jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Tarik Attar | Abbes Benchadlı | Esma Choukchou-Braham | Amal Benkhaled
Source: Journal of the Turkish Chemical Society Section A Chemistry (article, 2023-11-27)
Field: Materials Science — Materials Chemistry

Iodine–β-Cyclodextrin: An Effective Corrosion Inhibitor for Carbon Steel in Sulfuric Acid Solution - Experimental Design and Investigating Thermodynamic Parameters Widely used across industries, carbon steel is vulnerable to corrosion in aggressive environments, especially acidic ones. Thus, effective methods to mitigate metal corrosion from acids are crucial. Inhibitors are extensively used to prevent corrosion in industries, with the potential for improved protective performance. The design of experiments was employed to determine the optimal conditions for enhancing the inhibitor efficiency of Iodine–β-Cyclodextrin (Iodine/β-CD) in a sulfuric acid solution at temperatures ranging from 20°C to 50°C. The relationship between the factors and responses was established using response surface methodology (RSM), employing regression statistical analysis and probabilistic analysis. A single response was recorded: inhibitor efficiency was determined by measuring weight loss before and after immersion in the inhibitor solution. Thermodynamic parameters were also computed to determine adsorption and activation processes. The statistical analysis revealed that the quadratic models for inhibition efficiencies (IE) were highly significant with a coefficient of multiple regressions R2= 0.997. Further validation of the model indicated a good fit (R2 Adj= 0.994), and the experimentally observed values aligned well with predicted ones, demonstrating a highly significant model with Q2= 0.978. The theoretical efficiency predicted by the RSM model was 88.41%, whereas the efficiency observed during the experimental test procedure with the best-evaluated variables was 82.45%. In conclusion, this paper aims to identify the optimal conditions for employing Iodine–β-Cyclodextrin as a new corrosion inhibitor for carbon steel, utilizing experimental design methods. The results indicate that iodine/β-CD exhibits remarkable corrosion inhibitory properties for carbon steel under specific conditions. Sulfuric acid ; Chemistry ; Corrosion ; Carbon steel ; Response surface methodology ; Iodine ; Corrosion inhibitor ; Adsorption ; Metallurgy ; Inorganic chemistry ; Chromatography ; Materials science ; Organic chemistry Corrosion Behavior and Inhibition ; Hydrogen embrittlement and corrosion behaviors in metals ; Concrete Corrosion and Durability
Authors: Nicolai Bjødstrup Palstrøm | Amanda Campbell | Caroline A. Lindegaard | Samir Cakar | Rune Matthiesen | Hans Christian Beck
Source: PROTEOMICS (article, 2023-09-14)
Field: Chemistry — Spectroscopy

Spectral library search for improved TMTpro labelled peptide assignment in human plasma proteomics Clinical biomarker discovery is often based on the analysis of human plasma samples. However, the high dynamic range and complexity of plasma pose significant challenges to mass spectrometry-based proteomics. Current methods for improving protein identifications require laborious pre-analytical sample preparation. In this study, we developed and evaluated a TMTpro-specific spectral library for improved protein identification in human plasma proteomics. The library was constructed by LC-MS/MS analysis of highly fractionated TMTpro-tagged human plasma, human cell lysates, and relevant arterial tissues. The library was curated using several quality filters to ensure reliable peptide identifications. Our results show that spectral library searching using the TMTpro spectral library improves the identification of proteins in plasma samples compared to conventional sequence database searching. Protein identifications made by the spectral library search engine demonstrated a high degree of complementarity with the sequence database search engine, indicating the feasibility of increasing the number of protein identifications without additional pre-analytical sample preparation. The TMTpro-specific spectral library provides a resource for future plasma proteomics research and optimization of search algorithms for greater accuracy and speed in protein identifications in human plasma proteomics, and is made publicly available to the research community via ProteomeXchange with identifier PXD042546. Proteomics ; Human plasma ; Peptide ; Computational biology ; Chemistry ; Chromatography ; Biology ; Biochemistry ; Gene Advanced Proteomics Techniques and Applications ; Machine Learning in Bioinformatics ; Mass Spectrometry Techniques and Applications
Authors: Pablo Aledo | Juan Carlos Aledo
Source: International Journal of Molecular Sciences (article, 2023-01-02)
Field: Chemistry — Spectroscopy

