jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Kuleswan Pame | Saurabh Kumar Laskar | Simanku Borah | K. Kakoty | S. Choudhary
Source: Journal of Livestock Science (review, 2023-10-03)
Field: Chemistry — Analytical Chemistry

Machine-vision based quality evaluation of meat and meat products- a review The increasing demands for meat and meat products of high quality and safety standards has led to the development and search of technologies with accurate, fast and more objective quality determination.Machine vision provides an alternative for an automated, non-destructive and cost-effective technique on long run to accomplish the present requirements.The technology matches the function of human vision by electronically perceiving and evaluate into an image.Considerable research has highlighted its potential and already been successful in the inspection and grading of meat and meat products.The significant components of a computer vision system are introduced listed with advantage and disadvantage.The image processing technique coupled with a review of the most recent developments and possible application in quality evaluation of meat and meat products are discussed in this review paper. Quality (philosophy) ; Food science ; Meat packing industry ; Processed meat ; Business ; Chemistry Spectroscopy and Chemometric Analyses
Authors: Diego Patrício | Carlos Ré Signor | Nádia Canali Lângaro | Rafael Rieder
Source: Revista Brasileira de Computação Aplicada (article, 2023-04-25)
Field: Chemistry — Analytical Chemistry

Oat grains classification using deep learning Background: Based on their nutritional benefits, oat is classified as a cereal of great importance for both human and animal feeding. Throughout the production process, species and variety identification are vital for agricultural systems. The present work establishes SeedFlow, a method for image acquisition, processing, and classification of oat grains using deep learning techniques. We apply these techniques to the identification of the grains from the different oat species Avena sativa and Avena strigosa and to classify grains as varieties of Avena sativa, such as UPFA Ouro, UPFA Fuerza, and UPFA Gaudéria. Results: To achieve this proposition, we executed our solution considering six different deep learning architectures to evaluate which model presents the best performance. This approach attained an accuracy of 99.7% for oat species identification and 89.7% for oat varieties classification using DenseNet architecture. Conclusions: As a result, this tool can provide high value for practical quality control applications, and it is feasible to use in pre-screening tests, laboratory analysis pipelines, or computer support tools geared toward breeding programs or intellectual property assessment. Avena ; Deep learning ; Identification (biology) ; Artificial intelligence ; Machine learning ; Computer science ; Agricultural engineering ; Biology ; Agronomy ; Engineering ; Botany Spectroscopy and Chemometric Analyses
Authors: Rafaelle Franson Alves Coelho | I. S. B. do Nascimento | Marcela de Souza Coelho | Emília Akil
Source: Revista Foco (article, 2023-07-11)
Field: Chemistry — Organic Chemistry

EXTRA VIRGIN OLIVE OIL QUALITY INVESTIGATION OF DIFFERENT BRANDS ACQUIRED IN COMMERCE FROM RIO DE JANEIRO CITY, BRAZIL Olive oil is obtained by physical means without the usage of solvents. Different than edible vegetable oils, it can be consumed in the virgin form, also being an oil of a better nutritional quality and stability, since it is mainly composed by monounsaturated fatty acids (oleic acid) as well as many antioxidant compounds. Having its greatest value in raw state, the extra virgin olive oil is the one with best quality in organoleptic aspect. As a result, this kind of oil is the one that shows biggest interest to the population and has the highest commercial value, therefore being more susceptible to adulterations. This paper aims to assess the chemical characteristics which define its classification, chemical quality and possible presence of adulterations in different brands commercialized in Brazil, applying methods described in accordance with identity and quality standards, in conformity with current legislation. This paper consists in bromatological analyzes of quality research related to classification, oxidative state, and adulteration, applying analyzes of acidity, peroxide and iodine. According to the results obtained related to classification and oxidative state, all samples were found within limits of tolerance prescribed by all legislations. Regarding adulterations, based on the iodine analyzes, two samples showed higher values determined by legislations and one showed lower value. Values higher than those determined by legislations may show mixtures with lower quality vegetable oils, and lower values may indicate mixture with fats that are rich in saturated fatty acids or a correlation with its oxidative state. Seeing that it is a kind of food that has become a major interest for investigation due to its nutritional benefits, particularly in the prevention of cardiovascular diseases, besides assuring safety to the consumer, this research shows the importance of physicochemical analyzes in the quality of extra virgin olive oils found in the market. Iodine value ; Food science ; Peroxide value ; Population ; Olive oil ; Oleic acid ; Quality (philosophy) ; Mathematics ; Organoleptic ; Chemistry ; Business ; Biochemistry ; Environmental health Edible Oils Quality and Analysis ; Dye analysis and toxicity ; Spectroscopy and Chemometric Analyses
Authors: Ornella Bimaï | Ipsita A. Banerjee | Inna Rozman Grinberg | Ping Huang | Lucas Hultgren | Simon Ekström | Daniel Lundin | Britt‐Marie Sjöberg | Derek T. Logan
Source: eLife (article, 2023-08-16)
Field: Chemistry — Inorganic Chemistry

