jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Meichen Song | Ziyuan Niu | Karin Hasegawa | Yuefan Deng | Miriam Rafailovich | Marcia Simon | Peng Zhang
Source: Research Square (preprint, 2021-08-17)
Field: Materials Science — Materials Chemistry

Modeling of the Thermal Properties of SARS-CoV-2 S-protein Abstract We present the thermal and conformational states of the spike glycoprotein (S-protein) of SARS-CoV-2 at six temperatures ranging from 3℃ to 95℃ by all-atom molecular dynamics (MD) µs-scale simulations. While corroborating with clinical results of the temperature impact on the COVID-19 infection, we examine the potential phase transitions of the S-protein in the temperature range and our simulation results revealed the following thermal properties of the S-protein: (1) It is structurally stable at 3℃, agreeing with observations that the virus stays active for more than two weeks in the cold supply chain; (2) Its structure varies more significantly for temperature window of 60℃ to 80℃ than in all other windows; (3) The sharpest structural variations occur near 60℃, signaling a plausible critical temperature nearby; (4) The maximum deviation of the receptor-binding domain at 37°C suggests the anecdotal observation that the virus is most infective at 37°C; (5) The in silico data agree with reported experiments of the SARS-CoV-2 survival times from weeks to seconds by our clustering approach analysis. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ; Coronavirus disease 2019 (COVID-19) ; Environmental science ; Medicine ; Internal medicine Thermal properties of materials ; Energetic Materials and Combustion ; Thermography and Photoacoustic Techniques
Authors: Zicong Wu | Chuqian Lou | Zhu Jin | Shaoping Huang | Ning Liu | Yun Zou | Mirko Kovač | Anzhu Gao | Guang‐Zhong Yang
Source: arXiv (Cornell University) (preprint, 2021-06-07)
Field: Materials Science — Biomaterials

Robotic Electrospinning Actuated by Non-Circular Joint Continuum Manipulator for Endoluminal Therapy Electrospinning has exhibited excellent benefits to treat the trauma for tissue engineering due to its produced micro/nano fibrous structure. It can effectively adhere to the tissue surface for long-term continuous therapy. This paper develops a robotic electrospinning platform for endoluminal therapy. The platform consists of a continuum manipulator, the electrospinning device, and the actuation unit. The continuum manipulator has two bending sections to facilitate the steering of the tip needle for a controllable spinning direction. Non-circular joint profile is carefully designed to enable a constant length of the centreline of a continuum manipulator for stable fluid transmission inside it. Experiments are performed on a bronchus phantom, and the steering ability and bending limitation in each direction are also investigated. The endoluminal electrospinning is also fulfilled by a trajectory following and points targeting experiments. The effective adhesive area of the produced fibre is also illustrated. The proposed robotic electrospinning shows its feasibility to precisely spread more therapeutic drug to construct fibrous structure for potential endoluminal treatment. Electrospinning ; Spinning ; Materials science ; Imaging phantom ; Computer science ; Biomedical engineering ; Mechanical engineering ; Composite material ; Engineering ; Physics ; Polymer ; Optics Electrospun Nanofibers in Biomedical Applications ; Tissue Engineering and Regenerative Medicine ; Soft Robotics and Applications
Authors: Mochammad Wahyudi | Noor Akhmad Setiawan | Bambang Sugiyantoro | I Made Yulistya Negara | Gilang Adityasakti
Source: JAREE (Journal on Advanced Research in Electrical Engineering) (article, 2021-04-01)
Field: Materials Science — Materials Chemistry

Detection of Partial Discharge in Oil Filled-Tank using Acoustic in Audio Frequency In this paper, the acoustic emission of partial discharge (PD) in oil contained in the tank was detected by using microphone sensor. PD was generated by point-to-flat electrodes under DC high voltage. The given variables were the DC voltage stress, the electrode gap distance, and the location of PD and sensors. The acoustic and high frequency current were recorded along with the increased voltage. The acoustic signal was then transformed using the fast Fourier transform (FFT) to obtain the frequency spectrum. Furthermore, the acoustic waveforms, the acoustic frequency spectrum, and the PD current were analyzed and correlated. The results showed that the PD could be detected by its audio frequency signal. The impulse-shaped acoustic signal was recognized as a transition condition from normal to PD. The acoustic sensor attached to the outer wall of tank (contact type) was more sensitive than sensor that had a distance from the tank (non-contact type). The perfection level of impulse waveform may indicate the PD location in the oil-filled tank. The signal of acoustic and current did also not affect each other. Acoustics ; Waveform ; Microphone ; Materials science ; Partial discharge ; Impulse (physics) ; SIGNAL (programming language) ; Acoustic emission ; Voltage ; Electrode ; Sound pressure ; Electrical engineering ; Physics ; Engineering ; Computer science High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Aerosol Filtration and Electrostatic Precipitation
Authors: Jie Sun | Mei Li | Di Wang | Ting-Ru Lin | Jingyi Chen | Yu Zhang | Qing Mu | Huiting Su | Na Wu | Aiyu Liu | Yimeng Yu | Yulan Liu | Shaojie Wang | Xin Yu | Jingzhu Guo | Wei‐Dong Yu
Source: Research Square (preprint, 2021-06-29)
Field: Chemistry — Analytical Chemistry

