jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Cankun Qiu | Xia Wu | Zhi Luo | Huidong Yang | Bo Huang
Source: Research Square (preprint, 2021-03-10)
Field: Materials Science — Surfaces, Coatings and Films

Fast Inverse Design of Nanophotonics using Di fferential Evolutionn and Back-Propagation Abstract Deep learning technology have been used as a new approach for forward simulation and inverse design of nanophotonic structures. Deep learning technology greatly reduces the time of optical simulation and enables us to use back-propagation (BP) algorithm to optimize design parameters. But BP is very sensitive to the initial values and hard to converge to the optimal value for some initial values. In this research, we propose a hybrid optimization strategy that combined differential evolution (DE) with BP algorithm for the inverse design of multilayer nanofilms structures. The proposed method effectively utilizes the global parallel exploration capability of DE and the local exploitation capability of gradient descent based on BP. It can alleviate the sensitivity of the initial values for the BP algorithm and effectively compensates for the slower convergence properties of the DE. The results suggest that the hybrid DE-BP algorithm can greatly speeds up the inverse design process of multilayer nanofilms and can search in a larger parameter space that even exceeds the parameter range of the training dataset that are used to train the forward prediction neural networks. Nanophotonics ; Inverse ; Computer science ; Physics ; Optics ; Mathematics ; Geometry Optical Coatings and Gratings ; Photonic and Optical Devices ; Photonic Crystals and Applications
Authors: Srihari Padmanabhan
Source: Integrated Journal for Research in Arts and Humanities (article, 2021-11-30)
Field: Chemistry — Organic Chemistry

Role of Neurotransmitters in Plant Growth and Environmental Stress Response The term neurotransmitter denotes chemicals which help in the neurotransmission process in an organism’s body. These NTs can be found in both plants and animals. This particular research report aimed to examine the role of neurotransmitters on plant growth and environmental stress response. The findings of this research have shown that a wide variety of NTs such as acetylcholine, glutamate, and serotonin increases the growth of root, seeds and stem by using chemical channels. On the other hand, chemical channels such as Ca2+ also regulated by the presence of NTs of plants. Fight-or-flight response ; Environmental stress ; Stress (linguistics) ; Plant growth ; Environmental science ; Biology ; Environmental protection ; Botany ; Biochemistry Chemical synthesis and alkaloids ; Allelopathy and phytotoxic interactions ; GABA and Rice Research
Authors: Zach J. Patterson | Andrew P. Sabelhaus | Carmel Majidi
Source: arXiv (Cornell University) (preprint, 2021-10-19)
Field: Materials Science — Materials Chemistry

Robust Control of a Multi-Axis Shape Memory Alloy-Driven Soft Manipulator Control of soft robotic manipulators remains a challenge for designs with advanced capabilities and novel actuation. Two significant limitations are multi-axis, three-dimensional motion of soft bodies alongside actuator dynamics and constraints, both of which are present in shape-memory-alloy (SMA)-powered soft robots. This article addresses both concerns with a robust feedback control scheme, demonstrating state tracking control for a soft robot manipulator of this type. Our controller uses a static beam bending model to approximate the soft limb as an LTI system, alongside a singular-value-decomposition compensator approach to decouple the multi-axial motion and an anti-windup element for the actuator saturation. We prove stability and verify robustness of our controller, with robustness intended to account for the unmodeled dynamics. Our implementation is verified in hardware tests of a soft SMA-powered limb, showing low tracking error, with promising results for future multi-limbed robots. Control theory (sociology) ; Robustness (evolution) ; Actuator ; SMA* ; Robot ; Computer science ; Motion control ; Soft landing ; Control engineering ; Robust control ; Shape-memory alloy ; Engineering ; Control system ; Control (management) ; Artificial intelligence Shape Memory Alloy Transformations ; Soft Robotics and Applications ; Aortic Disease and Treatment Approaches
Authors: Benjamin Wiggins | Leah S. Lily | Haley Sefi-Cyr | Caroline L. Dahlberg
Source: Preprints.org (preprint, 2021-01-26)
Field: Chemistry — Physical and Theoretical Chemistry

