jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Rageia Elfageih | Alexandros Karyolaimos | Grant Kemp | Jan‐Willem De Gier | Gunnar von Heijne | Renuka Kudva
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2020-07-06)
Field: Materials Science — Materials Chemistry

Cotranslational folding of alkaline phosphatase in the periplasm of <i>Escherichia coli</i> Abstract Cotranslational protein folding studies using Force Profile Analysis, a method where the SecM translational arrest peptide is used to detect folding-induced forces acting on the nascent polypeptide, have so far been limited mainly to small domains of cytosolic proteins that fold in close proximity to the translating ribosome. In this study, we investigate the cotranslational folding of the periplasmic, disulfide bond-containing E. coli protein alkaline phosphatase (PhoA) in a wild-type strain background and a strain background devoid of the periplasmic thiol:disulfide interchange protein DsbA. We find that folding-induced forces can be transmitted via the nascent chain from the periplasm to the polypeptide transferase center in the ribosome, a distance of ~160 Å, and that PhoA appears to fold cotranslationally via at least two disulfide-stabilized folding intermediates. Thus, Force Profile Analysis can be used to study cotranslational folding of proteins in an extra-cytosolic compartment, like the periplasm. Periplasmic space ; DsbA ; Protein folding ; Folding (DSP implementation) ; Biochemistry ; Chemistry ; Cytosol ; Ribosome ; Protein disulfide-isomerase ; Biophysics ; Escherichia coli ; Biology ; Disulfide bond ; Enzyme ; RNA Enzyme Structure and Function ; Protein Structure and Dynamics ; RNA and protein synthesis mechanisms
Authors: Dongjian Li | Vasisht Venkatesh
Source: MATEC Web of Conferences (article, 2020-01-01)
Field: Materials Science — Materials Chemistry

RECENT ADVANCES IN TITANIUM TECHNOLOGY IN THE UNITED STATES Substantial progress has continued in the US since the last (13 th ) World Titanium Conference with regards to titanium technology, products, processing, computational modeling tools and applications. Titanium components produced by additive manufacturing have been qualified and achieved production applications in commercial and military aircraft hardware. New high-performance titanium alloys have been developed for higher temperature service and applications requiring more demanding static and dynamic properties. Current production processes for titanium have been optimized, and new processes have been developed to further reduce cost and improve product quality. Titanium suppliers, OEM’s, government labs and academia are working closely together to address fundamental industry-wide issues. Computer modeling is now used extensively in industrial and research facilities to accelerate the pace and success of these developments. Titanium ; Pace ; Original equipment manufacturer ; Manufacturing engineering ; Service (business) ; Computer science ; Materials processing ; Government (linguistics) ; Engineering ; Engineering management ; Process engineering ; Business ; Materials science ; Metallurgy ; Marketing Titanium Alloys Microstructure and Properties ; Additive Manufacturing Materials and Processes ; Advanced materials and composites
Authors: Suhwan Song | Stefan Vuckovic | Eunji Sim | Kieron Burke
Source: arXiv (Cornell University) (preprint, 2020-08-04)
Field: Materials Science — Materials Chemistry

Density sensitivity of empirical functionals Empirical fitting of parameters in approximate density functionals is common. Such fits conflate errors in the self-consistent density with errors in the energy functional, but density-corrected DFT (DC-DFT) separates these two. We illustrate with catastrophic failures of a toy functional applied to $H_2^+$ at varying bond lengths, where the standard fitting procedure misses the exact functional; Grimme's D3 fit to noncovalent interactions, which can be contaminated by large density errors such as in the WATER27 and B30 datasets; and double-hybrids trained on self-consistent densities, which can perform poorly on systems with density-driven errors. In these cases, more accurate results are found at no additional cost, by using Hartree-Fock (HF) densities instead of self-consistent densities. For binding energies of small water clusters, errors are greatly reduced. Range-separated hybrids with 100\% HF at large distances suffer much less from this effect. Density functional theory ; Range (aeronautics) ; Statistical physics ; Energy density ; Energy (signal processing) ; Physics ; Computational physics ; Materials science ; Quantum mechanics ; Theoretical physics Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Advanced NMR Techniques and Applications
Authors: Howida Abdallah Hashim | Mohamed Osman M. A. El-Fakii | A. E. M. Saeed
Source: Computational Chemistry (article, 2020-01-01)
Field: Chemistry — Organic Chemistry

