jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Konstantin Bob | David Teschner | Thomas Kemmer | David Gómez-Zepeda | Stefan Tenzer | Bertil Schmidt | Andreas Hildebrandt
Source: BMC Bioinformatics (article, 2022-07-20)
Field: Chemistry — Spectroscopy

Locality-sensitive hashing enables efficient and scalable signal classification in high-throughput mass spectrometry raw data Generated data and code are available at https://github.com/hildebrandtlab/mzBucket . Raw data is available at https://zenodo.org/record/5036526 . Computer science ; Raw data ; Scalability ; Locality-sensitive hashing ; Mass spectrometry ; Hash function ; Thresholding ; Data mining ; Database ; Hash table ; Artificial intelligence ; Chemistry Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Genomics and Phylogenetic Studies
Authors: Lin Lu | Bo Zeng | Shihua Yang | Mingxue Chen | Yonghong Yu
Source: Journal of Food Quality (article, 2022-12-13)
Field: Chemistry — Analytical Chemistry

Continuous Monitoring Analysis of Rice Quality in Southern China Based on Random Forest Rice quality has received more attention, so monitoring and analysis are of great significance to rice quality. General quality indexes of rice in southern China from 2011 to 2020 were determined, including processing quality (brown rice yield, milled rice recovery, head rice yield), appearance quality (grain length, length-width ratio, chalky rice percentage, chalkiness degree, transparency), and cooking quality (alkali spreading value, gel consistency, amylose). Principal component analysis was used to distinguish the regional quality of southern rice. The results showed that amylose and chalkiness were the main contributory quality indexes of rice in South China, the upper reaches of the Yangtze River, and the middle and lower reaches of the Yangtze River. In the past decade, the total high-quality rate of rice in the South has improved. The random forest was used to determine the important influence index of rice quality. The results showed that chalkiness degree, alkali spreading value, and gel consistency were important indexes affecting the quality of southern rice, and random forest could be used as an effective approach for continuous monitoring and analysis of rice quality. Yangtze river ; Amylose ; Grain quality ; Environmental science ; Agronomy ; Yield (engineering) ; Brown rice ; Mathematics ; Quality (philosophy) ; China ; Geography ; Biology ; Starch ; Food science Spectroscopy and Chemometric Analyses ; Rice Cultivation and Yield Improvement ; GABA and Rice Research
Authors: Yinjie Shen | Yanhu Tao | Qiansheng Tang | Liangyuan Xu
Source: Mobile Information Systems (article, 2022-08-08)
Field: Chemistry — Analytical Chemistry

Study on Multifactor Control Experiment and Design of Quality Detection System for Yuba Skin Production In view of the low control precision, low degree of intelligence, low utilization rate of soybean milk, and poor conjunctiva quality in current Yuba skin production technology, a system of multifactor control and intelligent quality detection for Yuba skin was studied and designed in this paper. The system uses LabVIEW as the upper computer and the single chip microcomputer as the lower computer. Uses programming electronic control technology to set process parameters in advance, precisely control each factor to achieve adaptive control of wind speed, concentration, liquid level, and temperature, the control error of each factor is within 1%, and the quality of Yuba skin was detected by image processing technology. The application of the system greatly improves the production efficiency and intellectualization of the production line and reduces the damage degree of Yuba skin. An orthogonal test and response surface optimization were carried out for the process parameters. The test results show that the accuracy of the test results using radial basis kernel function (RBF) can reach 92.06% when the characteristic combination mode is all the characteristics, and the optimal yield will be 48.57% and the optimal quality score is 9.20 when the export angle is 36.75°, the export diameter is 9.90 mm, the export wind speed is 1.22 m/s, the slurry concentration is 7.66%, the slurry temperature is 83.26°C, and the liquid level is 30.52 mm. Comparison between the results from the regression model validation test and those from the response surface methodology is made. The relative errors of yield and quality were 0.14% and 0.87%, which indicates that the response surface methodology can effectively optimize the process parameters of Yuba skin. Computer science ; Production line ; Microcomputer ; Intellectualization ; Process (computing) ; Automotive engineering ; Artificial intelligence ; Chip ; Mechanical engineering ; Engineering Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Microbial Metabolism and Applications
Authors: Carolyn Allen | Rico Meinl | Brian C. Searle | Seth Just | Lindsay K. Pino | William E. Fondrie
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2022-10-03)
Field: Chemistry — Spectroscopy

