jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Hugo Krynauw | Rodaina Omar | Josepha Koehne | Georges Limbert | Neil H. Davies | Deon Bezuidenhout | Thomas Franz
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2019-09-26)
Field: Materials Science — Biomaterials

Electrospun polyester-urethane scaffold preserves mechanical properties and exhibits strain stiffening during <i>in situ</i> tissue ingrowth and degradation Abstract Consistent mechanical performance from implantation through healing and scaffold degradation is highly desired for tissue-regenerative scaffolds, e.g. when used for vascular grafts. The aim of this study was the paired in vivo mechanical assessment of biostable and fast degrading electrospun polyester-urethane scaffolds to isolate the effects of material degradation and tissue formation after implantation. Biostable and degradable polyester-urethane scaffolds with substantial fibre alignment were manufactured by electrospinning. Scaffold samples were implanted paired in subcutaneous position in rats for 7, 14 and 28 days. Morphology, mechanical properties and tissue ingrowth of the scaffolds were assessed before implantation and after retrieval. Tissue ingrowth after 28 days was 83 ± 10% in the biostable scaffold and 77 ± 4% in the degradable scaffold. For the biostable scaffold, the elastic modulus at 12% strain increased significantly between 7 and 14 days and decreased significantly thereafter in fibre but not in cross-fibre direction. The degradable scaffold exhibited a significant increase in the elastic modulus at 12% strain from 7 to 14 days after which it did not decrease but remained at the same magnitude, both in fibre and in cross-fibre direction. Considering that the degradable scaffold loses its material strength predominantly during the first 14 days of hydrolytic degradation (as observed in our previous in vitro study), the consistency of the elastic modulus of the degradable scaffold after 14 days is an indication that the regenerated tissue construct retains it mechanical properties. Scaffold ; Polyester ; Materials science ; Biomedical engineering ; Tissue engineering ; Electrospinning ; Hydrolytic degradation ; In vivo ; Elastic modulus ; Regeneration (biology) ; Composite material ; Polymer Electrospun Nanofibers in Biomedical Applications ; Tissue Engineering and Regenerative Medicine ; Bone Tissue Engineering Materials
Authors: Andrei Komar | Rifat Ahmmed Aoni | Lei Xu | Mohsen Rahmani | Andrey E. Miroshnichenko | Dragomir N. Neshev
Source:  (article, 2019-12-31)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Dielectric metasurface based advanced image processing We numerically and experimentally demonstrate an optical image processing technique in the form of edge detection of an object by exploring the angular selectivity of dielectric metasurfaces. By taking the advantages of resonant dielectric metasurfaces with spatial dispersion property, we efficiently filter-out the lower k-vector components of an image and only allow the higher k-vectors resulting in displaying the silhouettes of an object. We have considered dielectric amorphous silicon (a-Si) nanodisk with hexagonal structure interface which provides nearly zero transmission for lower k-vectors and near-unity transmission for higher k-vectors at the operating wavelength of 1550 nm. The proposed metasurface has been fabricated using electron beam lithography followed by a lift-off process. Our results suggest a new way to realize the effective edge detection with dielectric metasurfaces and open new opportunities for ultracompact optical image processing devices, having various applications in microscopy. Dielectric ; Optics ; Materials science ; Lithography ; Electron-beam lithography ; Optoelectronics ; Image processing ; Computer science ; Image (mathematics) ; Physics ; Resist ; Nanotechnology ; Artificial intelligence Metamaterials and Metasurfaces Applications ; Neural Networks and Reservoir Computing ; Plasmonic and Surface Plasmon Research
Authors: Igor Ostanin
Source: Supercomputing Frontiers and Innovations (article, 2019-06-01)
Field: Materials Science — Materials Chemistry

