jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Renato Simões Moreira | Vilmar Benetti Filho | Guilherme Augusto Maia | Tatiany Aparecida Teixeira Soratto | Eric Kazuo Kawagoe | Bruna Caroline Russi | Luiz Cláudio Miletti | Glauber Wagner
Source: PeerJ (article, 2024-10-31)
Field: Chemistry — Spectroscopy

FastProtein—an automated software for <i>in silico</i> proteomic analysis Although various tools provide proteomic information, each tool has limitations related to execution platforms, libraries, versions, and data output format. Integrating data generated from different software is a laborious process that can prolong analysis time. Here, we present FastProtein, a protein analysis pipeline that is user-friendly, easily installable, and outputs important information about subcellular location, transmembrane domains, signal peptide, molecular weight, isoelectric point, hydropathy, aromaticity, gene ontology, endoplasmic reticulum retention domains, and N-glycosylation domains. It also helps determine the presence of glycosylphosphatidylinositol and obtain functional information from InterProScan, PANTHER, Pfam, and alignment-based annotation searches. FastProtein provides the scientific community with an easy-to-use computational tool for proteomic data analysis. It is applicable to both small datasets and proteome-wide studies. It can be used through the command line interface mode or a web interface installed on a local server. FastProtein significantly enhances proteomics analysis workflows by producing multiple results in a single-step process, thereby streamlining and accelerating the overall analysis. The software is open-source and freely available. Installation and execution instructions, as well as the source code and test files generated for tool validation, are available at https://github.com/bioinformatics-ufsc/FastProtein. In silico ; Computer science ; Computational biology ; Software ; Software engineering ; Biology ; Programming language ; Genetics Advanced Proteomics Techniques and Applications ; Genomics and Phylogenetic Studies ; Machine Learning in Bioinformatics
Authors: Gabe Nagy
Source: Journal of Mass Spectrometry (article, 2024-04-11)
Field: Chemistry — Spectroscopy

High‐resolution ion mobility separations coupled to mass spectrometry: What's next? Herein, I provide a personal perspective on high-resolution multipass ion mobility spectrometry-mass spectrometry (IMS-MS), with a specific emphasis on cyclic (cIMS) and structures for lossless ion manipulations (SLIM IMS)-based separations. My overarching goal for this perspective was to detail what I believe will be the key important areas in which IMS-MS will help shape the bioanalytical community and especially omics-based research. Chemistry ; Ion-mobility spectrometry ; Mass spectrometry ; Perspective (graphical) ; Bioanalysis ; Ion-mobility spectrometry–mass spectrometry ; Resolution (logic) ; High resolution ; Key (lock) ; Nanotechnology ; Analytical Chemistry (journal) ; Tandem mass spectrometry ; Chromatography ; Selected reaction monitoring ; Computer science ; Remote sensing Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Analytical Chemistry and Chromatography
Authors: Mgcini Keith Phuthi | Emil Annevelink | Venkatasubramanian Viswanathan
Source: The Journal of Open Source Software (article, 2024-10-21)
Field: Materials Science — Materials Chemistry

ASIMTools: A lightweight framework for scalable andreproducible atomic simulations Scalability ; Computer science ; Computational science ; Operating system Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Electron and X-Ray Spectroscopy Techniques
Authors: Reem Abukmeil | Ahmad Al-Mallahi | Felipe Campelo
Source: Smart Agricultural Technology (article, 2024-06-20)
Field: Chemistry — Analytical Chemistry

Calibrating lab and field reflectance spectra for nutrient estimation in potato plants using local support vector regression models This study presents a methodology based on multiple local support vector regression (SVR) to calibrate the spectra taken in the field in relative to lab-derived spectra. Laboratory based foliar spectral measurement is a common method to provide lab-derived spectra as a service where a grower sends sample leaves collected manually. The drawback of this method is being time-consuming when the samples are collected and analyzed. In contrast, in-field spectral measurements can be an alternative method capable of providing immediate readings. While both methods work based on the same priniciple, the insturmental differences as well as the conditional difference under which the instruments operate may cause differences in the spectral patterns of the same target. In this work, after developing the calibration method, we validated it by estimating NPK measurements in potato plants using in-field, lab, and field calibrated spectral measurements over two testing modes: dried and fresh. The results showed that the calibration using SVR models could minimize the percentage relative error (PRE) between lab and field spectra within the visible range by considering the influence of the neighboring wavebands up to 32 nm width which improved the alignment of the local maxima of the specral curves. Also, a substantial PRE reduction from 120 % to 20 % for some wavebands in the short-wave infrared (SWIR) region of the fresh mode was observed due to the influence of scaling within the SVR method. The calibration improved the alignment of NPK estimated values between lab and field calibrated spectra of both modes with an emphasis on its necessity to estimate nutrients in the fresh mode as the root mean square error was < 0.1 for the three elements. Reflectivity ; Nutrient ; Field (mathematics) ; Regression ; Estimation ; Support vector machine ; Environmental science ; Regression analysis ; Mathematics ; Biological system ; Statistics ; Remote sensing ; Geography ; Computer science ; Biology ; Artificial intelligence ; Ecology ; Optics ; Engineering ; Physics Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Remote Sensing in Agriculture
Authors: Aditya S Baheti | Ankush D. Sawarkar | Umayr Shaikh | Deepti D. Shrimankar
Source: Cureus Journal of Computer Science. (article, 2024-11-12)
Field: Chemistry — Analytical Chemistry