nf-encyclopedia: A cloud-ready pipeline for chromatogram library data-independent acquisition proteomics workflows Abstract Data independent acquisition (DIA) mass spectrometry methods provide systematic and comprehensive quantification of the proteome; yet, relatively few open-source tools are available to analyze DIA proteomics experiments. Fewer still are tools that can leverage gas phase fractionated (GPF) chromatogram libraries to enhance the detection and quantification of peptides in these experiments. Here, we present nf-encyclopedia, an open-source NextFlow pipeline that connects three open-source tools—MSConvert, EncyclopeDIA, and MSstats—to analyze DIA proteomics experiments with or without chromatogram libraries. We demonstrate that nf-encyclopedia is reproducible both when run on a cloud platform or a local workstation and provides robust peptide and protein quantification. Additionally, we found that MSstats enhances protein-level quantitative performance over EncyclopeDIA alone. Finally, we benchmarked the ability nf-encyclopedia to scale to large experiments in the cloud by leveraging the parallelization of compute resources. The nf-encyclopedia pipeline is available under a permissive Apache 2.0 license—run it on your desktop, cluster, or in the cloud: https://github.com/TalusBio/nf-encyclopedia . Encyclopedia ; Computer science ; Cloud computing ; Pipeline (software) ; Workflow ; KEGG ; Proteomics ; Leverage (statistics) ; Quantitative proteomics ; Chemistry ; Database ; Artificial intelligence ; Operating system ; Gene ontology ; Library science Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Ziliang Huang | Rujing Wang | Liusan Wang | Yue Teng | Shijian Zheng
Source: MATEC Web of Conferences (article, 2022-01-01)
Field: Chemistry — Analytical Chemistry

Identification of internal cracks in corn seed using convolutional neural networks The identification of seed quality is very important for which the quality of seed is crucial to the yield and quality of crops. There are two main problems with the acquisition and identification of cracks inside corn seed. One is that most of the methods of near-infrared spectroscopy or X-ray are used to obtain images of cracks inside the seed, the acquisition equipment is expensive and the operation is complicated. The other is the identification of crack images, and the traditional image processing method is usually used which requires professionals to design different model parameters each time, resulting in poor model robustness and low model accuracy. In this study, we originally proposed a simple but effective method to obtain the picture of corn seed internal cracks, which is combined with visible light transmission and ordinary camera acquisition method. We also proposed using the transfer learning methods not only solving the problem of the small scale of our corn seed internal cracks dataset but also avoiding extracting features manually. Our proposed method achieved a promising result, which is able to correctly identify the cracked and intact corn seed 100% in our training stage and testing stage. Robustness (evolution) ; Convolutional neural network ; Identification (biology) ; Artificial intelligence ; Computer science ; Artificial neural network ; Pattern recognition (psychology) ; Quality (philosophy) ; Agricultural engineering ; Biological system ; Engineering ; Botany Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Leaf Properties and Growth Measurement
Authors: Man Xia | Haojie Zhu | Yuwei Wang | Jiaxu Cai | Lu Liu
Source: Photonics (article, 2022-05-15)
Field: Chemistry — Analytical Chemistry

