jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Changqing Wang | Qing He | Peng Guo | Haoqiang Qi | Jianfeng Su | Weiguang Chen | Chunjuan Tang | Yu Jia
Source: Research Square (preprint, 2022-12-20)
Field: Materials Science — Materials Chemistry

Friction Properties of Black Phosphorus: A First-principles Study Abstract Based on the first-principle, the friction anisotropy, structural super-lubricity and oxidation induced ultra-low friction of black phosphorus at atomic scale under different loads have been studied. The results show that the interface friction of black phosphorus shows anisotropy, that is, the friction along the armchair direction is greater than that along the zigzag direction. Moreover, the friction between the black phosphorus interfaces shows a structural superlubricity property, and the incommensurate interface friction is about one thousandth of the commensurate interface friction. In addition, the oxidation of black phosphorus is beneficial to the lubrication between interfaces. Black phosphorus ; Lubricity ; Zigzag ; Anisotropy ; Lubrication ; Materials science ; Phosphorus ; Interface (matter) ; Dry friction ; Composite material ; Condensed matter physics ; Metallurgy ; Physics ; Optoelectronics ; Geometry ; Optics ; Mathematics MXene and MAX Phase Materials ; 2D Materials and Applications ; Metal and Thin Film Mechanics
Authors: Hind Alqurashi | Abhiyan Pandit | Bothina Hamad
Source: Materials Science and Engineering B (article, 2022-06-13)
Field: Materials Science — Materials Chemistry

Anharmonic effects on lattice dynamics and thermal transport of two-dimensional InTe monolayer Anharmonicity ; Monolayer ; Condensed matter physics ; Thermal ; Lattice (music) ; Dynamics (music) ; Materials science ; Physics ; Thermodynamics ; Nanotechnology ; Acoustics Advanced Thermoelectric Materials and Devices ; Thermal properties of materials ; Thermal Radiation and Cooling Technologies
Authors: Benita Wiatrak | Edward Krzyżak | Berenika M. Szczęśniak-Sięga | Marta Szandruk-Bender | Adam Szeląg | Beata Nowak
Source: Pharmacological Reports (article, 2022-09-21)
Field: Chemistry — Organic Chemistry

Effect of tricyclic 1,2-thiazine derivatives in neuroinflammation induced by preincubation with lipopolysaccharide or coculturing with microglia-like cells New tricyclic 1,2-thiazine derivatives exert a neuroregenerative effect in the neuroinflammation model, presumably via their inhibitory influence on COX activity and reduction of oxidative and nitrosative stress. Neuroinflammation ; Lipopolysaccharide ; Microglia ; Chemistry ; Tricyclic ; Pharmacology ; Thiazine ; Stereochemistry ; Immunology ; Medicine ; Inflammation ; Medicinal chemistry Synthesis and biological activity ; Phenothiazines and Benzothiazines Synthesis and Activities ; Tryptophan and brain disorders
Authors: Kseniya N. Sedenkova | Denis V. Zverev | Анна Назарова | Mstislav I. Lavrov | Eugene V. Radchenko | Yuri K. Grishin | A. V. Gabrel’yan | Vladimir L. Zamoyski | V. V. Grigoriev | Elena B. Averina | Vladimir A. Palyulin
Source: Molecules (article, 2022-11-26)
Field: Chemistry — Organic Chemistry

Novel Nanomolar Allosteric Modulators of AMPA Receptor of Bis(pyrimidine) Series: Synthesis, Biotesting and SAR Analysis Positive allosteric modulators (PAMs) of AMPA receptors represent attractive candidates for the development of drugs for the treatment of cognitive and neurodegenerative disorders. Dimeric molecules have been reported to have an especially potent modulating effect, due to the U-shaped form of the AMPA receptor's allosteric binding site. In the present work, novel bis(pyrimidines) were studied as AMPA receptor modulators. A convenient and flexible preparative approach to bis(pyrimidines) containing a hydroquinone linker was elaborated, and a series of derivatives with varied substituents was obtained. The compounds were examined in the patch clamp experiments for their influence on the kainate-induced currents, and 10 of them were found to have potentiating properties. The best potency was found for 2-methyl-4-(4-((2-methyl-5,6,7,8-tetrahydroquinazolin-4-yl)oxy)phenoxy)-6,7,8,9-tetrahydro-5<i>H</i>-cyclohepta[<i>d</i>]pyrimidine, which potentiated the kainate-induced currents by up to 77% in all tested concentrations (10<sup>-12</sup>-10<sup>-6</sup> M). The results were rationalized via the modeling of modulator complexes with the dimeric ligand binding domain of the GluA2 AMPA receptor, using molecular docking and molecular dynamics simulation. The prediction of ADMET, physicochemical, and PAINS properties of the studied bis(pyrimidines) confirmed that PAMs of this type may act as the potential lead compounds for the development of neuroprotective drugs. AMPA receptor ; Allosteric regulation ; Chemistry ; Kainate receptor ; Pyrimidine ; Allosteric modulator ; Stereochemistry ; Linker ; Lead compound ; Receptor ; Molecular model ; Biophysics ; Combinatorial chemistry ; Glutamate receptor ; Biochemistry ; In vitro ; Biology Multicomponent Synthesis of Heterocycles ; Neuroscience and Neuropharmacology Research ; Computational Drug Discovery Methods
Authors: RESHMA PISE | Kailas Patil | NEERAJ PISE
Source: Zenodo (CERN European Organization for Nuclear Research) (article, 2022-03-31)
Field: Chemistry — Analytical Chemistry