Activity Trends in Desoxy Anthrapyrazoles: The Influence of Molar Volume, Polarizability and Lipophilicity of N&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; C&amp;lt;sub&amp;gt;5&amp;lt;/sub&amp;gt; Side Chains on Their Anticancer Response QSAR methodology was used to assess the effects of lipophilicity (logP), molar volume (MV) and polarizability (pl) of the side chains at N2 and C5 of 20 known desoxy anthrapyrazoles on their in vitro anticancer activity expressed as the negative logarithm of the inhibitory concentration of 50% of L1210 murine leukemia cell line (1/logIC50). The main data set shows poor correlations between biological response and the descriptors with exception of MV of the C5 side chain, where a moderate correlation was discerned ( =0.60, n = 18, two outliers). To extract more information regarding mechanism, the main data set was visually classified to three clusters depending on N2 side chain. Cluster 1 containing six 5-substituted 2-[(2-hydroxyethyl) amino] ethyl anthrapyrazoles; cluster 2 contains ten 5-subsitutes 2-(diethyl amino) ethyl anthrapyrazoles and cluster 3 contains four anthrapyrazoles with miscellaneous substituents at both N2 and C5. For cluster 1, MV and pl of C5 show high correlation with biological response (R2’s = 0.75 and 0.72 respectively) while logP gives a weak correlation (R2 = 0.44). For cluster 2, the correlations of logP and pl of C2side chain are higher (=0.66 and 0.62 respectively) compared with MV (=0.16). Cluster 3 shows very poor correlation with all descriptors (~0.3). This indicates mechanistic distinction between the three clusters. Derived descriptors which represent the difference between the descriptors of N2 and C5 side chains where used to explore the presence of interplay between these descriptors in affecting variability of the biological response. Lipophilicity ; Polarizability ; Chemistry ; Quantitative structure–activity relationship ; Molar refractivity ; Stereochemistry ; Molecule ; Organic chemistry Synthesis and biological activity ; Synthesis and properties of polymers ; Free Radicals and Antioxidants
Authors: Maksym Zhelyeznyakov | Steven L. Brunton | Arka Majumdar
Source: arXiv (Cornell University) (preprint, 2020-08-24)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Deep learning to accelerate Maxwell's equations for inverse design of\n dielectric metasurfaces The inverse design of optical metasurfaces is a rapidly emerging field that\nhas already shown great promise in miniaturizing conventional optics as well as\ndeveloping completely new optical functionalities. Such a design process relies\non many forward simulations of a device's optical response in order to optimize\nits performance. We present a data-driven forward simulation framework for the\ninverse design of metasurfaces that is more accurate than methods based on the\nlocal phase approximation, a factor of $10^4$ times faster and requires $15$\ntimes less memory than mesh based solvers, and is not constrained to spheroidal\nscatterer geometries. We explore the scattered electromagnetic field\ndistribution from wavelength scale cylindrical pillars, obtaining\nlow-dimensional representations of our data via the singular value\ndecomposition. We create a differentiable model fiting the input geometries and\nconfigurations of our metasurface scatterers to the low-dimensional\nrepresentation of the output field. To validate our model, we inverse design\ntwo optical elements: a wavelength multiplexed element that focuses light for\n$\\lambda=633$nm and produces an annular beam at $\\lambda=400$nm and an extended\ndepth of focus lens.\n Inverse ; Lens (geology) ; Differentiable function ; Inverse problem ; Optics ; Dielectric ; Wavelength ; Focus (optics) ; Physics ; Field (mathematics) ; Representation (politics) ; Computer science ; Mathematics ; Geometry ; Mathematical analysis ; Optoelectronics Metamaterials and Metasurfaces Applications ; Radio Wave Propagation Studies ; Millimeter-Wave Propagation and Modeling
Authors: E. Acosta
Source: scholarworks - UTEP (The University of Texas at El Paso) (article, 2020-01-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Development of a MEMS Fabrication Process on Soi to Study High Strain in Transition-metal Dichalcogenides Over the recent years there has been an increasing demand of better performing electronics. However, as the semiconductor industry keeps on improving and scaling the technology to the nanometer regime, the passive power density has overcome the overall power consumption of transistors. The inability to reduce the power alongside the scaling of transistors has led the scientific community in the search for alternatives or different solutions to overcome this power crisis. The use of two-dimensional Transition-Metal Dichalcogenides (TMDCS) and Micro-Electro-Mechanical System (MEMS) actuators, in conjunction, has been proposed as an alternative solution [1]. Recent studies of TMDCS have shown a very promising potential for future use in electronics. One very interesting property in particular of TMDCs is that they are highly sensitive to strain [2, 3]. On the other side, MEMS offer excellent on/off ratios with very steep transitions as it has been demonstrated in [4, 5, 6, 7, 8]. Devices, which exploit the bandgap tunnability of the TMDCs to enhance their conductivity, have not been explored thoroughly. As a result, a MEMS device that takes full advantage of the TMDCS strain properties has been proposed, and shown a potential future for electronic devices [1]. Furthermore, such a device needs a reliable, reproducible, scalable, and ability to offer a promise for future research. In this Thesis, the effort to design, fabricate, and characterize a double anchor beam actuator will be discussed. This work is an important footstep to understand, analyze, and promote the simplification of the fabrication processes involved in a research environment, as well as, the use of Silicon On Insulator (SOI) for this type of application. Fabrication ; Silicon on insulator ; Materials science ; Transition metal ; Microelectromechanical systems ; Strain (injury) ; Process (computing) ; Nanotechnology ; Metallurgy ; Chemistry ; Computer science ; Silicon Organic and Molecular Conductors Research ; Chalcogenide Semiconductor Thin Films ; Inorganic Fluorides and Related Compounds
Authors: Filip Buric | Jan Zrimec | Aleksej Zelezniak
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2020-04-23)
Field: Chemistry — Spectroscopy