Stem and Calyx Identification of 3D Apples Using Multi-Threshold Segmentation and 2D Convex Hull Traditional machine vision is widely used to identify apple quality, but this method finds it difficult to distinguish the apple stem and calyx from defects. To address this, we designed a new method to identify the stem and calyx of apples based on their concave shape. This method applies a fringe projection in a computer vision system of 3D reconstruction, followed by multi-threshold segmentation and a 2D convex hull technique to identify the stem and calyx. A camera and projector were used to reconstruct the 3D surface of the front half of an inspected apple. The height information for each pixel was reconstructed by a fringe projection and mathematical transformation. The 3D-reconstructed result was subjected to a multi-threshold segmentation technique and the segmentation results contained a concave feature in the curved line, representing the concave stem and calyx. The segmentation results were then subjected to a 2D convex hull technique, allowing for the identification of the stem and calyx. This method was evaluated using four groups of apples, and the proposed method is able to identify the stem and calyx with 98.93% accuracy. Calyx ; Segmentation ; Artificial intelligence ; Computer vision ; Convex hull ; Computer science ; Identification (biology) ; Projection (relational algebra) ; Regular polygon ; Feature (linguistics) ; Machine vision ; Optics ; Mathematics ; Algorithm ; Geometry ; Physics Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Industrial Vision Systems and Defect Detection
Authors: Shanpeng Zhao | Tianyu Wang | Youpeng Zhang | Yuantao Liu
Source: Coatings (article, 2022-08-29)
Field: Materials Science — Materials Chemistry

Study on the Contamination Characteristics of V-Type Double Suspension Rod Insulators Based on the Influence of Wake Flow The insulators of the catenary of the Lanzhou-Xinjiang High-speed Railway in windy areas suffer from serious contamination, which has led to frequent flashover accidents. The catenary of the Lanzhou-Xinjiang High-speed Railway has adopted the unique external insulation of V-type double suspension rod insulators. To further determine the contamination characteristics of this type of insulator, a contamination simulation model of insulator is established in this paper based on the principles of fluid mechanics, which is used to analyze the contamination characteristics of the V-type double suspension rod insulators under the influence of wake flow. The research results show that wind speed directly determines the static pressure on the surface of the insulator, the wind speed and particle concentration are proportional to the contamination volumes on the windward and crosswind sides of insulator, while the particle size is inversely proportional to the contamination volume on the leeward side of the insulator. The direction of wake flow is consistent with the direction angle of external incoming flow, and the wake flow generating area affects the contamination characteristics of the insulator. When the incoming flow is at a prevailing wind direction of 0°, focus should be put on the windward and crosswind sides of the two insulators during insulator cleaning, and the contamination distributions on these two insulators are similar; when the incoming flow is at a prevailing wind elevation of 0°∼60°, focus should be put on the entire surface of 1# insulator and the windward and crosswind sides of 2# insulator during insulator cleaning. Crosswind ; Catenary ; Insulator (electricity) ; Arc flash ; Wake ; Contamination ; Environmental science ; Wind speed ; Mechanics ; Flow (mathematics) ; Materials science ; Meteorology ; Structural engineering ; Engineering ; Physics ; Composite material High voltage insulation and dielectric phenomena ; Aerodynamics and Fluid Dynamics Research ; Thermal Analysis in Power Transmission
Authors: Jim Boelrijk | Bernd Ensing | Patrick Forré | Bob W.J. Pirok
Source: ChemRxiv (preprint, 2022-07-29)
Field: Chemistry — Spectroscopy

Closed-loop automatic gradient design for liquid chromatography using Bayesian optimization Contemporary complex samples require sophisticated methods for full analysis. This work describes the development of a Bayesian optimization algorithm for the automated and unsupervised development of gradient programs. The algorithm was tailored to LC using a Gaussian process model with a novel covariance kernel. To facilitate unsupervised learning, the algorithm was designed to interface directly with the chromatographic system. Single-objective and multi-objective Bayesian optimization strategies were investigated for the separation of a complex (n>80) dye mixture. The multi-objective strategy was found to be very powerful and flexible in terms of exploring the Pareto front. The single-objective strategy was found to be slightly faster in finding a satisfactory optimum. One additional advantage of the multi-objective approach was that it allows a trade-off to be made between multiple objectives. In general, the Bayesian optimization strategy was found to be particularly suitable, but not limited to, cases where retention modelling is not possible, although its scalability might be limited in terms of the number of parameters that can be simultaneously optimized. Bayesian optimization ; Computer science ; Scalability ; Bayesian probability ; Gaussian process ; Kernel (algebra) ; Artificial intelligence ; Machine learning ; Multi-objective optimization ; Mathematical optimization ; Gaussian ; Mathematics ; Chemistry Analytical Chemistry and Chromatography ; Computational Drug Discovery Methods ; Crystallization and Solubility Studies
Authors: Jingyu Zhang
Source: Academic Journal of Computing & Information Science (article, 2022-01-01)
Field: Chemistry — Analytical Chemistry

