jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Qian Xie | Ruanqi Wu | Xiaoxiao Zhong | Yanhong Dong | Q H Fan
Source: RSC Advances (article, 2018-01-01)
Field: Chemistry — Analytical Chemistry

Real-time simultaneous detection of microbial contamination and determination of an ultra low-content active pharmaceutical ingredient in tazarotene gel by near-infrared spectroscopy This paper proposes and proves a real-time and non-destructive strategy for sensitive and simultaneous detection of microbial contamination and determination of an ultra low-content active pharmaceutical ingredient in tazarotene gel by near-infrared (NIR) spectroscopy. In this experiment, 88 samples of tazarotene gel (0.41-0.65 mg g<sup>-1</sup> of tazarotene) were prepared using the standard addition method. Among them, 47 samples were inoculated with 50 μl of different concentrations of <i>Escherichia coli</i> (<i>E. coli</i>) DH5a in Luria-Bertani (LB) broth to give 1-4 log CFU g<sup>-1</sup> of <i>E. coli</i> DH5a in the gel, 6 samples with 50 μl of LB broth, and 35 samples with nothing. Based on the gel NIR transflectance spectra, <i>E. coli</i> DH5a in the gel was detected by the counter propagation artificial neural network (CP-ANN) model with a classification accuracy of 100.0%, while tazarotene in the gel was simultaneously determined by the partial least squares regression (PLS) model with a root mean square error of cross-validation of 0.0232 mg g<sup>-1</sup>. Furthermore, 9 samples of real tazarotene gel were used to verify the practicality of the established NIR spectroscopy. The developed NIR strategy can be used to correctly and quickly release the pharmaceutical gels, required for sensitive and simultaneous control of microbial contamination and the active pharmaceutical ingredient (API) content, to the next stage. Active ingredient ; Ingredient ; Tazarotene ; Contamination ; Chemistry ; Chromatography ; Food science ; Dermatology ; Biology ; Medicine Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Essential Oils and Antimicrobial Activity
Authors: Kaoru Ohno | Aaditya Manjanath | Yoshiyuki Kawazoe | Rikizo Hatakeyama | Fuminori Misaizu | Eunsang Kwon | Hiroshi Fukumura | Hirohito Ogasawara | Y. Yamada | Chao Zhang | Naoya Sumi | T. Kamigaki | Keiji Kawachi | K. Yokoo | Shintaro Ono | Yasuhiko Kasama
Source: Nanoscale (article, 2018-01-01)
Field: Chemistry — Organic Chemistry

Extensive first-principles molecular dynamics study on Li encapsulation into C<sub>60</sub> and its experimental confirmation The aim of increasing the production ratio of endohedral C<sub>60</sub> by impinging foreign atoms against C<sub>60</sub> is a crucial matter of the science and technology employed towards industrialization of these functional building block materials. Among these endohedral fullerenes, Li<sup>+</sup>@C<sub>60</sub> exhibits a wide variety of physical and chemical phenomena and has the potential to be applicable in areas spanning the medical field to photovoltaics. However, currently, Li<sup>+</sup>@C<sub>60</sub> can be experimentally produced with only ∼1% ratio using the plasma shower method with a 30 eV kinetic energy provided to the impinging Li<sup>+</sup> ion. From extensive first-principles molecular dynamics simulations, it is found that the maximum production ratio of Li<sup>+</sup>@C<sub>60</sub> per hit is increased to about 5.1% (5.3%) when a Li<sup>+</sup> ion impinges vertically on a six-membered ring of C<sub>60</sub> with 30 eV (40 eV) kinetic energy, although many C<sub>60</sub> molecules are damaged during this collision. On the contrary, when it impinges vertically on a six-membered ring with 10 eV kinetic energy, the production ratio remains at 1.3%, but the C<sub>60</sub> molecules are not damaged at all. On the other hand, when the C<sub>60</sub> is randomly oriented, the production ratio reduces to about 3.7 ± 0.5%, 3.3 ± 0.5%, and 0.2 ± 0.03% for 30 eV, 40 eV, and 10 eV kinetic energy, respectively. Based on these observations we demonstrate the possibility of increasing the production ratio by fixing six-membered rings atop C<sub>60</sub> using the Cu(111) substrate or UV light irradiation. In order to assess the ideal experimental production ratio, the <sup>7</sup>Li solid NMR spectroscopy measurement is also performed for the multilayer randomly oriented C<sub>60</sub> sample irradiated by Li<sup>+</sup> using the plasma shower method combined with inductively coupled plasma atomic emission spectroscopy (ICP-AES). Time-of-flight mass spectroscopy measurements are also performed to cross check whether Li<sup>+</sup>@C<sub>60</sub> molecules are produced in the sample. The resulting experimental estimate, 4% for 30 eV incident kinetic energy, fully agrees with our simulation results mentioned above, suggesting the consistency and accuracy of our simulations and experiments. Encapsulation (networking) ; Molecular dynamics ; Materials science ; Nanotechnology ; Chemistry ; Computational chemistry ; Computer science Fullerene Chemistry and Applications ; Graphene research and applications ; Boron and Carbon Nanomaterials Research
Authors: Roberto Li Voti
Source: International Journal of Thermophysics (article, 2018-01-04)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Optimization of Perfect Absorbers with Multilayer Structures Emissivity ; Materials science ; Broadband ; Low emissivity ; Optics ; Range (aeronautics) ; Thermal ; Optoelectronics ; Tin ; Optimal design ; Solar energy ; Layer (electronics) ; Energy (signal processing) ; Physics ; Computer science ; Nanotechnology ; Composite material Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Advanced Materials and Mechanics
Authors: Mirco Michel | David Menéndez Hurtado | Arne Elofsson
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2018-08-02)
Field: Materials Science — Materials Chemistry

