jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Zhao Zhong | Lu Xue
Source: International Journal of Engineering and Applied Sciences (IJEAS) (article, 2020-03-31)
Field: Materials Science — Materials Chemistry

Development rule of temperature on oil-paper-insulated pin plate discharge under long-term operation Research In order to study the effect of temperature on the partial discharge of the oil-paper-insulated pin plate under long-term operation of the main transformer, we chose a vacuum heat aging 32-day simulation sample and a 28-year actual operation sample. And the step-up pressure method was used to test the local pressure of the needle plate of the two samples at ordinary temperature (30, 50) and high temperature (85 signal point, 105 trip point), and the relevant discharge characteristic quantity was analyzed by the partial discharge inspection instrument record.The results show:There is no significant difference between the heat-aged oil paper sample and the field sample in the early stage of discharge.However, there is a large difference in the development to the middle and late stages under the high temperature, especially the 105 trip point; The maximum discharge and total discharge at ordinary temperature near the breakdown time are both small, which is 2/3 of that at high temperature. The number of discharges gradually increased with the increase of compression time. The actual phase width and density of the actual samples at 105 during the middle and late periods of discharge were higher than those of the simulated aging samples. That is to say, the influence of high temperature on the oil-paper insulation of the main transformer during long-term operation is greater than that at low temperature. The oil-paper insulation level actually collected at the site increases with the extension of the operating time. It is easier to enter a dangerous period than a laboratory simulation sample at high temperatures, and the consequences of partial discharge are more serious. Term (time) ; Materials science ; Environmental science ; Physics High voltage insulation and dielectric phenomena ; Embedded Systems and FPGA Design ; Engineering Applied Research
Authors: Ersin YENİSU
Source: Mehmet Akif Ersoy Üniversitesi Sosyal Bilimler Enstitüsü Dergisi (article, 2020-05-23)
Field: Chemistry — Analytical Chemistry

INVESTIGATION OF THE OIL PRICE VOLATILITY WITH AUTOREGRESSIVE CONDITIONAL VARIANCE MODELS ARCH/GARCH Oil prices have had a significant volatility over the past century as a result of changes in international economic and political balances. Because oil is a major source of energy and is not evenly distributed among countries, it now has a strategic importance for each country. The aim of this study is to analyze the volatility of global oil prices with the Autoregressive Conditional Variance Models (ARCH/GARCH). In this direction, European Brent oil prices based on June 1987- June 2018 business day basis were used as data in the study. According to the results of analysis, it is seen that TARCH (1,1) model is the best volatility estimation model among different ARCH/GARCH type models. According to the model: I) Oil prices are positively affected by the previous period. II) The impact of shocks on oil price return does not spread over a long period. III) Volatility is generally high, so instability is dominant in prices. IV) Negative shocks on oil price return are more effective than positive shocks. Autoregressive conditional heteroskedasticity ; Conditional variance ; Econometrics ; Volatility (finance) ; Autoregressive model ; Arch ; Economics ; Forward volatility ; Oil price ; Stochastic volatility ; Mathematics ; Engineering ; Monetary economics Petroleum Processing and Analysis ; Hydrocarbon exploration and reservoir analysis
Authors: Jeffrey T. Klein | Michael L. Platt
Source: UNC Libraries (article, 2020-11-01)
Field: Chemistry — Organic Chemistry

Social Information Signaling by Neurons in Primate Striatum Social decisions depend on reliable information about others. Consequently, social primates are motivated to acquire information about the identity, social status, and reproductive quality of others [1]. Neurophysiological [2] and neuroimaging [3 and 4] studies implicate the striatum in the motivational control of behavior. Neuroimaging studies specifically implicate the ventromedial striatum in signaling motivational aspects of social interaction [5]. Despite this evidence, precisely how striatal neurons encode social information remains unknown. Therefore, we probed the activity of single striatal neurons in monkeys choosing between visual social information at the potential expense of fluid reward. We show for the first time that a population of neurons located primarily in medial striatum selectively signals social information. Surprisingly, representation of social information was unrelated to simultaneously expressed social preferences. A largely nonoverlapping population of neurons that was not restricted to the medial striatum signaled information about fluid reward. Our findings demonstrate that information about social context and nutritive reward are maintained largely independently in striatum, even when both influence decisions to execute a single action.► Single neurons in striatum encode social information ► Typically, striatal neurons signal social or fluid information, but not both ► Topographically distinct information channels process social and fluid reward Primate ; Striatum ; Neuroscience ; Cognitive science ; Psychology ; Dopamine Chemical synthesis and alkaloids
Authors: Kabir Bindawa Abdullahi
Source: Preprints.org (preprint, 2020-08-10)
Field: Materials Science — Materials Chemistry