Identification and Analysis of Glass Components by Fusing K-Means Clustering and Ridge Regression The craft production of glass has a long history, and glass has been a valuable physical evidence of trade exchanges during the Silk Road. As traditional value crafts, the study and identification of the chemical composition of glass is of great significance. This paper mainly completes the classification problem by K-means clustering analysis and clustering tree, etc.; the statistical law study and prediction analysis of data are completed by integrating radial basis ridge regression and ARIMA differential autoregression, etc., which solves the problem of identification, classification and prediction of glass components. Firstly, the correlation analysis of the given data is carried out, and the Pearson correlation coefficient is calculated and visualized as the heat map representation, and performed statistical law fitting analysis of the data by ridge regression with fused radial bases, and finally predicted the chemical composition content before and after weathering by Autoregressive Integrated Moving Average (ARIMA) differential autoregression. Cluster analysis ; Autoregressive model ; Ridge ; Hierarchical clustering ; Regression analysis ; Linear regression ; Regression ; Mathematics ; Statistics ; Geography ; Cartography Spectroscopy and Chemometric Analyses
Authors: Fei Shang | Liangquan Wang
Source: Sensors (article, 2022-08-08)
Field: Materials Science — Materials Chemistry

Typical Fragment Kinetic Energy Assessment Based on Acoustic Emission Technology Fragment kinetic energy is an important parameter to characterize the damage power of fragments. In this study, an acoustic emission technology-based method to evaluate fragment kinetic energy is proposed. The dynamic response of the fragment impacting an aluminum alloy target plate and the relationship between the initial kinetic energy of the fragment impact and the acoustic emission waveform were theoretically evaluated; the numerical simulation of typical spherical fragments (8 mm diameter) penetrating the aluminum alloy target plate was performed, the wavelet energy of the acoustic emission signal was obtained using wavelet packet theory, and a mathematical model of wavelet energy and fragment kinetic energy was constructed. A fragment kinetic energy test system was established, and a fragment penetration test was performed. The analysis showed that the wavelet energy mathematical models and the fragment kinetic energy exhibited favorable consistency, and the measurement errors of the three experiments were 3%, 3.7%, and 3%. This demonstrates the effectiveness of the typical acoustic emission fragment kinetic energy test methods proposed in this study and establishes a new method for the direct measurement of fragment kinetic energy. Kinetic energy ; Fragment (logic) ; Acoustic emission ; Energy (signal processing) ; Waveform ; Wavelet ; Materials science ; Acoustics ; Computational physics ; Physics ; Computer science ; Voltage ; Classical mechanics ; Algorithm High-Velocity Impact and Material Behavior ; Rock Mechanics and Modeling ; Geophysical Methods and Applications
Authors: Hirofumi Iyama | Hayato Yamaguchi | Masatoshi Nishi | Yoshikazu HIGA
Source: Metals (article, 2022-11-12)
Field: Materials Science — Materials Chemistry

