jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Philip Berg | George V. Popescu
Source: Molecular & Cellular Proteomics (article, 2023-10-07)
Field: Chemistry — Spectroscopy

Baldur: Bayesian Hierarchical Modeling for Label-Free Proteomics with Gamma Regressing Mean-Variance Trends Label-free proteomics is a fast-growing methodology to infer abundances in mass spectrometry proteomics. Extensive research has focused on spectral quantification and peptide identification. However, research toward modeling and understanding quantitative proteomics data is scarce. Here we propose a Bayesian hierarchical decision model (Baldur) to test for differences in means between conditions for proteins, peptides, and post-translational modifications. We developed a Bayesian regression model to characterize local mean-variance trends in data, to estimate measurement uncertainty and hyperparameters for the decision model. A key contribution is the development of a new gamma regression model that describes the mean-variance dependency as a mixture of a common and a latent trend-allowing for localized trend estimates. We then evaluate the performance of Baldur, limma-trend, and t test on six benchmark datasets: five total proteomics and one post-translational modification dataset. We find that Baldur drastically improves the decision in noisier post-translational modification data over limma-trend and t test. In addition, we see significant improvements using Baldur over the other methods in the total proteomics datasets. Finally, we analyzed Baldur's performance when increasing the number of replicates and found that the method always increases precision with sample size, while showing robust control of the false positive rate. We conclude that our model vastly improves over popular data analysis methods (limma-trend and t test) in several spike-in datasets by achieving a high true positive detection rate, while greatly reducing the false-positive rate. False discovery rate ; Bayesian probability ; Hyperparameter ; Computer science ; Variance (accounting) ; Benchmark (surveying) ; Proteomics ; Bayesian inference ; Bayes' theorem ; Statistics ; Artificial intelligence ; Mathematics ; Biology Advanced Proteomics Techniques and Applications ; Identification and Quantification in Food ; Metabolomics and Mass Spectrometry Studies
Authors: Hongchen Chu | Xiang Xiong | Nicholas X. Fang | Feng Wu | Runqi Jia | Ru‐Wen Peng | Mu Wang | Yun Lai
Source: arXiv (Cornell University) (preprint, 2023-03-22)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Transparent matte surfaces enabled by asymmetric diffusion of white light The traditional wisdom for achieving transparency is to minimize disordered scattering within and on the surface of materials, so as to avoid translucency. However, the lack of disordered scattering also deprives the possibility of achieving a matte surface, resulting in the specular reflection and glare on transparent materials as a severe light pollution issue. In this work, we propose a solution utilizing optical metasurfaces1-2 to overcome this long-existing dilemma. Our approach leverages an asymmetric background in metasurface design to achieve highly asymmetric diffusion of white light, maximizing diffusion in reflection while minimizing it in transmission across the entire visible spectrum. Using industrial lithography, we have created macroscale transparent matte surfaces with both strong matte appearance and clear transparency, defying the conventional belief that these two optical features are incompatible. These surfaces provide a remarkable phenomenon of switching between transparent or matte appearances via the brightness contrast between the front and rear ambient lights. They also support a unique application in transparent displays and augmented reality, offering perfectly preserved clarity, wide viewing angles, full color, and one-sided displays capabilities. Our findings usher in a new era of optical materials where the desirable properties of both transparent and matte appearances can be seamlessly merged. Specular reflection ; Transparency (behavior) ; Brightness ; Optics ; Opacity ; Materials science ; Scattering ; Light scattering ; Reflection (computer programming) ; Computer science ; Optoelectronics ; Physics Metamaterials and Metasurfaces Applications ; Advanced Optical Imaging Technologies ; Photonic Crystals and Applications
Authors: Jianwei Wang | Ze Zhang | Zhiyan Lin | Hanting Li | Hua Gao | Zhenjun Fan | Haifeng Liu
Source: Frontiers in Physics (article, 2023-08-16)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Tunable narrowband and broadband coexisting absorber enabled by a simple all-metal grating for sensing applications We realize a tunable narrowband and broadband coexisting absorber based on a simple step-shaped all-metal grating structure. The absorber presents an ultra-narrow absorption band of 1.5 nm and a relatively broad absorption band of 29.8 nm, both with nearly 100% absorption in the infrared region. The mechanism underlying the dual-band perfect absorption is the interaction between two diffraction coupled surface plasmon polariton (SPP) modes with one of them modulated by a cavity resonance. Influences of structure parameters on the absorption performance are numerically investigated. It is found that the positions of the two perfect absorption peaks can be easily tuned both independently and together by changing the structural parameters. In addition, the designed grating structure presents excellent sensing performance with sensitivity and figure of merit as high as 2,514 nm/RIU and 1,600 RIU −1 , respectively. The excellent sensing performance, flexible tenability and simple structure design endow this grating absorber with great potential in high-precision biochemical sensing applications. Grating ; Materials science ; Absorption (acoustics) ; Narrowband ; Broadband ; Optics ; Optoelectronics ; Absorption band ; Surface plasmon resonance ; Figure of merit ; Plasmon ; Diffraction grating ; Nanotechnology ; Physics ; Nanoparticle Metamaterials and Metasurfaces Applications ; Plasmonic and Surface Plasmon Research ; Advanced Antenna and Metasurface Technologies
Authors: Li Sun | Xin Zheng | Pengqi Zhang | Jianrong Cai | Junwen Bai
Source: Current Research in Food Science (article, 2023-01-01)
Field: Chemistry — Analytical Chemistry