Parallel factor analysis enables quantification and identification of highly-convolved data independent-acquired protein spectra Abstract High-throughput data-independent acquisition (DIA) is the method of choice for quantitative proteomics, combining the best practices of targeted and shotgun proteomics approaches. The resultant DIA spectra are, however, highly convolved and with no direct precursor-fragment correspondence, complicating the analysis of biological samples. Here we present PARADIAS (PARAllel factor analysis of Data Independent Acquired Spectra), a GPU-powered unsupervised multiway factor analysis framework that deconvolves multispectral scans to individual analyte spectra, chromatographic profiles, and sample abundances, using the PARAFAC tensor decomposition method based on variation of informative spectral features. The deconvolved spectra can be annotated with traditional database search engines or used as a high-quality input for de novo sequencing methods. We demonstrate that spectral libraries generated with PARADIAS substantially reduce the false discovery rate underlying the validation of spectral quantification. PARADIAS covers up to 33 times more total ion current than library-based approaches, which typically use less than 5 % of total recorded ions, thus allowing the quantification and identification of signals from unexplored DIA spectra. Analyte ; Pattern recognition (psychology) ; Computer science ; Shotgun proteomics ; Quantitative proteomics ; Identification (biology) ; Multispectral image ; Artificial intelligence ; Chemistry ; Proteomics ; Chromatography Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Mass Spectrometry Techniques and Applications
Authors: Randolph Arroo
Source: DMU Open Research Archive (De Montfort University) (article, 2020-12-09)
Field: Chemistry — Analytical Chemistry

Absorption, Distribution, Metabolism and Excretion (ADME) of Dietary Flavones and Their Glycosides ADME ; Flavones ; Excretion ; Chemistry ; Absorption (acoustics) ; Glycoside ; Metabolism ; Distribution (mathematics) ; Biochemistry ; Pharmacology ; Chromatography ; Medicine ; Organic chemistry ; Mathematics Chromatography in Natural Products ; Morinda citrifolia extract uses
Authors: Yueming Guo | Sergei V. Kalinin | Hui Cai | Kai Xiao | Sergiy Krylyuk | Albert V. Davydov | Andrew R. Lupini
Source: Microscopy and Microanalysis (article, 2020-07-30)
Field: Materials Science — Materials Chemistry

Investigation of Structural Phases in Mo<sub>1-x</sub>W<sub>x</sub>Te<sub>2</sub> in STEM Materials science ; Crystallography ; Chemistry Advanced Thermoelectric Materials and Devices ; 2D Materials and Applications ; Topological Materials and Phenomena
Authors: Yanghune Ha | Riccardo Spezia | Kihyung Song
Source: ChemRxiv (preprint, 2020-08-13)
Field: Chemistry — Spectroscopy