Study on High-Strain-Rate Deformation of Magnesium Alloy Using Underwater Shock Waves Generated by High-Voltage Electric Discharge of Thin Wire Magnesium is an abundant material with high specific strength, and its use as a structural metal is increasing. However, its properties cause difficulty in its formation at room temperature. Therefore, the objective of this study was to form a magnesium alloy at room temperature using an underwater shock wave generated by the discharge of an aluminum wire. Forming was conducted using an auxiliary plate composed of aluminum instead of magnesium alloy alone. In addition, hyperbolic and parabolic pressure vessels were employed. Numerical simulations were performed to measure the pressure values, propagation of underwater shock waves, and deformation of the magnesium alloy. Large deformation was observed when an auxiliary aluminum plate was placed on the upper surface of an AZ31 magnesium alloy plate inside the hyperbolic pressure vessel. Materials science ; Magnesium alloy ; Shock wave ; Magnesium ; Deformation (meteorology) ; Aluminium ; Shock (circulatory) ; Metallurgy ; Alloy ; Underwater ; Voltage ; Composite material ; Mechanics ; Electrical engineering ; Engineering ; Geology High-Velocity Impact and Material Behavior ; Fluid Dynamics Simulations and Interactions ; Metal Forming Simulation Techniques
Authors: S M Masum Alam
Source: International Journal of Research Publication and Reviews (article, 2022-09-16)
Field: Materials Science — Polymers and Plastics

Application of K-Means Clustering to Enhance the Quality Control and the Impact of the Productivity in the Apparel Industries Fabric inspection systems for measuring the quality are an essential part of producing best quality product in an apparel industry. The object of the research work is to analyze the acceptable fabric grade point based on the fabric grade points category using k-means clustering and their impact on the production. By applying the machine learning tools k-means clustering we categorized that hundred unsupervised data in three groups (A, B and C) based on acceptable grade points, of up to 15 (A), 15 to 30 (B), and 30 to 40 (C) respectively. The upper grade fabric can be consumed to produce better products. Thus, we can improve customer satisfaction as well as positive impact on the apparel manufacturing efficiency on both quality and quantity. Cluster analysis ; Clothing ; Productivity ; Quality (philosophy) ; Manufacturing engineering ; Product (mathematics) ; Production (economics) ; Control (management) ; Textile industry ; Point (geometry) ; Computer science ; Customer satisfaction ; Research Object ; Manufacturing ; Object (grammar) ; Operations management ; Business ; Industrial engineering ; Marketing ; Engineering ; Mathematics ; Artificial intelligence ; Business administration ; Economics Textile materials and evaluations ; Industrial Vision Systems and Defect Detection
Authors: Mickaël Binois | Régis Duvigneau | M. Elsawy | Patrice Genevet | S. Kadhir | Stéphane Lanteri | Nicolas Lebbe
Source: 2022 3rd URSI Atlantic and Asia Pacific Radio Science Meeting (AT-AP-RASC) (article, 2022-05-29)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Advanced Numerical Modeling Methods for the Characterization and Optimization of Metasurfaces The last 10 years have witnessed an impressive amount of works aiming at the development of thin metamaterials for controlling the wavefront of light, and thus realize planar photonics also referred as flat optics or metaoptics. The concept of metasurface is at the heart of almost all the discoveries in this domain. Metasurfaces are arrays of subwavelength-spaced and optically thin optical elements, which enable new physics and phenomena that are distinctly different from those observed in three-dimensional bulk metamaterials. We present here our recent activities and achievements in relation with the design of metasurfaces, which are concerned with two topics: on one hand, we study numerical characterization approaches that are well suited to the multiscale nature of metasurfaces; on the other hand, we develop inverse design strategies for discovering non-classical metasurface configurations for a target optical functionality. These two topics are addressed in the context of a multidisciplinary collaborative project, which involve computational scientists and physicists. In particular, we apply the proposed numerical methodologies to the design of phase gradient metasurfaces and light front shaping metalenses. In some cases, the numerically designed metasurfaces have been frabricated and experimentally characterized to confirm their predicted performances. Metamaterial ; Wavefront ; Context (archaeology) ; Characterization (materials science) ; Computer science ; Planar ; Photonics ; Relation (database) ; Optics ; Physics ; Computer graphics (images) Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Microwave Engineering and Waveguides