jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Xuguang Liu
Source: Scholarship@Western (Western University) (article, 2019-01-01)
Field: Chemistry — Organic Chemistry

Applications of Phosphotyrosine Superbinding SH2 Domain Variants Protein tyrosine kinases (PTKs, or TKs) have emerged as one of the most intensively pursued targets in the development of anti-cancer therapeutics, due to their critical roles in the phosphotyrosine (pTyr)-mediated signaling network that regulates many cancer-related cellular activities. The TKs, tyrosine phosphorylation phosphatases (PTPs) and pTyr recognition SH2 proteins are intensively tyrosine phosphorylated, which play a pivotal role in determining the signaling outcome of this network. More than 50% of all human proteins are tyrosine phosphorylated and many of these TK substrates have been proven functional in TK regulated cellular activities. Therefore, proteomics studies of tyrosine phosphorylation are of great value for expanding our understanding of this network and its role in tumorigenesis.\nTaking advantage an engineered SH2 domain with superb pTyr binding affinity, an SH2-affinity purification mass spectrometry (SH2-AP-MS) assay was developed and optimized for global TK status profiling by determining the abundance of functionally significant TK pTyr peptides including the activation loops. Multiple known TK biomarkers were identified by this assay from a minute amount of protein extracts from cultured cells or clinical leukemia or solid tumor samples. In the quantitative AP-MS study of cancer cells treated by targeted therapeutics, differential TK responses were monitored. The receptor c-Kit was found to be dramatically upregulated with long-term trastuzumab treatment which contributed to acquired trastuzumab resistance in the SK-BR-3 breast cancer cells. These results revealed the potential applications of SH2-AP-MS in the discovery of novel TK biomarkers and examination of TK positive cancers in the clinical setting. In addition, a SH2 superbinder modified yeast two hybrid (Y2H) system was developed that is potentially capable of identifying TK substrate in a high-precision and high-throughput manner. This system consisted of an SH2-superbinder-fused bait that greatly promoted the reporter gene readout, a TK substrate prey or cDNA library preys, and a co-expressed TK under the control of a conditional promoter that allowed for reverse screen to eliminate false positives. In a medium-scale cDNA library screening for Src kinase substrates, 94 positive colonies were isolated representing 48 unique in-frame proteins or protein fragments, of which at least 9 proteins are known Src substrates or direct Src interactors. SH2 domain ; Domain (mathematical analysis) ; Computer science ; Chemistry ; Computational biology ; Proto-oncogene tyrosine-protein kinase Src ; Biology ; Biochemistry ; Mathematics ; Signal transduction Organophosphorus compounds synthesis ; PI3K/AKT/mTOR signaling in cancer ; Chemical Synthesis and Analysis
Authors: John-Ioannis Grigoriadis
Source: Acta Scientific Pharmaceutical Sciences (article, 2019-07-10)
Field: Materials Science — Materials Chemistry

“Miracle Molecules” AI Computer-Designed, Quantum Thinking 3D Small Molecules for Brain Cancer Miracle ; Cognitive science ; Quantum ; Molecule ; Computer science ; Neuroscience ; Human–computer interaction ; Psychology ; Physics ; Philosophy ; Quantum mechanics Machine Learning in Materials Science
Authors: Z. Faidon Brotzakis | Peter G. Bolhuis
Source: The Journal of Chemical Physics (preprint, 2019-11-06)
Field: Chemistry — Physical and Theoretical Chemistry

Approximating free energy and committor landscapes in standard transition path sampling using virtual interface exchange Transition path sampling is a powerful technique for investigating rare transitions, especially when the mechanism is unknown and one does not have access to the reaction coordinate. Straightforward application of transition path sampling does not directly provide the free energy landscape nor the kinetics. This drawback has motivated the development of path sampling extensions able to simultaneously access both kinetics and thermodynamics, such as transition interface sampling, and the reweighted path ensemble. However, performing transition interface sampling is more involved than standard two-state transition path sampling and still requires (some) insight into the reaction to define interfaces. While packages that can efficiently compute path ensembles for transition interface sampling are now available, it would be useful to directly compute the free energy from a single standard transition path sampling simulation. To achieve this, we present here an approximate method, denoted virtual interface exchange transition path sampling, that makes use of the rejected pathways in a form of waste recycling. The method yields an approximate reweighted path ensemble that allows an immediate view of the free energy landscape from a standard single transition path sampling simulation, as well as enables a committor analysis. Path (computing) ; Interface (matter) ; Energy landscape ; Sampling (signal processing) ; Computer science ; Energy (signal processing) ; Umbrella sampling ; Algorithm ; Computational science ; Statistical physics ; Simulation ; Chemistry ; Mathematics ; Physics ; Computational chemistry ; Parallel computing ; Statistics ; Computer vision ; Thermodynamics ; Molecular dynamics Advanced Physical and Chemical Molecular Interactions ; NMR spectroscopy and applications ; Advanced Chemical Physics Studies
Authors: Rees Chang
Source: eScholarship (California Digital Library) (article, 2019-08-07)
Field: Materials Science — Materials Chemistry

