jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: B.A. BONDAREV | Pavel Komarov | Anton Kosta | Oleg Korneev | A.B. BONDAREV | Anastasia Korneeva
Source: The Eurasian Scientific Journal (article, 2021-02-01)
Field: Materials Science — General Materials Science

Research of the endurance of epoxy composite materials under cyclic compression The widespread use of polymer composite materials is largely constrained by the complexity of predicting the characteristics of their stress-strain state under cyclic types of loading. Due to the poor knowledge of the behavior of polymer composite materials under this kind of loading. At present, it is rather difficult to predict the durability of polymer composite materials under static types of loading, and the available methods for materials of a crystalline structure and polymers are not always applicable to them. Insufficient theoretical and experimental data on the assessment of the stress-strain state of polymer concretes under prolonged loading. Under long-term action of cyclic loads, changes in the structure of polymer composite materials occur due to local self-heating at the tops of growing submicrocracks and the associated change in the elastic-hesteretic properties of the material. In this case, the energy of fatigue manifests itself, when the simultaneous multifactorial cyclic action of natural and force stresses leads to an effect that exceeds the total action of certain types of stresses. And, if such processes have been sufficiently studied for wood, a natural polymer material, then for artificial conglomerates, such as polymer composites, these issues require careful study. Studies of the endurance of epoxy polymer concretes were carried out on samples of prisms 100x100x400 mm according to the method developed by the authors. The formula was used to determine the minimum number of samples required to build endurance lines. The value of the cycle asymmetry coefficient was taken equal to 0.6. The value of the maximum cyclic loading was taken from 0.62 Rв with a gradual decrease. The values of the endurance limit of an epoxy composite material under cyclic loading Rв,pul = 0.43 Rв or 93.72 MPa were obtained, which makes it possible to judge the sufficient durability of this material. Materials science ; Epoxy ; Composite material ; Polymer ; Composite number ; Stress (linguistics) ; Cyclic stress ; Durability Material Properties and Applications ; Structural mechanics and materials ; Polymer Science and Applications
Authors: Chanh-Nghiem Nguyen | Van-Linh Lam | Phuc-Hau Le | Huy-Thanh Ho | Chi-Ngon Nguyen
Source: International Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering (article, 2021-11-05)
Field: Chemistry — Analytical Chemistry

Early detection of slight bruises in apples by cost-efficient near-infrared imaging Near-infrared (NIR) spectroscopy has been widely reported for its useful applications in assessing internal fruit qualities. Motivated by apple consumption in the global market, this study aims to evaluate the possibility of applying NIR imaging to detect slight bruises in apple fruits. A simple optical setup was designed, and low-cost system components were used to promote the future development of practical and cost-efficient devices. To evaluate the effectiveness of the proposed approach, slight bruises were created by a mild impact with a comparably low impact energy of only 0.081 Joules. Experimental results showed that 100% of bruises in Jazz and Gala apples were accurately detected immediately after bruising and within 3 hours of storage. Thus, it is promising to develop customer devices to detect slight bruises for not only apple fruits but also other fruits with soft and thin skin at their early damage stages. Near-infrared spectroscopy ; Computer science ; Materials science ; Medicine ; Environmental science ; Optics ; Physics Spectroscopy and Chemometric Analyses ; Postharvest Quality and Shelf Life Management ; Fungal Plant Pathogen Control
Authors: Hesham El‐Sherif | Natalie Briggs | Joshua A. Robinson | Nabil Bassim
Source: Microscopy and Microanalysis (article, 2021-07-30)
Field: Materials Science — Materials Chemistry

Correlative Electron Microscopy Enables Scalable Characterization of 2D half-van der Waals Heterostructures An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button. Correlative ; van der Waals force ; Characterization (materials science) ; Scalability ; Electron microscope ; Nanotechnology ; Materials science ; Heterojunction ; Computer science ; Optoelectronics ; Physics ; Optics ; Molecule ; Quantum mechanics Quantum Dots Synthesis And Properties ; Electronic and Structural Properties of Oxides ; 2D Materials and Applications
Authors: Norhaida Hanum Ahmad Tajudin | Wei Lun Ang | Siti Masrinda Tasirin | Masli Irwan Rosli
Source: Jurnal Kejuruteraan (article, 2021-11-30)
Field: Chemistry — Analytical Chemistry

