jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Barbora Šalovská | Wenxue Li | Yi Di | Yansheng Liu
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2020-11-21)
Field: Chemistry — Spectroscopy

BoxCarmax: a high-selectivity data-independent acquisition mass spectrometry method for the analysis of protein turnover and complex samples ABSTRACT The data-independent acquisition (DIA) performed in the latest high-resolution, high-speed mass spectrometers offers a powerful analytical tool for biological investigations. The DIA mass spectrometry (MS) combined with the isotopic labeling approach holds a particular promise for increasing the multiplexity of DIA-MS analysis, which could assist the relative protein quantification and the proteome-wide turnover profiling. However, the wide isolation windows employed in conventional DIA methods lead to a limited efficiency in identifying and quantifying isotope-labelled peptide pairs. Here, we optimized a high-selectivity DIA-MS named BoxCarmax that supports the analysis of complex samples, such as those generated from Stable isotope labeling by amino acids in cell culture (SILAC) and pulse SILAC (pSILAC) experiments. BoxCarmax enables multiplexed acquisition at both MS1- and MS2-levels, through the integration of BoxCar and MSX features, as well as a gas-phase separation strategy. We found BoxCarmax modestly increased the identification rate for label-free and labeled samples but significantly improved the quantitative accuracy in SILAC and pSILAC samples. We further applied BoxCarmax in studying the protein degradation regulation during serum starvation stress in cultured cells, revealing valuable biological insights. Our study offered an alternative and accurate approach for the MS analysis of protein turnover and complex samples. Stable isotope labeling by amino acids in cell culture ; Chemistry ; Mass spectrometry ; Proteome ; Quantitative proteomics ; Protein turnover ; Label-free quantification ; Tandem mass tag ; Chromatography ; Proteomics ; Isotopic labeling ; Isotope ; Computational biology ; Analytical Chemistry (journal) ; Biochemistry ; Protein biosynthesis ; Biology Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Kim Seng Chia | Hong Fan
Source: Engineering Journal (article, 2020-11-30)
Field: Chemistry — Analytical Chemistry

Investigation of Parameters That Affect the Acquired Near Infrared Diffuse Reflected Signals in Non-Destructive Soluble Solids Content Prediction Near infrared spectroscopy is a susceptible technique which can be affected by various factors including the surface of samples. According to the Lambertian reflection, the uneven and matte surface of fruits will provide Lambertian light or diffuse reflectance where the light enters the sample tissues and that uniformly reflects out in all orientations. Bunch of researches were carried out using near infrared diffuse reflection mode in non-destructive soluble solids content (SSC) prediction whereas fewer of them studying about the geometrical effects of uneven surface of samples. Thus, this study aims to investigate the parameters that affect the near infrared diffuse reflection signals in non-destructive SSC prediction using intact pineapples. The relationship among the reflectance intensity, measurement positions, and the SSC value was studied. Next, three independent artificial neural networks were separately trained to investigate the geometrical effects on three different measurement positions. Results show that the concave surface of top and bottom parts of pineapples would affect the reflectance of light and consequently deteriorate the predictive model performance. The predictive model of middle part of pineapples achieved the best performance, i.e. root mean square error of prediction (RMSEP) and correlation coefficient of prediction (Rp) of 1.2104 °Brix and 0.7301 respectively. Diffuse reflection ; Diffuse reflectance infrared fourier transform ; Optics ; Reflection (computer programming) ; Near-infrared spectroscopy ; Infrared ; Intensity (physics) ; Materials science ; Correlation coefficient ; Reflectivity ; Root mean square ; Biological system ; Analytical Chemistry (journal) ; Mathematics ; Chemistry ; Statistics ; Physics ; Computer science ; Chromatography Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Leaf Properties and Growth Measurement
Authors: Shenghong Wu | Yueqian Huang | Xiaoying Chen | Xin Zhou | Wei-Min Zhang | Xiaoxia Gao
Source: Research Square (preprint, 2020-12-31)
Field: Chemistry — Organic Chemistry