Nucleotide binding to the ATP-cone in anaerobic ribonucleotide reductases allosterically regulates activity by modulating substrate binding A small, nucleotide-binding domain, the ATP-cone, is found at the N-terminus of most ribonucleotide reductase (RNR) catalytic subunits. By binding adenosine triphosphate (ATP) or deoxyadenosine triphosphate (dATP) it regulates the enzyme activity of all classes of RNR. Functional and structural work on aerobic RNRs has revealed a plethora of ways in which dATP inhibits activity by inducing oligomerisation and preventing a productive radical transfer from one subunit to the active site in the other. Anaerobic RNRs, on the other hand, store a stable glycyl radical next to the active site and the basis for their dATP-dependent inhibition is completely unknown. We present biochemical, biophysical, and structural information on the effects of ATP and dATP binding to the anaerobic RNR from <i>Prevotella copri</i>. The enzyme exists in a dimer-tetramer equilibrium biased towards dimers when two ATP molecules are bound to the ATP-cone and tetramers when two dATP molecules are bound. In the presence of ATP, <i>P. copri</i> NrdD is active and has a fully ordered glycyl radical domain (GRD) in one monomer of the dimer. Binding of dATP to the ATP-cone results in loss of activity and increased dynamics of the GRD, such that it cannot be detected in the cryo-EM structures. The glycyl radical is formed even in the dATP-bound form, but the substrate does not bind. The structures implicate a complex network of interactions in activity regulation that involve the GRD more than 30 Å away from the dATP molecules, the allosteric substrate specificity site and a conserved but previously unseen flap over the active site. Taken together, the results suggest that dATP inhibition in anaerobic RNRs acts by increasing the flexibility of the flap and GRD, thereby preventing both substrate binding and radical mobilisation. Ribonucleotide ; Nucleotide ; Allosteric regulation ; Cell biology ; Substrate (aquarium) ; Chemistry ; Adenosine triphosphate ; Biochemistry ; Biology ; Enzyme ; Biophysics ; Gene Metal-Catalyzed Oxygenation Mechanisms ; ATP Synthase and ATPases Research ; Advanced Electron Microscopy Techniques and Applications
Authors: Yin Wan | Ding Liu | Jun-Chao Ren | Shihai Wu
Source: Sensors (article, 2023-03-05)
Field: Materials Science — Materials Chemistry

Study on the Hierarchical Predictive Control of Semiconductor Silicon Single Crystal Quality Based on the Soft Sensor Model Silicon single crystal (SSC) quality monitoring and control has been a hot research topic in the field of the Czochralski crystal growth process. Considering that the traditional SSC control method ignores the crystal quality factor, this paper proposes a hierarchical predictive control strategy based on a soft sensor model for online control of SSC diameter and crystal quality. First, the proposed control strategy considers the V/G variable (V is the crystal pulling rate, and G is the axial temperature gradient at the solid-liquid interface), a factor related to crystal quality. Aiming at the problem that the V/G variable is difficult to measure directly, a soft sensor model based on SAE-RF is established to realize the online monitoring of the V/G variable and then complete hierarchical prediction control of SSC quality. Second, in the hierarchical control process, PID control of the inner layer is used to quickly stabilize the system. Model predictive control (MPC) of the outer layer is used to handle system constraints and enhance the control performance of the inner layer. In addition, the SAE-RF-based soft sensor model is used to monitor the crystal quality V/G variable online, thereby ensuring that the output of the controlled system meets the desired crystal diameter and V/G requirements. Finally, based on the industrial data of the actual Czochralski SSC growth process, the effectiveness of the proposed crystal quality hierarchical predictive control method is verified. Model predictive control ; Soft sensor ; Crystal (programming language) ; Quality (philosophy) ; Layer (electronics) ; Process control ; Control system ; Process (computing) ; Control theory (sociology) ; Materials science ; Engineering ; Control (management) ; Computer science ; Artificial intelligence ; Nanotechnology ; Electrical engineering ; Physics Solidification and crystal growth phenomena ; Silicon and Solar Cell Technologies ; Advanced Control Systems Optimization
Authors: Jeonghyeon Heo | Ji-Hoon Han
Source: Nanotechnology (article, 2023-07-05)
Field: Materials Science — Materials Chemistry

