jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Pan Gao | Chuanrong Hu | Dongping He
Source: Journal of Oleo Science (article, 2020-01-01)
Field: Chemistry — Organic Chemistry

Evaluation of Chemical Properties of Commercial Extra Virgin Olive Oil in China The aim of the study was to investigate the chemical properties of the most popular commercial extra virgin olive oils (EVOOs) in China. A total of 14 EVOO samples were collected and evaluated, and significant differences were observed with respect to physicochemical properties, fatty acid composition, minor components, and the oxidation stability index (OSI). The results showed that the chemical properties of EVOOs were significantly affected by different producing areas. The oleic acid (C18:1) content (average value: 77.80%), squalene content (average value: 6052.28 mg/kg), and OSI (average value: 9.90 h) of the Spanish olive oil were higher than those of the other oils investigated, while the total phenolic content (average value: 308.34 mg/kg) was the lowest. Greek EVOOs had the lowest total sterol content (average value: 1023.48 mg/kg) and OSI (average value: 4.22 h). The C18:1 content (66.42%) and squalene content (3173.42 mg/kg) of the EVOO from China were lower than those of the other oils, while the palmitic acid (C16:0, 16.82%), linoleic acid (C18:2, 12.18%), total phenolic (553.17 mg/kg), and total sterol content (1904.77 mg/kg) were higher than those of the other olive oils. The EVOOs of the various countries could be distinguished by hierarchical cluster analysis (HCA). In addition, multiple linear regression (MLR) analyses between the OSI and chemical properties revealed that squalene (R = 0.729) and the unsaturation determined by the specific UV adsorption at 232 nm (K<sub>232</sub>, R = -0.300) were the main factors to affecting the EVOO oxidation stability. Squalene ; Chemistry ; Food science ; Palmitic acid ; Oleic acid ; Linoleic acid ; Olive oil ; Fatty acid ; Acid value ; Chemical composition ; Degree of unsaturation ; Iodine value ; Sterol ; Chromatography ; Organic chemistry ; Biochemistry ; Cholesterol Edible Oils Quality and Analysis ; Antioxidant Activity and Oxidative Stress ; Cholesterol and Lipid Metabolism
Authors: Anna Flavia de Souza Silva | Luís Martins | Liz Mary Bueno de Moraes | Isabela C. Gonçalves | Bianca B. R. de Godoy | Sara W. Erasmus | Saskia M. van Ruth | Fábio R.P. Rocha
Source:  (article, 2020-11-09)
Field: Chemistry — Analytical Chemistry

Can Minerals Be Used as a Tool to Classify Cinnamon Samples? Cinnamon (Cinnamomum zeylanicum) is a spice largely consumed worldwide, but there is still restricted information about its fingerprint. This work aimed to investigate the mineral composition as a possible marker for the classification of cinnamon samples. To this aim, the mineral composition (P, S, Mg, Ca, K, Cu, Zn, B, Fe, Al, Mn, and Si contents) of 56 ground cinnamon samples from different regions of the State of São Paulo, Brazil was determined by inductively coupled plasma optical emission spectroscopy (ICP OES). Principal component analysis was exploited for sample classification, and the microelements presented the best correlation: PC1, PC2, and PC3 explained 93% of the observed variance at 95% confidence level. Si, Al, Fe, and Cu presented the most significant contributions to cluster analysis. Samples were classified into six groups, in which those presenting C. zeylanicum were well clustered, and the samples acquired in bulk as well as those whose labels declared traces of grains and/or spices presented the highest variability. Thus, it was pioneeringly demonstrated the possibility of identifying C. zeylanicum in commercial cinnamon powders, using microelements as authenticity markers. Cinnamomum zeylanicum ; Principal component analysis ; Chemistry ; Inductively coupled plasma atomic emission spectroscopy ; Composition (language) ; Food science ; Mathematics ; Inductively coupled plasma ; Statistics ; Physics Heavy Metals in Plants ; Agricultural and Food Sciences ; Cassava research and cyanide
Authors: Rocco Furferi | Franco Mantellassi | Yary Volpe
Source: Applied Sciences (article, 2020-01-18)
Field: Materials Science — Polymers and Plastics