AUTOMATIC CLASSIFICATION OF MOSQUITO GENERA USING TRANSFER LEARNING Certain species of mosquitoes are the main vectors of arboviruses that cause Dengue, Yellow fever,<br> Chikungunya, Zika and Japanese encephalitis. These species are contained in the genera Anopheles, Culex,<br> Aedes. Mosquito-borne diseases pose significant threat to public health. Therefore, vector surveillance and<br> vector control strategies are crucial. Automation of genera identification is essential to implement effective<br> vector control strategies. In the past decade several machine learning and deep learning models have been<br> investigated for image-based automatic and accurate classification of vector mosquitoes. Such applications<br> also aid entomologists in insect identification task. In this study, a deep convolutional neural network<br> technique to classify two genera of mosquitoes: Aedes and Culex based on the morphological features is<br> proposed. In our work, an optimization technique i.e., transfer learning using the pretrained deep learning<br> models has been employed. Transfer learning saves the model training time and addresses the problem of<br> low performance due to insufficient amount of training data. This paper presents the architecture of three<br> state of the art pretrained neural networks, including VGGNet, ResNet and GoogLeNet. The models were<br> trained with our own dataset of images of the two genera of mosquitoes. Classification performance of the<br> models is evaluated in terms of classification accuracy and loss during training and validation phases of<br> model building. Transfer of learning ; Artificial intelligence ; Computer science ; Zoology ; Biology Spectroscopy and Chemometric Analyses ; Fuzzy Logic and Control Systems ; Smart Agriculture and AI
Authors: Ryan B. Sills | Douglas L. Medlin
Source: Microscopy and Microanalysis (article, 2022-03-08)
Field: Materials Science — Surfaces, Coatings and Films

Semi-Automated, Object-Based Tomography of Dislocation Structures The characterization of the three-dimensional arrangement of dislocations is important for many analyses in materials science. Dislocation tomography in transmission electron microscopy is conventionally accomplished through intensity-based reconstruction algorithms. Although such methods work successfully, a disadvantage is that they require many images to be collected over a large tilt range. Here, we present an alternative, semi-automated object-based approach that reduces the data collection requirements by drawing on the prior knowledge that dislocations are line objects. Our approach consists of three steps: (1) initial extraction of dislocation line objects from the individual frames, (2) alignment and matching of these objects across the frames in the tilt series, and (3) tomographic reconstruction to determine the full three-dimensional configuration of the dislocations. Drawing on innovations in graph theory, we employ a node-line segment representation for the dislocation lines and a novel arc-length mapping scheme to relate the dislocations to each other across the images in the tilt series. We demonstrate the method for a dataset collected from a dislocation network imaged by diffraction-contrast scanning transmission electron microscopy. Based on these results and a detailed uncertainty analysis for the algorithm, we discuss opportunities for optimizing data collection and further automating the method. Electron tomography ; Dislocation ; Computer vision ; Artificial intelligence ; Tilt (camera) ; Computer science ; Algorithm ; Optics ; Materials science ; Scanning transmission electron microscopy ; Transmission electron microscopy ; Geometry ; Physics ; Mathematics Electron and X-Ray Spectroscopy Techniques ; Geophysical Methods and Applications ; Infrastructure Maintenance and Monitoring
Authors: Shichao Feng | Hong‐Long Ji | Huan Wang | Bailu Zhang | Ryan Sterzenbach | Chongle Pan | Xuan Guo
Source: PLoS Computational Biology (article, 2022-10-21)
Field: Chemistry — Spectroscopy

