jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Adilakshmi Dwarasala | Mehdi Rahimi | John L. Markley | Woonghee Lee
Source: Membranes (article, 2022-08-26)
Field: Chemistry — Spectroscopy

ssPINE: Probabilistic Algorithm for Automated Chemical Shift Assignment of Solid-State NMR Data from Complex Protein Systems The heightened dipolar interactions in solids render solid-state NMR (ssNMR) spectra more difficult to interpret than solution NMR spectra. On the other hand, ssNMR does not suffer from severe molecular weight limitations like solution NMR. In recent years, ssNMR has undergone rapid technological developments that have enabled structure–function studies of increasingly larger biomolecules, including membrane proteins. Current methodology includes stable isotope labeling schemes, non-uniform sampling with spectral reconstruction, faster magic angle spinning, and innovative pulse sequences that capture different types of interactions among spins. However, computational tools for the analysis of complex ssNMR data from membrane proteins and other challenging protein systems have lagged behind those for solution NMR. Before a structure can be determined, thousands of signals from individual types of multidimensional ssNMR spectra of samples, which may have differing isotopic composition, must be recognized, correlated, categorized, and eventually assigned to atoms in the chemical structure. To address these tedious steps, we have developed an automated algorithm for ssNMR spectra called “ssPINE”. The ssPINE software accepts the sequence of the protein plus peak lists from a variety of ssNMR experiments as inputs and offers automated backbone and side-chain assignments. The alpha version of ssPINE, which we describe here, is freely available through a web submission form. Probabilistic logic ; Chemical shift ; Computer science ; Algorithm ; Solid-state ; Chemistry ; Artificial intelligence ; Physical chemistry Advanced NMR Techniques and Applications ; NMR spectroscopy and applications ; Advanced MRI Techniques and Applications
Authors: Merzouk Haouchine | Coralie Biache | Catherine Lorgeoux | Pierre Faure | Marc Offroy
Source: ACS Omega (article, 2022-06-29)
Field: Chemistry — Analytical Chemistry

Handle Matrix Rank Deficiency, Noise, and Interferences in 3D Emission–Excitation Matrices: Effective Truncated Singular-Value Decomposition in Chemometrics Applied to the Analysis of Polycyclic Aromatic Compounds The characterization of organic compounds in polluted matrices by eco-friendly three-dimensional (3D) fluorescence spectroscopy coupled with chemometric algorithms constitutes a powerful alternative to the separation techniques conventionally used. However, the systematic presence of Rayleigh and Raman scattering signals in the excitation-emission matrices (EEMs) complicates the spectral decomposition via PARAllel FACtor analysis (PARAFAC) due to the nontrilinear structure of these signals. Likewise, the specific problem of selectivity in spectroscopy for unexpected chemical components in a complex sample may render its chemical interpretation difficult at first glance. The relevant chemical information can then be complicated to extract, especially if the raw data is noisy. There are several strategies to overcome these drawbacks, but weaknesses remain. As a consequence, a new alternative method is proposed to handle these interferences, the noise, and the rank deficiencies in the data and applied for the characterization of polycyclic aromatic compound (PAC) mixtures. It is based on effective truncated singular-value decomposition (MT-SVD) that does not require any prior knowledge of the raw data. The algorithm provides a valuable estimation of the global rank to choose on complex samples where selectivity problems are observed. It is a real alternative compared to other existing methods applied to the fluorescence matrix to filter the signal from noise or light scattering effects. The first exploratory results of the proposed algorithm are promising to handle matrix rank deficiencies as well as the effects of noise and light scattering on complex PAC mixtures. Chemometrics ; Singular value decomposition ; Rank (graph theory) ; Matrix (chemical analysis) ; Noise (video) ; Matrix decomposition ; Biological system ; Chemistry ; Computer science ; Algorithm ; Artificial intelligence ; Mathematics ; Physics ; Machine learning Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Water Quality Monitoring and Analysis
Authors: Dyhia Doufene | S. Benharat | S. Bouazabia | Sid Ahmed Bessedik
Source: Engineering Technology & Applied Science Research (article, 2022-06-06)
Field: Materials Science — Materials Chemistry

