; Chromatography ; Chemistry Synthetic Organic Chemistry Methods ; Microbial Applications in Construction Materials ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: Vitalii Emelianov | Nataliia Emelianova | Anton Zhilenkov | Sergei Chernyi
Source: Entropy (article, 2021-01-11)
Field: Materials Science — Materials Chemistry

Application of Information Technologies and Programming Methods of Embedded Systems for Complex Intellectual Analysis An information model is outlined, which represents an intelligent system of metallographic analysis in the form of a set of subsystems, the interaction of which ensures the performance of metallographic analysis functions. The structure of the information storage subsystem for metallographic analysis is presented. The deployment model of an intelligent metallographic analysis system is proposed and described. The paper outlines the approach to the presentation of an expert subsystem for metallographic quality control of metals based on a neural network. The process of finding a close precedent in metallographic analysis with reference to a multilayer neural network is described. An intelligent metallographic analysis system is described, which based on proposed information model. A specialized software of an intelligent metallographic analysis system is presented. The functioning results of the developed system for processing images of steel microstructures to determine the steel quantitative parameters is presented. Artificial neural network ; Computer science ; Process (computing) ; Software ; Expert system ; Set (abstract data type) ; Artificial intelligence ; Operating system Material Properties and Failure Mechanisms ; Stonefly species taxonomy and ecology ; Engineering Diagnostics and Reliability
Authors: Xujun Ye | Tamaki Doi | Osamu Arakawa | Shuhuai Zhang
Source: Scientific Reports (article, 2021-11-09)
Field: Chemistry — Analytical Chemistry

A novel spatially resolved interactance spectroscopy system to estimate degree of red coloration in red-fleshed apple Reliable information about degree of red coloration in fruit flesh is essential for grading and sorting of red-fleshed apples. We propose a spatially resolved interactance spectroscopy approach as a new rapid and non-destructive technique to estimate degree of red coloration in the flesh of a red-fleshed apple cultivar 'Kurenainoyume'. A novel measurement system was developed to obtain spatially resolved interactance spectra (190-1070 nm) for apple fruits at eight different light source-detector separation (SDS) distances on fruit surface. Anthocyanins in apple were extracted using a solvent extraction technique, and their contents were quantified with a spectrophotometer. Partial least squares (PLS) regression analyses were performed to develop estimation models for anthocyanin content from spatially resolved interactance spectra. Results showed that the PLS models based on interactance spectra obtained at different SDS distances achieved different predictive accuracy. Further, the system demonstrated the possibility to detect the degree of red coloration in the flesh at specific depths by identifying an optimal SDS distance. This might contribute to provide a detailed profile of the red coloration (anthocyanins) that is unevenly distributed among different depths of the flesh. This new approach may be potentially applied to grading and sorting systems for red-fleshed apples in fruit industry. Flesh ; Partial least squares regression ; Cultivar ; Chemistry ; Anthocyanin ; Food science ; Red Color ; Horticulture ; Botany ; Mathematics ; Biology ; Computer science Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Water Quality Monitoring and Analysis
Authors: Xiang Huang | Jie Huang | Lina Yang | Zhenfu Zhang | Hansi Ma | Qian Yang | Chengxi Li | Zhenrong Zhang | Junbo Yang
Source: IEEE photonics journal (article, 2021-04-12)
Field: Materials Science — Electronic, Optical and Magnetic Materials