Cell Cycle Arrest, An Important Mechanism of Action of Compound Kushen Injection, Prevents Colorectal Cancer: Network Pharmacology Analysis and Experimental Validation Abstract Compound Kushen injection (CKI) is the most widely used traditional Chinese medicine preparation for the comprehensive treatment of colorectal cancer (CRC) in China, but its underlying molecular mechanisms of action are still unclear. The present study employed a network pharmacology approach, in which we constructed a “bioactive compound-target-pathway” network. Experimental RNA sequencing (RNA-Seq) analysis was performed to identify a key “bioactive compound-target-pathway” network for subsequent experimental validation. Cell cycle, proliferation, autophagy, and apoptosis assays and a model of azoxymethane/dextran sodium sulfate-induced colorectal carcinogenesis in mice were employed to detect the biological effect of CKI on CRC. Real-time reverse-transcription polymerase chain reaction, Western blot, and immunohistochemistry were performed to verify the selected targets and pathways. We constructed a predicted network that included 82 bioactive compounds, 34 targets, and 33 pathways and further screened an anti-CRC CKI “biological compound (hesperetin 7-O-rutinoside, genistein 7-O-rutinoside, and trifolirhizin)-target (p53 and checkpoint kinase 1 [CHEK1])” network that targeted the “cell cycle pathway”. Validation experiments showed that CKI effectively induced the cell-cycle arrest of CRC cells in vitro and suppressed the development of CRC in vivo by downregulating the expression of p53 and CHEK1. Our findings confirmed that inducing cell-cycle arrest by CKI is an important mechanism of its anti-CRC action, which provides a direct and scientific experimental basis for the clinical application of CKI. Azoxymethane ; Cell cycle ; Cell cycle checkpoint ; Carcinogenesis ; Colorectal cancer ; Cancer research ; Cell growth ; Mechanism of action ; Pharmacology ; Apoptosis ; Chemistry ; Cancer ; Biology ; In vitro ; Biochemistry ; Gene ; Genetics Chromatography in Natural Products ; Medicinal Plant Pharmacodynamics Research ; Traditional Chinese Medicine Analysis
Authors: Sonja Jordeva | Silvana Zhezhova | Sashka Golomeova Longurova
Source: Goce Delchev University Repository (Goce Delčev University of Štip) (article, 2021-04-15)
Field: Materials Science — Polymers and Plastics

TECHNOLOGICAL PROCESS OF FINISHING OF THE MEN'S SHIRT AND QUALITY CONTROL The technological process of finishing as the last stage of the technology of making clothes is a very important stage of the production of clothes because the items of clothing get the final look. Due to this, every garment factory should be equipped with modern and productive machines and finishing devices (especially for final ironing), as well as with professional staff. Smaller garment companies and fashion studios mostly use simple steam presses and tables for ironing of the all parts of the clothes which extends the finishing time. The paper describes the procedures and machines in the final ironing as well as the way of quality control of men's shirts. In the practical part of the paper, an analysis of the process of finishing men's shirts in a fashion confection was made and a final control of 661 men's shirts was performed. The results show that the most common mistakes are: bad position of the button or damaged button, mistakes from the final ironing and mistakes in the shirt's seams. Thanks to the final control it is still possible to correct some mistakes in the shirts by their re-entering in the production process, and damaged products or those with irreparable defects can be classified into a lower class with a reduced price. Clothing ; Factory (object-oriented programming) ; Quality (philosophy) ; Engineering ; Process (computing) ; Production (economics) ; Control (management) ; Manufacturing engineering ; Operations management ; Computer science ; Law Textile materials and evaluations
Authors: Jake Kline | Christopher Mullen | Kenneth R. Durbin | Ryan Oates | Romain Huguet | John E. P. Syka | Luca Fornelli
Source: ChemRxiv (preprint, 2021-02-16)
Field: Chemistry — Spectroscopy