Hybrid Grey Wolf and Finite Element Method (GWO-FEM) Algorithm for Enhancing High Voltage Insulator String Performance in Wet Pollution Conditions The presence of wet pollution on the upper surface of a string insulator increases the electric field on the insulator surface, especially at the triple junction (pin-cement, cement-porcelain) as well as at the surrounding air of the insulator. The rise of the electric field leads to the ionization of the air surrounding the insulator. This phenomenon, called corona discharge, is accompanied by several consequences that are harmful to the electricity transmission network, such as electromagnetic interferences, energy losses, visible light, audible noise, and the destruction of materials by erosion. If favorable conditions are gathered, it may even cause the flashover of the insulator. Designing an optimal insulator shape that reduces this electric field value at the triple junction will be an important achievement in enhancing the performance of electrical grids. The objective of this paper is to evolve a hybrid algorithm based on the GWO-FEM for optimizing the shape and the electrical performance of a string insulator. To achieve this purpose, this work is structured in four parts. First, modeling of the insulator string geometry is conducted in Comsol-multiphysics, then FEM computation of the electric field on the polluted surface of the string insulator is completed, and the maximum electric field value at the triple junction is saved as the fitness function that will be sent to the GWO algorithm to be optimized (minimized). The third part of the work is devoted to the coding of the constrained (electrical and geometrical constraints) GWO algorithm in a Matlab interface, and finally, coupling the GWO code with the FEM code. This study is achieved in wet polluted conditions. The results are given in both 2D and 3D representations. From the obtained results we can confirm that the developed GWO-FEM hybrid algorithm for optimizing insulator strings is a very promising tool for designing and enhancing the shape and the electrical performance of insulators. Insulator (electricity) ; Finite element method ; Electric field ; Multiphysics ; Voltage ; Airfoil ; Computer science ; Materials science ; Electrical engineering ; Acoustics ; Electronic engineering ; Engineering ; Structural engineering ; Physics High voltage insulation and dielectric phenomena ; Engineering and Technology Innovations ; Plasma Diagnostics and Applications
Authors: Musthafa Haris Munandar | Saimarlina Harahap | Feri Irawan
Source: Bulletin of Computer Science and Electrical Engineering (article, 2022-06-30)
Field: Chemistry — Inorganic Chemistry

Image Processing Implementation to Classify Coconut Quality Based on Its Color At this time the processing of coconut into coconut flour is widely carried out by factories, especially in areas that have a large population of coconuts. Hal ini disebabkan karena keuntungan yang didapat dari hasil pengolahan kelapa tersebut bisa mendapatkan keuntungan yang besar. This is because the profits obtained from the results of processing coconut can get large profits. The problem that has occurred so far is that there are many people who want to process coconuts, but are not accompanied by sufficient knowledge and knowledge of the quality of coconuts that the factory wants, so it is undeniable that there are also many coconuts that have been processed into coconut flour but are not sold in the market. The analysis method used in this study used an image processing method based on digital images with a GUI (Graphical User Interface) interface media that utilizes matlab software. Image processing consists of several processes, the first of which is the operation of changing the color to grayscale. The second process is a grayscale to binary color change operation using the threshold method. The third process is the morphological process of filling holes to remove noise from the threshold image results. The results of the study using the Image Management method are expected to provide knowledge and knowledge to the public about the quality of coconuts expected by the factory, especially to identify the differences between rotten coconuts and rotten coconuts. Grayscale ; Factory (object-oriented programming) ; Image processing ; Computer science ; Process (computing) ; Population ; Artificial intelligence ; Digital image processing ; Graphical user interface ; Computer vision ; Image (mathematics) Coconut Research and Applications ; Computer Science and Engineering ; Agricultural and Environmental Management
Authors: Ralf Gabriels | Arthur Declercq | Robbin Bouwmeester | Sven Degroeve | Lennart Martens
Source: Journal of Proteome Research (article, 2022-12-12)
Field: Chemistry — Spectroscopy

