jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Qi Wang | Tao Wei | Xiaoying Zhou
Source: Journal of Biology and Life Science (article, 2020-12-17)
Field: Chemistry — Organic Chemistry

Inhibitory Effects of Cortex Dictamni Aqueous Extract on Dipeptidyl Peptidase I and Chymase Activities and the Screening of Active Ingredients in Cortex Dictamni Based on Molecular Docking Technique Dipeptidyl peptidase I (DPPI) and chymase, the granulo-proteases produced and released by mast cells, are important targets of anti-inflammatory drug research and development. Cortex Dictamni is a definite nature drug with anti-inflammatory activity, but the mechanism is unclear and effects of Cortex Dictamni on DPPI and chymase are unknown. This study focuses on effects of Cortex Dictamni aqueous extract (CDAE) on DPPI and chymase activities using cell model, bio-molecular interactions and the Molecular docking study by Discovery Studio (DS) analysis. The results showed that CDAE could significantly inhibit DPPI and chymase activities in vitro and in living rat spleen lymphocytes. Molecular docking simulation demonstrated that Troxerutin, the one of the active compounds of Cortex Dictamni, formed a hydrogen bond with amino acid ILE429 and a strong hydrophobic interaction with TYR64 CYS234 PRO279 ALA382 of DPPI. These interactions allow Troxerutin to form a stable complex with the DPPI, implicating that Troxerutin might be a potential natural inhibitor of DPPI. Dictamnoside M, another active compound of Cortex Dictamni formed hydrogen bonds and hydrophobic interactions within the binding pocket of chymase domain and form a stable complex with the chymase. Dictamnoside M maybe a potential natural inhibitor of chymase. This study suggested a new nature inhibitor Cortex Dictamni and its active components with the anti-inflammatory effects. Chymase ; Chemistry ; Proteases ; Docking (animal) ; Biochemistry ; Cerebellar cortex ; Cortex (anatomy) ; Pharmacology ; Biology ; Enzyme ; Neuroscience ; Cerebellum ; Medicine Click Chemistry and Applications ; Peptidase Inhibition and Analysis ; Coagulation, Bradykinin, Polyphosphates, and Angioedema
Authors: Keyvan Safaei Baghbaderani | Mohammadreza Nematollahi | Parisa Bayatimalayeri | Hediyeh Dabbaghi | Ahmadreza Jahadakbar | Mohammad Elahinia
Source: arXiv (Cornell University) (preprint, 2020-06-28)
Field: Materials Science — Materials Chemistry

Mechanical Evaluation Of Selective Laser Melted Ni-Rich Niti:\n Compression, Tension, And Torsion Two unique behaviors of superelasticity and shape memory effect have made\nshape memory alloy such as NiTi, an interesting alloy for different\napplications. Recently, additive manufacturing (AM) as a powerful tool for\nfabricating NiTi has become of interest to make complex geometries. Selective\nlaser melting (SLM) is an AM method that not only provides flexibility to make\ncomplex 3D shapes but also it can be possible to tailor the thermomechanical\nproperties of the parts just by changing the process parameters. The\nnon-homogeneous microstructure of as-fabricated parts as well as asymmetric\nmechanical behavior of NiTi, make it important to study the properties of SLM\nNiTi parts under different loading condition. In this study, Ni50.8Ti (at. %)\npowder was utilized to fabricate cube, dog-bone, and tube by SLM technique. The\ntransformation temperatures (TTs) of samples were measured by the differential\nscanning calorimetry (DSC) method and the variation of TTs was discussed. Three\ncoupons were tested mechanically under compression, tension, and torsion.\nIn-situ digital image correlation (DIC) was employed to measure and monitor the\nstrain field of samples during the mechanical tests. The strain distribution\nshowed localized strain for all three samples. The equivalent stress/strain was\ncalculated to compare the result of compressive, tensile, and torsional\nresponses and the significant asymmetric behavior was shown and discussed.\n Materials science ; Selective laser melting ; Nickel titanium ; Shape-memory alloy ; Pseudoelasticity ; Digital image correlation ; Composite material ; Microstructure ; Torsion (gastropod) ; Ultimate tensile strength ; Tensile testing ; Martensite Shape Memory Alloy Transformations
Authors: C. Benouali | M.N. Bachir bey | T. Sayah Sayah
Source: Tribology in Industry (article, 2020-12-14)
Field: Materials Science — Materials Chemistry