Research on the correlation between three-dimensional morphology and temperature changes in potato slices during drying Drying is an effective method to reduce potato storage loss. However, potatoes have high porosity with high water content. Shrinkage during drying can lead to folding and cracking of the dried product form. Therefore, this study explored the correlation between the 3D morphology and temperature distribution changes of potato slices during drying, with the aim of providing a reference for the detection of quality changes. An online automatic acquisition device to obtain 3D morphology and temperature information was designed and built. Hot air-drying experiments were conducted on the potato slices. 3D morphology images and temperature images of the potato slices were acquired by 3D and temperature sensors, and the two images were registered using the random sample consensus (RANSAC) algorithm. The region of interest of each image was extracted by algorithms such as threshold segmentation, hole filling and morphological erosion, and the 3D morphology information and temperature information were obtained. The mapping, range and average of each acquisition point were calculated for correlation analysis. Spearman's rank correlation coefficients and Maximum Information Coefficient (MIC) values were selected as measures for the correlation study. The results showed that the Spearman's rank correlation coefficients between average height and average temperature were mostly above 0.7 in absolute value, and the MICs were mostly above 0.9. The average values of the 3D information and temperature information exhibited an extremely strong correlation. This paper gives a new approach to investigate the morphological changes in the drying process by quantifying the relationship between 3D morphology and temperature distribution. This can guide the improvement of potato drying and processing methods. Spearman's rank correlation coefficient ; Correlation coefficient ; Rank correlation ; Materials science ; Shrinkage ; Morphology (biology) ; Air temperature ; Biological system ; Mathematics ; Statistics ; Geology Spectroscopy and Chemometric Analyses ; Food Supply Chain Traceability ; Food Drying and Modeling
Authors: Marjan Hadian-Jazi | Alireza Sadri
Source: Acta Crystallographica Section D Structural Biology (article, 2023-07-25)
Field: Materials Science — Materials Chemistry