Distinction Between Natural and Artificial Agarwood Based on Electronic Nose Data Agarwood ; Natural (archaeology) ; Electronic nose ; Artificial intelligence ; Computer science ; Geology ; Paleontology ; Medicine Wood and Agarwood Research ; Plant Pathogens and Fungal Diseases ; Forest Ecology and Biodiversity Studies
Authors: Luca Liviu Rus
Source: FARMACIA (article, 2020-08-01)
Field: Chemistry — Physical and Theoretical Chemistry

QUANTITATIVE CHARACTERIZATION OF SUSTAINED RELEASE TABLETS WITH DICLOFENAC SODIUM BY MEANS OF NEAR-INFRARED SPECTROSCOPY AND CHEMOMETRY A NIR-chemometric method for direct quantitative determination of diclofenac sodium and two major excipients (matrixforming excipient and diluent) in sustained release, inert matrix type tablets was developed. The 26 tablet batches were prepared according to an experimental design. The NIR spectra of samples were recorded in the transmittance mode and the spectral ranges were selected using Principal Component Analysis (PCA), scores plot and loadings plot. Multiple preprocessing methods were tested and 6 multivariate models for quantitative determination were developed based on partial least squares (PLS) methodology for each substance. The models with the best prediction capability were fully validated in accordance with the current guidelines and regulations. Validation results showed that the methods have good precision, trueness and accuracy. The tolerance limits were 10% for diclofenac sodium assay and 5% for Kollidon SR and lactose DC (direct compressible) , respectively. Diclofenac Sodium ; Characterization (materials science) ; Infrared spectroscopy ; Diclofenac ; Spectroscopy ; Chemistry ; Near-infrared spectroscopy ; Materials science ; Chromatography ; Nanotechnology ; Organic chemistry ; Biochemistry ; Optics ; Physics thermodynamics and calorimetric analyses ; Various Chemistry Research Topics ; Advanced Chemical Sensor Technologies
Authors: F. Collman | J. Buchanan | K. D. Micheva | K. D. Phend | R. J. Weinberg | S. J. Smith
Source: UNC Libraries (article, 2020-11-09)
Field: Materials Science — Surfaces, Coatings and Films

Mapping Synapses by Conjugate Light-Electron Array Tomography Synapses of the mammalian CNS are diverse in size, structure, molecular composition, and function. Synapses in their myriad variations are fundamental to neural circuit development, homeostasis, plasticity, and memory storage. Unfortunately, quantitative analysis and mapping of the brain's heterogeneous synapse populations has been limited by the lack of adequate single-synapse measurement methods. Electron microscopy (EM) is the definitive means to recognize and measure individual synaptic contacts, but EM has only limited abilities to measure the molecular composition of synapses. This report describes conjugate array tomography (AT), a volumetric imaging method that integrates immunofluorescence and EM imaging modalities in voxel-conjugate fashion. We illustrate the use of conjugate AT to advance the proteometric measurement of EM-validated single-synapse analysis in a study of mouse cortex. Conjugate ; Tomography ; Electron tomography ; Physics ; Optics ; Mathematics ; Mathematical analysis ; Electron microscope Electron and X-Ray Spectroscopy Techniques ; Advanced Electron Microscopy Techniques and Applications
Authors: Jie Luo | Yongming Zhang | Qixing Zhang
Source:  (preprint, 2020-11-05)
Field: Materials Science — Materials Chemistry