Computer Simulation of Collision Induced Dissociation and Isolobal Analogy: The Case of Biotin and Its Analogues We have studied how collision induced dissociation (CID) products and associated mechanism are modified when a chemical group is modified by isolobal groups, and in particular S, O, NH and CH2. At this end, we have considered protonated biotin (vitamin B7) and corresponding oxybiotin, N-biotin and C-biotin, which have the same structures except for one chemical group (the S in biotin which is substituted with the aforementioned isolobal ones). Collisional simulations with Ar were performed to model CID fragmentations and to have directly access to related mechanisms. Simulations have shown that the CID fragmentation of the four compounds were similar and the resulting fragments involve in a similar way the isolobal groups. Details on the mechanisms as obtained from simulations are reported and discussed. This result shows that it is possible in principle to predict, with a reasonable confidence, mass spectra of unknown molecules based on mass spectrum of the known one when isolobal modifications are done. Dissociation (chemistry) ; Fragmentation (computing) ; Biotin ; Protonation ; Collision-induced dissociation ; Collision ; Chemistry ; Molecule ; Computational chemistry ; Mass spectrometry ; Computer science ; Ion ; Tandem mass spectrometry ; Physical chemistry ; Organic chemistry ; Chromatography ; Biochemistry Mass Spectrometry Techniques and Applications ; Biotin and Related Studies ; Molecular Junctions and Nanostructures
Authors: Sibel Avunduk
Source: Biomedical Journal of Scientific & Technical Research (article, 2020-12-23)
Field: Chemistry — Physical and Theoretical Chemistry

The Pharmaceuticals Using for COVID-19 Patients and in Silico Natural Product Studies about COVID-19 The COVID-19 pandemic without a doubt will be regarded the biggest epidemic which is still going on to impact the whole world in the humanity history. That's why it is imperative to discover new therapeutic agents and vaccines by the scientific world. This review especially includes the studies and reviews about therapy protocols used in the cure of COVID-19, also the papers about in silico researches on phytochemical compounds and the other marketed drugs. The aim of the review to summarize the antiviral drugs experienced in COVID-19 cure during the first peak of the pandemic; compile and inform the in silico studies focused on the plant sourced compounds and repurposed drugs. The review will generate a guiding source to further in vitro and in vivo research in the way of looking for effective compounds to combat COVID-19 pandemic. Coronavirus disease 2019 (COVID-19) ; 2019-20 coronavirus outbreak ; Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ; Vocational education ; Medicine ; Medical education ; Family medicine ; Virology ; Political science ; Pathology ; Infectious disease (medical specialty) ; Outbreak ; Disease thermodynamics and calorimetric analyses ; Computational Drug Discovery Methods ; SARS-CoV-2 and COVID-19 Research
Authors: Daniel V. Samarov | Yufeng Liu | Chris Grulke | Alexander Tropsha | J. S. Marron
Source: UNC Libraries (article, 2020-11-09)
Field: Chemistry — Analytical Chemistry

Local kernel canonical correlation analysis with application to virtual drug screening Drug discovery is the process of identifying compounds which have potentially meaningful biological activity. A major challenge that arises is that the number of compounds to search over can be quite large, sometimes numbering in the millions, making experimental testing intractable. For this reason computational methods are employed to filter out those compounds which do not exhibit strong biological activity. This filtering step, also called virtual screening reduces the search space, allowing for the remaining compounds to be experimentally tested. Canonical correlation ; Kernel (algebra) ; Correlation ; Drug ; Virtual screening ; Computer science ; Mathematics ; Statistics ; Medicine ; Artificial intelligence ; Pharmacology ; Pure mathematics ; Bioinformatics ; Drug discovery ; Biology Spectroscopy and Chemometric Analyses ; Face and Expression Recognition ; Statistical Methods and Inference
Authors: Marc Marino
Source: eScholarship (California Digital Library) (article, 2020-01-01)
Field: Chemistry — Electrochemistry

