jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Asko Arkoma
Source: Aaltodoc (Aalto University) (article, 2018-01-01)
Field: Materials Science — Materials Chemistry

Modelling design basis accidents LOCA and RIA from the perspective of single fuel rods When designing a nuclear power plant and its fuel, certain accidents are postulated to occur with a predetermined low frequency. The consequences of these accidents are mitigated by various passive and active safety features, and an adequate safety level is implemented by the regulatory authority in the safety requirements.&#13;\nThe dissertation considers computational modelling of two main design basis accidents in current light water reactors: loss-of-coolant accident (abbreviated LOCA) and reactivity initiated accident (RIA). The applied computer programmes are designed for modelling the behaviour of a single fuel rod in transient and accident conditions.&#13;\nLOCA modelling is focused on developing a statistical analysis methodology for the evaluation of fuel failures in LOCA. The statistical system is applied to a large break LOCA in an EPR type reactor, and fulfilment of the regulations included in the Regulatory Guides on nuclear safety set by the Finnish nuclear safety authority STUK is studied. In order to determine the underlying factors affecting the fuel rod failures, a sensitivity analysis is performed. A systematic multistage procedure is developed for the sensitivity analysis.&#13;\nRIA modelling focuses on adaptation of the single rod RIA modelling code SCANAIR for boiling water reactor (BWR) conditions. The SCANAIR code, developed by the French research organisation Institut de Radioprotection et de Sûreté Nucléaire (IRSN), is specifically designed for modelling RIAs in pressurized water reactors (PWRs). In this dissertation, the code is adapted to take into account BWR specific properties and conditions. Perspective (graphical) ; Forensic engineering ; Environmental science ; Engineering ; Computer science Nuclear Materials and Properties ; Nuclear and radioactivity studies ; Risk and Safety Analysis
Authors: В. Е. Агабеков | O. А. Daiineko | Nadezhda Ivanova | А.Л. Потапов | В. А. Длугунович
Source: Electronic scientific archive of UrFU (Ural Federal University) (article, 2018-06-01)
Field: Materials Science — Polymers and Plastics

Optical Films of Polyvinyl Alcohol withSilver Nanoparticles or Carbon Nanotubes Polyvinyl alcohol ; Carbon nanotube ; Materials science ; Nanoparticle ; Nanotechnology ; Chemical engineering ; Composite material Synthesis and properties of polymers
Authors: Silvie Surmová
Source: Digital library - University of Pardubice (University of Pardubice) (article, 2018-01-01)
Field: Chemistry — Spectroscopy

Analýza těkavých organických látek v přírodních matricích metodou HS-SPME/GC-MS Disertační práce je zaměřena na analýzu těkavých organických látek ve vzorcích přírodního&#13;\nmateriálu. Zabývá se aplikací prekoncentračních technik, extrakčních technik (mikroextrakce&#13;\ntuhou fází, destilace, extrakce nadkritickou tekutinou) a použitím analytických separačních&#13;\nmetod pro identifikaci, příp. semikvantifikaci těkavých sloučenin charakteristických pro&#13;\nněkteré přírodní materiály či produkty z nich vyrobené.&#13;\nTeoretická část disertační práce je věnována poznatkům o silicích, principům a aplikacím&#13;\nextrakčních metod. Poměrná část práce je soustředěna na mikroextrakci tuhou fází, jež je&#13;\nprioritní extrakční metodou v disertační práci. Rovněž je v práci obsáhlá část o plynové&#13;\nchromatografii ve spojení s hmotnostní spektrometrií.&#13;\nExperimentální část disertační práce je rozdělena na tři hlavní kapitoly, kterými jsou&#13;\nproblematika extrakce těkavých sloučenin přítomných v okvětních lístcích růží, analýza&#13;\nrůzných druhů alkoholických nápojů a charakterizace profilu těkavých látek tonkových bobů.&#13;\nZákladní informace o zkoumaných matricích jsou vypsány v teoretické části práce,&#13;\nv praktické části jsou uvedeny použité chemikálie, přístroje a analytické postupy, včetně&#13;\njejich optimalizace. Každá kapitola obsahuje vlastní sekci, kde jsou diskutovány dosažené&#13;\nvýsledky, z nichž některé byly publikovány v odborných zahraničních časopisech. Chemistry ; Chromatography ; Extraction (chemistry) ; Mass spectrometry ; Gas chromatography–mass spectrometry ; Supercritical fluid extraction ; Solid-phase microextraction ; Gas chromatography ; Aroma Analytical Chemistry and Chromatography
Authors: Luis Humberto Mendoza-Huízar
Source: Journal of the Serbian Chemical Society (article, 2018-01-01)
Field: Chemistry — Organic Chemistry

