jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Kusnaeni Kusnaeni | Agus Mohamad Soleh | Farit Mochamad Afendi | Bagus Sartono
Source: BAREKENG JURNAL ILMU MATEMATIKA DAN TERAPAN (article, 2022-06-01)
Field: Chemistry — Analytical Chemistry

FUNCTION GROUP SELECTION OF SEMBUNG LEAVES (BLUMEA BALSAMIFERA) SIGNIFICANT TO ANTIOXIDANTS USING OVERLAPPING GROUP LASSO Functional groups of sembung leaf metabolites can be detected using FTIR spectrometry by looking at the spectrum's shape from specific peaks that indicate the type of functional group of a compound. There were 35 observations and 1866 explanatory variables (wavelength) in this study. The number of explanatory variables more than the number of observations is high-dimensional data. One method that can be used to analyze high-dimensional data is penalized regression. The overlapping group lasso method is a development of the group-based penalized regression method that can solve the problem of selecting variable groups and members of overlapping groups of variables. The results of selecting the variable groups using the overlapping group lasso method found that the functional groups that were significant for the antioxidants of sembung leaves were C=C Unstructured, CN amide, Polyphenol, Sio2. Lasso (programming language) ; Group (periodic table) ; Group selection ; Feature selection ; Regression analysis ; Mathematics ; Function (biology) ; Regression ; Selection (genetic algorithm) ; Linear regression ; Statistics ; Chemistry ; Computer science ; Artificial intelligence ; Biology ; Evolutionary biology ; Organic chemistry Spectroscopy and Chemometric Analyses
Authors: James R Capers | Stephen J. Boyes | Alastair P. Hibbins | S. A. R. Horsley
Source:  (preprint, 2022-03-31)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Designing metasurfaces to manipulate antenna radiation Designer manipulation of light at the nanoscale is key to several next–generation technologies, from sensing to optical computing. One way to manipulate light is to design a material structured at the sub–wavelength scale, a metamaterial, to have some desired scattering effect. Metamaterials typically have a very large number of geometric parameters than can be tuned, making the design process difficult. Existing design paradigms either neglect degrees of freedom or rely on numerically expensive full–wave simulations. In this work, we derive a simple semi–analytic method for designing metamaterials built from sub–wavelength elements with electric and magnetic dipole resonances. This is relevant to several experimentally accessible regimes. To demonstrate the versatility of our method, we apply it to three problems: the manipulation of the coupling between nearby emitters, focusing a plane wave to a single point and designing a dielectric antenna with a particular radiation pattern. Metamaterial ; Antenna (radio) ; Computer science ; Wavelength ; Radiation pattern ; Coupling (piping) ; Optics ; Electromagnetic radiation ; Physics ; Telecommunications ; Engineering Metamaterials and Metasurfaces Applications ; Plasmonic and Surface Plasmon Research ; Millimeter-Wave Propagation and Modeling
Authors: Christopher D. Delhom | John D. Wanjura | Mathew G. Pelletier | Gregory Holt | Eric Héquet
Source: Research Square (preprint, 2022-09-27)
Field: Materials Science — Polymers and Plastics