Repetition is Important to Students and Their Understanding During Laboratory Courses that Include Research Course-based undergraduate research experiences (CUREs) provide students with opportunities for the same gains that apprenticed research with faculty members offer. As their popularity increases, it is important that critical elements of CUREs are supported by thoughtful design. Student experiences in CUREs can provide important insights into why CUREs are so effective. We present evidence from students who participated in CUREs at the introductory, intermediate, and advanced levels, as well as from graduate teaching assistants for an introductory lab course that included a CURE. Students and teaching assistants describe repetition as a valuable element in CUREs and other laboratory experiences. We used student work and open-ended interviews to identify which of five previously described elements of CUREs students found important. Because repetition was particularly salient, we characterized how students described repetition as they experienced it in courses that contained full-length or &amp;ldquo;micro&amp;rdquo;-CUREs. In prompted interviews, students described how repetition in CUREs provided cognitive (learning concepts) and practical (learning technical skills) value. Recent graduates who had participated in CUREs at each level of their Biology education were particularly aware that they placed value in repetition and acknowledged it as motivational in their own learning. Many students described repetition in metacognitive terms, which also suggests that as students advance through laboratory and CURE curricula, their understanding of how repetition supports their learning becomes more sophisticated. Finally, we integrated student descriptions to suggest ways in which repetition can be designed into CUREs or other laboratory courses to support scientific learning and enhance students&amp;rsquo; sense of scientific identity. Repetition (rhetorical device) ; Psychology ; Value (mathematics) ; Curriculum ; Popularity ; Mathematics education ; Mindset ; Pedagogy ; Medical education ; Computer science ; Medicine ; Social psychology Various Chemistry Research Topics ; Innovative Teaching Methods ; Science Education and Pedagogy
Authors: Cristhian Antonio Taboada Moreno | Lizeth Y. Cruz Moreno | F. Sánchez-De Jesús | C.A. Cortés-Escobedo | Màrius Ramírez-Cardona | A.M. Bolarín-Miró
Source: Tópicos de Investigación en Ciencias de la Tierra y Materiales (article, 2021-10-05)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Papel del Sr2+ en las propiedades magnetocalóricas de La1-xSrxMnO3 La refrigeración magnética es una tecnología de alta eficiencia energética y bajo impacto ambiental. Los materiales más económicos para esta aplicación es la La0.7Ca0.3MnO3, sin embargo, su temperatura de trabajo es muy baja (260 K). En este trabajo se analizará el efecto de modificación con Sr2+sobre las propiedades magnetocalóricas y la temperatura de operación de la La1-xSrxMnO3 (0 ≤ x ≤ 0.5, Δx=0.1). Mediante DRX se confirmó la transformación de estructura ortorrómbica (Pnma) a trigonal (R3c:H) y tetragonal (P4/m) dependiendo de la concentración de estroncio. La magnetometría de muestra vibrante mostró orden ferromagnético a temperatura ambiente para todas las composiciones. Las temperaturas de Curie (Tc) se encontraron en el rango de 330 a 370 K. Asimismo, se obtuvieron las isotermas magnéticas alrededor de la Tc para la composición x=0.2, su análisis permitió obtener el efecto magnetocalórico a 18 kOe, obteniendo un cambio de entropía (-ΔS) de 2.76 Jkg-1K-1, y una capacidad de refrigeración (RC) de 98.3 J kg-1. Humanities ; Physics ; Chemistry ; Political science ; Philosophy Magnetic and transport properties of perovskites and related materials ; Intellectual Capital and Performance Analysis
Source: Machine Learning Theory and Practice (article, 2021-12-16)
Field: Chemistry — Analytical Chemistry

Maize Variety Identification Based on Support Vector Machines Seeds are the most basic and critical means of production in agricultural production.Declining purity of seed varieties will significantly reduce crop yield and product quality.The quality of crop seed varieties, especially purity testing, can protect the interests of farmers and promote the development of rural economies.The aim of this paper is to study maize variety identification based on support vector machines.Based on the morphological structure characteristics of maize varieties, a set of characteristic parameters that can accurately reflect the morphological structure of different maize varieties is proposed for variety identification.The parameter set consists of four components: shape, colour, size and sharpness parameters.The experimental results show that the support vector machine algorithm outperforms the BP neural network. Variety (cybernetics) ; Identification (biology) ; Support vector machine ; Vector (molecular biology) ; Computer science ; Biology ; Artificial intelligence ; Botany ; Genetics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Advanced Algorithms and Applications
Authors: Anna Bosi | Paolo Maria Mariano | Luca Salvatori
Source: Mathematical Methods in the Applied Sciences (article, 2021-05-06)
Field: Materials Science — Materials Chemistry