Design and Manufacturing of an Innovative Triple-Layer Thermo-Insulated Fabric Materials used for creating fabrics featuring insulation and thermoregulation are typically made of multi-layer materials consisting of two outer layers and inner padding, traditionally made from goose or duck feathers or even with synthetic materials. In this context, the development of a fabric in which the insulation is carried out directly thanks to the structure of its weave, i.e., where the thermoregulation function is entrusted to one of the yarns (suitably volumized to reduce its density and trap the air) may be an important improvement compared to the state of the art. Accordingly, the present work describes the development of a new kind of triple-layer thermo-insulated innovative fabric (named T4Innovation), in which the thermal insulation is not obtained by means of a padding but rather through the use of appropriate volumized yarns, able to ensure thermal insulation in a reduced thickness. This fabric is manufactured in a single weaving phase, greatly facilitating the subsequent operations of the garment maker. The designed and manufactured fabric was extensively tested to assess its performance. The test demonstrated the effectiveness of such a new class of textile product in terms of thermal performance, which is comparable to the ones of a padded material. Since T4Innovation demonstrates aesthetic properties very close to that of traditional unpadded fabrics, its future commercialization could open new horizons in terms of design, fashion, and style, which are cornerstones of the fashion textile industry. Padding ; Textile ; Thermal insulation ; Weaving ; Context (archaeology) ; Mechanical engineering ; Materials science ; Composite material ; Layer (electronics) ; Engineering ; Architectural engineering Textile materials and evaluations ; Skin Protection and Aging ; Dyeing and Modifying Textile Fibers
Authors: Shubham Gupta | Hannes Röst
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2020-01-23)
Field: Chemistry — Spectroscopy

Automated Workflow For Peptide-level Quantitation From DIA/ SWATH-MS Data Abstract Data Independent Acquisition (DIA) is a powerful method to acquire spectra from all ionized precursors of a sample. Considering the complexity of the highly multiplexed spectral data, sophisticated workflows have been developed to obtain peptides quantification. Here we describe an open-source and easy-to-use workflow to obtain a quantitative matrix from multiple DIA runs. This workflow requires as prior information an “assay library”, which contains the MS coordinates of peptides. It consists of OpenSWATH, pyProphet and DIAlignR software. For the ease of installation and to isolate operating system related dependency, docker-based containerization is utilized in this workflow. Workflow ; Computer science ; Software ; Data mining ; Sample (material) ; Database ; Chemistry ; Chromatography ; Operating system Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Vitiyah Manimaran | Norliza Abd Rahman | Jarinah Mohd Ali
Source: Jurnal Kejuruteraan (article, 2020-05-30)
Field: Chemistry — Inorganic Chemistry

‘SMART’ Manufacturing Method of Oleochemical Plants by Determining Fatty Acid Composition of C12 of Palm Kernel Stearin using Fuzzy Logic System Industry 4.0 is the name given to the latest evolution in the digitalisation and automation of manufacturing processes. Transitioning to Industry 4.0 is an emerging imperative for chemical processing based manufacturers throughout the world. “Smart” equipments, products and factories are transforming how companies do business, both internally and with suppliers and customers. At the present moment palm oil products particularly, Palm Kernel Oil have become a major feedstock for the oleochemical industries in Malaysia. Since Malaysia accounts for 42% of the global production of palm oil products, it is inevitable that the oleochemical industries has been flourishing and blooming in the last few years. The majority fatty acid found in palm kernel stearin is C12 which can be found in range of 54.8 to 64.0 wt%. But this value is determined by the iodine and saponification value of the palm kernel. The higher the iodine and saponification value, hence the higher the fatty acid composition can be found for higher extraction for oleochemical plant. The iodine value (Wjis) is ranged from 5.8 to 8.1 whereas the saponification value is ranged from 245 to 254 mgKOHg&lt;sup&gt;-1&lt;/sup&gt;oil. Fuzzy Logic system is developed to determine the fatty acid composition for the different range of iodine value and saponification value to ensure kernel with different composition of fatty acid to be separated and produce higher purity of oleochemical substances. This system will ensure ‘SMART’ manufacturing replacing the ‘NON-SMART’ methods where all kernels are grinded randomly and extracting altogether. Palm kernel oil ; Saponification value ; Iodine value ; Palm stearin ; Palm kernel ; Food science ; Saponification ; Raw material ; Chemistry ; Fatty acid ; Pulp and paper industry ; Mathematics ; Business ; Palm oil ; Organic chemistry ; Engineering Coconut Research and Applications ; Edible Oils Quality and Analysis ; Biodiesel Production and Applications
Authors: Gergely Tóth | Péter Király | Dániel Kovács
Source: Chemometrics and Intelligent Laboratory Systems (article, 2020-07-10)
Field: Chemistry — Analytical Chemistry