A Python package based on robust statistical analysis for serial crystallography data processing The term robustness in statistics refers to methods that are generally insensitive to deviations from model assumptions. In other words, robust methods are able to preserve their accuracy even when the data do not perfectly fit the statistical models. Robust statistical analyses are particularly effective when analysing mixtures of probability distributions. Therefore, these methods enable the discretization of X-ray serial crystallography data into two probability distributions: a group comprising true data points (for example the background intensities) and another group comprising outliers (for example Bragg peaks or bad pixels on an X-ray detector). These characteristics of robust statistical analysis are beneficial for the ever-increasing volume of serial crystallography (SX) data sets produced at synchrotron and X-ray free-electron laser (XFEL) sources. The key advantage of the use of robust statistics for some applications in SX data analysis is that it requires minimal parameter tuning because of its insensitivity to the input parameters. In this paper, a software package called Robust Gaussian Fitting library (RGFlib) is introduced that is based on the concept of robust statistics. Two methods are presented based on the concept of robust statistics and RGFlib for two SX data-analysis tasks: (i) a robust peak-finding algorithm and (ii) an automated robust method to detect bad pixels on X-ray pixel detectors. Python (programming language) ; Computer science ; Programming language Enzyme Structure and Function ; Mineral Processing and Grinding ; Hydrocarbon exploration and reservoir analysis
Authors: Yifei Liu | Wei Wu | Xiang Chen | Xin Nie | Mo Zhao | Rui Jia | Jinxi Li
Source: Energies (article, 2023-09-19)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A Test Method for Shielding Effectiveness of Materials against Electromagnetic Pulse Based on Coaxial Flange Aiming at the evaluation of the shielding effectiveness (SE) of materials against high-intensity electromagnetic pulse (EMP), the shielding mechanism in the frequency domain is investigated, and the factors that determine SE such as conductivity, thickness of material, and test frequency are analyzed. The attenuated waves of solid and perforated plate materials irradiated by EMP are simulated in CST. The results show that the two materials exhibit low-pass and high-pass filtering characteristics, respectively, which lead to a big difference in the transmitted waves (rise time and pulse width). Based on this, a time domain SE test method using coaxial flange is proposed which can obtain the incident and the transmitted and reflected waves, and the time domain SE of graphenes with different thicknesses (80, 100, 200, and 300 μm) are measured. The characteristics of the reflected and transmitted waves are analyzed in detail, and the change regulations comply with the theoretical shielding model well. The peak value SE and energy density SE, respectively, are calculated. Furthermore, the frequency domain SE can be obtained through the Fourier transform, so the method has a wide application in material SE performance evaluation against high-intensity EMP. Electromagnetic shielding ; Flange ; Coaxial ; Electromagnetic pulse ; Materials science ; Time domain ; Finite-difference time-domain method ; Frequency domain ; Acoustics ; Pulse (music) ; Electromagnetic radiation ; Intensity (physics) ; Optics ; Composite material ; Electrical engineering ; Engineering ; Physics ; Computer science Electromagnetic wave absorption materials ; Electromagnetic Compatibility and Measurements ; Graphite, nuclear technology, radiation studies
Authors: Adam Kolobaric | Rebecca Orrell‐Trigg | Seth Orloff | Vanessa Fraser | James Chapman | Daniel Cozzolino
Source: Sensors (article, 2023-11-04)
Field: Chemistry — Analytical Chemistry

The Use of a Droplet Collar Accessory Attached to a Portable near Infrared Instrument to Identify Methanol Contamination in Whisky The aim of this study was to evaluate the ability of a droplet collar accessory attached to a portable near-infrared (NIR) instrument to characterize the artificial contamination of methanol in commercial whisky samples. Unadulterated samples (n = 12) were purchased from local bottle shops where adulterated samples were created by adding methanol (99% pure methanol) at six levels (0.5%, 1%, 2%, 3%, 4% and 5% <i>v</i>/<i>v</i>) to the commercial whisky samples (controls). Samples were analyzed using a drop collar accessory attached to a MicroNIR Onsite instrument (900-1650 nm). Partial least squares (PLS) cross-validation statistics obtained for the prediction of all levels of methanol (from 0 to 5%) addition were considered adequate when the whole adulteration range was used, coefficient of determination in cross-validation (R<sup>2</sup><sub>cv</sub>: 0.95) and standard error in cross of validation (SECV: 0.35% <i>v</i>/<i>v</i>). The cross-validation statistics were R<sup>2</sup><sub>cv</sub>: 0.97, SECV: 0.28% <i>v</i>/<i>v</i> after the 0.5% and 1% <i>v</i>/<i>v</i> methanol addition was removed. These results showed the ability of using a new sample presentation attachment to a portable NIR instrument to analyze the adulteration of whisky with methanol. However, the low levels of methanol adulteration (0.5 and 1%) were not well predicted using the NIR method evaluated. Methanol ; Collar ; Analytical Chemistry (journal) ; Chromatography ; Near-infrared spectroscopy ; Chemistry ; Environmental science ; Materials science ; Engineering ; Physics ; Optics ; Mechanical engineering ; Organic chemistry Spectroscopy and Chemometric Analyses ; Identification and Quantification in Food ; Advanced Chemical Sensor Technologies
Authors: Bhubanananda Adhikari | Radhakrushna Senapati | Minati Mohapatra | L. N. Mohapatra | Rahul Nigam | Shyamaranjan Das Mohapatra
Source: Current Science (article, 2023-04-25)
Field: Chemistry — Analytical Chemistry