Alcohol Quality Analysis Using Machine Learning Regression Technique This research paper investigates the predictive modeling of alcohol quality machine learning regression analysis. The study employs a comprehensive approach to preprocessing, modeling, and evaluation to achieve accurate predictions. Initial data exploration reveals the dataset's structure and identifies potential issues such as missing values and outliers. Preprocessing steps include outlier removal using the interquartile range method and feature scaling to ensure uniformity. The dataset is split into two parts, i.e., training and testing, for development and evaluation. Regression models are built using the ordinary least squares method, incorporating features transformed to address skewness and scaled to improve model performance. Model diagnostics are conducted to assess assumptions including multicollinearity and normality of residuals. The final model exhibits strong predictive capability, as evidenced by high R-squared values and low mean squared error. Visualization techniques illustrate the relationship between actual and predicted values, providing insight into model accuracy. Overall, this paper demonstrates the effectiveness of linear regression in predicting alcohol content with an accuracy of 92%, offering valuable implications for quality control and production optimization in the alcohol industry along with other regression models such as gradient boosting with an accuracy of 90% and decision tree regressor with an accuracy of 83%. Quality (philosophy) ; Machine learning ; Regression analysis ; Computer science ; Regression ; Artificial intelligence ; Statistics ; Mathematics Spectroscopy and Chemometric Analyses
Authors: Yuzhan Ren | Chengcheng Liu | Youhua Wang
Source: AIP Advances (article, 2024-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Residual flux density estimation of the three-phase transformer using BP neural network When the off-line transformer is re-energized, the phase-controlled switching strategy can avoid the generation of inrush current by controlling the phase. To determine the closing phase, the residual flux density (Br) in the transformer core needs to be accurately measured. This paper proposes a Br estimation method for three-phase transformers based on the finite element method and BP neural network. Firstly, the direction of Br in each phase core is determined based on the transient current characteristics. Then, the three-phase transformer is simulated and the BP neural network is trained to estimate the Br based on the simulation results. The experimental results on a three-phase transformer show that the proposed method can accurately determine the direction and amplitude of Br in each phase of the three-phase transformer. Transformer ; Artificial neural network ; Residual ; Inrush current ; Three-phase ; Current transformer ; Amplitude ; Voltage ; Control theory (sociology) ; Computer science ; Engineering ; Algorithm ; Physics ; Electrical engineering ; Artificial intelligence ; Optics Magnetic Properties and Applications ; Non-Destructive Testing Techniques ; Power Transformer Diagnostics and Insulation
Authors: Ayyoub Zouaghi | Caterina Toigo | Arel Rako | T. Vu-Cong | Frank Jacquier | A. Girodet
Source:  (article, 2024-06-30)
Field: Materials Science — Materials Chemistry

Breakdown and Partial Discharge in Dry Air under Non-uniform Electric Field for MVDC Applications Medium and high voltage gas insulated switchgear (GIS) are key installations in the electrical power transmission and distribution network. The equipment in these substations are insulated with pressurized gas in order to guarantee their proper functioning. This work aims to investigate the performance, in DC, of dry air under non-uniform electric field conditions for medium voltage switchgear applications. Experimental investigations have been carried out to assess the breakdown and the partial discharge inception voltages as function of the electric field non-uniformity and dry air pressures. The experimental work has been compared with numerical study of the breakdown electric field based on streamer criterion using COMSOL Multiphysics numerical software. The results show that the breakdown maximum field decreases as a function of the utilization factor till 0.3, then it stabilizes for weakly non-uniform electric field. The breakdown maximum field is not dependent on the polarity of the DC voltage for utilization factors higher than 0.2. Otherwise, the breakdown maximum field seems to be lower under positive DC voltage for utilization factors under 0.2. Simulation results of the maximum field obtained using the streamer criterion are in good agreement with the experimental partial discharge results. Partial discharge ; Electric field ; Electric breakdown ; Electrical engineering ; Materials science ; Environmental science ; Engineering ; Voltage ; Physics High voltage insulation and dielectric phenomena ; Plasma Diagnostics and Applications ; Electrostatic Discharge in Electronics
Authors: Nikita Gurjar | Keith Bailey | Magda El‐Shenawee
Source: Journal of Medical Imaging (article, 2024-12-05)
Field: Chemistry — Physical and Theoretical Chemistry