Effects of black carbon morphology on the brown carbonabsorption estimation: from numerical aspects Abstract. In this work, we developed a numerical method to investigate the effects of black carbon morphology on the estimation of brown carbon (BrC) absorption using the Absorption Ångström exponent (AAE) method. Pseudo measurements of the total absorption were generated based on several morphologically mixed black carbon (BC) models, then the BrC absorption was inferred based on different AAE methods. By comparing the estimated BrC absorption with True BrC absorption, we found that both AAE = 1 and Mie AAE methods do not provide accurate estimation for the BrC absorption, and the estimated BrC absorption can deviate several times from True BrC absorption. The newly proposed Wavelength Dependent AAE (WDA) method does not necessarily improve the estimations, sometimes it may even provide worse estimations than the AAE = 1 and Mie AAE methods. Fixing the fractal dimension to be 1.8, the deviation between the estimated BrC mass absorption cross-section (MAC) and True BrC MAC can reach approximately 9 m2/g, which is far more than brown carbon MAC itself. Therefore, the estimation of BrC absorption based on the AAE method should carefully consider the morphological effects of BC. Our findings highlight the BC morphological effects on the BrC absorption estimation. Absorption (acoustics) ; Carbon black ; Angstrom ; Carbon fibers ; Absorption cross section ; Materials science ; Chemistry ; Mathematics ; Physics ; Optics ; Algorithm ; Cross section (physics) ; Crystallography ; Composite material ; Composite number Carbon Nanotubes in Composites ; Phase Equilibria and Thermodynamics ; Electrochemical Analysis and Applications
Authors: Matthew Sinnott | Sony Malhotra | M. S. Madhusudhan | Konstantinos Thalassinos | Maya Topf
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2020-03-26)
Field: Chemistry — Spectroscopy

Combining Information from Crosslinks and Monolinks in the Modelling of Protein Structures SUMMARY Monolinks are produced in a Chemical Crosslinking Mass Spectrometry experiment and are more abundant than crosslinks. They convey residue exposure information, but so far have not been used in the modelling of protein structures. Here we present the Monolink Depth Score (MoDS), for assessing structural models based on the depth of monolinked residues, corresponding to their distance to the nearest bulk water. Using simulated and reprocessed experimental data from the Proteomic Identification Database, we compare the performance of MoDS to MNXL - our previously-developed score for assessing models based on crosslinking data. Our results show that MoDS can be used to effectively score model structures based on monolinks, and that combining it with MNXL leads to overall higher scoring performance. The work strongly supports the use of monolink data in the context of integrative structure determination. We also present XLM-Tools, a programme to assist in this effort, available at: https://github.com/Topf-Lab/XLM-Tools . Computer science ; Context (archaeology) ; Identification (biology) ; Data mining ; Biology Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Advanced Proteomics Techniques and Applications
Authors: Song Liu | Wei Ya-ping | Shiqiang Chen | Qin Liu
Source: Advances in Materials Science and Engineering (article, 2020-01-01)
Field: Materials Science — Polymers and Plastics

Development and Application of an Ultrahigh‐Temperature Steam Generator A device which could produce high‐temperature steam quickly was designed. The overall structure of the heating device and the heating pipe of key components were introduced mainly, and the working process of the heating device was analyzed and discussed. This high‐temperature steam device with high heating efficiency, produces steam fast and could realize precise temperature control. This device could expand application research of polymer materials and composite materials and provide key guide parameters in the process of technical research. Materials science ; Boiler (water heating) ; Process (computing) ; Nuclear engineering ; Generator (circuit theory) ; Process engineering ; Key (lock) ; Mechanical engineering ; Computer science ; Thermodynamics ; Waste management ; Power (physics) ; Engineering Synthesis and properties of polymers ; Polymer composites and self-healing ; Industrial Technology and Control Systems
Authors: Arnold Steckel | Adina Borbély | Katalin Uray | Gitta Schlosser
Source: Journal of the American Society for Mass Spectrometry (article, 2020-06-19)
Field: Chemistry — Spectroscopy

Quantification of the Effect of Citrulline and Homocitrulline Residues on the Collision-Induced Fragmentation of Peptides Posttranslational modifications of proteins like citrullination and carbamylation are associated with several diseases. Detailed analytical characterization of citrullinated and carbamylated proteins or peptides could be difficult due to the low concentration of the analytes in complex biological samples. High structural similarity and chemical behavior of citrullinated and carbamylated residues also pose a challenge. We previously reported the "citrulline effect" phenomenon that is manifested in the generation of intense y type ions originating from Cit-Zzz amide bond scissions in collision-induced dissociation tandem mass spectra of citrullinated tryptic peptides. In this study, we created a rigorous tryptic-like model system of both citrulline and homocitrulline-containing peptides that included appropriate and well-defined controls and fragment analogues to quantify the citrulline effect and investigate whether there is an effect for homocitrulline residues as well. Our results show that citrulline residues significantly increased fragmentation at their C-terminus relatively independent of the identity of the following amino acid. In comparison, homocitrulline residues displayed inconclusive results at the same energies. However, the strength of effects was dependent on collision energy and the position of citrulline and homocitrulline in the sequences. As newer software algorithms tend to observe structure-intensity relationships during annotation, this finding increases reliable identification of modified proteins/peptides. Chemistry ; Citrulline ; Fragmentation (computing) ; Citrullination ; Tandem mass spectrometry ; Amino acid ; Peptide ; Biochemistry ; Mass spectrometry ; Arginine ; Chromatography Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: E. S. Tsobkallo | O. A. Moskalyuk | V. E. Yudin | А. Н. Алешин
Source: Physics of Complex Systems (article, 2020-01-01)
Field: Materials Science — Materials Chemistry