PconsC4: fast, free, easy, and accurate contact predictions Abstract Motivation Residue contact prediction was revolutionized recently by the introduction of direct coupling analysis (DCA). Further improvements, in particular for small families, have been obtained by the combination of DCA and deep learning methods. However, existing deep learning contact prediction methods often rely on a number of external programs and are therefore computationally expensive. Results Here, we introduce a novel contact predictor, PconsC4, which performs on par with state of the art methods. PconsC4 is heavily optimized, does not use any external programs and therefore is significantly faster and easier to use than other methods. Availability PconsC4 is freely available under the GPL license from https://github.com/ElofssonLab/PconsC4 . Installation is easy using the pip command and works on any system with Python 3.5 or later and a modern GCC compiler. Contact arne@bioinfo.se Python (programming language) ; Computer science ; License ; MIT License ; Compiler ; Deep learning ; Artificial intelligence ; Programming language ; Machine learning ; Operating system Machine Learning in Materials Science ; Software Engineering Research ; Protein Structure and Dynamics
Authors: Emel Önal
Source: Advances in Materials Science and Engineering (article, 2018-01-01)
Field: Materials Science — Materials Chemistry

Breakdown Mechanism of Different Sulphur Hexafluoride Gas Mixtures Sulphur hexafluoride (SF 6 ) gas and SF 6 gas mixtures are widely used in gas‐insulated systems (GIS) because they have good dielectric and thermal properties. Among the various gas mixtures investigated so far, SF 6 ‐air, SF 6 ‐CO 2 , and SF 6 ‐N 2 are most used gas mixtures. Also, these mixtures have much technical superiority in GIS. These are nontoxic and nonflammable gases, and they have less sensitivity to nonuniformities and higher liquefaction temperature at high pressure. GIS, switchgears, circuit breakers, and substations are systems that work with alternating current and have nonuniform electric fields. For this reason, in this study the breakdown mechanisms of 0.125, 0.5, 1, and 20% SF 6 gas mixtures with rod‐plane configuration under AC voltage are investigated and explained breakdown mechanism. Sulfur hexafluoride ; Materials science ; Mechanism (biology) ; Sulfur ; Organic chemistry ; Metallurgy ; Physics High voltage insulation and dielectric phenomena ; ZnO doping and properties ; Plasma Applications and Diagnostics
Authors: Diego Manuel Martínez Gila | Pablo Cano Marchal | Juan Gómez Ortega | Javier Gámez García
Source: Sensors (article, 2018-03-25)
Field: Chemistry — Analytical Chemistry