Proteome-Wide Structural Computations Provide Insights into Empirical Amino Acid Substitution Matrices The relative contribution of mutation and selection to the amino acid substitution rates observed in empirical matrices is unclear. Herein, we present a neutral continuous fitness-stability model, inspired by the Arrhenius law (qij=aije-ΔΔGij). The model postulates that the rate of amino acid substitution (i→j) is determined by the product of a pre-exponential factor, which is influenced by the genetic code structure, and an exponential term reflecting the relative fitness of the amino acid substitutions. To assess the validity of our model, we computed changes in stability of 14,094 proteins, for which 137,073,638 in silico mutants were analyzed. These site-specific data were summarized into a 20 square matrix, whose entries, ΔΔGij, were obtained after averaging through all the sites in all the proteins. We found a significant positive correlation between these energy values and the disease-causing potential of each substitution, suggesting that the exponential term accurately summarizes the fitness effect. A remarkable observation was that amino acids that were highly destabilizing when acting as the source, tended to have little effect when acting as the destination, and vice versa (source → destination). The Arrhenius model accurately reproduced the pattern of substitution rates collected in the empirical matrices, suggesting a relevant role for the genetic code structure and a tuning role for purifying selection exerted via protein stability. Substitution (logic) ; Proteome ; Computational biology ; Amino acid substitution ; Chemistry ; Amino acid ; Computation ; Human proteome project ; Computer science ; Biochemistry ; Bioinformatics ; Proteomics ; Biology ; Algorithm ; Mutation Advanced Proteomics Techniques and Applications ; Genomics and Phylogenetic Studies ; RNA and protein synthesis mechanisms
Authors: Shupeng Zeng | Xiaohong Wu | Bin Wu | Haoxiang Zhou | Meng Wang
Source: Food Science and Technology (article, 2023-01-01)
Field: Chemistry — Analytical Chemistry

Rapid determination of cadmium residues in tomato leaves by Vis-NIR hyperspectral and Synergy interval PLS coupled Monte Carlo method Excessive heavy metal cadmium in tomatoes is harmful to human health. The detection of heavy metals in tomato leaves can determine whether the heavy metals in tomatoes exceed the standard. In order to quickly, non-destructively and efficiently detect whether heavy metals on the surface of tomato leaves exceed the standard, a new wavelength interval selection method called Synergy interval PLS couple with Monte Carlo method (MC-siPLS) was proposed. From the seedling stage, concentration of 0, 0.05, 0.1, 0.2, 0.5, 1, 2, 5, 10 mg/L cadmium chloride (CdCl2) was used for irrigation under normal nutrient elements respectively. A total of 405 leaf samples were collected. Using the VIS-NIR hyperspectral instrument, the tomato leaves were set as the region of interest to obtain hyperspectral data, then used Atomic Absorption Spectrometry (AAS) method to detect heavy metals in tomato leaves. In addition, 5 different PLS algorithm were used to compare with MC-siPLS. Furthermore, the best model was given by MC-siPLS with RMSEP = 0.5378, R2 = 0.9870. The results show that MC-siPLS was better than similar wavelength interval selection methods, which had great application potential in the nondestructive detection of heavy metals in tomato leaves. This method maybe determines whether tomatoes contain excess cadmium early. Cadmium ; Hyperspectral imaging ; Chemistry ; Monte Carlo method ; Analytical Chemistry (journal) ; Environmental chemistry ; Mathematics ; Remote sensing ; Statistics Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Advanced Chemical Sensor Technologies
Authors: Jiang Wang | Kai Hu | Kechen Tang | Yubing Xing | Yani Xiao | Yutian Liu | Yonggao Yan | Dongwang Yang
Source: Preprints.org (preprint, 2023-04-24)
Field: Materials Science — Materials Chemistry