Influence of particle aspect ratio and ability to aggregate on electrical conductivity of fiber-forming polymer composites Fiber-forming polymer composites filled with carbon nanoparticles of three types (carbon black is a spherical filler; carbon nanofibers and carbon nanotubes are anisotropic nanoparticles) were produced by melt technology. Electrical conductivity of the fiber-forming polymer composites was measured; a function of the filler concentration and the percolation thresholds were determined. It was found that an increase in the aspect ratio of carbon nanoparticles leads to a decrease in the percolation threshold. The correlation between the axial ratio, stiffness, filler concentration and electrical conductivity of the percolation cluster in fiber-forming polymer composites was analysed. Materials science ; Composite material ; Percolation threshold ; Percolation (cognitive psychology) ; Carbon nanotube ; Aspect ratio (aeronautics) ; Carbon black ; Electrical resistivity and conductivity ; Fiber ; Particle (ecology) ; Polymer ; Carbon nanofiber ; Anisotropy ; Nanoparticle ; Conductivity ; Nanocomposite ; Filler (materials) ; Nanotechnology ; Natural rubber Carbon Nanotubes in Composites ; Nanotechnology research and applications ; Material Properties and Applications
Authors: Dauda Duncan | Mmoloki Mangwala | Bokani Mtengi | Adamu Murtala Zungeru | Bakary Diarra | Joseph Chuma
Source: International Journal of Engineering Research and Technology (article, 2020-09-30)
Field: Materials Science — Materials Chemistry

Hybridization of Photovoltaic and Thermoelectric Energy Harvesting Systems at Seismic Nodes Seismic data is one of the most important data for analysis and interpretation of subsurface, but remote seismic node fails frequently. This is one of the main constraints that limits seismic network to acquire continuous seismic data and near real-time prediction of seismicity of an area. There are several ambient energy sources at the remote seismic nodes. Optimization of their energy transducers and DC-DC converters is inevitable. In this study, solar and thermal sources are utilized with maximum power point tracking (MPPT) algorithm. The algorithm is based on the Neural Network model to supply the duty cycle across the converter optimally. Historical data were generated from Perturb and Observe algorithm in PSIM for the Neural Network Model to train the data and predict the duty cycles for both within and outside the data. The proposed system delivered an over 75% conversion rate of the Photovoltaic module's power. The system was modeled in Simulink under the ideal conditions of its components. It could face few constraints during prototype implementation due to the unusual characteristics of the thermoelectric elements. However, certain additional electrical energy was achieved for a low duty power load, such as a remote seismic node. The significant contributions are to identify operating constraints and design optimal hybrid energy harvesting systems at a remote seismic node. Photovoltaic system ; Energy harvesting ; Thermoelectric effect ; Energy (signal processing) ; Electrical engineering ; Engineering ; Physics Advanced Thermoelectric Materials and Devices ; Innovative Energy Harvesting Technologies ; Mechanical and Optical Resonators
Authors: Maher Assaad
Source: International Journal on Smart Sensing and Intelligent Systems (article, 2020-01-01)
Field: Chemistry — Analytical Chemistry