Detection of rice leaf folder, &lt;i&gt;Cnaphalocrocis medinalis&lt;/i&gt; (Guenée) (Lepidoptera: Crambidae) infestation using ground-based hyperspectral radiometry Hyperspectral remote sensing is a useful technique for detecting spatio-temporal changes in crop morphological and physiological health.In order to identify the pestsensitive bands for rice leaf folder (RLF), the groundbased hyperspectral data were recorded at varying damage levels.The first-and second-order derivatives were correlated with correlation coefficient r and per cent leaf damage.The common region identified were recognized as sensitive regions (508-529, 671-680, 721-759, 779-786 and 804-820 nm).The absorption dips were also found using Sensitivity and Continuum Removal Analysis.Combining all, a total of nine spectral bands (518, 549, 661, 674, 678, 731, 789, 816 and 898 nm) were identified as pest-sensitive bands for RLF.The feature-selection method was employed using RELIEFF algorithm to find out the band combinations and bands 518, 661 and 731 nm yielded maximum accuracy of 81.67%. Crambidae ; Cnaphalocrocis medinalis ; Lepidoptera genitalia ; Hyperspectral imaging ; Infestation ; Biology ; Botany ; Remote sensing ; Geography Spectroscopy and Chemometric Analyses ; Insect Pest Control Strategies
Authors: François Bavaud
Source: Journal of Multivariate Analysis (article, 2023-07-23)
Field: Chemistry — Analytical Chemistry

Exact first moments of the RV coefficient by invariant orthogonal integration The RV coefficient measures the similarity between two multivariate configurations, and its significance testing has attracted various proposals in the last decades. We present a new approach, the invariant orthogonal integration, permitting to obtain the exact first four moments of the RV coefficient under the null hypothesis. Our proposal can be applied to any multivariate setting endowed with Euclidean distances between the observations. It also covers the weighted setting of observations of unequal importance, where the exchangeability assumption, justifying the usual permutation tests, breaks down. The proposed RV moments express as simple functions of the kernel eigenvalues occurring in the weighted multidimensional scaling of the two configurations (spectral effective dimensionality, spectral skewness and spectral excess kurtosis). The expressions for the third and fourth moments seem original, and explain the marked asymmetry and kurtosis of the RV coefficient. They permit to test the significance of the RV coefficient by Cornish–Fisher cumulant expansion, beyond the normal approximation, as illustrated on a small dataset. The first three moments can be obtained by elementary means, but computing the fourth moment requires a more sophisticated apparatus, the Weingarten calculus for orthogonal groups. Mathematics ; Kurtosis ; Invariant (physics) ; Eigenvalues and eigenvectors ; Skewness ; Applied mathematics ; Mathematical analysis ; Pure mathematics ; Statistics Spectroscopy and Chemometric Analyses ; Statistical Methods and Bayesian Inference ; Sensory Analysis and Statistical Methods
Authors: Tine Claeys | Tim Van Den Bossche | Yasset Pérez‐Riverol | Kris Gevaert | Juan Antonio Vizcaíno | Lennart Martens
Source: Research Square (preprint, 2023-05-23)
Field: Chemistry — Spectroscopy