Distinct Element Simulation of Mechanical Properties of Hypothetical CNT Nanofabrics A universal framework for modeling composites and fabrics of micro- and nanofibers, such as carbon nanotubes, carbon fibers and amyloid fibrils, is presented. Within this framework, fibers are represented with chains of rigid bodies, linked with elastic bonds. Elasticity of the bonds utilizes recently developed enhanced vector model formalism. The type of interactions between fibers is determined by their nature and physical length scale of the simulation. The dynamics of fibers is computed using the modification of rigid particle dynamics module of the waLBerla multiphysics framework. Our modeling system demonstrates exceptionally high parallel performance combined with the physical accuracy of the modeling. The efficiency of our technique is demonstrated with an illustrative mechanical test on a hypothetical carbon nanotube textile. In this example, the elasticity of the fibers represents the coarse-grained covalent bond within CNT surface, whereas interfiber interactions represent coarse-grained van der Waals forces between cylindrical segments of nanotubes. Numerical simulation demonstrates stability and extremal strength of a hypothetical carbon nanotube fabric. Carbon nanotube ; Materials science ; van der Waals force ; Multiphysics ; Molecular dynamics ; Composite material ; Elasticity (physics) ; Covalent bond ; Finite element method ; Nanotechnology ; Structural engineering ; Computational chemistry ; Molecule ; Physics ; Chemistry Carbon Nanotubes in Composites ; Graphene research and applications ; Fiber-reinforced polymer composites
Authors: Olof Svensson | Maciej Gilski | Didier Nurizzo | Matthew W. Bowler
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2019-02-22)
Field: Materials Science — Materials Chemistry

A comparative anatomy of protein crystals: lessons from the automatic processing of 56,000 samples Synopsis The automatic processing of over 56,000 crystals by the autonomous ESRF beamline MASSIF-1 has provided a data set of crystal characteristics and properties that allows many theoretical proposals and assumptions to be evaluated experimentally. Abstract The fully automatic processing of crystals of macromolecules has presented a unique opportunity to gather information on the samples that is not usually recorded. This has proved invaluable in improving the sample location, characterisation and data collection algorithms. After operating for four years, MASSIF-1 has now processed over 56,000 samples, gathering information at each stage, from the volume of the crystal to the unit cell dimensions, space group, quality of the data collected and the reasoning behind the decisions made in data collection. This provides an unprecedented opportunity to analyse these data together, providing a detailed landscape of macromolecular crystals and intimate details of their contents and, importantly, how the two are related. The data show that mosaic spread is unrelated to the size or shape of crystals and demonstrate experimentally that diffraction intensities scale in proportion to crystal volume and molecular weight. It is also shown that crystal volume scales inversely with molecular weight. The results set the scene for the development of X-ray crystallography in a changing environment for structural biology. Crystal (programming language) ; Volume (thermodynamics) ; Massif ; Set (abstract data type) ; Sample (material) ; Data set ; Crystallography ; Protein Data Bank ; Computer science ; Data collection ; Scale (ratio) ; Data mining ; Space (punctuation) ; Data processing ; Algorithm ; Biology ; Chemistry ; Artificial intelligence ; Mathematics ; Physics ; Geography ; Statistics ; Cartography ; Database ; Paleontology ; Protein structure ; Thermodynamics Enzyme Structure and Function ; Protein Structure and Dynamics ; Mass Spectrometry Techniques and Applications
Authors: Ricardo Daniel López | Araceli Maldonado | Carlos Eduardo Belman López | Juan E. Guzmán | Mario A. García
Source: PÄDI Boletín Científico de Ciencias Básicas e Ingenierías del ICBI (article, 2019-12-13)
Field: Materials Science — Materials Chemistry