psm_utils: A High-Level Python API for Parsing and Handling Peptide-Spectrum Matches and Proteomics Search Results A plethora of proteomics search engine output file formats are in circulation. This lack of standardized output files greatly complicates generic downstream processing of peptide-spectrum matches (PSMs) and PSM files. While standards exist to solve this problem, these are far from universally supported by search engines. Moreover, software libraries are available to read a selection of PSM file formats, but a package to parse PSM files into a unified data structure has been missing. Here, we present psm_utils, a Python package to read and write various PSM file formats and to handle peptidoforms, PSMs, and PSM lists in a unified and user-friendly Python-, command line-, and web-interface. psm_utils was developed with pragmatism and maintainability in mind, adhering to community standards and relying on existing packages where possible. The Python API and command line interface greatly facilitate handling various PSM file formats. Moreover, a user-friendly web application was built using psm_utils that allows anyone to interconvert PSM files and retrieve basic PSM statistics. psm_utils is freely available under the permissive Apache2 license at https://github.com/compomics/psm_utils. Python (programming language) ; Computer science ; Parsing ; File format ; Operating system ; Software ; Programming language ; Mascot ; Database ; World Wide Web Advanced Proteomics Techniques and Applications ; Machine Learning in Bioinformatics ; Mass Spectrometry Techniques and Applications
Authors: A. V. Shkirin | Maxim E. Astashev | Dmitry N. Ignatenko | Nikolai V. Suyazov | Maria V. Vedunova | Sergey V. Gudkov
Source: Applied Sciences (article, 2022-12-07)
Field: Chemistry — Analytical Chemistry

Laser Scatterometric Device for Inline Measurement of Fat Percentage and the Concentration Level of Large-Scale Impurities in Milk A compact laser scatterometric device for determining the fat percentage of milk filling a cylindrical tube has been designed. The device operates by detecting the angular distribution of the scattered radiation of a semiconductor laser using an axial array of photodiodes. We have experimentally found that the light-scattering indicatrix in cow milk has a monotonous dependence on milk fat content. The intensity at side- or forward-scattering angles normalized to the backscattering intensity proves to be a reliable, informative parameter. A polynomial approximation for the calibration curve of fat percentage versus normalized scattering intensity is constructed to enable fat content measurements in the fairly wide range of ~0.01–10%. Furthermore, the intensity at forward scattering angles responds to the presence of large-scale particles in milk. The device was tested in a laminar flow regime at milk flow rates up to 100 mL/s. Scattering ; Intensity (physics) ; Laser ; Materials science ; Optics ; Photodiode ; Laminar flow ; Physics ; Mechanics Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Flow Measurement and Analysis
Authors: Jack Freestone | Temana Short | William Stafford Noble | Uri Keich
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2022-02-01)
Field: Chemistry — Spectroscopy

Group-walk, a rigorous approach to group-wise false discovery rate analysis by target-decoy competition Abstract Target-decoy competition (TDC) is a commonly used method for false discovery rate (FDR) control in the analysis of tandem mass spectrometry data. This type of competitionbased FDR control has recently gained significant popularity in other fields after Barber and Candès laid its theoretical foundation in a more general setting that included the feature selection problem. In both cases, the competition is based on a head-to-head comparison between an (observed) target score and a corresponding decoy (knockoff) score. However, the effectiveness of TDC depends on whether the data is homogeneous, which is often not the case: in many settings, the data consists of groups with different score profiles or different proportions of true nulls. In such cases, applying TDC while ignoring the group structure often yields imbalanced lists of discoveries, where some groups might include relatively many false discoveries and other groups include relatively very few. On the other hand, as we show, the alternative approach of applying TDC separately to each group does not rigorously control the FDR. We developed Group-walk , a procedure that controls the FDR in the target-decoy / knockoff setting while taking into account a given group structure. Group-walk is derived from the recently developed AdaPT — a general framework for controlling the FDR with sideinformation. We show using simulated and real datasets that when the data naturally divides into groups with different characteristics Group-walk can deliver consistent power gains that in some cases are substantial. These groupings include the precursor charge state (4% more discovered peptides at 1% FDR threshold), the peptide length (3.6% increase) and the mass difference due to modifications (26% increase). Group-walk is available at https://cran.r-project.org/web/packages/groupwalk/index.html Decoy ; False discovery rate ; Group (periodic table) ; Computer science ; Competition (biology) ; Biology ; Medicine ; Physics ; Internal medicine Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Analytical Chemistry and Chromatography
Authors: Jianwen Zeng | Yu Wang | Zheng Xiao-Juan | Conghua Zhou
Source: Journal of Physics D Applied Physics (article, 2022-08-12)
Field: Materials Science — Materials Chemistry