Automating Anharmonic Lattice Thermal Conductivity Calculations using Compressed Sensing Lattice Dynamics Engineering heat transfer is critical for applications\nin heat exchangers, semiconductor devices,\nthermoelectrics and more. This demand motivates a\nhigh-throughput computational methodology for\nsystematically designing materials with improved\nthermal properties. One emerging method which can\nrapidly and explicitly consider phonon-phonon\ninteractions even for highly anharmonic materials is\nCompressive Sensing Lattice Dynamics (CSLD). In\nfact, CSLD accurately predicts 2nd (harmonic) and\n3rd+ order (anharmonic) interatomic force\nconstants (IFCs) with orders of magnitude fewer\nDensity Functional Theory (DFT) calculations than\nconventional methods. However, doing CSLD can be\nan exhaustive, many-step process requiring an\nintimate knowledge of its sensitivity to parameters.\nConsequently, this work implements an automatic\nCSLD workflow capable of obtaining the thermal\nconductivity of potentially thousands of materials,\nbenchmarks the stability of the workflow against\nmaterials with a range of anharmonicity, and begins\nconstructing a dataset of thermal conductivity values\nand phonon dispersion curves to be stored in the Materials Project for public use. Anharmonicity ; Phonon ; Thermal conductivity ; Thermoelectric materials ; Materials science ; Lattice (music) ; Condensed matter physics ; Workflow ; Statistical physics ; Computer science ; Physics ; Composite material Machine Learning in Materials Science ; Thermal properties of materials ; Advanced Thermoelectric Materials and Devices
Authors: Brian J. Caffrey | Alexander V. Maltsev | Marta González‐Freire | Lisa M. Hartnell | Luigi Ferrucci | Sriram Subramaniam
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2019-01-01)
Field: Materials Science — Surfaces, Coatings and Films

Automated methods for 3D Segmentation of Focused Ion Beam-Scanning Electron Microscopic Images Abstract Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) is an imaging approach that enables analysis of the 3D architecture of cells and tissues at resolutions that are 1-2 orders of magnitude higher than that possible with light microscopy. The slow speeds of data collection and analysis are two critical problems that limit more extensive use of FIB-SEM technology. Here, we present a robust method that enables rapid, large-scale acquisition of data from tissue specimens, combined with an approach for automated data segmentation using machine learning, which dramatically increases the speed of image analysis. We demonstrate the feasibility of these methods through the 3D analysis of human muscle tissue by showing that our process results in an improvement in speed of up to three orders of magnitude as compared to manual approaches for data segmentation. All programs and scripts we use are open source and are immediately available for use by others. Impact Statement The high-throughput, easy-to-use and versatile segmentation pipeline described in our manuscript will enable rapid, large-scale statistical analysis of sub-cellular structures in tissues. Focused ion beam ; Segmentation ; Computer science ; Pipeline (software) ; Artificial intelligence ; Process (computing) ; Computer vision ; Image segmentation ; Scanning electron microscope ; Pattern recognition (psychology) ; Optics ; Ion ; Chemistry ; Physics Electron and X-Ray Spectroscopy Techniques ; Molecular Biology Techniques and Applications ; Advanced Electron Microscopy Techniques and Applications
Authors: Mariem Ben Ameur
Source: SPIRE - Sciences Po Institutional REpository (preprint, 2019-12-14)
Field: Materials Science — Polymers and Plastics