Micro‐to‐macro interactions in complex bodies: Wavelet‐based post‐processing detection We propose to couple finite element simulations and wavelet‐based post‐processing analysis to explore deeply the interaction degree of microscopic events on the gross behavior of complex bodies (which class includes metamaterials), above all around material or load discontinuities. After summarizing the theoretical structures our procedure refers to, as a sample case we select a special class of complex materials, namely, quasicrystals, and show how the proposed scheme works. As a result, we point out the effects of atomic rearrangements characterizing the quasicrystal structure on the stress field around a crack tip in static and dynamical setting. Our procedure can be also used for the analysis of dynamic experimental data. In this case, it allows us to detect discontinuities at least along directions selected within the body. In turn, our procedure can be used for monitoring purposes. Classification of discontinuities ; Wavelet ; Macro ; Class (philosophy) ; Point (geometry) ; Quasicrystal ; Mathematics ; Finite element method ; Field (mathematics) ; Statistical physics ; Algorithm ; Computer science ; Theoretical physics ; Mathematical analysis ; Artificial intelligence ; Geometry ; Structural engineering ; Pure mathematics ; Physics ; Engineering Quasicrystal Structures and Properties ; High-Velocity Impact and Material Behavior ; Ultrasonics and Acoustic Wave Propagation
Authors: Bertrand Jern Han Wong | Weijia Kong | Wilson Wen Bin Goh
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-11-15)
Field: Chemistry — Spectroscopy

Single-sample proteome enrichment enables missing protein recovery and phenotype association Abstract Proteomic studies characterize the protein composition of complex biological samples. Despite recent developments in mass spectrometry instrumentation and computational tools, low proteome coverage remains a challenge. To address this, we present Proteome Support Vector Enrichment (PROSE), a fast, scalable, and effective pipeline for scoring protein identifications based on gene co-expression matrices. Using a simple set of observed proteins as input, PROSE gauges the relative importance of proteins in the phenotype. The resultant enrichment scores are interpretable and stable, corresponding well to the source phenotype, thus enabling reproducible recovery of missing proteins. We further demonstrate its utility via reanalysis of the Cancer Cell Line Encyclopedia (CCLE) proteomic data, with prediction of oncogenic dependencies and identification of well-defined regulatory modules. PROSE is available as a user-friendly Python module from https://github.com/bwbio/PROSE . Proteome ; Computational biology ; Phenotype ; Computer science ; Proteomics ; Pipeline (software) ; Python (programming language) ; Biology ; Bioinformatics ; Gene ; Genetics Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Mass Spectrometry Techniques and Applications
Authors: Déborah Harrus
Source: Acta Crystallographica Section A Foundations and Advances (article, 2021-07-30)
Field: Materials Science — Materials Chemistry

Crystallization conditions in the Protein Data Bank Crystallization ; Protein Data Bank ; Protein crystallization ; Materials science ; Chemical engineering ; Chemistry ; Protein structure ; Biochemistry ; Engineering Enzyme Structure and Function ; Advanced Proteomics Techniques and Applications
Authors: A. Hakan Aktaş | Halil Orhun ŞAHİN
Source: GAZI UNIVERSITY JOURNAL OF SCIENCE (article, 2021-02-02)
Field: Chemistry — Analytical Chemistry

A speedy method for simultaneous determination in tablet active content by NIR and UV-Vis spectrophotometry: Comparison of PLS-1 and ICA-ANN models In this study, the NIR and UV-Vis spectroscopy methods, which are frequently used in pharmaceutical industry, were applied to the environments where Paracetamol, Propyphenazone and Caffeine active substances are present, and the spectroscopic data obtained were evaluated comparatively with ICA-ANN and PLS-1, which are powerful chemometric methods. When using solid agents in NIR method, liquid solutions equivalent to them were used in UV-Vis method. Following the application of both methods, spectral data were evaluated as chemometrics and in both spectroscopic methods ICA-ANN method yielded more accurate results than PLS-1. High recovery rates and relatively low standard deviations were found in the applied methods and recommended for use in the pharmaceutical industry. Chemometrics ; Chromatography ; Spectrophotometry ; Chemistry ; Ultraviolet visible spectroscopy ; Analytical Chemistry (journal) ; Near-infrared spectroscopy ; Relative standard deviation ; Biological system ; Detection limit Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Water Quality Monitoring and Analysis
Authors: Julia A. Giannini | Ethan Stanifer | M. Lisa Manning
Source: arXiv (Cornell University) (preprint, 2021-11-24)
Field: Materials Science — Materials Chemistry