MetaLP: An integrative linear programming method for protein inference in metaproteomics Metaproteomics based on high-throughput tandem mass spectrometry (MS/MS) plays a crucial role in characterizing microbiome functions. The acquired MS/MS data is searched against a protein sequence database to identify peptides, which are then used to infer a list of proteins present in a metaproteome sample. While the problem of protein inference has been well-studied for proteomics of single organisms, it remains a major challenge for metaproteomics of complex microbial communities because of the large number of degenerate peptides shared among homologous proteins in different organisms. This challenge calls for improved discrimination of true protein identifications from false protein identifications given a set of unique and degenerate peptides identified in metaproteomics. MetaLP was developed here for protein inference in metaproteomics using an integrative linear programming method. Taxonomic abundance information extracted from metagenomics shotgun sequencing or 16s rRNA gene amplicon sequencing, was incorporated as prior information in MetaLP. Benchmarking with mock, human gut, soil, and marine microbial communities demonstrated significantly higher numbers of protein identifications by MetaLP than ProteinLP, PeptideProphet, DeepPep, PIPQ, and Sipros Ensemble. In conclusion, MetaLP could substantially improve protein inference for complex metaproteomes by incorporating taxonomic abundance information in a linear programming model. Metaproteomics ; Metagenomics ; Computational biology ; Shotgun proteomics ; Inference ; Proteomics ; Biology ; Computer science ; Proteome ; Protein sequencing ; Microbiome ; Amplicon ; Bioinformatics ; Artificial intelligence ; Gene ; Genetics ; Peptide sequence Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Genomics and Phylogenetic Studies
Authors: Lielin Wang | Hua Xie | Yuqi Xie | Pingtao Hu | Wen Yin | Xinyue REN | Yun Ding
Source: Journal of Inorganic Materials (article, 2022-01-01)
Field: Materials Science — Materials Chemistry

Structural Evolution and Chemical Durability of Thorium-incorporated Nd<sub>2</sub>Zr<sub>2</sub>O<sub>7</sub> Pyrochlore at A and B Sites Nd 2 Zr 2 O 7 AB , , , , , , ( Pyrochlore ; Materials science ; Thorium ; Durability ; Crystallography ; Nuclear chemistry ; Uranium ; Metallurgy ; Composite material ; Physics Nuclear materials and radiation effects ; Advanced Condensed Matter Physics ; Nuclear Materials and Properties
Authors: Kang Zhou | Yu-Tang Chen | Chengshuo Sun | Bin Na
Source: BioResources (article, 2022-08-26)
Field: Chemistry — Analytical Chemistry

Prediction of veneer moisture content based on near infrared spectroscopy The physical properties of wood, particularly the dimensional stability, are affected by the water content. Most wood properties can be detected by near infrared spectroscopy (NIRS), which is used as a nondestructive testing method. At different wavelengths, different absorption peaks are presented with the moisture absorbed by wood. According to this feature, the absorption peaks can be collected, and the data can be processed by partial least squares method combined with NIRS. In this study, softwood oak and hardwood ash tree specimens were studied. In the infrared spectrum range, the wood moisture absorption curve was noticeable and the curve trend was similar, although the tree species were different. After centralization, standardization, and derivative processing of the spectral data, the correlation coefficients of oak and ash tree validations were high, reaching 0.9021 and 0.9661, respectively. The wood moisture content was predicted using NIRS and an algorithm. The experiments showed that this method is feasible. Softwood ; Materials science ; Water content ; Hardwood ; Moisture ; Absorption of water ; Spectroscopy ; Near-infrared spectroscopy ; Infrared spectroscopy ; Absorption (acoustics) ; Analytical Chemistry (journal) ; Veneer ; Infrared ; Composite material ; Environmental science ; Optics ; Chemistry ; Environmental chemistry ; Botany ; Geology Spectroscopy and Chemometric Analyses ; Wood Treatment and Properties ; Industrial Vision Systems and Defect Detection
Authors: Hao Sun | Yingshuai Liu | Ning Li | Jianwei Tan
Source: Processes (article, 2022-06-22)
Field: Materials Science — Materials Chemistry