Caractérisation mécanique et suivi par émission acoustique des mécanismes d’endommagement des composites à fibres hybrides lin/carbone L'utilisation de fibres naturelles comme renfort permet d'améliorer les performances environnementales des matériaux composites ainsi que leurs propriétés d’amortissement. Néanmoins, ces composites à fibres naturelles présentent des performances mécaniques moins intéressantes que celles des composites à fibres synthétiques. Dans ce contexte, cette étude propose d'élaborer des structures composites à renfort hybrides constituées des fibres de lin et de carbone. L’objectif de cette hybridation est de trouver un compromis entre les propriétés mécaniques et dissipatives. Tout d'abord, le comportement en statique des composites à fibres de lin, fibres de carbone et fibres hybrides lin/carbone a été analysé. Les caractéristiques élastiques principales d’ un pli UD en contraintes planes sont ainsi déterminées .Par ailleurs, un suivi et une analyse des mécanismes d'endommagement ont été effectués au moyen de la technique d'émission acoustique associée à des observations microscopiques. Dans un souci de mieux répondre aux besoins industriels, le comportement des composites soumis aux essais de fatigue cyclique doit être étudié. Pour ce faire, le comportement en fatigue de ces matériaux à renforts non-hybrides et hybrides a été analysé sous sollicitations de traction et de flexion trois points. L’ influence de l’ hybridation sur la durée de vie en fatigue de ces composites a été établie. Enfin, une étude expérimentale et une modélisation par élément finis du comportement vibratoire des composites non-hybrides et hybrides ont été réalisées. Ainsi, le rôle des différentes fibres, de l’orientations des fibres, de séquences d’empilement dans l'amortissement en vibrations a été discuté. Acoustic emission ; Composite material ; Characterization (materials science) ; Materials science ; Fiber ; Nanotechnology Natural Fiber Reinforced Composites ; Mechanical Behavior of Composites ; Cellular and Composite Structures
Authors: Mr. Vaibhav S. Yende
Source: International Journal for Research in Applied Science and Engineering Technology (article, 2019-05-31)
Field: Chemistry — Analytical Chemistry

Quality Analysis and Grading of Soybean using Image Processing and Neural Network 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 is very important in food industry because 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. This paper attempts to automate the grading process by using image processing and machine vision techniques. Soybean's grade is affected by damaging, decolourization, infection by insects, immaturity and shrivels, splitting, breaking, cracks, inorganic and organic foreign matter present in the sample. One of the objectives of this paper is to study the effect of these parameters on shape, colour, size and texture of the soybean image. In the present soybean-handling scenario, type and quality are identified manually by visual inspection which is tedious and not accurate. There is need for the growth of accurate, fast and objective system for quality determination of food grains. This paper is automate the system for grading of soybean by extracting morphological features as attributes for classification using image processing techniques and artificial neural network. This method requires minimum time and it is low in cost. Grading (engineering) ; Artificial neural network ; Computer science ; Artificial intelligence ; Image processing ; Image quality ; Pattern recognition (psychology) ; Computer vision ; Agricultural engineering ; Image (mathematics) ; Engineering Spectroscopy and Chemometric Analyses
Authors: Bart Van Puyvelde | Sander Willems | Ralf Gabriels | Simon Daled | Laura De Clerck | Sofie Vande Casteele | An Staes | Francis Impens | Dieter Deforce | Lennart Martens | Sven Degroeve | Maarten Dhaenens
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2019-06-26)
Field: Chemistry — Spectroscopy

Removing the hidden data dependency of DIA with predicted spectral libraries Data-Independent Acquisition (DIA) generates comprehensive yet complex mass spectrometric data, which imposes the use of data-dependent acquisition (DDA) libraries for deep peptide-centric detection. We here show that DIA can be redeemed from this dependency by combining predicted fragment intensities and retention times with narrow window DIA. This eliminates variation in library building and omits stochastic sampling, finally making the DIA workflow fully deterministic. Especially for clinical proteomics, this has the potential to facilitate inter-laboratory comparison. Significance of the Study Data-independent acquisition (DIA) is quickly developing into the most comprehensive strategy to analyse a sample on a mass spectrometer. Correspondingly, a wave of data analysis strategies has followed suit, improving the yield from DIA experiments with each iteration. As a result, a worldwide wave of investments in DIA is already taking place in anticipation of clinical applications. Yet, there is considerable confusion about the most useful and efficient way to handle DIA data, given the plethora of possible approaches with little regard for compatibility and complementarity. In our manuscript, we outline the currently available peptide-centric DIA data analysis strategies in a unified graphic called the DIAmond DIAgram. This leads us to an innovative and easily adoptable approach based on predicted spectral information. Most importantly, our contribution removes what is arguably the biggest bottleneck in the field: the current need for Data Dependent Acquisition (DDA) prior to DIA analysis. Fractionation, stochastic data acquisition, processing and identification all introduce bias in the library. By generating libraries through data independent, i.e. deterministic acquisition, stochastic sampling in the DIA workflow is now fully omitted. This is a crucial step towards increased standardization. Additionally, our results demonstrate that a proteome-wide predicted spectral library can surrogate an exhaustive DDA Pan-Human library that was built based on 331 prior DDA runs. Computer science ; Data acquisition ; Workflow ; Bottleneck ; Data mining ; Data science ; Profiling (computer programming) Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Biosensors and Analytical Detection
Authors: Carlos Henrique Lauermann
Source: Lume (Universidade Federal do Rio Grande do Sul) (article, 2019-01-01)
Field: Materials Science — Materials Chemistry