Evaluation of mechanical properties of triple-junction-free polycrystalline graphene Although chemical vapor deposition (CVD) has emerged as an important method for producing large-scale and relatively high-quality graphene, CVD-grown graphene inherently contains grain boundaries (GBs), which degrade its mechanical properties. To compensate for these characteristics, various studies have been conducted to maintain the mechanically superior properties by controlling the density of defects and GBs. In this study, the mechanical properties of triple junction (TJ)-free polycrystalline graphene, which is expected to exhibit excellent properties, were investigated through molecular dynamics simulations because TJ is well-known as a crack nucleation site due to stress concentration. We adopted the phase-field crystal method to model CVD-grown graphene-containing TJ-free polycrystalline materials. From a series of numerical simulations, we found that the fracture strength increases as the density of the GB increases. This trend is consistent with that presented in a previous experimental study measured by nanoindentation. It was determined that the variation in the fracture strength is related to the discontinuous density of 5-7 pairs, which act as stress-concentration sites. Additionally, we observed that the fracture strength was higher than that of polycrystalline graphene with TJ. We believe that these results have a higher mechanical advantage compared to the low strength of TJs shown in previous studies and will be important for future structural reliability-based graphene applications. Materials science ; Graphene ; Crystallite ; Nucleation ; Chemical vapor deposition ; Grain boundary ; Molecular dynamics ; Composite material ; Nanoindentation ; Stress (linguistics) ; Fracture (geology) ; Microstructure ; Nanotechnology ; Metallurgy ; Thermodynamics ; Computational chemistry Graphene research and applications ; Thermal properties of materials ; Aluminum Alloys Composites Properties
Authors: Jack Broad | Richard J. Wheatley | R. Graham
Source: Journal of Chemical Theory and Computation (article, 2023-06-27)
Field: Materials Science — Materials Chemistry

Parallel Implementation of Nonadditive Gaussian Process Potentials for Monte Carlo Simulations A strategy is presented to implement Gaussian process potentials in molecular simulations through parallel programming. Attention is focused on the three-body nonadditive energy, though all algorithms extend straightforwardly to the additive energy. The method to distribute pairs and triplets between processes is general to all potentials. Results are presented for a simulation box of argon, including full box and atom displacement calculations, which are relevant to Monte Carlo simulation. Data on speed-up are presented for up to 120 processes across four nodes. A 4-fold speed-up is observed over five processes, extending to 20-fold over 40 processes and 30-fold over 120 processes. Monte Carlo method ; Computer science ; Statistical physics ; Gaussian ; Gaussian process ; Process (computing) ; Dynamic Monte Carlo method ; Molecular dynamics ; Computational science ; Algorithm ; Computational chemistry ; Physics ; Mathematics ; Chemistry ; Statistics Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Advanced Chemical Physics Studies
Authors: David Jany | Eric Rothchild | D. C. Chrzan
Source: Physical Review Materials (article, 2023-10-17)
Field: Materials Science — Materials Chemistry