Effect of variable allocation on validation and optimality parameters and on cross-optimization perspectives We investigated the allocation dependence of validation and design of experiment optimality parameters by modifying the pattern of the independent variables. They were scanned from a centre-like to corner-like positions and fixed design of experiment settings were checked, too. The response variable was modelled with multivariate linear regression. The calculations were performed on simulated data in two and 4-dimensional independent variable spaces and on datasets of power plant and QSAR studies. Our results showed that almost all parameters evaluating validation or design of experiment optimality could be tuned by intentionally increasing the number of samples taken close to the edges of the variable domain. We got strong rank correlation among most of the parameters. It coincides well with the primary aim of design of experiment to obtain validatable models, where design of experiment is performed before the model building, or even before the experiments, and validation takes place after the model building. Surprisingly, the best subsets of the selected samples for the different parameters overlapped only weakly. We found a reasonable cross optimization power only for some goodness-of-fit and robustness parameters, the overlap was rather weak concerning predictivity and design of experiment optimality parameters. For the simulated data we calculated the exact integrated error of prediction, its value strongly depended on the error features of the individual subsets and showed minimal cross-optimization power. We might conclude that design of experiment using optimality parameters need not to provide the allocations with best validation parameters in many cases. Robustness (evolution) ; Mathematics ; Cross-validation ; Variable (mathematics) ; Design of experiments ; Linear regression ; Multivariate statistics ; Statistics ; Regression ; Mathematical optimization ; Variables ; Computer science Spectroscopy and Chemometric Analyses ; Advanced Statistical Methods and Models ; Optimal Experimental Design Methods
Authors: Xuelong Hao | Wen Chen | Ning Zhao | Lu Lu | Kai Zhang | Donghui Zhang
Source: International Journal of Photoenergy (article, 2020-12-19)
Field: Materials Science — Materials Chemistry

Prototype of an Expert System for the Selection of Aircraft Structural Materials Expert systems (ES) are widely used for engineering and manufacturing applications nowadays. In order to solve the problems in material selection in the aviation field, an aircraft material expert system (AMES) was developed. This expert system is based on the knowledge of multiple experts and aviation data. A decision support system (DSS) was designed for selecting the materials used in aviation fields. The flows of material selection were designed, and the models of AMES were established. A data base system was also designed to implement AMES. Aviation ; Expert system ; Selection (genetic algorithm) ; Field (mathematics) ; Computer science ; Knowledge base ; Systems engineering ; Aircraft maintenance ; Engineering ; Aeronautics ; Artificial intelligence ; Aerospace engineering Material Selection and Properties ; Manufacturing Process and Optimization ; Extenics and Innovation Methods
Authors: Yue Jin | Na Zhao | Liu Liu
Source: Cancer Management and Research (article, 2020-03-01)
Field: Chemistry — Analytical Chemistry

&lt;p&gt;Prediction and Monitoring Method for Breast Cancer: A Case Study for Data from the University Hospital Centre of Coimbra&lt;/p&gt; Breast cancer is the second most common cancer in women after skin cancer. Breast cancer can occur in both men and women, but it is far more common in women. Real-time monitoring of breast cancer indicators is becoming increasingly important. It can help create advances in the diagnosis and treatment of breast cancer. In this paper, we provide a nonparametric statistical method to predict and detect breast cancer occur. The exponentially weighted moving average (EWMA) control scheme is based on rank methods so that it is completely nonparametric. It is efficient in detecting the shifts for multivariate processes. A real example data from the University Hospital Centre of Coimbra is given to illustrate this method. Breast cancer ; EWMA chart ; Medicine ; China ; Cancer ; Nonparametric statistics ; Oncology ; Family medicine ; Statistics ; Internal medicine ; Mathematics ; Geography ; Computer science ; Control chart Spectroscopy and Chemometric Analyses ; Advanced Statistical Process Monitoring ; Statistical Methods and Inference
Authors: Michał Kunicki
Source: Archives of Acoustics (article, 2020-12-28)
Field: Materials Science — Materials Chemistry