Sequential Ion-Ion Reactions for Enhanced Gas-Phase Sequencing of Large Intact Proteins in a Tribrid Orbitrap Mass Spectrometer Obtaining extensive sequencing of an intact protein is essential in order to simultaneously determine both the nature and exact localization of chemical and genetic modifications which distinguish different proteoforms arising from the same gene. To effectively achieve such characterization is necessary to take advantage of the analytical potential offered by the top-down mass spectrometry (TDMS) approach to protein sequence analysis. However, as a protein increases in size, its gas-phase dissociation produces overlapping, low signal-to-noise fragments. The application of advanced ion dissociation techniques such as electron transfer dissociation (ETD) and ultraviolet photodissociation (UVPD) can improve the sequencing results compared to slow-heating techniques such as collisional dissociation; nonetheless, even ETD and UVPD-based approaches have thus far fallen short in their capacity to reliably enable comprehensive characterization of proteoforms 30 kDa. To overcome this issue, we have applied proton transfer charge reduction (PTCR) to limit signal overlap in tandem mass spectra (MS 2 ) produced by ETD (alone or with supplemental ion activation, EThcD). Compared to conventional MS 2 experiments, following ETD/EThcD MS 2 with PTCR MS 3 prior to m/z analysis of deprotonated product ions in the Orbitrap mass analyzer proved beneficial for the identification of additional large protein fragments (10 kDa), thus improving the overall sequencing and in particular the coverage of the central portion of all four analyzed proteins spanning from 29 to 56 kDa. Specifically, PTCR-based data acquisition led to 39% sequence coverage for the 56 kDa glutamate dehydrogenase, further increased to 44% by combining fragments obtained via HCD followed by PTCR MS 3 . Orbitrap ; Mass spectrometry ; Chemistry ; Ion ; Gas phase ; Analytical Chemistry (journal) ; Chromatography ; Physical chemistry ; Organic chemistry Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Ion-surface interactions and analysis
Authors: Anand Dixit | Vivekananda Roy
Source: Statistical Analysis and Data Mining The ASA Data Science Journal (preprint, 2021-09-25)
Field: Chemistry — Analytical Chemistry

Analyzing relevance vector machines using a single penalty approach Abstract Relevance vector machine (RVM) is a popular sparse Bayesian learning model typically used for prediction. Recently it has been shown that improper priors assumed on multiple penalty parameters in RVM may lead to an improper posterior. Currently in the literature, the sufficient conditions for posterior propriety of RVM do not allow improper priors over the multiple penalty parameters. In this article, we propose a single penalty relevance vector machine (SPRVM) model in which multiple penalty parameters are replaced by a single penalty and we consider a semi‐Bayesian approach for fitting the SPRVM. The necessary and sufficient conditions for posterior propriety of SPRVM are more liberal than those of RVM and allow for several improper priors over the penalty parameter. Additionally, we also prove the geometric ergodicity of the Gibbs sampler used to analyze the SPRVM model and hence can estimate the asymptotic standard errors associated with the Monte Carlo estimate of the means of the posterior predictive distribution. Such a Monte Carlo standard error cannot be computed in the case of RVM, since the rate of convergence of the Gibbs sampler used to analyze RVM is not known. The predictive performance of RVM and SPRVM is compared by analyzing two simulation examples and three real life datasets. Relevance vector machine ; Prior probability ; Computer science ; Posterior probability ; Bayesian probability ; Penalty method ; Bayesian inference ; Monte Carlo method ; Markov chain Monte Carlo ; Artificial intelligence ; Algorithm ; Support vector machine ; Mathematical optimization ; Machine learning ; Mathematics ; Statistics Spectroscopy and Chemometric Analyses ; Statistical Methods and Inference ; Face and Expression Recognition
Authors: Scott A. Robson | Çağdaş Dağ | Hongwei Wu | Joshua J. Ziarek
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-01-19)
Field: Chemistry — Spectroscopy