Process Variables Optimization for Heat Pump Drying of Roselle Calyx by Using Response Surface Methodology Heat pump drying technology has been recognized for its capability to conserve energy consumption and product quality in drying process. Understanding the influence of drying conditions on product quality and optimisation are necessary to cut down the drying cost. In this study, the drying of Roselle calyx using heat pump dryer was optimized using response surface method where Central Composite Design (CCD) was employed to investigate the effects of independent variables: drying temperature (40-60ᵒC) and sample mass (100-300 g), on the response variables (drying time, energy consumption and colour changes). The drying study aimed to achieve minimum drying time, energy consumption and total colour changes. It was discovered that temperature factor has dominant effect on drying time while sample mass on energy consumption and colour changes. The interplay between the variables was closely related to heat transfer and moisture evaporation rates of the sample. The optimum drying conditions as determined were at drying temperature of 60ᵒC and sample mass of 100 g. Under these conditions, the drying time, energy consumption, and colour difference were 332.3 min, 27.05 kWh, and 4.29 ∆E, respectively. The optimization model was well validated since the difference between the predicted and experimental results was below 3%. Response surface methodology ; Central composite design ; Energy consumption ; Heat pump ; Calyx ; Mass transfer ; Evaporation ; Process engineering ; Process (computing) ; Materials science ; Pulp and paper industry ; Sample (material) ; Water content ; Environmental science ; Chemistry ; Chromatography ; Heat exchanger ; Mechanical engineering ; Computer science ; Horticulture ; Thermodynamics ; Engineering Spectroscopy and Chemometric Analyses ; Natural Products and Biological Research ; Food Drying and Modeling
Authors: Mullangi VinodKumar | Dinesh Sharma
Source: Soft Computing Research Society eBooks (review, 2021-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A Review on Metasurface and Metamaterials for Antenna Design The primary goal of this review paper is to present the fundamentals of left-handed materials and the silent features and drawbacks of Metamaterial, and the recent development of Metasurface antennas. Metamaterials are made up of periodic subwavelength structures resonantly related to the electric and magnetic fields of incident electromagnetic waves and possess unique features that do not present in naturally occurring materials. Metamaterials are challenging to fabricate due to their 3D geometry complexity, while Metasurface are easy to fabricate due to their planar structure. The specific properties and uses of Metamaterial and Metasurface are discussed in this work, as well as cloaking systems, phase correction methods, and perfect lenses. Metamaterial ; Cloaking ; Planar ; Metamaterial antenna ; Antenna (radio) ; Optics ; Physics ; Split-ring resonator ; Metamaterial cloaking ; Computer science ; Optoelectronics ; Metamaterial absorber ; Tunable metamaterials ; Directional antenna ; Slot antenna ; Telecommunications Metamaterials and Metasurfaces Applications ; Antenna Design and Analysis ; Advanced Antenna and Metasurface Technologies
Authors: Yiling Elaine Chen | Xinzhou Ge | Kyla Woyshner | MeiLu McDermott | Antigoni Manousopoulou | Scott B. Ficarro | Jarrod A. Marto | Kexin Li | Leo D. Wang | Jingyi Jessica Li
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-09-10)
Field: Chemistry — Spectroscopy