Analysis on Acoustic Disturbance Signals Expected During Partial Discharge Measurements in Power Transformers This paper presents comparative analysis of various acoustic signals expected during partial discharge (PD) measurements in operating power transformer. Main purpose of the paper is to yield relevant and reliable method to distinguish between various acoustic emission (AE) signals emitted by PD and other sources, with particular consideration of real-life results rather than laboratory simulations. Therefore, selected examples of real-life AE signals registered in seven different power transformers, under normal operation conditions, within few years are showed and analyzed. Five scenarios are investigated, which represent five types of AE sources: PD generated by artificial sources, and next four real-life sources (including PD in working transformer, oil flow, oil pumps and core). Several different signal processing methods are applied and compared in order to identify the PD signals. As a result, an energy patterns analysis based on the wavelet decomposition is found as the most reliable tool for identification of PD signals. The presented results may significantly support the process of interpretation of the PD measurement results, and may be used by field engineers as well as other researchers involved in PD analysis using AE method. Finally, observed properties also provide a solid basis for establishing or improving complete classification method based on the artificial intelligence algorithms. Partial discharge ; Disturbance (geology) ; Acoustics ; Transformer ; Computer science ; Voltage ; Electrical engineering ; Physics ; Geology High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Non-Destructive Testing Techniques
Authors: Jianjiang Li | Baixue Ji | Yun Yang | Wei Peng | Jie Wu
Source: Tsinghua Science & Technology (article, 2020-10-12)
Field: Materials Science — Materials Chemistry

Parallel optimization of the Crystal-KMC on Tianhe-2 The Kinetic Monte Carlo (KMC) is one of the commonly used methods for simulating radiation damage of materials. Our team develops a parallel KMC software named Crystal-KMC, which supports the Embedded Atom Method (EAM) potential energy and utilizes the Message Passing Interface (MPI) technology to simulate the vacancy transition of the Copper (Cu) element under neutron radiation. To make better use of the computing power of modern supercomputers, we develop the parallel efficiency optimization model for the Crystal-KMC on Tianhe-2, to achieve a larger simulation of the damage process of materials under irradiation environment. Firstly, we analyze the performance bottleneck of the Crystal-KMC software and use the MIC offload statement to implement the operation of key modules of the software on the MIC coprocessor. We use OpenMP to develop parallel optimization for the Crystal-KMC, combined with existing MPI inter-process communication optimization, finally achieving hybrid parallel optimization. The experimental results show that in the single-node CPU and MIC collaborative parallel mode, the speedup of the calculation hotspot reaches 30.1, and the speedup of the overall software reaches 7.43. Speedup ; Bottleneck ; Computer science ; Coprocessor ; Software ; Kinetic Monte Carlo ; Computational science ; Parallel computing ; Monte Carlo method ; Embedded system ; Operating system Nuclear Materials and Properties ; Nuclear reactor physics and engineering ; Graphite, nuclear technology, radiation studies
Authors: Morad Biagooi | Mohammad Samanipour | S. Alireza Ghasemi | SeyedEhsan Nedaaee Oskoee
Source: AIP Advances (article, 2020-03-01)
Field: Chemistry — Physical and Theoretical Chemistry