Efecto del Tamaño de Grano Austenítico en el Comportamiento Mecánico para los Aceros AISI 1045 y 4140 Mediante Experimentación y Modelado Los aceros de medio C son ampliamente utilizados en la fabricación de piezas y componentes mecánicos tales como engranajes, ejes, pernos, acoplamientos, husillos, ruedas dentadas, bielas y cigüeñales, debido a su buena resistencia mecánica, tenacidad y resistencia al desgaste. Muchas investigaciones para este tipo de aceros se han enfocado en estudiar el comportamiento al desgaste, deformación y análisis de propiedades mecánicas a temperaturas elevadas. Sin embargo, existen pocos estudios que se han enfocado en evaluar su comportamiento mecánico en función del tamaño de grano austenítico (TGA). En esta investigación, se presentan los resultados experimentales y mediante modelado numérico, del efecto del TGA antes del temple en dos aceros de medio C, AISI 1045 y 4140, con la finalidad de determinar las condiciones óptimas de procesamiento para obtener las propiedades mecánicas deseadas. El tamaño de grano fue evaluando entre 5 y 110 µm. Se utilizaron técnicas experimentales para determinar la microestructura, resistencia a la cedencia, resistencia a la tensión, la dureza y pruebas de dilatometría de temple para determinar su deformación. Los resultados simulados fueron obtenidos mediante el software JMatPro. De estos resultados se pueden mencionar que el TGA juega un papel importante en la evolución de las propiedades mecánicas para los aceros estudiados. Cuando el TGA fue superior a 15 y 45 µm para los aceros AISI 4140 y 1045 respectivamente, las propiedades mecánicas estuvieron en rangos más elevados. Los resultados mediante JMatPro estuvieron muy cercanos a los obtenidos experimentalmente, validando la simulación numérica en la predicción de las propiedades mecánicas estudiadas. Humanities ; Physics ; Materials science ; Art Metal Alloys Wear and Properties ; Microstructure and Mechanical Properties of Steels ; Metallurgy and Material Forming
Authors: Yudhi Adhitya | Armin Lawi | Hartono Hartono | Mursalin Mursalin
Source: Proceedings of the Proceedings of the 1st Workshop on Multidisciplinary and Its Applications Part 1, WMA-01 2018, 19-20 January 2018, Aceh, Indonesia (article, 2019-01-01)
Field: Chemistry — Analytical Chemistry

Cocoa Beans Digital Image Classification Based On Color Features using Multiclass Ensemble Least-Squares Support Vector Machine This research aims to determine the quality of cocoa beans through their fermentation status of their digital images. Samples of cocoa beans were scattered on a bright white paper under a controlled lighting condition. A compact digital camera was used to capture the images. The images were then pro Artificial intelligence ; Support vector machine ; Digital image ; Digital camera ; Computer vision ; Computer science ; Color balance ; Pattern recognition (psychology) ; Color image ; Image (mathematics) ; Mathematics ; Image processing Spectroscopy and Chemometric Analyses
Authors: Srilatha Panchanathan
Source: Digital Scholarship - UNLV (University of Nevada Reno) (article, 2019-05-29)
Field: Chemistry — Analytical Chemistry

Anomaly detection in hyperspectral signatures using automated derivative spectroscopy methods The goal of this research was to detect anomalies in remotely sensed Hyperspectral images using automated derivative based methods. A database of Hyperspectral signatures was used that had simulated additive Gaussian anomalies that modeled a weakly concentrated aerosol in several spectral bands. The automated pattern detection system was carried out in four steps. They were: (1) feature extraction, (2) feature reduction through linear discriminant analysis, (3) performance characterization through receiver operating characteristic curves, and (4) signature classification using nearest mean and maximum likelihood classifiers. The Hyperspectral database contained signatures with various anomaly concentrations ranging from weakly present to moderately present and also anomalies in various spectral reflective and absorptive bands. It was found that the automated derivative based detection system gave classification accuracies of 97 percent for a Gaussian anomaly of SNR -45 dB and 70 percent for Gaussian anomaly of SNR -85 dB. This demonstrates the applicability of using derivative analysis methods for pattern detection and classification with remotely sensed Hyperspectral images. Hyperspectral imaging ; Anomaly detection ; Remote sensing ; Pattern recognition (psychology) ; Anomaly (physics) ; Computer science ; Artificial intelligence ; Geology ; Physics Spectroscopy and Chemometric Analyses
Authors: Mr. Vaibhav S. Yende
Source: International Journal for Research in Applied Science and Engineering Technology (article, 2019-12-14)
Field: Chemistry — Analytical Chemistry