Investigation into a practical approach and application of cotton fiber elongation Abstract The strength of cotton fiber has been extensively studied and significantly improved through selective breeding, but fiber elongation has largely been ignored, even though elongation contributes to determining the energy needed to break fibers. Recent developments to calibrate the High Volume Instrument (HVI) for elongation has renewed interest in elongation. However, it is not understood how best to utilize yet another fiber property which has the potential to add to the complexity of fiber selection. To explore a practical approach to applying elongation, cotton samples were tested using single fiber methods, the Stelometer, and the HVI. Comparison of strength, elongation, and combined properties such as modulus were explored. HVI testing was shown to be sensitive enough to characterize elongation differences but unlike single fiber testing it was unable to capture within-sample variation. Fiber bundle testing, like Stelometer and HVI was shown to reduce bias due to fiber selection. The use of secant modulus, an intrinsic material property, allowed for one value to represent both strength and elongation. Secant modulus was shown to contain more useful information than either elongation or work-to-break. Work-to-break was shown to be more influenced by a specific value of breaking force or elongation rather than the intrinsic behavior of the sample being tested.Exploring the influence of genetics and environment on elongation, and its interaction with other fiber properties, requires additional work. Secant modulus, by combining strength and elongation into one value, shows the potential to incorporate elongation values into fiber characterization without increasing the complexity of current fiber selection processes. Elongation ; Fiber ; Computer science ; Agricultural engineering ; Materials science ; Engineering ; Composite material ; Ultimate tensile strength Textile materials and evaluations
Authors: Wern Huay Mah | Nadzran Hafiy Ahmad Nazuan | Wei Sheung Yeap | Farah Hasyeena Fakharudin | Ibrahima Faye | Cecilia Devi Wilfred
Source: Comptes Rendus Chimie (article, 2022-02-23)
Field: Chemistry — Spectroscopy

Deciding which is the best <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msup> <mml:mrow/> <mml:mn>1</mml:mn> </mml:msup> <mml:mtext>H</mml:mtext> </mml:mrow> </mml:math> NMR predictor for organic compounds using statistical tools <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msup> <mml:mrow/> <mml:mn>1</mml:mn> </mml:msup> <mml:mtext>H</mml:mtext> </mml:mrow> </mml:math> NMR chemical shifts for 30 organic compounds (396 data points) were predicted using four NMR predictor software and compared with the experimental data from SDBS. The NMR predictors involved were MestReNova, ChemDraw, NMRShiftDB and ACD Workbook Suite. Root mean square deviation (RMSD) and mean absolute percentage error (MAPE) were calculated from the data obtained. One-way analysis of variance (ANOVA), Tukey’s honestly significant difference (HSD) and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>t</mml:mi> </mml:math> -test were carried out to analyse the statistical significance of the differences between the predictors. The results from the statistical analysis were used to predict chemical shifts of three organic compounds. Mathematics ; Statistics ; Analysis of variance ; Mean squared error ; Analytical Chemistry (journal) ; Chemistry ; Artificial intelligence ; Computer science ; Chromatography Molecular spectroscopy and chirality ; Metabolomics and Mass Spectrometry Studies ; Computational Drug Discovery Methods
Authors: Doaa Abd-El-Galiel | Ahmed El-Matarawy | Eman Mohy El-Dien
Source: Journal of Advanced Research in Fluid Mechanics and Thermal Sciences (article, 2022-08-13)
Field: Chemistry — Physical and Theoretical Chemistry

Determination of Al2O3 Powder Thermal Conductivity Using DSC at NIS-Egypt The mission of the thermal metrology laboratory is to maintain, disseminate, develop and realize the International Temperature Scale 1990 (ITS-90). One of the services that the laboratory has introduced is the routine calibration to all industrial sectors that covers almost all fields inside and outside Egypt. This paper explains how to use Differential Scanning Calorimeter (DSC) to determine the thermal conductivity of unknown powders. The paper is based on the ability to determine the thermal conductivity (k) of powders from the melting peak of the reference metal. This technique assists for the first time to establish a new activity at the National Institute for Standardization to test the thermal conductivity of powders, which had been requested by many clients. Experiments were carried out using alumina powder Al2O3 and metal reference beads of Sn and Zn which have diameter ranges from 1.9 mm up to 4.12 mm in an atmosphere of nitrogen during Sn and Zn melting. The results show good performance. The results showed confidence that will enable to do more studies at NIS to see if this technology can be applied to a wider spectrum of materials. Thermal conductivity ; Differential scanning calorimetry ; Materials science ; Metrology ; Calibration ; Standardization ; Calorimeter (particle physics) ; Thermal conductivity measurement ; Thermal ; Conductivity ; Analytical Chemistry (journal) ; Mineralogy ; Metallurgy ; Composite material ; Computer science ; Chemistry ; Thermodynamics ; Optics ; Physics ; Environmental chemistry ; Telecommunications thermodynamics and calorimetric analyses ; Calibration and Measurement Techniques
Authors: Daniel Nicholls | Jack Wells | Alex W. Robinson | Amirafshar Moshtaghpour | Maryna Kobylynska | Roland A. Fleck | Angus I. Kirkland | Nigel D. Browning
Source: arXiv (Cornell University) (preprint, 2022-11-07)
Field: Materials Science — Surfaces, Coatings and Films