Polymorphic structure of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mrow><mml:mo>〈</mml:mo><mml:mi>a</mml:mi><mml:mo>〉</mml:mo></mml:mrow></mml:math>-type screw dislocation cores in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>α</mml:mi></mml:math>-Ti The dislocation core structure has a significant role in determining the dominant slip plane and the magnitude of the Peierls stress for a dislocation. An important challenge when studying dislocation cores is to determine the stable and metastable core morphologies, and then relate these structures to the dynamics of the dislocations. This study introduces a method for identifying core structures that are metastable at zero temperature. Application of this method to $\ensuremath{\langle}a\ensuremath{\rangle}$-type screw dislocations in $\ensuremath{\alpha}$-Ti (as described using an empirical potential) reveals a multitude of (meta)stable nonplanar cores. Molecular dynamics studies show how the competing metastable core structures determine the properties of the dislocations at temperature and under a range of non-Schmid stresses. Metastability ; Materials science ; Dislocation ; Core (optical fiber) ; Glide plane ; Crystallography ; Molecular dynamics ; Condensed matter physics ; Physics ; Chemistry ; Quantum mechanics Microstructure and mechanical properties ; Titanium Alloys Microstructure and Properties ; Advanced materials and composites
Authors: Jozefovič Patrik | Ambrož Ondřej | Jan Čermák | Man Jiří | Mikmeková Šárka
Source: Microscopy and Microanalysis (article, 2023-07-22)
Field: Materials Science — Materials Chemistry

A Comparison of Image Analysis Tools for Segmentation on SEM Micrographs – Zeiss ZEN Intellesis vs. Thermofisher AVIZO Micrograph ; Computer graphics (images) ; Segmentation ; Computer science ; Computer vision ; Artificial intelligence ; Materials science ; Scanning electron microscope ; Composite material Machine Learning in Materials Science ; Electron and X-Ray Spectroscopy Techniques
Authors: Mateusz Banach
Source: Molecules (article, 2023-12-21)
Field: Materials Science — Materials Chemistry

Structural Outlier Detection and Zernike–Canterakis Moments for Molecular Surface Meshes—Fast Implementation in Python Object retrieval systems measure the degree of similarity of the shape of 3D models. They search for the elements of the 3D model databases that resemble the query model. In structural bioinformatics, the query model is a protein tertiary/quaternary structure and the objective is to find similarly shaped molecules in the Protein Data Bank. With the ever-growing size of the PDB, a direct atomic coordinate comparison with all its members is impractical. To overcome this problem, the shape of the molecules can be encoded by fixed-length feature vectors. The distance of a protein to the entire PDB can be measured in this low-dimensional domain in linear time. The state-of-the-art approaches utilize Zernike-Canterakis moments for the shape encoding and supply the retrieval process with geometric data of the input structures. The BioZernike descriptors are a standard utility of the PDB since 2020. However, when trying to calculate the ZC moments locally, the issue of the deficiency of libraries readily available for use in custom programs (i.e., without relying on external binaries) is encountered, in particular programs written in Python. Here, a fast and well-documented Python implementation of the Pozo-Koehl algorithm is presented. In contrast to the more popular algorithm by Novotni and Klein, which is based on the voxelized volume, the PK algorithm produces ZC moments directly from the triangular surface meshes of 3D models. In particular, it can accept the molecular surfaces of proteins as its input. In the presented PK-Zernike library, owing to Numba's just-in-time compilation, a mesh with 50,000 facets is processed by a single thread in a second at the moment order 20. Since this is the first time the PK algorithm is used in structural bioinformatics, it is employed in a novel, simple, but efficient protein structure retrieval pipeline. The elimination of the outlying chain fragments via a fast PCA-based subroutine improves the discrimination ability, allowing for this pipeline to achieve an 0.961 area under the ROC curve in the BioZernike validation suite (0.997 for the assemblies). The correlation between the results of the proposed approach and of the 3D Surfer program attains values up to 0.99. Python (programming language) ; Zernike polynomials ; Computer science ; Polygon mesh ; Protein Data Bank ; Algorithm ; Protein Data Bank (RCSB PDB) ; Outlier ; Theoretical computer science ; Data mining ; Artificial intelligence ; Protein structure ; Computer graphics (images) ; Physics Enzyme Structure and Function ; Genomics and Phylogenetic Studies ; Advanced Proteomics Techniques and Applications
Authors: Matthew S. Johnson | Joy N. Mueller | Craig Daniels | Habib N. Najm | Judit Zádor
Source: ChemRxiv (preprint, 2023-10-24)
Field: Materials Science — Materials Chemistry