TRACT revisited: an algebraic solution for determining overall rotational correlation times from cross-correlated relaxation rates Abstract Accurate rotational correlation times ( τ c ) are critical for quantitative analysis of fast timescale NMR dynamics. As molecular weights increase, the classic derivation of τ c using transverse and longitudinal relaxation rates becomes increasingly unsuitable due to the non-trivial contribution of remote dipole-dipole interactions to longitudinal relaxation. Derivations using cross-correlated relaxation experiments, such as TRACT, overcome these limitations but are erroneously calculated in 65% of the citing literature. Herein, we developed an algebraic solutions to the Goldman relationship that facilitate rapid, point-by-point calculations for straightforward identification of appropriate spectral regions where global tumbling is likely to be dominant. The rigid-body approximation of the Goldman relationship has been previously shown to underestimate TRACT-based rotational correlation time estimates. This motivated us to develop a second algebraic solution that employs a simplified model-free spectral density function including an order parameter term that could, in principle, be set to an average backbone S 2 ≈ 0.9 to further improve the accuracy of τ c estimation. These solutions enabled us to explore the boundaries of the Goldman relationship as a function of the H-N internuclear distance ( r ), difference of the two principal components of the axially-symmetric 15 N CSA tensor ( Δδ N ), and angle of the CSA tensor relative to the N-H bond vector ( θ ). We hope our algebraic solutions and analytical strategies will increase the accuracy and application of the TRACT experiment. Relaxation (psychology) ; Algebraic number ; Tensor (intrinsic definition) ; Dipole ; Function (biology) ; Correlation function (quantum field theory) ; Mathematics ; Phase (matter) ; Algebraic solution ; Set (abstract data type) ; Statistical physics ; Physics ; Mathematical analysis ; Spectral density ; Quantum mechanics ; Geometry ; Computer science ; Statistics Advanced NMR Techniques and Applications ; NMR spectroscopy and applications ; Electron Spin Resonance Studies
Authors: Jingye Tan | Kathryn Maupin | Shuai Shao | Danial Faghihi
Source:  (article, 2021-11-01)
Field: Materials Science — Materials Chemistry

A Bayesian Machine Learning Framework for Selection of the Strain Gradient Plasticity Multiscale Model Abstract A class of sequential multiscale models investigated in this study consists of discrete dislocation dynamics (DDD) simulations and continuum strain gradient plasticity (SGP) models to simulate the size effect in plastic deformation of metallic micropillars. The high-fidelity DDD explicitly simulates the microstructural (dislocation) interactions. These simulations account for the effect of dislocation densities and their spatial distributions on plastic deformation. The continuum SGP captures the size-dependent plasticity in micropillars using two length parameters. The main challenge in predictive DDD-SGP multi-scale modeling is selecting the proper constitutive relations for the SGP model, which is necessitated by the uncertainty in computational prediction due to DDD’s microstructural randomness. This contribution addresses these challenges using a Bayesian learning and model selection framework. A family of SGP models with different fidelities and complexities is constructed using various constitutive relation assumptions. The parameters of the SGP models are then learned from a set of training data furnished by the DDD simulations of micropillars. Bayesian learning allows the assessment of the credibility of plastic deformation prediction by characterizing the microstructural variability and the uncertainty in training data. Additionally, the family of the possible SGP models is subjected to a Bayesian model selection to pick the model that adequately explains the DDD training data. The framework proposed in this study enables learning the physics-based multiscale model from uncertain observational data and determining the optimal computational model for predicting complex physical phenomena, i.e., size effect in plastic deformation of micropillars. Plasticity ; Machine learning ; Artificial intelligence ; Bayesian probability ; Randomness ; Computer science ; Model selection ; Bayesian inference ; Algorithm ; Statistical physics ; Materials science ; Mathematics ; Physics ; Statistics Microstructure and mechanical properties ; Advanced Electron Microscopy Techniques and Applications ; Force Microscopy Techniques and Applications
Authors: Kai Huang | Bigyuan Lin | Haiyong Ren | Qifen Mao | Qiaofeng Guo | Yiyang Liu | Qi You
Source: Research Square (preprint, 2021-06-11)
Field: Chemistry — Organic Chemistry