Dependence of the conductivity of two-dimensional site percolation network on the length-ratio of conducting paths to all bonds: the viewpoint of effective path theory Abstract Previous studies have found that the network conductivity of 2-dimensional disordered nanowire networks (DNNs) scaled linearly with the length-ratio of conducting-paths to all nanowires. To show the universality of this rule, the conducting behavior of a 2-dimensional site percolation problem is studied in this article with the assistance of a Monte Carlo based numerical simulation. It is observed that, as the existence probability of site increases in the 2-dimensional site percolated network, more conducting-paths are formed, and the network becomes more conductive. After correlating the site-percolated lattice to DNNs, the normalized network conductivity is observed to scale linearly with the length-ratio of conducting-paths to all bonds, which could be well described by the linear formula using a slope of 2 and an incept of 0.5. As a result, the length-ratio of conducting-paths could again serve as a basic topological parameter in describing the conducting behavior of 2-dimensional site percolation networks. Such universality enables the definition of an ‘effective path theory’, in which the normalized network conductivity scales linearly with the length-ratio of conducting-paths to all bonds. Universality (dynamical systems) ; Conductivity ; Percolation threshold ; Statistical physics ; Percolation critical exponents ; Monte Carlo method ; Percolation (cognitive psychology) ; Percolation theory ; Nanowire ; Electrical conductor ; Lattice (music) ; Condensed matter physics ; Path (computing) ; Materials science ; Physics ; Electrical resistivity and conductivity ; Mathematics ; Computer science ; Nanotechnology ; Quantum mechanics ; Statistics Graphene research and applications ; Carbon Nanotubes in Composites ; Nanopore and Nanochannel Transport Studies
Authors: Raghav Mattay | Karapet Davtyan | Jeffrey D. Rudie | Govind S. Mattay | Dina Jacobs | Matthew K. Schindler | Laurie A. Loevner | Mitchell D. Schnall | Michel Bilello | Alexander C. Mamourian | Tessa S. Cook
Source: Journal of Neuroimaging (article, 2022-03-16)
Field: Materials Science — Materials Chemistry

Economic impact of selective use of contrast for routine follow‐up MRI of patients with multiple sclerosis Implementation of a new protocol to limit contrast in MS follow-up MRIs led to a minimal decrease in revenue when controlled for scanner time utilized and is outweighed by other benefits, including substantial decreased gadolinium administration, increased patient comfort, and increased availability of scanner time, which depending on type of studies performed could result in additional financial benefit. Medicine ; Contrast (vision) ; Multiple sclerosis ; Gadolinium ; Protocol (science) ; Magnetic resonance imaging ; Radiology ; Reimbursement ; Neuroimaging ; Nuclear medicine ; Pathology Lanthanide and Transition Metal Complexes ; Multiple Sclerosis Research Studies ; MRI in cancer diagnosis
Authors: Ganning Zeng | Sa Lou | Fengyan Lou | Mingming Du | Hongwei Luo | Ning Ai
Source: Journal of Chemical Technology & Biotechnology (article, 2022-06-08)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Insights into forming behavior and <scp>CO<sub>2</sub></scp> adsorption properties of graphene from <i>Sargassum horneri</i> by Fe(<scp>NO<sub>3</sub></scp>)<sub>3</sub>/<scp>KOH</scp> activation Abstract BACKGROUND Macroalgae biomass as a graphene source shows great potential at large scale in an energy shortage era. To achieve a more moderate and economic graphene synthesis method, porous graphenes were synthesized using Sargassum horneri as precursor, in combination with Fe(NO 3 ) 3 and KOH composite. RESULTS The addition of 10 wt% Fe(NO 3 ) 3 obviously accelerated KOH activation and decreased KOH loading and reaction temperature. Meanwhile, the graphene synthesized by Fe(NO 3 ) 3 /KOH had better regeneration performance than that activated merely by KOH, even under more moderate thermal condition. The porous graphene displayed high specific surface area (~2311 m 2 g −1 ) and exhibited good CO 2 uptake capacity (~4.39 mmol g −1 ) at 30 °C and 1 bar. The CO 2 adsorption rate equations of the graphene were consistent with the intraparticle diffusion model, indicating that CO 2 adsorption was mainly controlled by the pore structure and additionally influenced by the chemical functional groups. CONCLUSION The present work focuses on the high value‐added comprehensive utilization of macroalgae, which not only has important significance for on‐scale preparation of bio‐originated graphene and CO 2 adsorption, but also has positive benefits for macroalgae resource development. © 2022 Society of Chemical Industry (SCI). Graphene ; Adsorption ; Chemical engineering ; Sargassum ; Economic shortage ; Specific surface area ; Diffusion ; Biomass (ecology) ; Chemistry ; Materials science ; Nanotechnology ; Organic chemistry ; Catalysis ; Botany Supercapacitor Materials and Fabrication ; Graphene research and applications ; Layered Double Hydroxides Synthesis and Applications
Authors: Yan Li | Kailong Nie | Qingguo Tang | Guangyan Tian | Jinsheng Liang
Source: Microporous and Mesoporous Materials (article, 2022-10-31)
Field: Chemistry — Analytical Chemistry