A DFT study of the chemical reactivity of thiobencarb and its oxidized derivatives in aqueous phase In the present work, the global and local reactivity of S-(4-chlorobenzyl)- N,N-diethylthiocarbamate (TB) and its oxidized derivatives (sulfone (TBSu) and sulfoxide (TBS) were analyzed. In addition, the chemical reactivities of the dechlorinated forms of TB (DTB), TBSu (DTBSu) and TBS (DTBS) were studied. The calculations were performed at the wB97XD/6- -311++G(2d,2p) level of theory in the aqueous phase. The condensed Fukui functions indicated that for TB and DTB, the most preferred sites for donating electron in a reaction are located on the S and N atoms, while the most reactive sites for accepting electrons are associated with the aromatic ring (AR). For TBS and DTBS, the more reactive sites are located on AR, S and AR for nucleophilic, electrophilic and free radical attacks, respectively. In the case of TBSu and DTBSu, the results showed AR to be the more reactive zone for the three kinds of attacks. These last results suggest that cleavage of the C?S bond in TB, TBS and their dechlorinated forms is favored by electrophilic attacks. Additionally, the obtained results suggest that in TB, it is plausible that the cleavage of the C?N is favored on attack of this molecule by electrophiles. Electrophile ; Nucleophile ; Reactivity (psychology) ; Chemistry ; Sulfone ; Cleavage (geology) ; Aqueous solution ; Medicinal chemistry ; Bond cleavage ; Sulfoxide ; Photochemistry ; Reactive intermediate ; Aqueous two-phase system ; Computational chemistry ; Polymer chemistry ; Organic chemistry ; Materials science ; Catalysis Chemical Reaction Mechanisms ; Free Radicals and Antioxidants ; Organic Chemistry Cycloaddition Reactions
Authors: М. А. Борик | А. В. Кулебякин | Е. Е. Ломонова | В. А. Мызина | П. А. Попов | Filipp Milovich | Н. Ю. Табачкова
Source: Физика твердого тела (article, 2018-01-01)
Field: Materials Science — Materials Chemistry

Теплопроводность монокристаллов твердых растворов на основе ZrO-=SUB=-2-=/SUB=-, стабилизированных оксидами скандия и иттрия, в интервале температур 50-300 K AbstractThe thermal conductivity of single-crystal (ZrO_2)_1 – _ x (Sc_2O_3)_ x ( x = 0.09, 0.10) and (ZrO_2)_1 ‒ _ x _‒ _ y (Sc_2O_3)_ x (Y_2O_3)_ y ( x = 0.003–0.10; y = 0.01–0.025) solid solutions has been experimentally determined in the temperature range 50–300 K. The results are analyzed with allowance made for the phase compositions and features of imperfect crystal structures. Allowance (engineering) ; Materials science ; Crystallography ; Atmospheric temperature range ; Crystal (programming language) ; Thermal conductivity ; Phase (matter) ; Analytical Chemistry (journal) ; Range (aeronautics) ; Chemistry ; Thermodynamics ; Physics ; Computer science ; Composite material Advancements in Solid Oxide Fuel Cells ; Nuclear materials and radiation effects ; Thermal Expansion and Ionic Conductivity
Authors: Paolo Inglese | Gonçalo Correia | Pamela Pruski | Robert C Glen | Zoltan Takats
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2018-10-11)
Field: Chemistry — Spectroscopy