Non-Invasive Methodology to Estimate Polyphenol Content in Extra Virgin Olive Oil Based on Stepwise Multilinear Regression Normally the olive oil quality is assessed by chemical analysis according to international standards. These norms define chemical and organoleptic markers, and depending on the markers, the olive oil can be labelled as lampante, virgin, or extra virgin olive oil (EVOO), the last being an indicator of top quality. The polyphenol content is related to EVOO organoleptic features, and different scientific works have studied the positive influence that these compounds have on human health. The works carried out in this paper are focused on studying relations between the polyphenol content in olive oil samples and its spectral response in the near infrared spectra. In this context, several acquisition parameters have been assessed to optimize the measurement process within the virgin olive oil production process. The best regression model reached a mean error value of 156.14 mg/kg in leave one out cross validation, and the higher regression coefficient was 0.81 through holdout validation. Organoleptic ; Polyphenol ; Olive oil ; Context (archaeology) ; Food science ; Mathematics ; Olea ; Regression analysis ; Quality (philosophy) ; Chemistry ; Statistics ; Biology ; Botany ; Biochemistry Spectroscopy and Chemometric Analyses ; Edible Oils Quality and Analysis ; Advanced Chemical Sensor Technologies
Authors: Mohammad Nazmul Hossain | Mohammad Nashir | Mohammad Mainul Karim | Ajoy Kumar Das | Ashequl Alam Rana | Rumana Akther Jahan
Source: Journal of Scientific and Innovative Research (article, 2018-06-30)
Field: Chemistry — Analytical Chemistry

Prediction of viscosity index of motor oils using FTIR spectral data and chemometrics In order to ensure the quality of motor oils by measuring viscosity index (VI), regulatory agencies and producers need a more precise, easy and cost effective method for monitoring the qualities. Multivariate data analysis based on Fourier transform infrared (FTIR) spectroscopy was reported in this work as an alternative for measuring viscosity index of motor oils. 27 samples of motor oils of different brands were collected from different regions of Bangladesh. Viscosity index of the samples were first determined by the conventional technique. Savitzky-Golay (S-G), smoothing and mean normalization are the three distinct data preprocessing methods and these were assessed to measure their efficiencies by applying them in developing calibration procedures prior to modeling. Artificial neural network (ANN), principal component regression (PCR) and partial least-square regression (PLSR) were then developed using these processed data for determination of viscosity index of motor oils. Results showed that PCR performed best when it used Savitzky-Golay smoothing data. Performance of PLSR was slightly more than that of PCR (R2≈ 98%). PLSR (R2≈ 99%) had better predictive performance comparing to ANN (R2≈ 97%). Among the calibration techniques studied here, PLSR showed the best prediction results with Savitzky-Golay smoothed FTIR spectral data. The method proposed here to determine viscosity index of motor oils requires less staff dedication, shorter turnaround times and lower expenses than conventional approaches. Partial least squares regression ; Chemometrics ; Principal component analysis ; Viscosity index ; Smoothing ; Mathematics ; Fourier transform infrared spectroscopy ; Calibration ; Viscosity ; Multivariate statistics ; Principal component regression ; Analytical Chemistry (journal) ; Statistics ; Biological system ; Chemistry ; Chromatography ; Materials science ; Engineering ; Biology Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Advanced Chemical Sensor Technologies
Authors: Mustafa Nevzat Örnek
Source: International Journal of Intelligent Systems and Applications in Engineering (article, 2018-06-29)
Field: Chemistry — Analytical Chemistry

Determining the Carrot Volume via Radius and Length Using ANN In this study a total of 464 carrots were taken from Kaşınhanı, where the most carrots are produces in Turkey. The length and radiuses with an interval of 5 cm and volume were measured and recorded. Three different Artificial Neural Network models: BP, LM and PUNN were designed for predicting the carrot volume. To assess the success of the system, statistical measures such as Root Mean Squared Error, Mean Absolute Error and R2 were used. The results were showed that all three methods are successful in this problem, while LM and PUNN seems bit. RADIUS ; Mean squared error ; Volume (thermodynamics) ; Artificial neural network ; Computer science ; Mean absolute error ; Square root ; Statistics ; Approximation error ; Statistical error ; Root mean square ; Algorithm ; Mathematics ; Artificial intelligence ; Physics ; Geometry ; Thermodynamics Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI
Authors: Md. Faizul Islam | Mohammad Nashir Uddin | Ashequl Alam Rana | Mohammad Mainul Karim
Source: Journal of Scientific and Innovative Research (article, 2018-06-30)
Field: Chemistry — Analytical Chemistry