All-Dielectric Metasurfaces Color Filter Arrays Designed by Evolutionary Search Compared with traditional dyes, structural color has been studied widely due to several outstanding advantages. When choosing structural color materials, both metal and dielectric materials have great potential, however compared with metal, dielectric material have the characteristics of low cost and low loss, so been studied widely. At present, the design of metasurface structural color based on dielectric materials is mostly carried out by manually adjusting parameters. Although good results can achieved by this method, but the design cycle is too long and the method is not smart enough, which is not conducive to industrial design. In this article, we proposed a combination of intelligent algorithms and finite domain time domain solution, and designed matesurface structural color successfully that can reflect high-quality colors. The reflection peak value of the RGB colors reached 90%, 82.2%, 45.8% respectively, also accompany with narrow FWHM, the designed structural color has strong robustness and method reusability, meanwhile, our work provides a novel way for the design of reflective structural color. Structural coloration ; Color gel ; RGB color model ; Dielectric ; Robustness (evolution) ; Reusability ; Computer science ; Color filter array ; Materials science ; Reflection (computer programming) ; Finite-difference time-domain method ; Artificial intelligence ; Optoelectronics ; Electronic engineering ; Computer vision ; Optics ; Nanotechnology ; Layer (electronics) ; Photonic crystal ; Engineering Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Photonic Crystals and Applications
Authors: I. Bandyopadhyay | Matteo Barbarino | A. Bhattacharjee | N.W. Eidietis | A. Huber | A. Isayama | Jayhyun Kim | С. В. Коновалов | M. Lehnen | E. Nardon | Gabriella Pautasso | Cristina Rea | C. Sozzi | F. Villone | Long Zeng
Source: Nuclear Fusion (article, 2021-05-06)
Field: Materials Science — Materials Chemistry

Summary of the IAEA technical meeting on plasma disruptions and their mitigation Abstract This report summarizes the contributions presented at the IAEA technical meeting on plasma disruptions and their mitigation, held virtually, 20–23 July 2020. The meeting brought together more than 120 experts from nuclear fusion research sites worldwide to discuss experimental, theoretical and modelling work in the field of plasma disruptions with special emphasis on developing a solid basis for possible disruption mitigation strategies in ITER and next generation fusion devices. The main topics of the meeting were: (i) disruption consequences, including electromagnetic loads, heat loads, and runaway electrons; (ii) disruption prediction and avoidance, including machine learning and physics-based approaches, and control aspects; and (iii) disruption mitigation, including shattered pellet injection, alternative techniques and general aspects of disruption mitigation. Fusion power ; Nuclear fusion ; Work (physics) ; Nuclear engineering ; Plasma ; Field (mathematics) ; Systems engineering ; Risk analysis (engineering) ; Computer science ; Engineering ; Physics ; Nuclear physics ; Mechanical engineering ; Business Fusion materials and technologies ; Magnetic confinement fusion research
Authors: Huiyu Chang | Jiale Gao | Senfeng Lai | Yanghui Wu | Chen Fu | Wenhua Gu
Source: IEEE photonics journal (article, 2021-08-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Prediction of the Electromagnetic Shielding Effectiveness of Metal Grid Using Neural Network Algorithm With the advantages of simple structure, high electromagnetic (EM) shielding effectiveness (SE), wide shielding bandwidth and adjustable transmittance, the metal grid is a popular tool in the field of electromagnetic shielding. In this work, the deep learning algorithm of artificial neural network was used to predict the EM SE of the metal grid. After certain number of trainings, both the SE spectrum and the minimum SE value in a given frequency band can be predicted accurately and effectively. On the other hand, for a target SE, the design parameters of the metal grid structure can be immediately predicted. The results show that the relative mean square deviation of the predicted SE curve is about 5%, the relative error of the minimum SE value of the curve is less than 5%, and the average relative error of the minimum SE value in the predicted frequency band is 11.5%. Electromagnetic shielding ; Grid ; Approximation error ; Artificial neural network ; Computer science ; Mean squared error ; Algorithm ; Bandwidth (computing) ; Electromagnetic field ; Frequency band ; Electromagnetic compatibility ; Optics ; Electronic engineering ; Telecommunications ; Artificial intelligence ; Physics ; Mathematics ; Geometry ; Electrical engineering ; Statistics ; Engineering Electromagnetic wave absorption materials ; Electromagnetic Compatibility and Measurements ; Advanced Antenna and Metasurface Technologies
Authors: Jian Song | Changbin Yu
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-04-09)
Field: Chemistry — Spectroscopy