A Targeted Sampling Strategy for Compressive Cryo Focused Ion Beam Scanning Electron Microscopy Cryo Focused Ion-Beam Scanning Electron Microscopy (cryo FIB-SEM) enables three-dimensional and nanoscale imaging of biological specimens via a slice and view mechanism. The FIB-SEM experiments are, however, limited by a slow (typically, several hours) acquisition process and the high electron doses imposed on the beam sensitive specimen can cause damage. In this work, we present a compressive sensing variant of cryo FIB-SEM capable of reducing the operational electron dose and increasing speed. We propose two Targeted Sampling (TS) strategies that leverage the reconstructed image of the previous sample layer as a prior for designing the next subsampling mask. Our image recovery is based on a blind Bayesian dictionary learning approach, i.e., Beta Process Factor Analysis (BPFA). This method is experimentally viable due to our ultra-fast GPU-based implementation of BPFA. Simulations on artificial compressive FIB-SEM measurements validate the success of proposed methods: the operational electron dose can be reduced by up to 20 times. These methods have large implications for the cryo FIB-SEM community, in which the imaging of beam sensitive biological materials without beam damage is crucial. Focused ion beam ; Materials science ; Scanning electron microscope ; Nanoscopic scale ; Leverage (statistics) ; Compressed sensing ; Ion beam ; Electron beam-induced deposition ; Sampling (signal processing) ; Beam (structure) ; Nanotechnology ; Optics ; Ion ; Computer science ; Artificial intelligence ; Scanning transmission electron microscopy ; Composite material ; Chemistry ; Physics ; Detector Electron and X-Ray Spectroscopy Techniques ; Integrated Circuits and Semiconductor Failure Analysis ; Advanced Electron Microscopy Techniques and Applications
Authors: Emine Kanberoğlu | Ayçin Asma | Naz KADINKIZ | Ertuğrul Polat | Muhammet Uzun
Source: Tekstilna industrija (article, 2022-01-01)
Field: Materials Science — Polymers and Plastics

Design and characterization of Tencel-based Seersucker fabrics Seersucker fabric design features a new combination of fabric structures that can also be used in various yarns based on sustainable fibers. Such fabric structures attract attention mainly due to their comfort properties, as well as easy-care clothing. One of the most commonly used regenerated fibers is Tencel, which is also known as lyocell fiber. Tencel is produced by using eucalyptus trees. Tencel has a number of applications, such as denim fabrics, pants, t-shirts, silky underwear, etc. It is also important to note that Tencel fiber-based new design approaches based on Tencel fibers are gaining attention in the context of circular design thinking. In this study, the effect of the same blend ratio of Tencel on different puckering surface designs was used, and the key properties of the designed fabrics were tested and analyzed. The principal objective is to apply the properties of Tencel fibers to improve the structural comfort of seersucker fabrics. The manufacturing process of the designed fabrics was optimized after the initial tests with the settings of the loom and the number of warp and weft threads. After 30 different process combinations, 6 different fabrics were selected for production. The structural properties of the 6 different patterns were successfully standardized and their structural properties were examined. Lyocell ; Yarn ; Composite material ; Fiber ; Materials science ; Denim ; Context (archaeology) ; Fabric structure Textile materials and evaluations ; Additive Manufacturing and 3D Printing Technologies ; Natural Fiber Reinforced Composites
Authors: Ali Khumaidi | Ridwan Raafi’udin
Source: International Journal on Advanced Science Engineering and Information Technology (article, 2022-05-01)
Field: Chemistry — Analytical Chemistry