Exploration of Anti-Staphylococcus Aureus Activity and Molecular Mechanism of Wuweixiaoduyin using Network Pharmacology Anti-Staphylococcus Aureus Activity of Wuweixiaoduyin using Network Pharmacology Abstract Background: S. aureus (Staphylococcus aureus) infection imposes a serious burden to global healthcare systems. WWXDY (Wuweixiaoduyin) is a traditional Chinese medicine, and it is usually used to treat infections in China. This study aimed to explore the active compounds, therapeutic targets, key pathways, and potential mechanisms of WWXDY in the treatment of S. aureus infection. Materials &amp; Methods: Data related to active compounds and therapeutic targets of WWXDY for treating S. aureus were collected from DisGeNET, GeneCards, and DrugBank databases. To explore the roles of the active targets in gene function and signaling pathways, KEGG (Kyoto Gene and Genomics Encyclopedia) pathway enrichment and GO (Gene Ontology) analyses of the 122 target genes in the PPI (protein-protein interaction) network were performed. We further performed NP (network pharmacology) by using a network analyzer to screen 30 key targets. Results: A total 92 active compounds of WWXDY were screened. The 122 overlapped genes were found from 785 therapeutic targets and 684 S. aureus-related genes. Besides, 92 active compounds of WWXDY, such as mandenol, ethyllinolenate, eriodyctiol, secologanic dibutylacetal_qt, etc., were identified. The PPI network of the effective ingredients of WWXDY in treating S. aureus infection identified the top 30 genes, including IL-6 (interleukin-6), TNF-α (tumor necrosis factor-α), VEGFA (vascular endothelial growth factor A), AKT1, CXCL8, MAPK3 (mitogen-activated protein kinase 3), TLR (toll-like receptor 4), IL-1β, EGFR (epidermal growth factor receptor), and MMP9 (matrix metalloproteinase-9). Conclusion: The GO functional and KEGG pathway enrichment analyses indicated that 122 overlapped genes were mainly enriched in COVID-19, AGE-RAGE signaling pathway, C-type lectin receptor signaling pathway, Pertussis, and Chagas disease. Our findings indicated the active compounds and therapeutic targets of WWXDY in treating S. aureus infection, as well as its potential mechanisms. KEGG ; Staphylococcus aureus ; AKT1 ; MMP9 ; DrugBank ; Biology ; Signal transduction ; Interaction network ; Gene ; Pharmacology ; Gene expression ; Gene ontology ; PI3K/AKT/mTOR pathway ; Biochemistry ; Genetics ; Downregulation and upregulation Synthesis and biological activity ; Phytochemistry and Bioactivity Studies ; Microbial Metabolism and Applications
Authors: Jean-Philippe Jehl
Source: theses.fr (ABES) (preprint, 2021-02-05)
Field: Materials Science — Biomaterials

Instrumented indentation of cardiac tissue : towards the development of a bio-prosthesis Malgré des progrès indéniables dans la compréhension de la fonction cardiaque et dans l’amélioration des techniques médicales et chirurgicales, l'insuffisance cardiaque ischémique représente toujours une cause majeure de mortalité dans le monde De nouvelles approches thérapeutiques, telles que la médecine régénérative et le génie tissulaire, sont développées pour compenser voire se substituer aux tissus endommagés. Une des tentatives de l’ingénierie tissulaire est de reproduire le plus fidèlement possible le comportement mécanique du tissu à traiter. Dans ce travail de thèse, une approche liant la caractérisation mécanique du tissu cardiaque sain avec sa microstructure a été réalisée. A cet effet et afin d’éviter la dégradation des propriétés du matériau due à son asséchement et/ou à sa dé-vascularisation, un protocole expérimental a été défini permettant d’effectuer les mesures dans un environnement proche de son milieu physiologique. Le tissu cardiaque a été ainsi caractérisé à travers l’estimation des modules d’Young suivant deux directions principales par indentations sphériques. Ces résultats ont confirmé ainsi la nature anisotrope du tissu cardiaque. La recherche des durées limites d’exploitation des échantillons après prélèvement (expérimentation ex-vivo) nous a permis de définir une cinétique de rigidification des tissus pouvant être comparée aux techniques de datation utilisées en médecine légale. Une perspective à ces travaux de thèse est l’élaboration d’un matériau de substitution passif dans le but d’obtenir des membranes dont les propriétés mécaniques sont proches du tissu cardiaque. Sur la base de la caractérisation mécanique du myocarde, une modélisation du comportement mécanique d’une bio-prothèse a été définie. Un premier prototype de membrane a été réalisé et expérimenté sur le petit animal. Ces résultats ont constitué une étape indispensable dans le développement d’une assistance biomécanique dans le cadre d’un projet européen FEDER ASCATIM (2018-2021). Enfin, une première transposition de la méthode développée pour le tissu cardiaque a été proposée pour un matériau biologique dont les caractéristiques mécaniques sont peu connues : l’os cortical. Indentation ; Prosthesis ; Biomedical engineering ; Materials science ; Engineering ; Medicine ; Composite material ; Surgery Electrospun Nanofibers in Biomedical Applications ; Cardiac Valve Diseases and Treatments ; Tissue Engineering and Regenerative Medicine