Polarimetry terahertz imaging of human breast cancer surgical specimens THz polarimetry imaging shows a potential for improving image contrast in excised tumor tissues compared with single polarization imaging. Cross-polarization signals demonstrated smaller amplitudes compared with co-polarized signals. However, averaging the signal during measurements has tremendously improved the image. Furthermore, in post-processing, averaging the frequency domain images and the Mueller matrix elements with respect to frequency has led to better image contrast. Some patterns in the Mueller matrix images were difficult to interpret leading to the necessity of more investigation of the Mueller matrix and its physiological interpretation of breast tumor tissues. Medicine ; Breast cancer ; Radiology ; Terahertz radiation ; Human breast ; Polarimetry ; Medical physics ; Cancer ; Optics ; Internal medicine thermodynamics and calorimetric analyses ; Terahertz technology and applications ; Infrared Thermography in Medicine
Authors: E. Suárez | O. Guzmán-Juárez | R. Lemus
Source: Molecules (article, 2024-07-25)
Field: Chemistry — Organic Chemistry

Novel Criteria to Provide a Locality/Normality Degree in Molecules and Their Relevance in Physical Chemistry In contrast to the traditional analysis of molecules using local mode behavior, where the degree of locality is given through a function in terms of Morse potential parameters, new criteria for locality/normality (LN) suitable for application to any molecular system are proposed. The approach is based on analysis of the connection between the algebraic normal and local mode representations. It is shown that both descriptions are equivalent as long as the polyad (total number of quanta) in the local representation is not conserved. The constraint of a local polyad conservation naturally provides a criterion for assigning an LN degree in quantitative form, without an analogue in configuration space. The correlation between the different parameters reveals the physical properties of molecules. A clear connection between the LN degree (based on the fundamentals) and spectroscopic properties is also presented, suggesting a promising approach for identifying mixtures of isotopologues. Degree (music) ; Locality ; Normality ; Connection (principal bundle) ; Mathematics ; Constraint (computer-aided design) ; Representation (politics) ; Space (punctuation) ; Molecule ; Statistical physics ; Computational chemistry ; Physics ; Chemistry ; Computer science ; Pure mathematics ; Quantum mechanics ; Statistics ; Geometry Chemical Thermodynamics and Molecular Structure ; Spectroscopy and Quantum Chemical Studies ; Thermodynamic properties of mixtures
Authors: Moustapha Godi Tchéré | Stéphane Robert | Julie Dutems | Hugo Bruhier | Bernard Bayard | Yves Jourlin | Damien Jamon
Source: Applied Optics (article, 2024-04-15)
Field: Materials Science — Surfaces, Coatings and Films

Characterization of a perfect sinusoidal grating profile using an artificial neural network for plasmonic-based sensors In this paper, we present a system intended to detect a targeted perfect sinusoidal profile of a diffraction grating during its manufactured process. Indeed, the sinusoidal nature of the periodic structure is essential to ensure optimal efficiency of specific applications as plasmonic sensors (surface plasmon resonance -based sensors). A neural network is implemented to characterize the geometrical shape of the structure under testing at the end of the laser interference lithography process. This decision tool operates in classifier mode prior to further processing. Then, the geometrical parameters of the structure can be reliably determined if necessary. Two solutions can be considered: the detection of a fixed geometrical shape operating on a binary mode and the identification of a geometrical shape from a limited number of profiles. These methods are validated in the context of plasmonic sensors on experimental sinusoidal grating structures with a grating period of 627 nm. Grating ; Optics ; Plasmon ; Diffraction grating ; Artificial neural network ; Surface plasmon ; Interference (communication) ; Computer science ; Materials science ; Physics ; Artificial intelligence Optical Coatings and Gratings ; Photonic and Optical Devices ; Photonic Crystals and Applications
Authors: Huanqing Zou | Yufeng Yin | Juan Chen | Shun Zhang | Fuqiang Tian
Source: Applied Sciences (article, 2024-10-23)
Field: Materials Science — Materials Chemistry