CAVIAR: A simulation package for charged particles in environments surrounded by conductive boundaries We introduce CAVIAR, new scientific software that is developed for molecular simulation of ionic-liquids or charged colloids inside conductive boundaries. CAVIAR imports computer-aided-design geometries and uses them to simulate boundary walls. Then based on this geometry, a finite element mesh is generated and utilized for solving the Poisson equation. To avoid the complexity due to the singularity of point charges, we propose a new method, using the advantages of the superposition theorem of the linear partial differential equations. Within this paper, the CAVIAR structure, its features, and basic scientific algorithms are discussed. Superposition principle ; Singularity ; Gravitational singularity ; Boundary value problem ; Finite element method ; Partial differential equation ; Electrical conductor ; Point (geometry) ; Boundary (topology) ; Poisson's equation ; Computer science ; Differential equation ; Computational science ; Geometry ; Mathematical analysis ; Physics ; Mathematics ; Quantum mechanics ; Thermodynamics Electrostatics and Colloid Interactions ; Electrohydrodynamics and Fluid Dynamics ; Aerosol Filtration and Electrostatic Precipitation
Authors: Sadella C. Santos | John J. La Scala | Giuseppe R. Palmese
Source: Polymers (article, 2020-12-21)
Field: Materials Science — Polymers and Plastics

Effect of Microcapsule Content on Diels-Alder Room Temperature Self-Healing Thermosets A furan functionalized epoxy-amine thermoset with an embedded microcapsule healing system that utilizes reversible Diels-Alder healing chemistry was used to investigate the influence of microcapsule loading on healing efficiency. A urea-formaldehyde encapsulation technique was used to create capsules with an average diameter of 150 µm that were filled with a reactive solution of bismaleimide in phenyl acetate. It was found that optimum healing of the thermoset occurred at 10 wt% microcapsule content for the compositions investigated. The diffusion of solvent through the crack interface and within fractured samples was investigated using analytical diffusion models. The decrease in healing efficiency at higher microcapsule loading was attributed partially to solvent-induced plasticization at the interface. The diffusion analysis also showed that the 10% optimum microcapsule concentration occurs for systems with the same interfacial solvent concentration. This suggests that additional physical and chemical phenomena are also responsible for the observed optimum. Such phenomena could include a reduction in surface area available for healing and the saturation of interfacial furan moieties by reaction with increasing amounts of maleimide. Both would result from increased microcapsule loading. Thermosetting polymer ; Materials science ; Solvent ; Self-healing material ; Epoxy ; Maleimide ; Self-healing ; Chemical engineering ; Furan ; Plasticizer ; Polymer chemistry ; Composite material ; Organic chemistry ; Chemistry Polymer composites and self-healing ; Lignin and Wood Chemistry ; Flame retardant materials and properties
Authors: David Uhrig | G. V. M. Williams | Gabriel Bioletti | Shen V. Chong
Source: Superconductor Science and Technology (article, 2020-03-04)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Residual oxygen responsible for universal superconducting phase diagram in annealed FeSe <sub> 1− <i>x</i> </sub> Te <i> <sub>x</sub> </i> Abstract We report the results from a comprehensive study of the effect that annealing FeSe 0.35 Te 0.65 single crystals in different atmospheres has on the surface chemistry, the superconducting transition temperature, T c , and the critical current density, J c . A review of the literature and our data shows that annealing in oxygen, nitrogen, air or vacuum atmosphere leads to a universal superconducting phase diagram that is independent of the variance in the as-grown properties. We show that atmospheres with an oxygen partial pressure of p &gt; 10 −3 hPa during annealing are necessary to improve the superconducting properties in this compound. This is demonstrated by Raman and magnetisation measurements on air, nitrogen, or low vacuum annealed FeSe 0.35 Te 0.65 samples, which show that the improvement in the superconducting properties is strongly correlated to the formation of a thin iron oxide surface layer. However, annealing under high vacuum does not lead to the formation of an iron oxide layer and no improvement in the superconducting properties is observed. Our findings show that the previously reported improvements in the superconducting properties after annealing under vacuum or in nitrogen are thus likely to have been caused by residual oxygen. Furthermore, we propose a diffusion model for the formation of the iron oxide layer as the driving force for the reduction of interstitial excess iron that suppresses superconductivity in this compound. Overall, our results show that the presence of an iron reactant, such as oxygen, during annealing is necessary to improve the superconducting properties of FeSe 1− x Te x . Annealing (glass) ; Superconductivity ; Materials science ; Oxygen ; Oxide ; Phase diagram ; Nitrogen ; Condensed matter physics ; Iron oxide ; Analytical Chemistry (journal) ; Phase (matter) ; Metallurgy ; Chemistry ; Physics Iron-based superconductors research ; Physics of Superconductivity and Magnetism ; Rare-earth and actinide compounds