Study on Characteristics and Control Strategy of Diesel Particulate Filters Based on Engine Bench The ignition temperature of a diesel oxidation catalyst (DOC) and the internal temperature-field distribution of the diesel particulate filter (DPF) during active regeneration are investigated during an engine bench test in this study. Based on the dropped to idle (DTI) test, a test method is developed to determine the safe regeneration temperature of the DPF. The results show that when the inlet temperature of the DOC is more than 240 °C, the DOC begins ignition and reaches the target temperature of 600 °C set for active regeneration of DPF; when the inlet exhaust temperature of the DOC is between 240 and 280 °C, a higher injection rate is required to reduce the secondary pollution of HC and thus make the DPF reach the set target temperature as soon as possible. The active regeneration process of the DPF is divided into three stages. During ignition, the temperature of the DPF inlet and outlet increases rapidly and successively. The internal and outlet temperatures of DPF during regeneration are approximately 50 °C higher than the inlet temperature. At the end of regeneration, the DPF inlet to outlet temperature drops rapidly. A feed-forward design and feedback algorithm are used to verify the change in the target regeneration temperature. The overshoot of the DPF control strategy was less than 3%, and the steady-state temperature control error was less than 20 °C. The results of this study provide a basis for the safe control of DPFs’ active regeneration temperatures. Diesel particulate filter ; Inlet ; Particulates ; Test bench ; Temperature control ; Diesel fuel ; Ignition system ; Environmental science ; Diesel engine ; Overshoot (microwave communication) ; Automotive engineering ; Chemistry ; Engineering ; Mechanical engineering Catalytic Processes in Materials Science ; Vehicle emissions and performance ; Biodiesel Production and Applications
Authors: Zhiyong Zou | Jie CHEN | Man Zhou | Zhitang Wang | Liu Ke | Yongpeng Zhao | Yuchao WANG | Weijia Wu | Lijia Xu
Source: Food Science and Technology (article, 2022-01-01)
Field: Chemistry — Analytical Chemistry

Identification of peanut storage period based on hyperspectral imaging technology Peanut storage time affected the quality of peanut seed sowing and germination and also affected the taste of edible peanuts. With the increase of peanut storage time, the total amount of water and amino acids decreased, and peanuts appeared moldy. The artificial judgment of peanut storage time mostly relied on visual classification to evaluate the color, which leads to large differences in color classifications between observers. This research was conducted to determine the fresh state of peanuts during storage based on the hyperspectral imaging (HSI) technology, and to identify the storage time of peanuts through hyperspectral images (387~1035 nm). Three models, two preprocessing methods, and two feature band extraction methods were combined. The experimental results shows that the DT-MF-Catboost model was the best method to detect the storage time of peanuts, and its accuracy of identifying the storage time of peanuts was 97.53%. Studies have shown that HSI has great potential in classifying the freshness and identification of peanuts, and provides a basis for non-destructive testing classification as well as grading of peanuts during storage. Hyperspectral imaging ; Preprocessor ; Sowing ; Artificial intelligence ; Food science ; Mathematics ; Agronomy ; Computer science ; Chemistry ; Biology Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Mohd Yusuf | Shafat Ahmad Khan | P Miossec | D Scott | F Wolfe | T Huizinga | A Bruno | S Tacconelli | P Patrignani | A Van Walsem | S Pandhi | R Nixon | P Guyot | A Karabis | R Moore | N Chandrasekharan | H Dai | K Roos | N Evanson | J Tomsik | T Elton | D Simmons | J Ryn | G Trummlitz | M Pairet | M Sohilait | H Pranowo | W Haryadi | D Kesharwani | R Paliwal | T Satapathy | S Paul | C Sostres | C Gargallo | M Arroyo | A Lanas | P Singh | A Mittal | S Kaur | W Holzer | S Kumar | P O'daniel | Z Peng | H Pi | S Testero | D Ding | E Spink | E Leemans | M Boudreau | T Yamaguchi | V Schroeder | W Wolter | L Llarrull | W Song | S Kortagere | S Ekins | W Cui | A ; Aouidate | S Wang | Q Yu | Y Li | S Yuan | O Hamad | S Amran | A Sabbah | T Ringbom | U Huss | Stenholm | S Flock | L Skattebl | P Perera | L Bohlin | H Magpantay | I Malaluan | J Manzano | M Quimque | K Pueblos | N Moor | S Budde | P Bangcaya | D Lim-Valle | H Dahse | A Khan | H Pallavi | F Al-Ostoot | H Vivek | S Khanum | Design | P Mukherjee | S Bahadur | R Harwansh | S Biswas | S Banerjee | P Khanal | U Chawla | S Praveen | Z Malik | S Malik | M Yusuf | S Khan
Source: Biointerface Research in Applied Chemistry (article, 2022-01-07)
Field: Chemistry — Organic Chemistry