lesSDRF Is More: Maximizing The Value Of Proteomics Data Through Streamlined Metadata Annotation Metadata ; Annotation ; Value (mathematics) ; Computer science ; Proteomics ; Data science ; Computational biology ; World Wide Web ; Information retrieval ; Biology ; Artificial intelligence ; Genetics Advanced Proteomics Techniques and Applications ; Genomics and Phylogenetic Studies ; Biomedical Text Mining and Ontologies
Authors: Tianshuo Qiu | Qiang An | Jianqi Wang | Jiafu Wang | Cheng‐Wei Qiu | Shiyong Li | Hao Lv | Ming Cai | Jianyi Wang | Lin Cong | Shaobo Qu
Source: Research Square (preprint, 2023-05-16)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Vision-Driven Metasurfaces for Perception Enhancement Perception ; Psychology ; Computer vision ; Computer science ; Cognitive psychology ; Artificial intelligence ; Neuroscience Metamaterials and Metasurfaces Applications ; Advanced Memory and Neural Computing ; Tactile and Sensory Interactions
Authors: Steven Golovkine | Edward Gunning | Andrew J. Simpkin | Norma Bargary
Source: arXiv (Cornell University) (preprint, 2023-06-22)
Field: Chemistry — Analytical Chemistry

On the use of the Gram matrix for multivariate functional principal components analysis Dimension reduction is crucial in functional data analysis (FDA). The key tool to reduce the dimension of the data is functional principal component analysis. Existing approaches for functional principal component analysis usually involve the diagonalization of the covariance operator. With the increasing size and complexity of functional datasets, estimating the covariance operator has become more challenging. Therefore, there is a growing need for efficient methodologies to estimate the eigencomponents. Using the duality of the space of observations and the space of functional features, we propose to use the inner-product between the curves to estimate the eigenelements of multivariate and multidimensional functional datasets. The relationship between the eigenelements of the covariance operator and those of the inner-product matrix is established. We explore the application of these methodologies in several FDA settings and provide general guidance on their usability. Principal component analysis ; Functional principal component analysis ; Functional data analysis ; Dimension (graph theory) ; Dimensionality reduction ; Covariance matrix ; Covariance ; Inner product space ; Multivariate statistics ; Computer science ; Operator (biology) ; Gramian matrix ; Product (mathematics) ; Key (lock) ; Mathematics ; Data mining ; Artificial intelligence ; Algorithm ; Statistics ; Machine learning ; Eigenvalues and eigenvectors Spectroscopy and Chemometric Analyses ; Face and Expression Recognition ; Blind Source Separation Techniques
Authors: Armen H. Poghosyan | Stéphane Abel | Joachim Koetz
Source: Colloid & Polymer Science (article, 2023-02-02)
Field: Chemistry — Organic Chemistry

Simulation of AOT reverse micelles with polyethylenimine in hexane Polyethylenimine ; Micelle ; Chemistry ; Hexane ; Molar ratio ; Hydrodynamic radius ; Adsorption ; Molecular dynamics ; Counterion ; RADIUS ; Crystallography ; Polymer chemistry ; Physical chemistry ; Analytical Chemistry (journal) ; Ion ; Aqueous solution ; Computational chemistry ; Chromatography ; Organic chemistry Surfactants and Colloidal Systems ; Electrostatics and Colloid Interactions ; Advanced Polymer Synthesis and Characterization
Authors: Ricardo Stefani | Isabelle Silva Aguiar
Source: ChemRxiv (preprint, 2023-01-20)
Field: Materials Science — Biomaterials

On the molecular dynamic of quercetin and chitosan behavior in water and 1-octhanol at different temperatures rug delivery control systems allow the controlled transportation of therapeutic agents. In order to understand the behavour of chitosan as a drug delivery system, the behaviour of chitosan and quercetin in water and 1-octanol at 300 K and 310 K as a complex was calculated with molecular dynamics (MD) calculations. Meanwhile, Molecular docking (MDK) were used to make the complex of these molecules. Of nine quercetin’s conformations around chitosan, two were chosen to make a complex due to better energy affinity. The molecules interact between each other with hydrogen bonds. The molecules do not interact with 1-octanol, independent of temperature. In water, chitosan maintained insoluble with the increase of temperature. On the other hand, quercetin demonstrated a better solubilization with temperature increasement. The complex demonstrate a behaviour favorable to a drug delivery control system. Chitosan ; Quercetin ; Hydrogen bond ; Drug delivery ; Molecule ; Molecular dynamics ; Chemistry ; Octanol ; Combinatorial chemistry ; Computational chemistry ; Chemical engineering ; Organic chemistry ; Partition coefficient Nanocomposite Films for Food Packaging ; Surfactants and Colloidal Systems ; Chemical and Physical Properties in Aqueous Solutions