Development of a chemometric method for the analysis of Sudan III-IV dyes adulteration in chili powder using UV-visible spectroscopy data Chili powder is a globally traded commodity and one of the most important parts of regular diet of the people of Bangladesh. It is reported that chili power has been adulterated by Sudan III-IV dyes since 2003. A simple, fast and cost effective method for the identification of Sudan dyes (III and IV) present in chili powder was proposed here and the method was based on the characterization of UV-visible spectral data using artificial neural network (ANN). Artificial neural network (ANN) was developed for the simultaneous assay of chili powder adulterated with Sudan III-IV. 47 standard mixture solutions were prepared using orthogonal experimental design (OED) to build a calibration data set. UV-visible spectra of these mixtures were obtained between 200 and 800 nm at 1 nm interval. The results of the artificial neural network were compared with that of other two calibration techniques namely, principal component regression (PCR) and partial least square regression (PLSR). ANN shows better prediction efficiencies comparing with PCR and PLSR. Prediction by ANN on the basis of spectroscopic data is 85% for chili powder, 70% for Sudan III and 60% for Sudan IV in terms of coefficient of determination (R2 ). Six different branded chili powders collected from the local market, and were measured by using the proposed method. It was found that no samples contained Sudan III-IV. So, the proposed method can be easily used in the quality control of any chili powder adulterated with Sudan IIIIV dyes as an alternative analysis tool. Partial least squares regression ; Calibration ; Principal component analysis ; Ultraviolet visible spectroscopy ; Principal component regression ; Artificial neural network ; Analytical Chemistry (journal) ; Materials science ; Mathematics ; Chromatography ; Chemistry ; Computer science ; Statistics ; Artificial intelligence Dye analysis and toxicity ; Biochemical Analysis and Sensing Techniques ; Advanced Chemical Sensor Technologies
Authors: Yuedan Liu | Chunlei Xia | Zhongya Fan | Renren Wu | Xianglin Chen | Liu Zuo-yi
Source: Journal of Toxicology (article, 2018-02-26)
Field: Chemistry — Analytical Chemistry

Implementation of Fractal Dimension and Self-Organizing Map to Detect Toxic Effects of Toluene on Movement Tracks of<i> Daphnia magna</i> Movement behaviors of an indicator species, <i>Daphnia magna</i>, in response to contaminants have been implemented to monitor environmental disturbances. Complexity in movement tracks of <i>Daphnia magna</i> was characterized by use of fractal dimension and self-organizing map. The individual movement tracks of <i>D. magna</i> were continuously recorded for 24 hours before and after treatments with toluene at the concentration of 10 mg/L, respectively. The general complexity in movement tracks (10 minutes) was characterized by fractal dimension. Results showed that average fractal dimension of movement tracks was decreased from 1.62 to 1.22 after treatments. The instantaneous movement parameters of movement segments in 5 s were input into the self-organizing map to investigate the swimming pattern changes under stresses of toluene. Abnormal behaviors of <i>D. magna</i> are more frequently observed after treatments than before treatments. Computational methods in ecological informatics could be utilized to obtain the useful information in behavioral data of <i>D. magna</i> and would be further applied as an in situ monitoring tool in water environment. Daphnia magna ; Fractal dimension ; Dimension (graph theory) ; Toluene ; Fractal ; Movement (music) ; Artificial intelligence ; Cartography ; Pattern recognition (psychology) ; Computer science ; Geology ; Geography ; Mathematics ; Physics ; Chemistry ; Mathematical analysis ; Toxicity ; Combinatorics Spectroscopy and Chemometric Analyses
Authors: Fashui Hong | Yingjun Zhou | Jianhui Ji | Ling Wang
Source: Journal of Biomedical Sciencies (article, 2018-01-01)
Field: Materials Science — Materials Chemistry