Effect of the Normal Load on the Friction and Wear Behaviour of Nickel-based Alloys Ni-Cr-B-Si-C-W The purpose of this paper is to compare the influence of the normal load on the friction and wear behaviour of nickel-based alloys, which is use communally in the industry. We chose two samples of nickel-based alloys (NI-Cr-B-Si-C-W) elaborated by isostatic compression with a difference in their microstructure composition and quantity of micro constituent. The friction coefficient, the wear loss and the wear rate are evaluated using a tribometer (pin on disc) and a test bench created to reproduce the same industrial environment. Experiments showed that the applied normal load affects differently on the behaviour of the samples. The results conclude that the friction and wear resistance of the alloy do not just depend on the increase of the normal load but also on the distribution, the location and the morphology of the hard compounds formed in the alloys. Nickel ; Materials science ; Metallurgy ; Composite material Metal Alloys Wear and Properties ; Advanced materials and composites ; Aluminum Alloys Composites Properties
Authors: Elena A. Chelnokova
Source: International Journal of Emerging Trends in Engineering Research (article, 2020-07-25)
Field: Materials Science — General Materials Science

Microanalysis of the structure of Carbon Cast Iron The research is aimed at studying the microstructure of white, gray, malleable and high-strength cast iron with different carbon content and establishing relationships between the composition, production conditions and structure of the studied cast iron. The microstructure of cast iron was examined using an optical microscope and a set of microshifts. Microanalysis ; Carbon fibers ; Metallurgy ; Materials science ; Chemistry ; Composite material Material Properties and Applications ; Metal and Thin Film Mechanics ; Metal Alloys Wear and Properties
Authors: Anton Römer | Lukas Hasecke | Peter E. Blöchl | Ricardo A. Mata
Source: Preprints.org (review, 2020-10-06)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A Review of Density Functional Models for the Description of Fe(II) Spin Crossover Complexes Spin crossover (SCO) complexes are in the forefront of image, memory and sensing devices, with applications already established since for thirty years. In order to reach magnetic multistability conditions, the high-spin (HS) and low-spin (LS) states have to be carefully balanced by ligand field stabilization and spin pairing energies. Both of these effects could be effectively modelled by electronic structure theory, if the description would be accurate enough to describe these concurrent influences to within a few kJ/mol. Such a milestone would allow for the in silico-driven development of SCO complexes. However, so far, the ab initio simulation of such systems has been dominated by general gradient approximation density functional calculations. The latter can only provide the right answer for the wrong reasons, given that the LS states are grossly stabilized. In this contribution, we explore different venues for the parameterisation of hybrid functionals. A fitting set is provided on the basis of explicitly correlated coupled cluster calculations, with single- and multi-dimensional fitting approaches being tested to selected classes of hybrid functionals (hybrid, range separated and local hybrid). Promising agreement to benchmark data is found for a rescaled PBE0 hybrid functional and a local version thereof, with a discussion of different atomic exchange factors. Hybrid functional ; Benchmark (surveying) ; Density functional theory ; Spin crossover ; Spin (aerodynamics) ; Ab initio ; Statistical physics ; Field (mathematics) ; Crossover ; Physics ; Computer science ; Quantum mechanics ; Mathematics ; Condensed matter physics ; Thermodynamics ; Artificial intelligence ; Pure mathematics Magnetism in coordination complexes ; Metal-Catalyzed Oxygenation Mechanisms ; Electron Spin Resonance Studies
Authors: Anh Nguyễn Thúy | Bằng Lý Hải
Source: The Transport and Communications Science Journal (article, 2020-12-28)
Field: Materials Science — Materials Chemistry