A Moment-Based Method of Optinalysis Graph symmetry detection, similarity, and identity measures have been extensively studied in graph automorphism and isomorphism problems. Nevertheless, graph isomorphism and automorphism detection remain an open (unsolved) problem for many decades. In this paper, a new optinalytic coefficient termed as an optical moment coefficient was introduced for optinalysis. Its characteristic efficiency was tested for bijective property, invariance, deterministic polynomiality and non-polynomiality. The test results show that the new optical moment coefficient is very efficient for symmetry detections, similarity and identity measures between two isometric isomorphs and automorphs; and deterministic on polynomial and non-polynomial graph models. Graph automorphism ; Mathematics ; Graph ; Combinatorics ; Automorphism ; Graph isomorphism ; Isomorphism (crystallography) ; Bijection ; Similarity (geometry) ; Moment (physics) ; Polynomial ; Discrete mathematics ; Voltage graph ; Mathematical analysis ; Computer science ; Line graph ; Physics ; Artificial intelligence Nanocluster Synthesis and Applications ; Graph theory and applications ; Molecular spectroscopy and chirality
Authors: " | Harionovsky A.А. | MNIIЕKO TЕК" | , 60, Nikolai Ostrovsky street, Perm, 614007, Russia | Danilova M.Yu.
Source: Bulletin of Research Center for Safety in Coal Industry (Industial Safety) (article, 2020-01-01)
Field: Chemistry — Inorganic Chemistry

COAL INDUSTRY SHARE IN THE NEGATIVE ENVIRONMENTAL IMPACT 4 2018 Coal ; Environmental impact assessment ; Environmental science ; Business ; Natural resource economics ; Waste management ; Economics ; Engineering ; Ecology ; Biology Zeolite Catalysis and Synthesis
Authors: Oleg Koltun | Galina Malykha | Alexander S. Pavlov
Source: E3S Web of Conferences (article, 2020-01-01)
Field: Materials Science — Materials Chemistry

Using multi-criteria analysis to select an energy source Multi-criteria analysis is widely used to solve various technical and economic problems. There are a large number of applications of multi-criteria analysis. Methods for evaluating the total set of criteria have been investigated. However, the selection of criteria for various specific tasks remains the prerogative of specialists in the relevant branches. The goal of this study was to implement a multi-criteria analysis for assessing the potential of renewable energy sources' competitiveness. Renewable energy sources also include a closed nuclear fuel cycle based on fast-neutron reactors. The advantage of such cycle is the reproduction of nuclear fuel in the same or even greater quantity than it was used. At the same time, uranium isotopes are involved in the cycle, which are waste in conventional nuclear generation. The disadvantage of a nuclear fuel cycle is an output of hazardous waste and a complex technology for its processing. This task is a strategic one, and economic reason is not sufficient in this case. A structure of criteria for strategic decision making was compiled, and eight groups of main criteria were created. An expert analysis of the criteria was carried out and their relative significance was determined. Results. The significance of economic, environmental, technological and safety criteria is revealed. The formulae for criteria normalizing to apply the integration were proposed. Preliminary multi-criteria analysis has shown that a closed nuclear fuel cycle can compete with renewable energy sources such as wind and solar power plants. Nuclear power ; Renewable energy ; Nuclear fuel cycle ; Environmental economics ; Computer science ; Production (economics) ; Operations research ; Risk analysis (engineering) ; Fuel cycle ; Environmental science ; Engineering ; Business ; Waste management ; Economics Graphite, nuclear technology, radiation studies ; Advanced Power Generation Technologies ; Nuclear reactor physics and engineering
Authors: Javier Omar Corvi
Source: LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (article, 2020-02-17)
Field: Chemistry — Spectroscopy