Analysis of different Approaches to Grading of Soybean using Image Processing and Neural Network This review paper presents the recent developments of image processing and machine vision system in an automated soybean grading system. In the field of agricultural, the accuracy and efficiency in grading process is very essential to increase the productivity of the yield. Soybean is cultivated in many regions across India. Soybean is one of the most important crops in Maharashtra. In agriculture field, Process Industries quality estimation and grading of soybean seed is one of the important task. The use of good quality seed is very important for the better production of a good quality crop and is essential for export in markets. Quality control process is very important in food industry, based on quality of food products are classified and graded into different grades. Soybean is primarily graded based on its grain shape, colour, size and texture. It is tedious for people to analyze the grades and quality in the market. The Soybean varieties and their quality are assessed through visual inspection by food quality Managers. The decision making capabilities of food quality Managers are subjected to an external influences. In this paper, image processing techniques are implemented to automate the process which overcomes the drawbacks of manual process. Here, various procedures are reviewed to obtain the percentage, quality of soybean seeds based on its size and morphological features. Artificial neural network ; Computer science ; Grading (engineering) ; Image processing ; Artificial intelligence ; Pattern recognition (psychology) ; Image (mathematics) ; Engineering Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI
Authors: Thilo Bauch | Stuart Berkowitz | Jian Chen | Daniel Cunnane | Cathy Foley | Emile Hoskinson | Rainer Krber | Anna Leese | Britton Plourde | Paul Seidel | Enrico Silva | John Martinis | Nobuyuki Yoshikawa | Keynote Speaker | Ronny Stolz | Keynote Speakers | Steve Anlage | Peter Beerel | Jim Booth | Karl Berggren | Mustafa Celik | Hypres Chen | Hsaio Mei | Sherry Cho | Jia Du | Eric Rigetti | Antonio Corcoles | Ibm Mutsuo Hidaka | Sebastian Kempf | Dieter Koelle | Eric Ladizinsky D-Wave | Ed Leonard | Thomas Ortlepp | Cis Kevin | Osborn Lps | Jie Ren | Joel Strand | Hirotaka Terai | Heqing Wang | Simit Warburton | Dag Winkler | Chalmers Wollman | Qikun Xue | Jonilyn Yoder | Zhimin Zhang | ; China | P China | Peiheng Wu | Dmitri Kirichenko | ( Hypres | Inc | ; Weiwei | Oleg Astafiev
Source:  (article, 2019-07-01)
Field: Chemistry — Spectroscopy

Organizing Sponsors More than 5 decades after the invention of Superconducting Quantum Interference Devices (SQUIDs), they are still driving research as an enabling technology and lead to emerging applications due to their unique properties. This presentation will not provide an exhaustive review on the background, theory and working principles of SQUID sensors and the Josephson effects, but will review the key facets of SQUID design, fabrication, readout circuitry and operation. In terms of fabrication technology, a short excursion will be provided on the differences between low and high temperature SQUIDs, new developments, and specific aspects in their readout circuitry. There are a variety of SQUID readout electronics which enable use of SQUIDs in a number of applications with demanding properties such as bandwidths of more than 100 MHz, exceptional slew rate and dynamic range without compromises on the usable resolution even at very low frequencies. Some examples will be introduced and discussed in view of specific applications. Squid ; USable ; Electronics ; Computer science ; Electrical engineering ; Electronic circuit ; Multiplexing ; Amplifier ; Slew rate ; Detector ; Electronic engineering ; Fabrication ; Nanotechnology ; Bandwidth (computing) ; Engineering ; Telecommunications ; Materials science Spectroscopy and Laser Applications
Authors: John Hunt
Source: Microscopy and Microanalysis (article, 2019-08-01)
Field: Materials Science — Surfaces, Coatings and Films