Searching for structural predictors of plasticity in dense active packings In amorphous solids subject to shear or thermal excitation, so-called structural indicators have been developed that predict locations of future plasticity or particle rearrangements. An open question is whether similar tools can be used in dense active materials, but a challenge is that under most circumstances, active systems do not possess well-defined solid reference configurations. We develop a computational model for a dense active crowd attracted to a point of interest, which does permit a mechanically stable reference state in the limit of infinitely persistent motion. Previous work on a similar system suggested that the collective motion of crowds could be predicted by inverting a matrix of time-averaged two-particle correlation functions. Seeking a first-principles understanding of this result, we demonstrate that this active matter system maps directly onto a granular packing in the presence of an external potential, and extend an existing structural indicator based on linear response to predict plasticity in the presence of noisy dynamics. We find that the strong pressure gradient necessitated by the directed activity, as well as a self-generated free boundary, strongly impact the linear response of the system. In low-pressure regions the linear-response-based indicator is predictive, but it does not work well in the high-pressure interior of our active packings. Our findings motivate and inform future work that could better formulate structure-dynamics predictions in systems with strong pressure gradients. Work (physics) ; Boundary (topology) ; Statistical physics ; Plasticity ; Active matter ; Computer science ; Mechanics ; Classical mechanics ; Physics ; Mathematics ; Mathematical analysis ; Thermodynamics Material Dynamics and Properties ; Micro and Nano Robotics ; Pickering emulsions and particle stabilization
Authors: Maxim Zakharov | Alexander Paramonov | Ammar Muthanna | Ruslan Kirichek
Source: International Journal of Advanced Computer Science and Applications (article, 2021-01-01)
Field: Chemistry — Physical and Theoretical Chemistry

Prototype Design and Experimental Evaluation e-Healthcare System based on Molecular Analysis Devices Recently, wireless body area networks (WBANs) and mobile Internet of Things (IoT) have been greatly increased and integrated into a different type of systems such as electronic/mobile-healthcare (e/m-healthcare) systems. In addition, analyzing the composition of drugs or performing the medical rapid tests in the conditions field are the main tasks of the m-healthcare system, in which the traditional laboratory methods of analysis are not suitable. Therefore, in this study, we proposed a novel structure with a distributed e-health system to perform such analysis, where portable infrared micro spectrometers are utilized and then boundary calculations are applied. More specifically, this system is proposed to use a portable infrared micro spectrometer with a specially designed application connected to a public communication network, which can process the results of analysis using boundary calculations. Moreover, it provides remote processing and long-term storage of analysis data using artificial neural networks and cloud technologies. Finally, simulation results show that preprocessing (error checking), data buffering and Edge Computing can significantly reduce the network latency and volume of transferred data. Computer science ; Preprocessor ; Cloud computing ; Data pre-processing ; Field (mathematics) ; Process (computing) ; Wireless ; Real-time computing ; Artificial intelligence ; Telecommunications ; Operating system Various Chemistry Research Topics
Authors: Elsa Ordoñez-Casanova | Ruth Romero-Dominguez | M. Galicia | Hector A. Trejo-Mandujano
Source: Microscopy and Microanalysis (article, 2021-07-30)
Field: Materials Science — Metals and Alloys