Estudo numérico e experimental de desvolatilização de carvão mineral em DTF O objetivo deste trabalho foi avaliar o processo de desvolatilização de um carvão brasileiro a fim de aumentar o entendimento do processo de combustão e apoiar o desenvolvimento de ferramentas e processos mais eficientes no uso desse combustível. O estudo da desvolatilização foi feito experimentalmente utilizando-se um reator de queda livre (DTF), em atmosfera de nitrogênio, para cinco temperaturas e diferentes tempos de residência. A análise do resíduo carbonoso gerado foi feita por meio de técnicas termogravimétricas (TGA). A menor temperatura em que a desvolatilização ocorreu foi 670ºC e a maior desvolatilização em 1100ºC. No desenvolvimento do estudo numérico, foi empregado um modelo físico-matemático unidimensional, transiente para determinar parâmetros cinéticos para cinética de Arrhenius e Arrhenius modificada. Os resultados mostraram que a cinética de Arrhenius representa melhor o comportamento tanto para baixas temperaturas (BT) como para altas temperaturas (AT). Os parâmetros cinéticos obtidos são Ev = 1,1559.105 J/mol, Av = 2,5948.105 s-1 para BT e Ev = 1,3081.105 J/mol, Av = 3,2459.105 s-1 para AT. Geology ; Mineralogy Graphite, nuclear technology, radiation studies ; Zeolite Catalysis and Synthesis ; Iron and Steelmaking Processes
Authors: Nicole Hondow | Martha Ilett | John W. Wills | Stuart Micklethwaite | Rik Brydson | Andy Brown
Source: Microscopy and Microanalysis (article, 2019-08-01)
Field: Materials Science — Surfaces, Coatings and Films

Quantifying the Dispersion of Nanoparticles by Electron Microscopy The concept of representative imaging and analysis is a significant challenge in characterisation and is one of vital importance when examining 'real-world' samples, which are often multi-component, complex systems. This is especially evident with nanoparticles, which have increasing applications in strategically important fields, from healthcare to energy generation. When appropriately engineered nanoparticles can be the central and active component of a product, e.g. as agents for MRI contrast enhancement or the UV block in suncream. Kingdom ; Library science ; Media studies ; Art history ; Sociology ; History ; Computer science Electron and X-Ray Spectroscopy Techniques ; Advanced Electron Microscopy Techniques and Applications ; Anodic Oxide Films and Nanostructures
Authors: Arief Sudarmaji | Agus Margiwiyatno | Susanto Budi Sulistyo
Source: Jurnal Keteknikan Pertanian Tropis dan Biosistem (article, 2019-08-30)
Field: Chemistry — Analytical Chemistry

Karakteristik Deret Sensor Gas Mos dalam Identifikasi Patchouli Alcohol pada Minyak Nilam Menggunakan Metode Jaringan Syaraf Tiruan Penentuan kualitas minyak nilam menggunakan metode Gas Chromatography and Mass Spektrometry (GC-MS) secara laboratorium tidak memungkinkan dilakukan oleh Usaha Mikro, Kecil, dan Menengah (UMKM). Untuk itu, perlu ada suatu alat dan analisis yang dapat mengidentifikasi minyak nilam yang lebih sederhana dan murah yaitu menggunakan alat ukur aroma dan volatil berbasis sensor gas. Penelitian ini menggunakan jenis sensor gas Metal Oxide Semiconductor (MOS) yang terdiri dari 9 deret sensor gas MOS (TGS-2600, TGS-2602, TGS-2620, MQ-3, MQ-135, MQ-137, F-AQ1, F-SB30, dan FIS-12A) dan sistem akuisisi data. Penelitian ini bertujuan untuk (1) mengetahui respon sensitifitas individu sensor gas terhadap konsentrasi patchouli alcohol pada minyak nilam, (2) mengetahui tingkat keberhasilan sensor gas dengan perbedaan modulasi pada sensor gas dalam mengklasifikasi konsentrasi patchouli alcohol pada minyak nilam menggunakan metode jaringan syaraf tiruan backpr opagation . Luaran sensor MOS dinyatakan dengan Sensitivitas, yaitu perbandingan antara resistansi saat pengukuran udara kering dengan resistansi saat pengukuran minyak nilam. Hasil penelitian menunjukkan sensor TGS-2602 memberikan respon sensitifitas paling tinggi. Modulasi terbaik selama pengukuran yaitu pada frekuensi 0,25Hz duty cycle 75% dengan 9 neuron hidden layer menghasilkan akurasi pelatihan 98,6% dan akurasi pengujian 81,9%. Rata-rata akurasi sistem identifikasi ini adalah 90,3%. Patchouli ; Chemistry ; Mathematics ; Physics ; Chromatography ; Essential oil Spectroscopy and Chemometric Analyses
Authors: Mayank Aggarwal
Source: Acta Crystallographica Section A Foundations and Advances (article, 2019-07-20)
Field: Materials Science — Materials Chemistry