APIR: Aggregating Universal Proteomics Database Search Algorithms for Peptide Identification with FDR Control Abstract Advances in mass spectrometry (MS) have enabled high-throughput analysis of proteomes in biological systems. The state-of-the-art MS data analysis relies on database search algorithms to quantify proteins by identifying peptide-spectrum matches (PSMs), which convert mass spectra to peptide sequences. Different database search algorithms use distinct search strategies and thus may identify unique PSMs. However, no existing approaches can aggregate all user-specified database search algorithms with a guaranteed increase in the number of identified peptides and control on the false discovery rate (FDR). To fill in this gap, we propose a statistical framework, Aggregation of Peptide Identification Results (APIR), that is universally compatible with all database search algorithms. Notably, under an FDR threshold, APIR is guaranteed to identify at least as many, if not more, peptides as individual database search algorithms do. Evaluation of APIR on a complex proteomics standard shows that APIR outpowers individual database search algorithms and empirically controls the FDR. Real data studies show that APIR can identify disease-related proteins and post-translational modifications missed by some individual database search algorithms. The APIR framework is easily extendable to aggregating discoveries made by multiple algorithms in other high-throughput biomedical data analysis, e.g., differential gene expression analysis on RNA sequencing data. The APIR R package is available at https://github.com/yiling0210/APIR . Database search engine ; False discovery rate ; Computer science ; Identification (biology) ; Sequence database ; Algorithm ; Data mining ; Database ; Mascot ; Proteomics ; Proteome ; Computational biology ; Information retrieval ; Search engine ; Bioinformatics ; Biology ; Gene Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Machine Learning in Bioinformatics
Authors: Hebatallah M. Essam | Amani Morsi | Mohammed B El-Zeiny
Source: Journal of AOAC International (article, 2021-01-07)
Field: Chemistry — Spectroscopy

Multivariable Manipulation of Spectrophotometric Data with Genetic Algorithm Selection for Novel Quantitative Resolution of Five Antiviral Drugs in Their Pharmaceutical Products The proposed models offer a powerful analytical alternative for laboratories that consider economic strategies in their requirements. Partial least squares regression ; Residual ; Sofosbuvir ; Selection (genetic algorithm) ; Ledipasvir ; Genetic algorithm ; Computer science ; Algorithm ; Data mining ; Artificial intelligence ; Machine learning ; Chemistry Analytical Chemistry and Chromatography ; Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Tian-Cheng Yi | Richard T. Scalettar | Rubem Mondaini
Source: Research Square (preprint, 2021-11-30)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Hamming Distance and the onset of quantum criticality Criticality ; Hamming distance ; Quantum ; Computer science ; Physics ; Statistical physics ; Mathematics ; Algorithm ; Quantum mechanics ; Nuclear physics Organic and Molecular Conductors Research ; Quantum many-body systems ; Physics of Superconductivity and Magnetism
Authors: K. Lawrence Galloway | Erin G. Teich | Xiaoguang Ma | Christoph Kammer | Ian Graham | Nathan C. Keim | Celia Reina | D. J. Jerolmack | Arjun G. Yodh | Paulo E. Arratia
Source: Research Square (preprint, 2021-05-26)
Field: Materials Science — Materials Chemistry

Relationships among structure, memory, and flow in sheared disordered materials Psychology ; Flow (mathematics) ; Materials science ; Mechanics ; Physics Material Dynamics and Properties ; Archaeology and Rock Art Studies ; Building materials and conservation
Authors: Tomonori Ikeda | Atsushi Takada | Mitsuru Abe | Kei Yoshikawa | Masaya Tsuda | S. Ogio | Shinya Sonoda | Yoshitaka Mizumura | Yura Yoshida | T. Tanimori
Source: Progress of Theoretical and Experimental Physics (preprint, 2021-07-05)
Field: Materials Science — Materials Chemistry

Development of convolutional neural networks for an electron-tracking Compton camera Abstract The Electron-Tracking Compton Camera (ETCC), which is a complete Compton camera that tracks Compton scattering electrons with a gas micro time projection chamber, is expected to open up MeV gamma-ray astronomy. The technical challenge for achieving several degrees of the point-spread function is precise determination of the electron recoil direction and the scattering position from track images. We attempted to reconstruct these parameters using convolutional neural networks. Two network models were designed to predict the recoil direction and the scattering position. These models marked 41$^\circ$ of angular resolution and 2.1 mm of position resolution for 75 keV electron simulation data in argon-based gas at 2 atm pressure. In addition, the point-spread function of the ETCC was improved to 15$^\circ$ from 22$^\circ$ for experimental data from a 662 keV gamma-ray source. The performance greatly surpassed that using traditional analysis. Recoil ; Physics ; Tracking (education) ; Compton scattering ; Position (finance) ; Angular resolution (graph drawing) ; Electron ; Electron scattering ; Scattering ; Resolution (logic) ; Optics ; Xenon ; Computational physics ; Nuclear physics ; Computer science ; Artificial intelligence ; Mathematics Chemical and Physical Properties of Materials ; Ion-surface interactions and analysis ; Particle Detector Development and Performance
Authors: Phan Xuan Le | Le Hung Tien
Source: Bulletin of Electrical Engineering and Informatics (article, 2021-07-07)
Field: Materials Science — Materials Chemistry