Detection of small synaptic signals in noisy electrophysiological data by means of artificial neural networks The miniature excitatory post synaptic current (mEPSC) is a fundamental electrophysiological measurement of quantal vesicular release of transmitter at synapses. Typically, for excitatory transmission at central nervous system neurons, due to the small size of the electrical signal relative to the noise, recordings containing mEPSCs are analyzed by eye in conjunction with a basic peak/template finding algorithm. Such methods require expertise and considerable time, and generally require elimination of signals smaller than ~8-10 pA to avoid counting noise (i.e. false positives). Here we describe an entirely automated approach to detect mEPSCs using a machine learning based tool. This method eliminates inter observer bias, and permits accurate detection of spontaneous mEPSCs smaller than 10 pA from brain slice neurons. Using whole cell recordings from the soma of CA1 hippocampal slice neurons this tool can detect more than 95% of mEPSCs identified by a trained human observer. Importantly, this tool identifies few events as mEPSCs in a recording of the same cell when excitatory postsynaptic receptors are blocked, indicating a low false positive rate. Such recordings permit calculation of a true (96.6 ± 0.9%; n=10) and false (1.4 ± 0.1%; n=10) positive detection rate for mEPSCs. Using this new tool mEPSCs can be rapidly and accurately measured in an unbiased manner, and permits analysis of previously undetected mEPSCs. Excitatory postsynaptic potential ; Neuroscience ; Electrophysiology ; Computer science ; Pattern recognition (psychology) ; Biology ; Artificial intelligence ; Inhibitory postsynaptic potential Electrochemical Analysis and Applications ; Neural dynamics and brain function ; Neuroscience and Neural Engineering
Authors: L. P. Panicheva | E. A. Sidorovskaya | N. Yu. Tretyakov | Svetlana S. Volkova | E. A. Turnaeva | A. A. Groman | O. A. Nurieva | G. Yu. Shcherbakov | I. N. Koltsov
Source: Proceedings of universities Applied chemistry and biotechnology (article, 2020-04-02)
Field: Chemistry — Analytical Chemistry

Determination of equivalent alkane carbon number for West Siberian oils as a stage of optimisation in surfactant-polymer compositions for chemical flooding The hydrophobicity of oil and oil products can be characterised in terms of its equivalent alkane carbon number (EACN). This characteristic can be determined on the basis of the correlation between the interfacial tension data and other characteristics for homologous oils and a number of alkanes having subsequent interpretation for oil and oil products. The EACN is a useful metric for selecting an effective surfactant for the emulsification of oil and oil products. The research is aimed at determining the equivalent alkane car-bon number of various crude oil samples obtained in the oil fields of Western Siberia using standard high-performance compositions of imported and domestic industrial sulphonate surfactants. In order to determine the EACN of oil and oil products, the S* characteristic was applied representing the optimal NaCl concentration (optimum salinity) in the aqueous surfactant phase, as well as providing the minimum surface tension and formation of the maximum microemulsion volume during the phase experiment at the interface with the hydro-carbon phase. Direct determination of the interfacial tension at the "oil / surfactant solution" interface was car-ried out with a tensiometer using the spinning drop method at a temperature of 87 ° С . Linear dependencies are identified in accordance to the empirical correlation equations between the EACN, surfactant parameters and phase behaviour parameters of aqueous surfactant solutions and oil or a mixture of hydrocarbons. The K characteristic parameter of the proposed three standard surfactant compositions is determined to be consistent with the literature data for individual surfactants. The composition of industrial surfactants for determining the EACN of oil and oil products is proposed. The equations of linear regression for the logS* ~ EACN dependency with high correlation coefficients (R² = 0.9444-0.9999) are obtained, resulting in the determination of the EACN for kerosene and seven oil samples from Western Siberian oil fields. Promising surfactants can be selected on the basis of this indicator for reducing interfacial tension in the "hydrocarbon / water solution" system, as well as for predicting the most effective composition for obtaining emulsions. Pulmonary surfactant ; Alkane ; Surface tension ; Microemulsion ; Chemistry ; Aqueous two-phase system ; Aqueous solution ; Hydrocarbon ; Phase (matter) ; Enhanced oil recovery ; Carbon chain ; Chromatography ; Chemical engineering ; Organic chemistry ; Thermodynamics Petroleum Processing and Analysis ; Enhanced Oil Recovery Techniques ; Hydrocarbon exploration and reservoir analysis