Microstructural defects in AISI 4000 series steel subjected to a 3% NaCl corrosion process. AISI 4000 Series Steel IS one of the most important materials used in engineering. Steel Stainless achieves this degree of importance because of its combination of strength, ease of fabrication, and a wide range of properties at low cost. Some steels are relatively soft, ductile, and can be quickly manufactured into automotive or aircraft parts These stainless steels maintain a stable ferritic structure from room temperature to melting point, so their corrosion resistance is considered moderate, which increases with chromium content The present work aims to identify the microstructural defects of two pieces of AISI 4000 Series Steel obtained from different manufacturing processes and subjected to an experimental process through electrochemical techniques to obtain their corrosion rate. This process consisted of immersing the pieces in a NaCl solution at 3% by weight at room temperature. For microstructural analysis, the chemical composition was verified by optical emission spectroscopy (OES) using Foundry Master equipment and Worldwide Analytical Systems AG (WAS) software and using x-ray energy dispersion spectroscopy (EDS), Figure Scanning electron microscopy (SEM) was used to analyze the microstructural defects of the piece subjected to 3% NaCl. This microstructural analysis presents a contribution to the electrochemical technique to contribute and enrich the studies of resistance to corrosion of stainless steels. In figures 2, The pitting corrosion behavior induced by chloride ions can be seen (Red Arrow), which is a common situation in marine environments Structural defects on steel parts are considered slight, due to the concentration percentage and the exposure time of 23 hours at room temperature. Similarly, the spectra (OES) are presented for each of the areas of interest, verifying that it corresponds to the base metal of the AISI 4000 Series Steel pieces, the elements present are mainly Fe, Mn, Cr, W, Al and C, Mo, all elements of the alloy. Scanning electrochemical microscopy is a very appropriate technique for the local study of corrosion processes because it provides information on site, at micrometric and submicrometric scales, relative to the topography and electrochemical activity of reactive surfaces in aqueous solution Metallurgy ; Materials science ; Corrosion ; Series (stratigraphy) ; Process (computing) ; Action (physics) ; Forensic engineering ; Engineering ; Computer science ; Physics ; Geology Hydrogen embrittlement and corrosion behaviors in metals ; Microstructure and Mechanical Properties of Steels ; Corrosion Behavior and Inhibition
Authors: Katya Giannios | Abhishek Chaurasia | Guillaume Thibault | Jessica L. Riesterer | Erin Stempinski | Terence P. Lo | Bambi DeLaRosa | Joe W. Gray
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-05-28)
Field: Materials Science — Surfaces, Coatings and Films

Noise Reconstruction &amp; Removal Network: A New Architecture to Denoise FIB-SEM Images Summary Recent advances in Focused Ion Beam-Scanning Electron Microscopy (FIB-SEM) allows the imaging and analysis of cellular ultrastructure at nanoscale resolution, but the collection of labels and/or noise-free data sets has several challenges, often immutable. Reasons range from time consuming manual annotations, requiring highly trained specialists, to introducing imaging artifacts from the prolonged scanning during acquisition. We propose a fully unsupervised Noise Reconstruction and Removal Network for denoising scanning electron microscopy images. The architecture, inspired by gated recurrent units, reconstructs and removes the noise by synthesizing the sequential data. At the same time the fully unsupervised training guides the network in distinguishing true signal from noise and gives comparable results to supervised architectures. We demonstrate that this new network specialized on 3D electron microscopy data sets, achieves comparable and even better results than supervised networks. Noise (video) ; Computer science ; Noise reduction ; Artificial intelligence ; Focused ion beam ; Network architecture ; Scanning electron microscope ; Pattern recognition (psychology) ; Resolution (logic) ; Signal-to-noise ratio (imaging) ; Computer vision ; Image (mathematics) ; Optics ; Telecommunications ; Physics ; Ion Electron and X-Ray Spectroscopy Techniques ; Advanced Electron Microscopy Techniques and Applications ; Integrated Circuits and Semiconductor Failure Analysis
Authors: Feng Xie | Ti- al- v 的组织随切削速度的变化情况 | LIU Yulei | Dong Yang
Source: Journal of Mechanical Engineering (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Quantitative Characterization Method of Microstructure Characteristics of Dual-phase Ti-6Al-4V Alloy 摘要： 如何快速、准确地对钛合金的微观组织含量、尺寸、分布和形态进行表征是实现其组织定量调控的关键。为实现这一目标，以钛合金Ti-6Al-4V的等轴组织为研究对象，针对钛合金中粘连组织轮廓具有不规则性而不易进行组织分割的问题，通过采用改进的快速特征点检测与绘制模板圆相结合的方法，对其切削加工后的表面微观组织图像中的粘连组织进行分割；进而采用定向度和圆形度参数来描述钛合金微观组织的分布情况和形态，并对其体积分数和晶粒尺寸进行定量表征，以便更完整地描述钛合金微观组织的特征信息。采用该方法研究钛合金Ti-6Al-4V的组织随切削速度的变化情况，验证该方法的可行性和有效性。所研究的改进的快速特征点检测与绘制模板圆相结合的方法可为材料的微观组织定量表征提供一种新思路和新方法。 Microstructure ; Alloy ; Materials science ; Characterization (materials science) ; Phase (matter) ; Dual (grammatical number) ; Titanium alloy ; Metallurgy ; Chemistry ; Nanotechnology Titanium Alloys Microstructure and Properties ; Metallurgy and Material Forming ; Aluminum Alloy Microstructure Properties