Numerical Simulation on Thermoelectric Cooling of Core Power Devices in Air Conditioning Air conditioners are indispensable necessities in daily life and industrial production. However, the heat generation of their internal core power components can limit their performance release. In this work, we explore the application of thermoelectric coolers (TECs) in the field of power device heat dissipation through finite element simulation. First, we geometrically modeled the structure and typical operating conditions of core power devices in air conditioners. We compared the temperature fields in air cooling and TEC active cooling modes for high power consumption power devices in a 319 K operating environment. The simulation results show that in the single air cooling mode, the maximum temperature of the 173.8 W power device reaches 394.4 K and the average temperature reaches 373.9 K, which exceeds its rated operating temperature of 368.1 K. However, after adding TEC, the maximum temperature of the power device drops to 331.8 K at an operating current of 7.5 A and the average temperature of the device is 326.5 K. It indicates that TEC active cooling has a significant effect on the temperature control of the power device. At the same time, we also studied the effect of TEC working current on the temperature control effect of power devices. For TEC, there is a minimum working current of 5 A; when it is less than 5 A, TEC has no cooling effect; the cooling effect of TEC increases with an increase in working current. When the TEC working current is 10 A, the average temperature of the power device can be reduced to 292.9 K. This study has made a meaningful exploration of the application of TEC in chip temperature control and heat dissipation, providing a new solution for chip thermal management and accurate temperature control. TEC ; Thermoelectric cooling ; Air conditioning ; Power (physics) ; Active cooling ; Thermoelectric effect ; Materials science ; Cooling capacity ; Operating temperature ; Water cooling ; Nuclear engineering ; Work (physics) ; Environmental science ; Mechanics ; Electrical engineering ; Mechanical engineering ; Thermodynamics ; Engineering ; Physics Advanced Thermoelectric Materials and Devices ; Heat Transfer and Optimization ; Thermal properties of materials
Authors: Thomas A. R. Purcell | Matthias Scheffler | Luca M. Ghiringhelli
Source: arXiv (Cornell University) (preprint, 2023-05-02)
Field: Materials Science — Materials Chemistry

Recent advances in the SISSO method and their implementation in the SISSO++ code Accurate and explainable artificial-intelligence (AI) models are promising tools for the acceleration of the discovery of new materials, ore new applications for existing materials. Recently, symbolic regression has become an increasingly popular tool for explainable AI because it yields models that are relatively simple analytical descriptions of target properties. Due to its deterministic nature, the sure-independence screening and sparsifying operator (SISSO) method is a particularly promising approach for this application. Here we describe the new advancements of the SISSO algorithm, as implemented into SISSO++, a C++ code with Python bindings. We introduce a new representation of the mathematical expressions found by SISSO. This is a first step towards introducing ``grammar'' rules into the feature creation step. Importantly, by introducing a controlled non-linear optimization to the feature creation step we expand the range of possible descriptors found by the methodology. Finally, we introduce refinements to the solver algorithms for both regression and classification, that drastically increase the reliability and efficiency of SISSO. For all of these improvements to the basic SISSO algorithm, we not only illustrate their potential impact, but also fully detail how they operate both mathematically and computationally. Computer science ; Python (programming language) ; Symbolic regression ; Solver ; Feature (linguistics) ; Code (set theory) ; Simple (philosophy) ; Artificial intelligence ; Range (aeronautics) ; Theoretical computer science ; Machine learning ; Programming language ; Genetic programming Machine Learning in Materials Science ; Electron and X-Ray Spectroscopy Techniques ; Topic Modeling
Authors: Kyowon Jeong | Philipp T. Kaulich | Wonhyeuk Jung | Jihyung Kim | Andreas Tholey | Oliver Kohlbacher
Source: PROTEOMICS (article, 2023-11-23)
Field: Chemistry — Spectroscopy