Colocalization features for classification of tumors using desorption electrospray ionization mass spectrometry imaging Abstract Supervised modeling of mass spectrometry imaging (MSI) data is a crucial component for the detection of the distinct molecular characteristics of cancerous tissues. Currently, two types of supervised analyses are mainly used on MSI data: pixel-wise segmentation of sample images, and whole-sample-based classification. A large number of mass spectra associated with each MSI sample can represent a challenge for designing models that simultaneously preserve the overall molecular content while capturing valuable information contained in the MSI data. Furthermore, intensity-related batch effects can introduce biases in the statistical models. Here we introduce a method based on ion colocalization features that allows the classification of whole tissue specimens using MSI data, which naturally preserves the spatial information associated the with the mass spectra and is less sensitive to possible batch effects. Finally, we propose data visualization strategies for the inspection of the derived networks, which can be used to assess whether the correlation differences are related to co-expression/suppression or disjoint spatial localization patterns and can suggest hypotheses based on the underlying mechanisms associated with the different classes of analyzed samples. Colocalization ; Mass spectrometry imaging ; Pattern recognition (psychology) ; Mass spectrometry ; Segmentation ; Sample (material) ; Mass spectrum ; Visualization ; Spatial analysis Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Ion-surface interactions and analysis
Authors: Najwa Abu Nassif
Source: التصميم الدولية (article, 2018-01-01)
Field: Materials Science — Polymers and Plastics

Predicting the seam efficiency of sewn blended fabrics using ANN and linear regression models In most cases, quality of sewn apparel products is characterized by seam performance. The durability of the seam is mainly defined by its efficiency along the seam line; therefore it is one of the most important characteristics to obtain the desired seam quality. Throughout this study, seam efficiencies of woven blended fabrics were predicted using two different methodologies, i.e. ANN and regression methods. ANN with four neurons input layer, 15 neuron hidden layer and output layer with one neuron focusing on the seam efficiency was used and compared to regression line. The input variables in both predictive modes were polyester ratios, sewing needle size, stitch density and sewing thread count. The findings of this work revealed that ANN predictive model is outperformed the multiple linear regression one with lower vales of RMSE and MBE and high R2 values. Linear regression ; Regression analysis ; Regression ; Thread (computing) ; Layer (electronics) ; Computer science ; Statistics ; Artificial intelligence ; Mathematics ; Materials science ; Composite material Textile materials and evaluations ; Color perception and design ; Industrial Vision Systems and Defect Detection
Authors: Ghada Ali Abou-Nassif | R Ogulata | E Koc | M Tokarska | A Das | S Ishtiaque | F Wallenberger | R Dhingra | R Postle | P Lord | P Grady | A Ibrahima | A Amr | B Eid | A Almetwally | M Mourad | Ahmet Cay | Isk Tarakcoglu | Alsaid Ahmed | Almetwally | Rasa Urbas | Klara Kostanjsek | Krste Dimitrovski | Alsaid Ahmed Almetwally | H Idrees | Ali Ali | Hebeish | Ahmed El-Salmawy | Fabio Rombaldoni1 | Yasser | Ahmed Eid | Alsaid Alsalmawy | Abeer Ebraheem | Eldsoky Mohammed
Source: International Journal of ChemTech Research (article, 2018-01-01)
Field: Materials Science — Polymers and Plastics

Single-criterion optimization of the air permeability of woven fabrics using Taguchi method Woven fabric's breathability is one of the most important characteristics concerning fabrics used as tents, raincoats and uniform shirtings. It is mainly evaluated and compared significantly via fabric air permeability. This study aimed to optimization of the fabric parameters influencing the woven cotton fabrics' air permeability. Twenty seven different fabric combinations using a 3 3 full factorial design were diminished to only nine fabric samples according to L 9 Taguchi's orthogonal design. These fabric samples were produced, tested and evaluated. Using S/N ratios, the best combinations of factor levels which yield the highest value of fabric air permeability were detected efficiently. Taguchi methods ; Air permeability specific surface ; Permeability (electromagnetism) ; Materials science ; Composite material ; Chemistry ; Membrane Textile materials and evaluations
Authors: Jonathan Richetti
Source:  (article, 2018-11-13)
Field: Chemistry — Analytical Chemistry

Modelos agrometeorológicos, espectrais e de inteligência artificial para estimação de produtividade de soja Submitted by Neusa Fagundes (neusa.fagundes@unioeste.br) on 2019-04-02T17:38:43Z\nNo. of bitstreams: 2\nJonathan_Richetti2018.pdf: 3954800 bytes, checksum: 36f18c996a00fc62f3f0ad5168fde41c (MD5)\nlicense_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Humanities ; Physics ; Philosophy Spectroscopy and Chemometric Analyses ; Leaf Properties and Growth Measurement ; Soybean genetics and cultivation
Authors: Thejashwini. K. S | Sayeeqa Anjum | Sowmya K. N C R Manjunath
Source: International Journal of Trend in Scientific Research and Development (article, 2018-06-30)
Field: Materials Science — Polymers and Plastics