Research on the Inner Surface Discharge of the Insulation Sheath of Electric Locomotive Cable Terminals Adding an insulating sheath to the exposed metal part of the outer insulation of a roof cable terminal can extend the creepage distance of the leakage current and significantly reduce the probability of pollution flashover on the outer insulation of the equipment. However, during the actual operation of the locomotive, the inner surface of the insulating sheath is discharged, resulting in cable insulation breakdown, the mechanism of which is unclear. This paper establishes a cable terminal–sheath electric field simulation model and studies the interface air gap, the interface with wet pollution, and the distribution of damp pollution on the outer surface and other factors on the electric field distribution of the cable terminal–sheath structure and the interface discharge, revealing the mechanism of discharge on the inner surface of the cable terminal’s insulation sheath. A voltage of 25 kV rms is applied, and the simulation results show that when the outer surface of the cable terminal is clean and there are air gaps and wet dirt on the inner surface, the maximum distortion electric field at the inner surface is 0.8 × 105~3.4 × 105 V/m, and the value of the electric field at this time is not enough to cause a partial discharge; when there is a uniform layer of wet dirt on the outer surface of the cable terminal, the electric field on the inner surface averages 1.5 × 105 V/m, which is about 275% higher than the average electric field when the outer surface is clean; when there is wetting or an air gap on the inner surface at the same time, the maximum aberration electric field on the inner surface is 1.8 × 105~1.9 × 106 V/m. The wetting on the outer surface of the cable terminal strengthens the non-uniformity degree of the distribution of the electric field, and when there is wetting and an air gap on the inner surface, the over-voltage on the cable terminal inevitably leads to a discharge phenomenon in the air gap. This provides a theoretical basis for optimizing the insulation sheath structure to solve the discharge problem. Engineering ; Electrical engineering ; Mechanical engineering ; Materials science High voltage insulation and dielectric phenomena ; Aerosol Filtration and Electrostatic Precipitation ; Thermal Analysis in Power Transmission
Authors: Jianmin Huang | Qingchun Jiao | Yifan Zhang | Gaoqing Xu | Lijun Wang | Yue Dong
Source: PLoS ONE (article, 2024-04-16)
Field: Materials Science — Polymers and Plastics

Fabric tearing performance state perception and classification driven by multi-source data The tear strength of textiles is a crucial characteristic of product quality. However, during the laboratory testing of this indicator, factors such as equipment operation, human intervention, and test environment can significantly influence the results. Currently, there is a lack of traceable records for the influencing factors during the testing process, and effective classification of testing activities is not achieved. Therefore, this study proposes a state-awareness and classification approach for fabric tear performance testing based on multi-source data. A systematic design is employed for fabric tear performance testing activities, which can real-time monitor electrical parameters, operational environment, and operator behavior. The data are collected, preprocessed, and a Decision Tree Support Vector Machine (DTSVM) is utilized for classifying various working states, and introducing ten-fold cross-validation to enhance the performance of the classifier, forming a comprehensive awareness of the testing activities. Experimental results demonstrate that the system effectively perceives fabric tear performance testing processes, exhibiting high accuracy in the classification of different fabric testing states, surpassing 98.73%. The widespread application of this system contributes to continuous improvement in the workflow and traceability of fabric tear performance testing processes. Traceability ; Workflow ; Computer science ; Classifier (UML) ; Manual testing ; Reliability engineering ; Process (computing) ; Decision tree ; Support vector machine ; Artificial intelligence ; Machine learning ; Data mining ; Engineering ; Software engineering ; Database Textile materials and evaluations ; Industrial Vision Systems and Defect Detection ; Food Supply Chain Traceability
Authors: Amrita Singh | A. O. Varghese | Jugal Kishore Mani | Ashish Kumar Sharma | G. Sreenivasan
Source: Current Science (article, 2024-04-10)
Field: Chemistry — Analytical Chemistry

Analysis of Various Spectral Indices and their Weighted Fusion Techniques for the Accurate Extraction of Forest Burn Scar in a Tropical Deciduous Forest The present study was conducted in the tropical dry deciduous forests of Vidarbha region, Maharashtra, India.Burn scar discrimination capabilities of seven widely used spectral indices (SIs) such as burn area index (BAI), burned area index modified-LSWIR (BAIML), burned area index modified-sSWIR (BAIMs), normalized burn ratio (NBR), normalized difference vegetation index (NDVI), normalized difference moisture index (NDMI), modified soil-adjusted vegetation index (MSAVI) and their weighted fusion were examined in a multi-temporal domain.This study generated different images during fire season using individual SIs, change vector analysis and weighted fusion normalized difference image technique.Comparative analysis was performed between these approaches for burn scar discrimination with M statistics, burned and unburned class distribution and evaluation of confusion matrix.The study demonstrates that the weighted fusion of BAI, MSAVI and BAIMs can more accurately discriminate burn scars with good overall accuracy (86.61%). Deciduous ; Tropical forest ; Extraction (chemistry) ; Fusion ; Ecology ; Biology ; Chemistry Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Water Quality Monitoring and Analysis