Dự đoán sức kháng cắt của dầm bê tông cốt thanh FRP không có cốt thép đai sử dụng mạng thần kinh nhân tạo Việc sử dụng thanh cốt sợi polyme (FRP) để gia cố kết cấu bê tông đã nhận được rất nhiều sự quan tâm trong thời gian gần đây do các thanh FRP có độ bền kéo cao, chống ăn mòn và đặc tính không từ tính tốt. Tuy nhiên, các đặc tính vật liệu của FRP có sự khác biệt đáng kể so với các đặc tính của cốt thép, đặc biệt là mô đun đàn hồi. Điều này cho thấy khả năng áp dụng các mô hình tính toán truyền thống sẽ không còn phù hợp với dầm bê tông cốt thanh FRP. Trong nghiên cứu này, một cách tiếp cận sử dụng thuật toán học máy mạng nơ-ron truyền thẳng (FNN) với kỹ thuật một bước One-step secant (OSS) đã được đề xuất để dự đoán sức kháng cắt của dầm bê tông cốt thanh FRP không có cốt thép đai. Hiệu suất của mô hình được đánh giá bằng các tiêu chí thống kê, cụ thể là hệ số tương quan (R), sai số toàn phương trung bình gốc (RMSE) và sai số tuyệt đối trung bình (MAE) với các giá trị lần lượt là 0,9963; 3,5625; 2,5837 cho tập dữ liệu đào tạo và 0,9732; 12,1796; 8,8089 cho tập dữ liệu kiểm chứng. Bên cạnh đó, nghiên cứu này sử dụng biểu đồ phụ thuộc một phần (PDP) để đánh giá mức độ quan trọng của từng thông số ảnh hưởng đến sức kháng cắt của dầm bê tông cốt thanh FRP không có cốt thép đai. Kết quả của nghiên cứu này cho thấy mô hình FNN-OSS được đề xuất có khả năng dự đoán một cách nhanh chóng và chính xác, đồng thời xem xét được các yếu tố ảnh hưởng đến sức kháng cắt của dầm bê tông cốt thanh FRP không có cốt thép đai. Physics Structural mechanics and materials ; Geodetic Measurements and Engineering Structures
Authors: Omar Belguendouz | Bendaoud Mebarek | М. Кеддам | Yassine El Guerri
Source: Annales de Chimie Science des Matériaux (article, 2020-08-20)
Field: Materials Science — Materials Chemistry

Diffusion Model for Simulating the Kinetics of Boronizing Process in the Case of FeB/Fe2B Bilayer Configuration In this work, we developed a diffusion model based on the second Fick's law and the solving of the mass balance equations of the (FeB/Fe2B) interface to simulate the boronizing kinetics in the case of bilayer configuration (FeB/Fe2B) formed on AISI D2 steel. It is known that the boronizing process is a thermochemical surface treatment generally carried out at temperatures ranging between 1223 K and 1323 K. The knowledge of the temperature and the processing time are necessary to simulate and optimize the boronizing process. The developed model in this study is used to estimate the value of the growth rate constant in each phase, to simulate the boride layer thickness formed on AISI D2 steel, to determine the boron concentration profile and to evaluate the mass gain at the surface of the borided AISI D2 steel. To validate the developed model, we used the experimental data taken from the literature concerning the layers thicknesses of FeB and Fe2B layers obtained for different process parameters. Finally, these experimental values are compared to the calculated results. A good agreement was observed between the simulated results and the experimental data. Bilayer ; Diffusion ; Kinetics ; Diffusion process ; Process (computing) ; Materials science ; Chemistry ; Thermodynamics ; Physics ; Computer science ; Classical mechanics ; Operating system ; Membrane Metal Alloys Wear and Properties ; Microstructure and Mechanical Properties of Steels ; Powder Metallurgy Techniques and Materials
Authors: Seema Chahar | A. K. Ghosh | Bhabani S. Das | Nagarjuna N. Reddy | K. M. Hati | Nishant K. Sinha | Nilimesh Mridha
Source:  (preprint, 2020-08-10)
Field: Chemistry — Analytical Chemistry