Assessment of ADME and in silico Characteristics of Natural-Drugs from Turmeric to Evaluate Significant COX2 Inhibition Turmeric contains a variety of natural phytoconstituents, effective in reducing the risk of certain diseases and disorders, for example, heart disease, diabetes, neoplastic, and other health disorders. In the present study, ten compounds that occurred in turmeric were evaluated for ADME properties and COX-2 inhibitory potential as anti-inflammatory agents through the in silico approach. ADME properties and docking studies revealed that L1, L3, and L4 displayed the best performance and were found suitable to be high-quality COX2 inhibitors. The maximum binding energies were observed in superior mode in comparison to valdecoxib (L, B.E. = -8.7) for ligands- L1, B.E. = -8.8; L2, B.E.= -9.7; L3, B.E.= -8.9&amp;L4, B.E.= -9.6. The keto-isomeric form is found more familiar with the COX2 inhibiting activity than the enol-isomeric form. The significant bioavailability scores L1, L3, and L4 suggest that they exhibit good drug-likeness abilities. The results indicate that the curcuminoids in turmeric showed remarkable biological functionalities, particularly COX-2 inhibiting property, which might further be used as oral therapeutics after clinical trials. ADME ; In silico ; Pharmacology ; Bioavailability ; Chemistry ; Docking (animal) ; Drug ; Computational biology ; Stereochemistry ; Biochemistry ; Medicine ; Biology Synthesis and biological activity ; Computational Drug Discovery Methods ; Synthesis of heterocyclic compounds
Authors: Anthony Annerino | Mark V. Lawson | Pelagia‐Irene Gouma
Source: International Journal of Ceramic Engineering & Science (article, 2022-08-09)
Field: Materials Science — Materials Chemistry

Future insights on high temperature ceramics and composites for extreme environments Abstract This document summarizes key research directions as they emerged during the proceedings of the Inaugural Orton Workshop that aimed to define scientific areas of current interest to the ceramics community around the theme of: “High Temperature Ceramics and Composites for Extreme Environments.” The topic was selected due to the timely interest in such materials to meet the needs of hypersonic aviation and space exploration and habitation. Experts from funding agencies supporting ceramics research, thought‐leaders from academia with expertise spanning materials processing, characterization, and modeling, as well as research and development leaders from key (aviation‐related) industries, gathered to evaluate the state‐of‐the‐art in this field and to address key questions with the intent of accelerating research and development efforts on all fronts. Highlights of the work presented and of the discussion and brainstorming sessions are provided here. It was the purpose of the organizers (The Orton Ceramic Foundation and the Orton Chair in Ceramic Engineering at OSU) to establish this event as a service to the Ceramics community in the spirit the founder of the field of Ceramic Engineering, Dr. Edward Orton Jr. Brainstorming ; Theme (computing) ; Aviation ; Service (business) ; Ceramic ; Field (mathematics) ; Engineering ; Architectural engineering ; Aeronautics ; Computer science ; Aerospace engineering ; Business ; Materials science ; World Wide Web ; Composite material ; Marketing MXene and MAX Phase Materials ; Advanced ceramic materials synthesis ; Energetic Materials and Combustion
Authors: He Liu | Wenjun Hu | Yuzhen Wei
Source: Spectroscopy (article, 2022-08-01)
Field: Chemistry — Analytical Chemistry

Lignocellulose Determination and Categorization Analysis for Biofuel Pellets Based on FT-IR Spectra Lignocellulose determination and categorization analysis are critical to the treatment of biofuel pellets. For lignocellulose determination, partial least square (PLS) regression models based on full-range spectra, feature intervals, and feature bands were established. The models that were based on feature bands displayed the best performance, with the determination coefficients of 0.956, 0.864, and 0.926 for cellulose, hemicellulose, and lignin, respectively. For the categorization analysis issue, two specific cases were studied. First, linear discriminant analysis and random forest were used for biofuel pellet classification. Second, fuzzy clustering based on transitive closure was adopted to implement the hierarchical clustering of biofuel pellets without the label information. Excellent categorization results were obtained. This paper provides an effective auxiliary means for the pretreatment and storage of biofuel pellets with the utilization of Fourier transform infrared (FT-IR) spectra. Pellets ; Categorization ; Biofuel ; Linear discriminant analysis ; Cellulose ; Cluster analysis ; Feature (linguistics) ; Computer science ; Chemistry ; Mathematics ; Pattern recognition (psychology) ; Artificial intelligence ; Biological system ; Materials science ; Engineering ; Organic chemistry ; Waste management Spectroscopy and Chemometric Analyses ; Biofuel production and bioconversion ; Fermentation and Sensory Analysis