Análisis de coevolución en alineamientos múltiples de secuencias de proteínas evolucionados artificialmente Fil: Corvi, Javier Omar. Fundación Instituto Leloir. Laboratorio de Bioinformática Estructural; Argentina. Medicine Advanced Proteomics Techniques and Applications ; Genomics and Phylogenetic Studies ; Bioinformatics and Genomic Networks
Authors: K. Sujatha | Vijayakumar Selvaraj | N. Nevashini
Source: International Journal of Current Microbiology and Applied Sciences (article, 2020-04-10)
Field: Chemistry — Analytical Chemistry

Clustering and Validation of Iris Flower Dataset using Relative Criteria In the present work, attempts have been made to analyze the Iris data set with clustering technique which is the main task of exploratory data mining and a common technique for statistical data analysis, used in many fields, including machine learning, pattern recognition, image analysis, information retrieval and bioinformatics. The Iris flower data set is a popular multivariate data set introduced by Sir Ronald Fisher as an example of discriminant analysis. The data on four characteristics of the three species of the Iris Flower, sepal length, sepal width, petal length and petal width has been taken from https://ieeexplore.ieee.org/document/771092 and has been analyzed using SAS software. Here we have extended the algorithm for better visualization of possible cluster structures and also to validate clusters. The optimal number of clusters was found in this dataset by using the four cluster validity indices viz., Dunn, DB, RMSSTD and RS indices which yield three and this is configurable to the real partitions of the dataset. Cluster analysis ; Sepal ; Computer science ; Pattern recognition (psychology) ; Set (abstract data type) ; Data set ; Data mining ; Visualization ; Artificial intelligence ; Petal ; IRIS (biosensor) ; Multivariate statistics ; Rand index ; Software ; Machine learning ; Biology Spectroscopy and Chemometric Analyses ; Phytochemistry and Biological Activities
Authors: Ethan Merrill | J. H. Yuen | Manasi Danke
Source: Digital WPI (article, 2020-01-31)
Field: Chemistry — Spectroscopy

Transaction Validation and Analysis While working for a large investment firm, our team aimed to enhance its reporting capabilities. We updated the firm's system for portfolio performance tracking and reporting and created a tool to confirm, automate, and customize commentary describing investment performance. In addition, we developed scripts to validate transaction data, generate commentary on top contributors and detractors for gross profit month over month, and utilize timeseries data to investigate trends and perform statistical analysis. Our Azure Validaton Dashboard visualizes data with Microsoft Power Business Intelligence and provides users the ability to customize their view and drill through the raw data to find what caused certain alerts and movement in performance of strategies. Computer science ; Database transaction ; Business ; Database Analytical Chemistry and Chromatography ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: Laila Rashid
Source: Lund University Publications Student Papers (Lund University) (article, 2020-01-01)
Field: Materials Science — Materials Chemistry

Funktionskrav på vägars bärighet The Swedish Transport Administration procures performance contracts to increase the attractiveness of the construction industry. In this procurement, The Swedish Transport Administration has transformed technical solutions into functional requirements. This allows the contractor to develop his own technical solutions. As a customer, The Swedish Transport Administration needs to find out the quality of the product that is delivered. The quality can be investigated through a load bearing capacity control. In this master's thesis, the concept of load bearing capacity is used to describe the road structure's ability to receive loads from traffic before failure. The client has developed a test of bearing capacity to determine whether the road will last during its entire lifespan. The control requirements are in the form of a falling weight deflectometer performed during the minimum guaranteed instruction period. Implementation requirements exist today, however the monitoring of the measurement results are missing since there is no required limit to be met by the control. In this thesis, the conditions and consequences of using traditional Falling Weight Deflectometer (FWD) as a functional requirement is investigated. Should demands be made on the bearing capacity in a design, construct and maintain contract? In this case, what kind of measurement should be used? The thesis has been carried out by analyzing three different study objects to evaluate if FWD measurements are applicable to all different types of roads. Interviews have also been conducted to get a deeper understanding on the subject and problem area. The conclusions that can be drawn are; Demands on the load bearing capacity should be made because performance requirements on load bearing capacity is the only way to check if the delivered road will last the entire design period. If the measurement is performed according to the method description, there should be no uncertainties in the measurement results. The study objects show that control requirements with a Falling Weight Deflectometer (FWD) measurement can be used on all types of roads, but the method needs to be adjusted for roads with shorter distances. Measurements that are beneficial to use in reporting/documenting load bearing capacity are SCI, BCI and subgrade modulus. The SCI to be used to control the surface course and binder course, BCI to control the structure of the base course and sub-base course and the subgrade modulus to control the structure of the terrace. With the conclusions above recommendations have also been made to follow up the work. Procurement ; Bearing capacity ; Control (management) ; Quality (philosophy) ; Engineering ; Transport engineering ; Computer science ; Business ; Structural engineering Material Selection and Properties
Authors: Xia Xiao | Chao Shang | Jinbo Bi | Sanguthevar Rajasekaran
Source:  (article, 2020-07-01)
Field: Materials Science — Materials Chemistry