(Y,Gd)BO&lt;sub&gt;3&lt;/sub&gt;:Eu red phosphor for dual-layer phosphor structure to enhance the optical performance of white light-emitting diodes Among the structures using for fabricating white light-emitting diodes (WLEDs) such as the conformal coating or in-cup geometries, the remote phosphor structure gives the highest luminous efficacy. However, in terms of color quality, its performance is not as good as the others. The red-light compensation has been reported as the effective solution for enhancing the color quality of WLEDs. Hence, this study adopted the idea and applied to the dual-layer phosphor structure. The phosphor used to boost the red color in light formation is (Y,Gd)BO3:Eu particle. The dual-layer remote phosphor structure was simulated with the red (Y,Gd)BO3:Eu phosphor layer above the original yellow phosphor YAG:Ce3+ one. The WLEDs with different correlated color temperatures of 5600 K, 6600 K and 7700K were experimented. Mie-theory and Lambert-Beer law were applied to examine the results. The growth in color rendering index (CRI) and color quality scale (CQS) with the increase of (Y,Gd)BO3:Eu phosphor concentration was observed. Nevertheless, the lumen efficacy would be degraded if the concentration was over a certain number. The information provided in this article is useful for the development of high-power WLED production with greater color quality. Phosphor ; Color rendering index ; Materials science ; Luminous efficacy ; Diode ; Color temperature ; Optoelectronics ; Dual layer ; Light-emitting diode ; Luminous flux ; Luminescence ; Optics ; Layer (electronics) ; Nanotechnology ; Physics ; Light source Luminescence Properties of Advanced Materials
Authors: Firmansyah Nur Budiman | Ali Muhammad Ali Rushdi
Source: Communications in Science and Technology (article, 2021-12-31)
Field: Materials Science — Materials Chemistry

Dimensional analysis of partial discharge initiated by a metallic particle adhering to the spacer surface in a gas-insulated system Partial discharges (PDs) constitute important phenomena in a Gas-Insulated System (GIS) that warrant recognition (and, subsequently, mitigation) as they are obvious symptoms of system degradation. This paper proposes the application of dimensional analysis, based on Buckingham pi theorem, for characterizing PDs provoked by the presence of metallic particles adhering to the spacer surface in a GIS employing SF6 (Sulphur hexafluoride). The ultimate goal of the analysis is to formulate the relationships that express three PD indicator quantities, namely current, charge, and energy, in terms of six independent quantities that collectively influence these indicators. These six quantities (henceforth referred to as the influencing, determining or affecting variables) include the level of applied voltage, the SF6 pressure, the length and position of the particle on the spacer, the duration of voltage application, and the gap between electrodes. To compute the pertinent dimensionless products, we implement three computational methods based on matrix operations. These three methods produce exactly the same dimensionless products, which are subsequently used for constructing the models depicting the relationships between each of the three PD dependent quantities and the common six determining variables. The models derived provide partial quantitative information and facilitate qualitative reasoning about the considered phenomenon. Dimensionless quantity ; Partial discharge ; Partial pressure ; Voltage ; Particle (ecology) ; Partial charge ; Position (finance) ; Current (fluid) ; Sulfur hexafluoride ; Mechanics ; Charge (physics) ; Chemistry ; Computer science ; Materials science ; Physics ; Engineering ; Electrical engineering ; Quantum mechanics High voltage insulation and dielectric phenomena
Authors: Klemens Fröhlich | Eva Brombacher | Matthias Fahrner | Daniel Vogele | Lucas Kook | Peter Bronsert | Sylvia Timme | Alexander Schmidt | Katja Baerenfaller | Clemens Kreutz | Oliver Schilling
Source: Research Square (preprint, 2021-09-20)
Field: Chemistry — Spectroscopy