Maternal Exposure to Nano Titanium Dioxide Induces Neurotoxic Effects in Offspring Mice Although nano-TiO 2 has been extensively used in food industrial application, and in daily products for infants and children, its potential neurotoxicity presents a significant concern. As previous studies have demonstrated the neurological effects of nano-TiO 2 in mice, the main objective of the current investigation was to establish the effects of prenatal exposure of nano-TiO 2 on developing embryos and offspring. ICR female mice were orally administered (1, 2, and 3 mg/kg body weight) nano-TiO 2 from prenatal day 2 to postnatal day 21. Morphological changes, learning and memory, and potential target molecules of neurodevelopmental toxicity in offspring mice of nano-TiO 2 -exposed mothers were examined. The results showed that nano-TiO 2 could translocate from prenatally exposed maternal to offspring hippocampi, resulting in hippocampal damage including: a 29.07%-61.4% reduction in spatial recognition; a 22.55% -61.34% reduction in total dendritic length; a 53.57%-71.42% reduction in dendritic branch number; and a 27.72%-75.74% reduction in spine density in offspring CA1 pyramidal cells. Furthermore, expression of several proteins involved in dendritic development was decreased including: a 47.62%-73.81% in microtubule-associated proteins; a 14.58%-54.17% in mitotic kinesin-like protein 1; a 1.14%-31.82% in collapsin response mediator protein 3; a 65.17%-79.05% in neuregulin tyrosine kinase receptor 4; a 1.13%-76.92% in kinesin superfamily protein 17; and a 25.73%-61.4% in post synaptic density protein -95 in offspring hippocampi. Hippocampal neurons may present a major target of neurotoxicity in offspring following maternal exposure to nano-TiO 2 during the prenatal period. Therefore, food application of nano-TiO 2 should be performed with caution. Offspring ; Titanium dioxide ; Toxicology ; Nano- ; Medicine ; Biology ; Pregnancy ; Materials science ; Metallurgy ; Genetics Nanoparticles: synthesis and applications ; Anesthesia and Neurotoxicity Research
Authors: Skripsi Dan | Fazida Hanim Hashim | Thinal Raj | Aqilah Baseri Huddin | Amna Hussain
Source: International Journal of Engineering & Technology (article, 2018-10-02)
Field: Chemistry — Analytical Chemistry

Classification of Oil Palm Fresh Fruit Bunches (FFB) Using Raman Spectroscopy The current practice in determining oil palm fresh fruit bunches (FFB) ripeness is by its colour which could be inaccurate. This study investigates the classification of oil palm FFB ripeness using Raman spectroscopy. A feature extraction model is developed based on the different organic compositions that contribute to the ripeness classification. Samples are collected according to the Malaysian Palm Oil Board (MPOB) standards which are unripe, underripe, ripe, overripe, and rotten. Different characteristics of the Raman shift were detected which represent the material composition for each sample. The Raman intensity of the oil palm fruit increases from unripe to ripe before decreasing to rotten due to the carotenoid content in the fruit. In conclusion, Raman spectroscopy is a suitable technique to observe the changes in the composition of oil palm fruit classified by its ripeness.Â Â Ripeness ; Palm oil ; Raman spectroscopy ; Palm ; Bunches ; Horticulture ; Chemistry ; Food science ; Botany ; Environmental science ; Materials science ; Ripening ; Biology ; Optics ; Physics Spectroscopy and Chemometric Analyses ; Oil Palm Production and Sustainability ; Coconut Research and Applications
Authors: Miguel Á. G. Aranda
Source: Journal of Applied Crystallography (article, 2018-11-28)
Field: Materials Science — Materials Chemistry

Sharing powder diffraction raw data: challenges and benefits Scientific data are as important as scientific publications. If this statement holds true, why are we not routinely sharing scientific data? The tools are now out there, for instance Zenodo and related repositories. It could be a lack of motivation of researchers derived from an apparent lack of short-term reward. Here the author will try to show the importance of sharing ready-to-analyse raw powder diffraction data with immediate benefits for authors and for the wider community. Moreover, it is speculated that sharing curated scientific data may have more important medium-term benefits, including credibility and not least reproducibility. Raw data sharing is coming. Raw data ; Credibility ; Data sharing ; Term (time) ; Statement (logic) ; Computer science ; Data science ; Raw material ; Chemistry ; Political science ; Physics ; Medicine X-ray Diffraction in Crystallography ; Cultural Heritage Materials Analysis
Authors: Matteo Stocchero | Samantha Riccadonna | Pietro Franceschi
Source: Journal of Chemometrics (article, 2018-05-01)
Field: Chemistry — Analytical Chemistry

Projection to latent structures with orthogonal constraints for metabolomics data Starting from OSC filters theory, we have formulated a general framework integrating orthogonal constraints within standard projection multivariate techniques.Orthogonally constrained PCA (oCPCA) and orthogonally constrained PLS2 (oCPLS2), a more general formulation of orthogonal PLS (OPLS) and post-transformation of PLS2 (ptPLS2), orthogonal two-block PLS (O2PLS), and orthogonal Wold's two-block Mode A PLS (OPLS-W2A) are presented within the same theoretical framework.Algorithms, mathematical properties, limit cases, and comparison with existing methods are also discussed. Computer science ; Principal component analysis ; Block (permutation group theory) ; Multivariate statistics ; Data mining ; Algorithm ; Data science ; Mathematics ; Artificial intelligence ; Machine learning Spectroscopy and Chemometric Analyses ; Metabolomics and Mass Spectrometry Studies ; Advanced Chemical Sensor Technologies