Autoscoring of protein crystallization drops in <i>ROCK MAKER</i> using <i>MARCO</i> Crystallization ; Protein crystallization ; Materials science ; Chemical engineering ; Engineering Enzyme Structure and Function ; Crystallization and Solubility Studies ; Freezing and Crystallization Processes
Authors: Ondrej Dyck | Andrew R. Lupini | Maxim Ziatdinov | Xin Li | Sergei V. Kalinin | Stephen Jesse
Source: Microscopy and Microanalysis (article, 2019-08-01)
Field: Materials Science — Materials Chemistry

Towards Atomic Scale Quantum Structure Fabrication in 2D Materials Atomic units ; Fabrication ; Scale (ratio) ; Materials science ; Nanotechnology ; Quantum ; Physics ; Quantum mechanics ; Medicine Graphene research and applications ; Electronic and Structural Properties of Oxides ; Quantum and electron transport phenomena
Authors: Darusman Darusman | Zulfahrizal Zulfahrizal | Agus Arip Munawar
Source:  (article, 2019-01-01)
Field: Chemistry — Analytical Chemistry

Rapid Assessment of Soil Quality Indices Using Infrared Reflectance Spectroscopy In this present study, we investigated the use of near infrared reflectance spectroscopy (NIRS) as a rapid and robust method to assess and evaluate soil quality namely soil carbon organic (SOC) and pH. Diffuse reflectance spectral data were acquired and recorded for 20 g soil samples from four diff Diffuse reflectance infrared fourier transform ; Reflectivity ; Near infrared reflectance spectroscopy ; Infrared spectroscopy ; Environmental science ; Soil carbon ; Infrared ; Soil quality ; Spectroscopy ; Remote sensing ; Near-infrared spectroscopy ; Materials science ; Soil test ; Soil water ; Soil science ; Chemistry ; Geology ; Optics ; Physics Spectroscopy and Chemometric Analyses
Authors: Jana Kholová | K Chandalavada | Vadez | S. Choudhary | M Govindaraj | P Bagade | Martin D. Smith | Robert M. Lindsay | Stefan Gerth | Joelle Claußen | W Palmer | A Matheka | Joshua N. Cobb | N G Enghwa
Source: Open Access Repository of ICRISAT (International Crops Research Institute for the Semi-Arid Tropics) (article, 2019-09-01)
Field: Chemistry — Analytical Chemistry

Development of mobile sensors for estimation of grain qualities and contaminants to enhance nutrition and safety of grain-products in developing countries; current status The governments of several developing countries responded to their population “malnutrition crisis” (P.Webb et al., 2018), among others, by promotion of crops of high nutritional value and their enhanced usage for food products formulations (e.g. “Millet Mission” in India or “Blending Policy” in Kenya). Simultaneously, several CGIAR crop improvement programs-initiated the development of nutritionally enhanced crop cultivars (e.g. ICRISAT, CIAT, IIT). In developing countries, the promotion of novel cultivars is generally a slow and tedious process, especially if the improved grain (quantity or quality) doesn’t ultimately result in the economic incentives (e.g. the market price). Thus far, there is no economic advantage directly linked to the trade of bio-fortified crop cultivars in developing countries which does prevents their accelerated adoption. This may change if/once the necessary information on a crops value is enabled. Developing country ; Incentive ; Business ; Promotion (chess) ; Malnutrition ; Crop ; Population ; Agricultural economics ; Cultivar ; Biotechnology ; Natural resource economics ; Economic growth ; Economics ; Agronomy ; Biology ; Environmental health ; Political science Spectroscopy and Chemometric Analyses ; Banana Cultivation and Research ; Smart Agriculture and AI