Effects of Oversampling Smote and Spectral Transformations in the Classification of Mango Cultivars Using Near-Infrared Spectroscopy Near-Infrared spectroscopy (NIR) is a non-destructive analytical technique that can provide chemical and structural information on samples in a speedy and accurate time. NIR has a wavelength of 750-2500 nm. However, the absorbance bands of the NIR spectrum are often broad, non-specific, and overlapping. NIR spectrum analysis requires a multivariate method which is very subjective to noise arising from instrumentation. There is no standard protocol in modeling for classification and prediction using NIR spectra. Several models have been developed with and without pre-processing techniques. The SMOTE technique can improve the model to predict all class responses accurately. This research contributes to creating a multiclass classification model for grouping mango cultivars by finding the best pre-processing technique and using SMOTE oversampling. The results of the four test scenarios on the model's performance built using the Support Vector Machine (SVM) that the best model is obtained using spectral transformations with LSNV and CLIP operations with 100% accuracy, precision, and recall values. The Decision Tree (DT) has the performance results in 100% model was obtained by using spectral transformation with LSNV, CLIP and SAVGOL operations with parameters {'deriv_order': 0,1, 2, 'filter_win': 11, 13, 'poly_order': 3}. Using SMOTE has better accuracy than without pre-processing, with an accuracy of 92% on SVM and 94% on DT. In comparison, the combination of SMOTE and Spectral Transformation gives classification results for SVM and DT with the same accuracy of 96%, better than using SMOTE only. Oversampling ; Support vector machine ; Computer science ; Pattern recognition (psychology) ; Transformation (genetics) ; Artificial intelligence ; Filter (signal processing) ; Near-infrared spectroscopy ; Precision and recall ; Remote sensing ; Data mining ; Chemistry ; Computer vision ; Bandwidth (computing) ; Optics Spectroscopy and Chemometric Analyses ; Date Palm Research Studies
Authors: Mingze Bai | Jingwen Deng | Chengxin Dai | Julianus Pfeuffer | Yasset Pérez‐Riverol
Source: ChemRxiv (preprint, 2022-10-03)
Field: Chemistry — Spectroscopy

LFQ-based peptide and protein intensity downstream analysis Testing for significant differences in quantities on protein level is a common goal of many LFQ-based mass spectrometry proteomics experiments. Starting from a table of protein and/or peptide quantities from a fixed proteomics quantification software, there exists a multitude of tools and R packages to perform the final tasks of imputation, summarization, normalization, and statistical testing. To evaluate the effect of packages and settings in their sub-steps on the final list of significant proteins, we studied several packages on three public datasets with known expected protein fold changes. We found that the final results between packages and even across different parameters of the same package can vary significantly and therefore hope that this benchmark helps in identifying the right package for a certain dataset in question. In addition to usability aspects and feature/compatibility lists of different packages, this manuscript highlights sensitivity and specificity trade-offs that come with certain packages and settings. Computer science ; Normalization (sociology) ; Usability ; Automatic summarization ; Software ; Data mining ; Quantitative proteomics ; Proteomics ; R package ; Information retrieval ; Biology ; Programming language ; Human–computer interaction Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Mass Spectrometry Techniques and Applications
Authors: Jason Derks | Nikolai Slavov
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2022-11-05)
Field: Chemistry — Spectroscopy