In-situ synthesis of duster-like hollow mesoporous copper silicate composites for high-efficiency adsorption of aflatoxin B1 from water Adsorption ; Mesoporous material ; Chemical engineering ; Materials science ; Fourier transform infrared spectroscopy ; Mesoporous silica ; Silicate ; Chemistry ; Catalysis ; Organic chemistry Analytical chemistry methods development ; Adsorption and biosorption for pollutant removal ; Mesoporous Materials and Catalysis
Authors: Li Zhang | Qibo Xia | Cong Zhang | Hong Wu | Guiting Liu | Rong Chen | Shaoyun Guo
Source: Composites Part A Applied Science and Manufacturing (article, 2022-03-26)
Field: Materials Science — Biomaterials

Controlled directional drug release from poly(ε-caprolactone)/polyethylene oxide/metoprolol tartrate composites with multi-layered structures Metoprolol Tartrate ; Materials science ; Oxide ; Diffusion ; Polyethylene oxide ; Layer (electronics) ; Composite material ; Polyethylene ; Caprolactone ; Controlled release ; Epoxy ; Chemical engineering ; Polymer ; Metoprolol ; Copolymer ; Nanotechnology Electrospun Nanofibers in Biomedical Applications ; biodegradable polymer synthesis and properties ; Orthopaedic implants and arthroplasty
Authors: Van Minh Dang | Vinh Dinh Nguyen | Huu Tạp Van | Nguyễn Văn Quảng | Trọng Nghĩa Nguyễn | Long D. Nghiem
Source: Separation Science and Technology (article, 2022-05-06)
Field: Materials Science — Materials Chemistry

Removal of Cr(VI) and Pb(II) from aqueous solution using Mg/Al layered double hydroxides-mordenite composite Mg/Al layered double hydroxides-mordenite nanocomposite (LDH@mordenite) was prepared via the in-situ method to enhance the Cr(VI) and Pb(II) removal efficiency. The results showed that the Cr(VI) and Pb(II) removal efficiency was enhanced by the formation of core-shell structure (mordenite core-LDH shell). The synthesized material with an LDH content of 30% had the highest removal efficiency for both metals at the pH of 5.0. The pseudo-second-order model was the best model for describing the adsorption kinetics of Cr(VI) and Pb(II) on LDH@mordenite. The calculation from the intra-particle diffusion model suggested that the adsorption processes included several steps. Fitting experimental data to the Langmuir, Freundlich, and Temkin models revealed that the Langmuir model was the best model for predicting the isotherms of the adsorption processes. The calculated maximum adsorption capacity at 25 ℃ was 54.80 mg/g for Cr(VI) and 67.91 mg/g for Pb(II). Based on the thermodynamic study, the Cr(VI) and Pb(II) adsorption on LDH@mordenite was endothermic and spontaneous. The adsorption mechanisms were studied using the statistical physics model and the calculated parameters indicated that Cr(VI) and Pb(II) ions could interact via one and two adsorption sites of the adsorbent. Mordenite ; Chemistry ; Adsorption ; Endothermic process ; Freundlich equation ; Langmuir ; Aqueous solution ; Langmuir adsorption model ; Layered double hydroxides ; Inorganic chemistry ; Ion exchange ; Nuclear chemistry ; Zeolite ; Ion ; Physical chemistry ; Organic chemistry ; Catalysis Layered Double Hydroxides Synthesis and Applications ; Nanomaterials for catalytic reactions ; Adsorption and biosorption for pollutant removal