In-Depth Benchmarking of DIA-type Proteomics Data Analysis Strategies Using a Large-Scale Benchmark Dataset Comprising Inter-Patient Heterogeneity Normalization (sociology) ; Benchmark (surveying) ; Computer science ; Benchmarking ; Software ; Workflow ; Proteomics ; Data mining ; Computational biology ; Pattern recognition (psychology) ; Artificial intelligence ; Biology ; Database ; Cartography Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Advanced Biosensing Techniques and Applications
Authors: Angela Altomare | Simon J. L. Billinge
Source: Acta Crystallographica Section A Foundations and Advances (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Modern crystallography and its foundations Authors and readers are reminded of the history and scope of Acta Crystallographica Section A, and simple steps to help maintain its prominence and impact as the premier journal for foundational work in crystallography are outlined. Scope (computer science) ; Section (typography) ; Simple (philosophy) ; Engineering ethics ; Computer science ; Epistemology ; Philosophy ; Engineering ; Programming language X-ray Diffraction in Crystallography ; History and advancements in chemistry ; Crystallography and molecular interactions
Authors: Qishuai Zhang | Kehu Yang | Luxian Li
Source: Cardiac and Cardiovascular Research (article, 2021-04-07)
Field: Chemistry — Analytical Chemistry

Research on inversion method of left ventricular myocardial tissue parameters based on BP neural network &lt;p&gt;Because it contains pathological characteristics such as changes in myocardial tissue characteristics, the deformation and dynamic characteristics of human left ventricle have become an important basis for clinical diagnosis of heart disease. Based on BP neural network method, this study carries out the identification of left ventricular myocardial tissue parameters through the inversion of left ventricular clinical diagnosis data. Firstly, the image recognition program is written in MATLAB language to extract the location points of inner and outer membranes in human left ventricular CT image, establish the real geometric model of left ventricle in solidworks software, and establish the finite element analysis model of left ventricle through ABAQUS software. Secondly, Mooney Rivlin hyperelastic model is used to simulate the characteristics of myocardial tissue, ABAQUS finite element software is used to conduct dynamic numerical analysis on the left ventricular finite element model, and 45 groups of input target vectors of BP neural network corresponding to three characteristic moments are obtained. Finally, the BP neural network program is written in MATLAB language to train the input target vector, and establish the nonlinear mapping relationship between left ventricular diagnostic data and myocardial tissue parameters. The analysis results of examples show that BP neural network can be well used for myocardial tissue parameter inversion based on clinical data, and is expected to become an effective method for clinical diagnosis of left ventricular lesions caused by changes in myocardial tissue characteristics.&lt;/p&gt; Artificial neural network ; Inversion (geology) ; Artificial intelligence ; Computer science ; Internal medicine ; Cardiology ; Pattern recognition (psychology) ; Biomedical engineering ; Medicine ; Geology ; Seismology Spectroscopy and Chemometric Analyses
Authors: Basílio de Bragança Pereira | Calyampudi R. Rao | Rubens L. Oliveira | Em ́ılia M. do Nascimento
Source: Journal of Data Science (article, 2021-07-10)
Field: Chemistry — Analytical Chemistry

Combining Unsupervised and Supervised Neural Networks in Cluster Analysis of Gamma-Ray Burst The paper proposes the use of Kohonen’s Self Organizing Map (SOM), and supervised neural networks to find clusters in samples of gammaray burst (GRB) using the measurements given in BATSE GRB. The extent of separation between clusters obtained by SOM was examined by cross validation procedure using supervised neural networks for classification. A method is proposed for variable selection to reduce the “curse of dimensionality”. Six variables were chosen for cluster analysis. Additionally, principal components were computed using all the original variables and 6 components which accounted for a high percentage of variance was chosen for SOM analysis. All these methods indicate 4 or 5 clusters. Further analysis based on the average profiles of the GRB indicated a possible reduction in the number of clusters. Self-organizing map ; Principal component analysis ; Artificial neural network ; Pattern recognition (psychology) ; Dimensionality reduction ; Curse of dimensionality ; Artificial intelligence ; Cluster (spacecraft) ; Computer science ; Feature selection ; Unsupervised learning ; Data mining Spectroscopy and Chemometric Analyses ; Fault Detection and Control Systems