Strategies for increasing the depth and throughput of protein analysis by plexDIA Abstract Accurate protein quantification is key to identifying protein markers, regulatory relationships between proteins, and pathophysiological mechanisms. Realizing this potential requires sensitive and deep protein analysis of a large number of samples. Toward this goal, proteomics throughput can be increased by parallelizing the analysis of both precursors and samples using multiplexed data independent acquisition (DIA) implemented by the plexDIA framework: https://plexDIA.slavovlab.net . Here we demonstrate the improved precisions of RT estimates within plexDIA and how this enables more accurate protein quantification. plexDIA has demonstrated multiplicative gains in throughput, and these gains may be substantially amplified by improving the multiplexing reagents, data acquisition and interpretation. We discuss future directions for advancing plexDIA, which include engineering optimized mass-tags for high-plexDIA, introducing isotopologous carriers, and developing algorithms that utilize the regular structures of plexDIA data to improve sensitivity, proteome coverage and quantitative accuracy. These advances in plexDIA will increase the throughput of functional proteomic assays, including quantifying protein conformations, turnover dynamics, modifications states and activities. The sensitivity of these assays will extend to single-cell analysis, thus enabling functional single-cell protein analysis. Abstract Figure Computer science ; Throughput ; Multiplexing ; Quantitative proteomics ; Proteomics ; Proteome ; Computational biology ; Bioinformatics ; Chemistry ; Biology ; Telecommunications Advanced Proteomics Techniques and Applications ; Single-cell and spatial transcriptomics ; Advanced Biosensing Techniques and Applications
Authors: Eva Lopez-Fornieles | Bruno Tisseyre | Anice Cheraïet | Belal Gaci | Jean‐Michel Roger
Source: Frontiers in Analytical Science (article, 2022-04-14)
Field: Chemistry — Analytical Chemistry

Potential of N-CovSel for Variable Selection: A Case Study on Time-Series of Multispectral Images Multispectral image time-series have been promising for some years; yet, the substantial advance of the technology involved, with unprecedented combinations of spatial, temporal, and spectral capabilities for remote sensing applications, raises new challenges, in particular, the need for methodologies that can process the different dimensions of satellite information. Considering that the multi-collinearity problem is present in remote sensing time-series, regression models are widespread tools to model multi-way data. This paper presents the results of the analysis of a high order data of Sentinel-2-time series, conducted in the framework of extreme weather event. A feature extraction method for multi-way data, N-CovSel was used to identify the most relevant features explaining the loss of yield in Mediterranean vineyards during the 2019 heatwave. Different regression models (uni-way and multi-way) from features extracted from the N-CovSel algorithm were calibrated based on available heat wave impact data for 107 vineyard blocks in the Languedoc-Roussillon region and multispectral time-series predictor data for the period May to August. The performance of the models was evaluated by the r 2 and the root mean square of error (RMSE) as follows: for the temporal N-PLS model ( r 2 = 0.62—RMSE = 11%), for the spatial N-PLS model ( r 2 = 0.61—RMSE = 12%) and the temporal-spectral PLS model ( r 2 = 0.63—RMSE = 11%). The results validated the effectiveness of the proposed N-CovSel algorithm in order to reduce the number of total variables and restricting it to the most significant ones. The N-CovSel algorithm seems to be a suitable choice to interpret complex multispectral imagery by temporally discriminating the most appropriate spectral information. Multispectral image ; Mean squared error ; Collinearity ; Time series ; Feature selection ; Series (stratigraphy) ; Computer science ; Remote sensing ; Data mining ; Mathematics ; Statistics ; Artificial intelligence ; Geography ; Machine learning Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Remote-Sensing Image Classification
Authors: Jiaxin Li | Zhou Zhou | Zile Li | Guoxing Zheng
Source: Frontiers in Nanotechnology (article, 2022-08-17)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Single-sized metasurface for simultaneous pseudo-color nanoprinting and holographic image display Metasurfaces provide a novel platform for multifunctional devices due to their incomparable competence for the manipulation of different optical properties. Recently, many works have emerged to merge distinct functions into a single metasurface, which effectively increase the information density and capacity of meta-devices. In this work, combining the dual-wavelength polarizer and the orientation degeneracy of the Malus law, we further exploit the design degree of freedom of the metasurface, and realize color control and phase manipulation simultaneously with single-sized nanostructures. We experimentally demonstrate our concept by integrating the function of pseudo-color nanoprinting and holographic image display together. Our research can effectively improve the functionalities of metasurface and promote advanced research of multimode displays, information encryption, optical multiplexing, and many other related fields. Holography ; Polarizer ; Computer science ; Multiplexing ; Optics ; Optoelectronics ; Physics ; Birefringence ; Telecommunications Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Photonic Crystals and Applications