Non-destructive, non-invasive, in-line real-time phase-based reflectance for quality monitoring of fruit Abstract Food quality monitoring in the production process is essential. The control of food quality and freshness is of growing interest for both consumer and food industry. Near infrared (NIR) spectroscopy is popular as it does not need any sample preparation. However, NIR spectroscopy is costly and needs reliable calibration. A non-contact, non-destructive optical process is proposed in this work to monitor the quality of the food. It is shown that the reflected phase information can be used to detect the quality of the fruits. The color and the spectral reflectance change with storage. The changes in the spectral feature due to ripening or decay of apples are used to non-destructively monitor the quality of the fruit. A closed relationship between the reflected phase information and degradation is obtained. The developed model is simple, low cost, and does not need extensive calibration as compared to conventional technologies currently used like NIR besides being robust to skin color or appearances of the fruit. The phase-based reflectance spectroscopy could revolutionize the on/inline quality monitoring of the fruits. Reflectivity ; Near-infrared spectroscopy ; Quality (philosophy) ; Remote sensing ; Calibration ; Process engineering ; Materials science ; Environmental science ; Phase (matter) ; Process (computing) ; Sample (material) ; Computer science ; Optics ; Mathematics ; Engineering ; Chemistry ; Geography ; Statistics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Water Quality Monitoring and Analysis
Authors: Kai Jiang | Wei Si | Chang Chen | Chenglong Bao
Source: arXiv (Cornell University) (preprint, 2020-02-23)
Field: Materials Science — Materials Chemistry

Efficient numerical methods for computing the stationary states of phase field crystal models Finding the stationary states of a free energy functional is an important problem in phase field crystal (PFC) models. Many efforts have been devoted for designing numerical schemes with energy dissipation and mass conservation properties. However, most existing approaches are time-consuming due to the requirement of small effective step sizes. In this paper, we discretize the energy functional and propose efficient numerical algorithms for solving the constrained non-convex minimization problem. A class of gradient based approaches, which is the so-called adaptive accelerated Bregman proximal gradient (AA-BPG) methods, is proposed and the convergence property is established without the global Lipschitz constant requirements. A practical Newton method is also designed to further accelerate the local convergence with convergence guarantee. One key feature of our algorithms is that the energy dissipation and mass conservation properties hold during the iteration process. Moreover, we develop a hybrid acceleration framework to accelerate the AA-BPG methods and most of existing approaches through coupling with the practical Newton method. Extensive numerical experiments, including two three dimensional periodic crystals in Landau-Brazovskii (LB) model and a two dimensional quasicrystal in Lifshitz-Petrich (LP) model, demonstrate that our approaches have adaptive step sizes which lead to a significant acceleration over many existing methods when computing complex structures. Discretization ; Convergence (economics) ; Acceleration ; Mathematical optimization ; Lipschitz continuity ; Computer science ; Dissipation ; Applied mathematics ; Coupling (piping) ; Field (mathematics) ; Kuramoto model ; Mathematics ; Topology (electrical circuits) ; Synchronization (alternating current) ; Physics ; Mathematical analysis ; Classical mechanics Solidification and crystal growth phenomena ; Advanced Mathematical Modeling in Engineering ; Aluminum Alloy Microstructure Properties
Authors: J. Boryca | C. Kolmasiak | T. Wyleciał | D. Urbaniak
Source: Hrčak Portal of scientific journals of Croatia (University Computing Centre) (article, 2020-04-01)
Field: Materials Science — General Materials Science

Effect of furnace efficiency on scale adhesion in the steel charge heating process The paper presents the results of research on the influence of the efficiency of a metallurgical heating furnace on the adhesion of scale formed during the heating process of the steel charge. The methodology for measuring the adhesion of scale to the steel substrate as well as the measurement stand by means of which the research plan was carried out were presented. In addition, the method for determining the heating curves for selected furnace performance and measurement results are presented. The calculation results demonstrating the effect of efficiency on scale adhesion are summarized. Materials science ; Metallurgy ; Process (computing) ; Adhesion ; Scale (ratio) ; Charge (physics) ; Process engineering ; Composite material ; Engineering ; Computer science Material Properties and Applications ; Metal Alloys Wear and Properties ; Mechanical and Thermal Properties Analysis