Precursor deconvolution error estimation: The missing puzzle piece in false discovery rate in top‐down proteomics Top-down proteomics (TDP) directly analyzes intact proteins and thus provides more comprehensive qualitative and quantitative proteoform-level information than conventional bottom-up proteomics (BUP) that relies on digested peptides and protein inference. While significant advancements have been made in TDP in sample preparation, separation, instrumentation, and data analysis, reliable and reproducible data analysis still remains one of the major bottlenecks in TDP. A key step for robust data analysis is the establishment of an objective estimation of proteoform-level false discovery rate (FDR) in proteoform identification. The most widely used FDR estimation scheme is based on the target-decoy approach (TDA), which has primarily been established for BUP. We present evidence that the TDA-based FDR estimation may not work at the proteoform-level due to an overlooked factor, namely the erroneous deconvolution of precursor masses, which leads to incorrect FDR estimation. We argue that the conventional TDA-based FDR in proteoform identification is in fact protein-level FDR rather than proteoform-level FDR unless precursor deconvolution error rate is taken into account. To address this issue, we propose a formula to correct for proteoform-level FDR bias by combining TDA-based FDR and precursor deconvolution error rate. False discovery rate ; Deconvolution ; Computer science ; Proteomics ; Inference ; Identification (biology) ; Data mining ; Computational biology ; Algorithm ; Chemistry ; Artificial intelligence ; Biology Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Advanced Biosensing Techniques and Applications
Authors: Raja Ghosh
Source: Processes (article, 2023-07-19)
Field: Materials Science — Materials Chemistry

Membrane-Based Micro-Volume Dialysis Method for Rapid and High-Throughput Protein Crystallization Protein crystallization techniques are very important in drug development. This paper discusses a membrane-based micro-volume dialysis method suitable for rapid and high-throughput protein crystallization. A droplet of protein solution was deposited on the membrane surface in a micro-volume dialysis device. Crystallizing agents could be added to the protein solution either directly or through the membrane. The crystallization process could easily be monitored in real time under a microscope. Tiny specks, indicative of forming crystals, were observed as early as 30 s from the start of the experiment, and these were clearly distinguishable as tetragonal lysozyme crystals within 2 min. This method is particularly suitable for carrying out screening and optimization experiments, and for studying crystallization kinetics. The easy and direct manner in which protein and crystallizing agents are introduced into the device makes this method amenable to miniaturization and automation. Additionally, this approach would potentially allow for rapid screening of the effects of drug molecules on the crystallization process and the nature of crystal formation. Crystallization ; Protein crystallization ; Dialysis ; Membrane ; Volume (thermodynamics) ; Materials science ; Tetragonal crystal system ; Nanotechnology ; Nucleation ; Chemical engineering ; Chromatography ; Chemistry ; Crystallography ; Crystal structure ; Biochemistry ; Organic chemistry ; Engineering ; Medicine Enzyme Structure and Function ; Protein Structure and Dynamics ; Mass Spectrometry Techniques and Applications
Authors: Ya Gao
Source: Textile & Leather Review (article, 2023-10-29)
Field: Materials Science — Polymers and Plastics

A Design of Apparel Appearance: Recognition and Evaluation of Clothing Pattern Styles under Deep Learning Designing the appearance of clothing can effectively enhance its attractiveness and expand its marketability. This paper briefly introduces the Convolutional Neural Network (CNN) and applies it to the recognition and evaluation of clothing pattern styles to assist in evaluating clothing appearance design. A case analysis was then conducted. Firstly, the CNN algorithm was compared with the traditional Back-Propagation Neural Network (BPNN) algorithm, and then the design scheme proposed in this paper, called "Sanduo and Jiuru", was evaluated. The results showed that, compared to the BPNN algorithm, the CNN algorithm not only converged faster during training but also demonstrated superiority after the convergence became stable. In addition, the test set also verified the accuracy of the CNN algorithm in recognizing and evaluating clothing pattern styles. The evaluation of the "Sanduo and Jiuru" design was also very similar to human evaluation, and its excellence was analyzed accordingly. Clothing ; Convolutional neural network ; Computer science ; Artificial intelligence ; Attractiveness ; Set (abstract data type) ; Convergence (economics) ; Excellence ; Artificial neural network ; Scheme (mathematics) ; Pattern recognition (psychology) ; Machine learning ; Deep learning ; Mathematics ; Psychology Textile materials and evaluations ; Consumer Perception and Purchasing Behavior ; Color Science and Applications
Authors: Liang Xiao-li | Shan Wei | Yanpeng Xu | Liang Yin | Ruiming Wang | Piwu Li | Kaiquan Liu
Source: Polymers (article, 2023-12-07)
Field: Materials Science — Biomaterials