IoT Based Smart Clothing Smart clothing is on tremendous high demand for the various safety purposes, for heath in hazardous environment, for improvising business performance, appearance and in entertainment. With the wearable devices like smart jackets and other accessories it is possible to collect and detect the signals for the organizations to respond the incidents in many different ways.Smart Clothing joins in materials and remote sensor and organizes with regards to human body observing with measurable strategies for the information and treatment. Clothing ; Internet of Things ; Computer science ; Architectural engineering ; Business ; Computer security ; Engineering ; History Textile materials and evaluations ; Color perception and design ; Consumer Retail Behavior Studies
Authors: Marc De Graef
Source: Microscopy and Microanalysis (article, 2018-08-01)
Field: Materials Science — Surfaces, Coatings and Films

Indexing of Large SEM Diffraction Data Sets Using a Dictionary Approach Recent years have seen a significant increase in the use of electron diffraction modalities in a scan-ning electron microscope (SEM) to cover large areas of complex microstructures, both in advanced engineering materials and natural geological samples. In addition to the well established Electron Back-Scatter Diffraction (EBSD) technique, Electron Channeling Patterns (ECP) and Transmission Kikuchi Diffraction (TKD) have seen increased use as well as progress in the quantitative modeling of the diffracted intensities. As shown in [1], these three techniques can be described theoretically in a single framework consisting of a Monte Carlo simulation followed by generation of a master pattern using the dynamical scattering theory. Combining this model with a uniform sampling of orienta-tion space SO(3) as well as a geometrical detector model allows us to generate a dictionary of all possible diffraction patterns for the selected angular step size in orientation space. These dictionar-ies can then be used in combination with a similarity metric to index large scale experimental data sets. Search engine indexing ; Content (measure theory) ; Computer science ; Diffraction ; Information retrieval ; Pattern recognition (psychology) ; Artificial intelligence ; Optics ; Mathematics ; Physics Electron and X-Ray Spectroscopy Techniques ; Machine Learning in Materials Science ; Advanced Electron Microscopy Techniques and Applications
Authors: Hasan Ali Gamal Al-Kaf | Kim Seng Chia | Musaed Al-subari
Source: APTIKOM Journal on Computer Science and Information Technologies (article, 2018-11-01)
Field: Chemistry — Analytical Chemistry

Genetic Algorithm Artificial Neural Network in Near Infrared Spectroscopic Quantification The implantation of a genetic algorithm (GA) in quantitating components of interest in near infrared spectroscopic analysis could improve the predictive ability of a regression model. Thus, this study investigates the feasibility of a single layer Artificial Neuron Network (ANN) that trained with Levenberg-Marquardt (SLM) coupled with GA in predicting the boiling point of diesel fuel and the blood hemoglobin using near infrared spectral data. The proposed model was compared with a well-known model of Partial Least Squares (PLS) with and without Genetic Algorithm. Results show that the proposed model achieved the best results with root mean square error of prediction (RMSEP) of 3.6734 and correlation coefficient of 0.9903 for the boiling point, and RMSEP of 0.2349 and correlation coefficient of 0.9874 among PLS with and without GA, and SLM without GA. Findings suggest that the proposed SLM-GA is insusceptible to the number of iterations when the SLM was trained with excessive iteration after the optimal iteration number. This indicates that the proposed model is capable of avoiding overfitting issue that due to excessive training iteration. Overfitting ; Correlation coefficient ; Artificial neural network ; Genetic algorithm ; Mean squared error ; Algorithm ; Convergence (economics) ; Computer science ; Boiling point ; Mathematics ; Artificial intelligence ; Biological system ; Statistics ; Mathematical optimization ; Engineering Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Water Quality Monitoring and Analysis
Authors: Ginny Xiaohe Li | Christine Vogel | Hyungwon Choi
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2018-02-01)
Field: Chemistry — Spectroscopy