Predicting Outcomes of Chemical Reactions: A Seq2Seq Approach with Multi-view Attention and Edge Embedding Materials Genomics initiative has the goal of rapidly synthesizing materials with a given set of desired properties using data science techniques. An important step in this direction is the ability to predict the outcomes of complex chemical reactions. Some graph-based feature learning algorithms have been proposed recently. However, the comprehensive relationship between atoms or structures is not learned properly and not explainable, and multiple graphs cannot be handled. In this paper, chemical reaction processes are formulated as translation processes. Both atoms and edges are mapped to vectors representing the structural information. We employ the graph convolution layers to learn meaningful information of atom graphs, and further employ its variations, message passing networks (MPNN) and edge attention graph convolution network (EAGCN) to learn edge representations. Particularly, multi-view EAGCN groups and maps edges to a set of representations for the properties of the chemical bond between atoms from multiple views. Each bond is viewed from its atom type, bond type, distance and neighbor environment. The final node and edge representations are mapped to a sequence defined by the SMILES of the molecule and then fed to a decoder model with attention. To make full usage of multi-view information, we propose multi-view attention model to handle self correlation inside each atom or edge, and mutual correlation between edges and atoms, both of which are important in chemical reaction processes. We have evaluated our method on the standard benchmark datasets (that have been used by all the prior works), and the results show that edge embedding with multi-view attention achieves superior accuracy compared to existing techniques. Computer science ; Embedding ; Convolution (computer science) ; Enhanced Data Rates for GSM Evolution ; Graph ; Theoretical computer science ; Benchmark (surveying) ; Feature (linguistics) ; Set (abstract data type) ; Node (physics) ; Algorithm ; Artificial intelligence ; Artificial neural network Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Advanced Graph Neural Networks
Authors: Rafael Nunes | Diogo Vila Viçosa | Paulo J. Costa
Source: ChemRxiv (preprint, 2020-02-25)
Field: Chemistry — Spectroscopy

Halogen Bonding: An Underestimated Player in Membrane–drug Interactions Halogen bonds (HaBs) are noncovalent interactions where halogen atoms act as electrophilic species interacting with Lewis bases. These interactions are relevant in biochemical systems being increasingly explored in drug discovery, mainly to modulate protein–ligand interactions. In this work, we report evidence for the existence of HaB-mediated halogen–phospholipid recognition phenomena as our molecular dynamics simulations support the existence of favorable interactions between halobenzene derivatives and both phosphate (PO) or ester (CO) oxygen acceptors from model phospholipid bilayers, thus providing insights into the role of HaBs in driving the permeation of halogenated drug like molecules across biological membranes. This represents a relevant molecular mechanism, previously overlooked, determining the pharmacological activity of halogenated molecules with implications in drug discovery and development, a place where halogenated molecules account for a significant part of the chemical space. Our data also shows that, as the ubiquitous hydrogen bond, HaBs should be accounted for in the development of membrane permeability models. Halogen bond ; Chemistry ; Membrane ; Hydrogen bond ; Drug discovery ; Molecule ; Drug ; Electrophile ; Halogen ; Phospholipid ; Non-covalent interactions ; Combinatorial chemistry ; Computational chemistry ; Organic chemistry ; Biochemistry ; Alkyl ; Biology Molecular Sensors and Ion Detection ; Crystallography and molecular interactions ; Lipid Membrane Structure and Behavior
Authors: Hiroya Nakata
Source: Computational Materials Science (preprint, 2020-08-18)
Field: Materials Science — Materials Chemistry