TMBA: DBW @70, STEM EELS SI @30, PANS TBD In recognition of David Williams' recent induction into the ranks of septuagenarian, it is appropriate to recognize TEM and STEM techniques developed under his direction, as well as postulate future directions from these works. Development of STEM spectrum-imaging is such an example, which has become the primary method for producing EELS quantitative maps of compositional and electronic properties. Geography Electron and X-Ray Spectroscopy Techniques ; Advanced Electron Microscopy Techniques and Applications ; Electronic and Structural Properties of Oxides
Authors: Vijay E V. | K. S. R. Anjaneyulu | G . Jagadesh | Poornima Chandana K . | Mohan Karthik K.
Source: International Journal of Research in Advent Technology (article, 2019-04-10)
Field: Chemistry — Analytical Chemistry

Crop Pestilence Detection Using Image Segmentation From the numerous hundreds of years, people and other living life forms' intensely reliant on Plants. Plants assume indispensable job on earth by giving them pabulum to living, wood for houses and different assets to live. Thus, we should deal with plants and farming harvests. About 68% of the populace relies upon agribusiness. Ranchers have cosmically tremendous scope of assorted variety for winnowing sundry harmonious harvests and finding the apt pesticides for plant. Ailment on plant prompts the vital decrease in both the quality and amount of rural items. The investigations of plant infection allude to the investigations of outwardly clear examples on the plants. Checking of wellbeing and sickness on plant assumes a fundamental job in prosperous development of harvests in the ranch. In early days, the checking and examination of plant maladies were done physically by the skill individual in that field. This requires colossal measure of work and also requires extortionate handling time. Early recognition and exact recognizable proof of sicknesses can control the spread of contamination; it ends up easy to distinguish plant illness with picture preparing procedures. For the most part we can watch the side effects of ailment on leafs, stems, blossoms and so on. So here we use plant leafs for ID of sickness influenced plants. Distinctive plant leaf bears diverse maladies. There are a rundown of techniques and classifiers to distinguish plant leaf illnesses , the examination is made on the plant leaf infection discovery using Digital Image processing approach. Crop ; Image segmentation ; Artificial intelligence ; Computer vision ; Segmentation ; Computer science ; Agronomy ; Biology Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI
Authors: Jonathon J. O’Brien
Source: Carolina Digital Repository (University of North Carolina at Chapel Hill) (article, 2019-08-08)
Field: Chemistry — Spectroscopy

Statistical Methods for Mass Spectrometry Proteomics DNA makes RNA makes proteins is the central dogma of molecular biology. While the measurement of RNA has dominated the landscape of scientificc inquiry for many years, often the true outcome of interest is the final protein product. Microarray and RNAseq studies do not tell researchers anything about what happens during and after translation. For this reason interest in directly measuring the proteome has flourished. Unfortunately the direct analysis of proteins often creates a complicated inferential situation. When scientists want to see the whole proteome (or at least a large unknown sample of the proteome) mass spectrometry is often the most powerful technology available. Mass spectrometers allow researchers to separate proteins from complex samples and obtain information about the relative abundance of around 10,000 proteins in a given experiment. However the analysis of mass spectrometry proteomics data involves a complicated statistical inference problem. Inference is made on relative protein abundance by examining protein fragments called peptides. This inference problem is complicated by the two intrinsic statistical didifficulties of proteomics; matched pairs and non-ignorable missingness, which combine to create unexpected challenges for statisticians. Here I will discuss the complexities of modeling mass spectrometry proteomics and provide new methods to improve both the accuracy and depth of protein estimation. Beyond point estimation, great interest has developed in the proteomics community regarding the clustering of high throughput data. Although the strange nature of proteomics data likely causes unique problems for clustering algorithms, we found that work needed to be done regarding the statistical interpretation of clustering before any special cases could be considered. For this reason we have explored clustering from a statistical framework and used this foundation to establish new measures of clustering performance. These indices allow for the interpretation of a clustering problem in the commonly understood framework of sensitivity and specificity. Mass spectrometry ; Proteomics ; Chemistry ; Computer science ; Chromatography Advanced Proteomics Techniques and Applications ; Advanced Biosensing Techniques and Applications ; Machine Learning in Bioinformatics