PTMscape: an open source tool to predict generic post-translational modifications and map hotspots of modification crosstalk Abstract While tandem mass spectrometry can now detect post-translational modifications (PTM) at the proteome scale, reported modification sites are often incomplete and include false positives. Computational approaches can complement these datasets by additional predictions, but most available tools are tailored for single modifications and each tool uses different features for prediction. We developed an R package called PTMscape which predicts modifications sites across the proteome based on a unified and comprehensive set of descriptors of the physico-chemical microenvironment of modified sites, with additional downstream analysis modules to test enrichment of individual or pairs of modifications in functional protein regions. PTMscape is generic in the ability to process any major modifications, such as phosphorylation and ubiquitination, while achieving the sensitivity and specificity comparable to single-PTM methods and outperforming other multi-PTM tools. Maintaining generalizability of the framework, we expanded proteome-wide coverage of five major modifications affecting different residues by prediction and performed combinatorial analysis for spatial co-occurrence of pairs of those modifications. This analysis revealed potential modification hotspots and crosstalk among multiple PTMs in key protein domains such as histone, protein kinase, and RNA recognition motifs, spanning various biological processes such as RNA processing, DNA damage response, signal transduction, and regulation of cell cycle. These results provide a proteome-scale analysis of crosstalk among major PTMs and can be easily extended to other modifications. Contact all correspondence should be addressed to hwchoi@nus.edu.sg . Proteome ; Computational biology ; Computer science ; Crosstalk ; Posttranslational modification ; Histone ; Biology ; Bioinformatics ; DNA ; Genetics ; Biochemistry Advanced Proteomics Techniques and Applications ; RNA and protein synthesis mechanisms ; Genomics and Phylogenetic Studies
Authors: Qingrun Li | Shisheng Wang | Hongwen Zhu | Fang-Ying Xia | Peter Roepstorff | Jiarui Wu | Rong Zeng
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2018-11-07)
Field: Chemistry — Spectroscopy

Data-Independent Acquisition Mass Spectrometry to Localize Phosphosites Abstract In conventional data-dependent acquisition (DDA) mode used for phosphoproteome analysis by mass spectrometry, a considerable number of phosphosites are localized ambiguously. We found that data-independent acquisition (DIA) method could localize phosphosite accurately and confidently due to its acquisition nature of repeated and unbiased mode. Here, we present a robust and promising DIA workflow for modification sites determination. Through dedicated collection and analyses of site-determining ions following their chromatographic profilings, phosphosites could be assigned or rectified unambiguously. Mass spectrometry ; Data acquisition ; Workflow ; Computer science ; Isobaric labeling ; Computational biology ; Mode (computer interface) ; Chemistry ; Data mining ; Chromatography ; Biology ; Tandem mass spectrometry ; Protein mass spectrometry ; Database Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Astrid Carolina Avila Gelvez | Mile Yurley Hernandez Cadena
Source: Universidad Industrial de Santander (article, 2018-01-01)
Field: Chemistry — Analytical Chemistry

Prediction of t95 and flash point for diesel based on ir specters and artificial neural networks Para el desarrollo de este proyecto, se emplearon un grupo de 61 muestras de diésel con sus respectivas propiedades. La información fue proporcionada por sección materias primas y productos terminados de la GRB. Lo anterior dio lugar a realizar 2 pretratamientos a la matriz original, con el fin de corregir línea base y posibles fluctuaciones que impiden la identificación de las contribuciones a las propiedades analizadas. Para cada uno de estos pretratamientos se realizó un entrenamiento en con la herramienta toolbox de MATLAB. Los resultados obtenidos, establecieron que el mejor desempeño fue para el pretratamiento 1 con la función de activación TANSIG y arquitectura de red 20:25:1 FP, reportando un MSE de 0.9644 y un R² de 0.9775; y para el pretratamiento 2 con la función de activación LOGSIG y arquitectura de red 24:20:1 T95, reportando un MSE de 0.2784 y un R² de 0.9803. Por otra parte la prueba de resiliencia muestra que las redes neurales son resilientes a cambios presentados cuando se eliminan datos menos representativos. En último lugar, la prueba de sensibilidad nos indica que los picos que más contribuyen en el proceso, presentan menores áreas bajo la curva de los espectros pretratados más contribuyen en el proceso, presentan menores áreas bajo la curva de los espectros pretratados.. Artificial neural network ; Flash (photography) ; Diesel fuel Spectroscopy and Chemometric Analyses ; Forensic Fingerprint Detection Methods ; Water Quality Monitoring and Analysis