Diffusion Limited Kinetics Accounting for Reactive Species in 3D, 2D, and at 2D/3D Interfaces Proper representation of chemical kinetics is vital to understanding, modeling and optimizing many important chemical processes. In liquid and surface phases, where diffusion is slow, the rate at which the reactants diffuse together limits the overall rate of many elementary reactions. Commonly the textbook Smolchowski theory is utilized to estimate effective rate coefficients in liquid phase. On surfaces, modelers commonly resort to much more complex and expensive Kinetic Monte Carlo (KMC) simulations. Here we extend the Smolchowski model to allow the diffusing species to undergo chemical reactions, and derive analytical formulae for the diffusion limited rate coefficients for 3D, 2D and 2D/3D interface cases. With these equations we are able to demonstrate that when species react faster than they diffuse they can react orders of magnitude faster than predicted by Smolchowski theory, through what we term "the reactive transport effect." We validate the derived steady state equations against particle Monte Carlo (PMC) simulations, KMC simulations and non-steady state solutions. Furthermore, using PMC and KMC simulations, we propose corrections that agree with all limits and the computed data for the 2D and 2D/3D interface steady state equations, accounting for unique limitations in the associated derived equations. Additionally, we derive equations to handle couplings between diffusion limited rate coefficients in reaction networks. We believe these equations should make it possible to run much more accurate mean-field simulations of liquids, surfaces, and liquid-surface interfaces accounting for diffusion limitations and the reactive transport effect. Diffusion ; Monte Carlo method ; Kinetic Monte Carlo ; Statistical physics ; Steady state (chemistry) ; Representation (politics) ; Rate equation ; Reaction rate ; Chemical species ; Particle (ecology) ; Chemical reaction ; Chemistry ; Thermodynamics ; Kinetics ; Physics ; Physical chemistry ; Classical mechanics ; Mathematics Catalytic Processes in Materials Science ; Electrocatalysts for Energy Conversion ; CO2 Reduction Techniques and Catalysts
Authors: Vennila Kailasam Natesan | Selvakumar Balaraman | Elango Kuppannagounder Pitchaimuthu
Source: In Silico Pharmacology (article, 2023-09-25)
Field: Chemistry — Organic Chemistry

Insilico design of an allosteric modulator targeting the protein–protein interaction site of 3 Phosphoinositide dependent Kinase-1: design, synthesis and biological activity Allosteric regulation ; Pharmacophore ; Docking (animal) ; Chemistry ; Rational design ; Binding site ; Scaffold protein ; Metadynamics ; Virtual screening ; Protein–protein interaction ; Small molecule ; Biophysics ; Molecular dynamics ; Biochemistry ; Biology ; Nanotechnology ; Signal transduction ; Enzyme ; Materials science Synthesis and biological activity ; Biochemical and Molecular Research
Authors: Taras Yanko | Roman Datsenko | Ганна Володимирівна Карпенко
Source: Transactions of the Institute of Aviation (article, 2023-06-01)
Field: Materials Science — General Materials Science

Possibilities of Using Low-Density C–C Composites for Thermal Protection of Small Unmanned Aerial Vehicles Abstract The study demonstrates the possibilities of using, as well as the features associated with the use of, unmanned aerial vehicles (UAVs) for military and peaceful purposes. Information is provided on the need to use components that would contribute towards ensuring thermal protection against modern laser weapons. The requirements for such materials are given, according to the field of application of the UAV. An analysis of the available materials that can be used to create thermal protection of UAVs against laser weapons is provided. The thermophysical characteristics of various materials are presented. The work presents technological features of production and properties of low-density carbon–carbon composite materials (CCCM). It is proposed to consider the prospects of using CCCM materials for not only the UAV structural components but also other purposes. Thermal protection ; Field (mathematics) ; Aerospace engineering ; Thermal ; Work (physics) ; Laser ; Mechanical engineering ; Composite number ; Carbon fibers ; Computer science ; Systems engineering ; Materials science ; Engineering ; Composite material ; Physics ; Meteorology ; Optics Material Properties and Applications ; Aerospace, Electronics, Mathematical Modeling ; Advanced Theoretical and Applied Studies in Material Sciences and Geometry