Construction and Characterization of Fitting Equations for a New Wheat Straw Pulping Method The pretreatment of pulp with enzymes has been extensively studied in the laboratory. However, due to cost constraints, the application of enzymes in the pulp and paper industry is very limited. In this paper, an environment-friendly and efficient pulping method is proposed as an alternative to traditional pulping and papermaking methods. This new method overcomes the low efficiency and extreme pollution problems associated with traditional pulping methods. In addition, fitting equations for the new pulping method are constructed using data on enzyme treatments, which reflect the effect of enzymes and enable the realization of real-time control of the pulping process. The experimental results show that the efficiency of the pulping and papermaking process can be improved using biological enzymes, and the separation of cellulose can be facilitated using mixed enzymes, which have a better effect than single enzymes. Papermaking ; Pulp (tooth) ; Pulp and paper industry ; Biochemical engineering ; Cellulose ; Xylanase ; Computer science ; Process engineering ; Process (computing) ; Enzyme ; Chemistry ; Engineering ; Chemical engineering ; Biochemistry ; Dentistry Advanced Cellulose Research Studies ; Lignin and Wood Chemistry ; Biofuel production and bioconversion
Authors: Sinem Yelkovan | Erhan Kenan Çeven | Gizem Karakan Günaydın | Laura Chirilă
Source: Industria Textila (article, 2023-12-22)
Field: Materials Science — Polymers and Plastics

Research on thermal comfort and moisture management propertiesof drapery fabrics produced with polyester yarns having different fibrecross-sectional shapes and TiO2 amount This study aims to provide an investigation regarding the effect of fibre cross-sectional shape, incorporated TiO2 amount (%) during polyester yarn production, and the weft density parameters respectively, on thermal comfort, moisture management, water vapour permeability, and air permeability properties of polyester drapery fabrics. Completely randomized three-factor analysis of variance (ANOVA) was conducted at the significance level of 0.05. SNK tests were also performed to observe the means of each parameter. Some of the weft yarn production parameters and the weft density (picks/cm) factors were found as significant factors in some thermal comfort and moisture management, water vapour, and air permeability properties of drapery samples. Air permeability specific surface ; Polyester ; Materials science ; Composite material ; Moisture ; Permeability (electromagnetism) ; Yarn ; Water content ; Thermal ; Engineering ; Chemistry ; Geotechnical engineering ; Meteorology Textile materials and evaluations ; Natural Fiber Reinforced Composites ; Dyeing and Modifying Textile Fibers
Authors: Kudzanai Sekerere | Rehema Ndeda | Karanja Kabini
Source: World Journal of Engineering and Technology (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

An Investigation of the Effects of Thermal Interference between Adjacent Nitinol Spring Actuators in a Tactile Display Over the years, there has been increased research interest in the application of Nitinol as an actuator, due to its shape memory behaviour, simplicity, high power-to-weight ratio, compactness, and extreme high fatigue resistance to cyclic motion, and noiseless operation. Nitinol has found application in tactile displays which reproduce tactile parameters such as texture and shape, depending on the application. This paper presents the effects of thermal interference between adjacent Nitinol spring actuators in a tactile display. The tactile display is made of a 3 by 3 pin array whose spatial resolution was varied from 4 mm to 6 mm in steps of 1 mm while a current of 1.5 A was used to actuate 8 of the springs, and the centre spring was left unactivated to observe the thermal effects on it due to the heat gradient formed. A Finite Element (FE) model was developed using COMSOL Multiphysics and the results were further verified through experimentation. In both cases, there was visible thermal interference between actuators. The increase in spatial resolution saw a decrease in thermal interference by 12.7%. Using a fan to introduce forced convection, reduced the thermal interference in the simulation by 20% and during experimentation by 11%. The results of this research indicate a spatial resolution of 6 mm reduced the thermal inference to a negligible rate. However, thermal interference could not be eliminated with these two methods. Actuator ; Interference (communication) ; Multiphysics ; Materials science ; Thermal ; Spring (device) ; Finite element method ; Texture (cosmology) ; Acoustics ; Mechanical engineering ; Computer science ; Structural engineering ; Electrical engineering ; Engineering ; Artificial intelligence ; Physics ; Channel (broadcasting) Shape Memory Alloy Transformations ; Advanced Sensor and Energy Harvesting Materials ; Tactile and Sensory Interactions