Development of a fragment kinetic Monte Carlo method for efficient prediction of ionic diffusion in perovskite crystals Kinetic Monte Carlo ; Diffusion ; Ionic bonding ; Perovskite (structure) ; Materials science ; Monte Carlo method ; Chemical physics ; Hydrogen ; Nanometre ; Ionic crystal ; Ion ; Statistical physics ; Crystallography ; Chemistry ; Thermodynamics ; Physics ; Mathematics Advancements in Solid Oxide Fuel Cells ; Semiconductor materials and devices ; Ferroelectric and Piezoelectric Materials
Authors: Hiroya Nakata
Source: arXiv (Cornell University) (preprint, 2020-04-20)
Field: Materials Science — Materials Chemistry

Development of a fragment kinetic Monte Carlo method for efficient\n prediction of ionic diffusion in perovskite crystals A massively parallel kinetic Monte Carlo (kMC) approach is proposed for\nsimulating ionic migration in a crystal system by introducing the atomic\nfragmentation scheme (fragment kMC). The fragment kMC method achieved a\nreasonable parallel efficiency with 1728 central processing unit (CPU) cores,\nand the method enables the simulation of ionic diffusion in $\\mu$m-scale\nperovskite crystals. To demonstrate the feasibility of the proposed approach,\nthe fragment kMC method was applied to predict the diffusion coefficients of\nhydrogen and oxygen in SrTiO$_{(3-x)}$H$_x$ and BaTiO$_{(3-x)}$H$_x$ system.\nFinally, the fragment kMC method was customized for $\\mu$-scale BaTiO$_3$\nsimulation under an applied bias voltage, and oxygen diffusion in BaTiO$_3$\nmodel was evaluated. The respective grain sizes are sub-nanometre, and we\nconclude that the proposed fragment kMC method can be applied to calculate the\nextent of ionic migration in $\\mu$-scale materials with fully atomistic\nsimulation models at a reasonable computational cost.\n Kinetic Monte Carlo ; Diffusion ; Ionic bonding ; Perovskite (structure) ; Materials science ; Monte Carlo method ; Hydrogen ; Chemical physics ; Nanometre ; Ion ; Statistical physics ; Crystallography ; Chemistry ; Thermodynamics ; Physics ; Mathematics Ferroelectric and Piezoelectric Materials ; Advanced ceramic materials synthesis ; Advancements in Solid Oxide Fuel Cells
Authors: Brett W. Rickeard
Source: Scholarship at UWindsor (University of Windsor) (article, 2020-01-01)
Field: Chemistry — Organic Chemistry

Mechanism Determination of the Effects of Pancratistatin on Model Mitochondrial Membranes Apoptosis is programmed cell death that is essential for physiological development and tissue homeostasis. From a biochemical standpoint, this process can be exploited to target and eliminate specific cell types, such as cancer cells. Pancratistatin (PST) is an antiviral alkaloid metabolite that has demonstrated directed apoptotic action on various human cancer cell lines while having minimal/no toxic effect on normal cells. However, PST’s mechanism of action remains uncertain. To better understand how PST induces its anti-cancer action various biophysical techniques were employed. Neutron spin-echo (NSE) spectroscopy was used to examine how PST impacted the bending fluctuations of large unil- amellar vesicles (LUVs) bearing a lipid composition meant to mimic the inner mitochondrial membranes (IMM). The IMM mimic was composed of three lipids: 1-palmitoyl-2-oleoyl-sn- glycero-3-phosphocholine (POPC), 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine (POPE), and tetraoleoyl cardiolipin (TOCL). Small-angle neutron and X-ray scattering (SANS and SAXS) were utilized to determine how PST influences membranes structure. Molecular dynamics (MD) simulations were used to compliment the data gathered from the scattering experiments, while also examining lipid chain order, PST localization and the PST-lipid relationships. The results show that PST has a condensing effect the IMM mimic. This thesis elaborates on the possible implications of this finding with regard to the nature of PST’s interaction with the IMM mimic and proposes a hypothesis for the anti-cancer mechanism of PST. Mechanism (biology) ; Chemistry ; Philosophy ; Epistemology Chemical synthesis and alkaloids