Missing Value Imputation using XGboost for Label-Free Mass Spectrometry-Based Proteomics Data Abstract The label-free mass spectrometry-based proteomics data inevitably suffer from the problem of missing values. The existence of missing values prevents the downstream analyses which need a complete data matrix. Our motivation is to introduce the state-of-art machine learning algorithm XGboost to realize a method of imputation which can improve the accuracy of imputation. But in practical, XGboost has many parameters need to be tuned to deliver on its potential high performance. Although cross validation may find the best parameters, it is much time-consuming. Alternatively, we empirically determined the parameters to two kinds of base learners of XGboost. To explore the robustness and performance of XGboost based imputation with predetermined parameters, we conducted tests on three benchmark datasets. As a comparative, six common imputation methods were also experimented in terms of normalized root mean squared error and Pearson correlation coefficient. The comparative experimental results indicated that the XGboost based imputation method using the linear base learner is competitive to or out-performs its competitors, including the random forest based imputation, by achieving smaller imputation errors and better structure preservation under the empirical parameters for the three benchmark datasets. Imputation (statistics) ; Missing data ; Computer science ; Robustness (evolution) ; Data mining ; Random forest ; Statistics ; Artificial intelligence ; Mathematics ; Machine learning Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Mass Spectrometry Techniques and Applications
Authors: G. Vértesy | Antal Gasparics | Ildikó Szenthe | Madalina Rabung | Melanie Kopp | James Griffin
Source: Materials (article, 2021-09-13)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Analysis of Magnetic Nondestructive Measurement Methods for Determination of the Degradation of Reactor Pressure Vessel Steel Nondestructive magnetic measurement methods can be successfully applied to determine the embrittlement of nuclear pressure vessel steel caused by neutron irradiation. It was found in previous works that reasonable correlation could be obtained between the nondestructively measured magnetic parameters and destructively determined ductile-to-brittle transition temperature. However, a large scatter of the measurement points was detected even in the cases of the non-irradiated reference samples. The reason for their scattering was attributed to the local inhomogeneity of material. This conclusion is verified in the present work by applying three different magnetic methods on two sets of Charpy samples made of two different reactor steel materials. It was found that by an optimal magnetic pre-selection of samples, a good, linear correlation can be found between magnetic parameters as well as the ductile-to-brittle transition temperature with low scattering of points. This result shows that neutron irradiation embrittlement depends very much on the local material properties. Embrittlement ; Materials science ; Charpy impact test ; Pressure vessel ; Reactor pressure vessel ; Brittleness ; Nondestructive testing ; Scattering ; Composite material ; Nuclear physics ; Optics ; Microstructure ; Physics Magnetic Properties and Applications ; Non-Destructive Testing Techniques ; Microstructure and Mechanical Properties of Steels
Authors: Emine Utkun
Source: Industria Textila (article, 2021-12-21)
Field: Materials Science — Polymers and Plastics

Comparison of sensorial comfort properties of different cotton fabricsusing the Kawabata Evaluation System Cotton fabrics are among the most preferred fabrics for both underwear and outerwear. The sensory comfort properties of the fabrics are important for consumers’ choice of clothing. The majority of consumers visually like the clothes that they buy and try to feel these features sensually by touching them, and then, they may want to try the garment or they can make direct purchasing decisions according to these tactile feelings. In this study, the sensorial properties of a double-layered cotton fabric developed for use as a garment were compared and evaluated with cotton plain woven and interlock fabrics currently used in the market for this purpose. Sensorial comfort properties of the fabrics were researched with KES-F Kawabata equipment. Clothing ; Purchasing ; Architectural engineering ; Business ; Materials science ; Engineering ; Marketing ; Geography Textile materials and evaluations ; Ergonomics and Musculoskeletal Disorders
Authors: Angelica Arioli | Arianna Dagliati | Bethany Geary | Niels Peek | Philip A. Kalra | Anthony D. Whetton | Nophar Geifman
Source: PLoS ONE (article, 2021-04-15)
Field: Chemistry — Spectroscopy

OptiMissP: A dashboard to assess missingness in proteomic data-independent acquisition mass spectrometry OptiMissP provides support for researchers' and clinicians' qualitative assessment of missingness in proteomic datasets in order to define study-specific strategies for the handling of missing values. OptiMissP considers biases in protein distributions related to the choice of imputation method and helps analysts to balance the information loss caused by low missingness thresholds and the noise introduced by selecting high missingness thresholds. This is complemented by topological data analysis which provides additional insight to the structure of the data and their missingness. We use an example in Chronic Kidney Disease to illustrate the main functionalities of OptiMissP. Mass spectrometry ; Missing data ; Computer science ; Computational biology ; Data science ; Chemistry ; Biology ; Chromatography ; Machine learning Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Mass Spectrometry Techniques and Applications