Evaluation of Multivariate Regression Models to Predict Electrical conductivity Using Vis-NIR and MIR Spectra Salts in the root zone have high spatial variability, changes rapidly and adversely affects soil quality and crop productivity. Rapid detection of electrical conductivity (EC) using visible-near infrared (Vis-NIR) and midinfrared (MIR) spectroscopy can alleviate the adverse effects on soil and plant, which through conventional method is time consuming. Soils were collected from the Indo-Gangetic plains and analyzed for EC using conventional, Vis-NIR, MIR spectroscopy and there was wide variation in EC measured by the conventional method. The spectral regions in 460-500 and 1890-1906 nm in the Vis-NIR region and 4200-4310, 5275-5280, 6660-6670, 7305-7310 and 8290-8300 nm in the MIR region were sensitive to detection of EC. Partial least square regression (PLSR) outperformed random forest regression (RF), support vector regression (SVR), and multivariate adaptive regression splines (MARS) both in Vis-NIR and MIR region during calibration. The ratio of performance deviation (RPD), coefficient of determination (R2) and root mean square error (RMSE) of the validation dataset were used to assess the prediction accuracy and the predictive performance of PLSR (2.44, 0.84, 0.21), RF (1.95, 0.81, 0.20), SVR (2.09, 0.78, 0.22) and MARS (1.81, 0.73, 0.27) models. PLSR model performed very well in the Vis-NIR range; however, in the MIR range, RF (1.43, 0.52, 0.20), followed by PLSR (1.40, 0.55, 0.35), performed better than SVR (1.39, 0.53, 0.35) and MARS (1.29, 0.44, 0.37). Vis-NIR spectroscopy with PLSR algorithm predicted EC better than MIR spectroscopy and would be the method of choice for rapid estimation and prediction of EC in the study region. Partial least squares regression ; Mars Exploration Program ; Mean squared error ; Multivariate statistics ; Multivariate adaptive regression splines ; Near-infrared spectroscopy ; Coefficient of determination ; Calibration ; Support vector machine ; Spectroscopy ; Linear regression ; Random forest ; Analytical Chemistry (journal) ; Regression analysis ; Root mean square ; Correlation coefficient ; Regression ; Materials science ; Mathematics ; Statistics ; Bayesian multivariate linear regression ; Chemistry ; Environmental chemistry ; Artificial intelligence ; Computer science ; Optics ; Physics Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI
Authors: Elke De Zitter | Siewert Hugelier | Sam Duwé | Wim Vandenberg | Alison G. Tebo | Luc Van Meervelt | Peter Dedecker
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2020-09-25)
Field: Materials Science — Materials Chemistry

Integrated structure-function dataset reveals key mechanisms underlying photochromic fluorescent proteins Abstract Photochromic fluorescent proteins have become versatile tools in the life sciences, though our understanding of their structure-function relation is limited. Starting from a single scaffold, we have developed a range of 27 photochromic fluorescent proteins that cover a broad range of spectroscopic properties, yet differ only in one or two mutations. We also determined 43 different crystal structures of these mutants. Correlation and principal component analysis of the spectroscopic and structural properties confirmed the complex relationship between structure and spectroscopy, suggesting that the observed variability does not arise from a limited number of mechanisms, but also allowed us to identify consistent trends and to relate these to the spatial organization around the chromophore. We find that particular changes in spectroscopic properties can come about through multiple different underlying mechanisms, of which the polarity of the chromophore environment and hydrogen bonding of the chromophore are key modulators. Furthermore, some spectroscopic parameters, such as the photochromism, appear to be largely determined by a single or a few structural properties, while other parameters, such as the absorption maximum, do not allow a clear identification of a single cause. We also highlight the role of water molecules close to the chromophore in influencing photochromism. We anticipate that our dataset can open opportunities for the development and evaluation of new and existing protein engineering methods. Chromophore ; Photochromism ; Fluorescence ; Fluorescent protein ; Function (biology) ; Chemistry ; Protein function ; Biological system ; Biophysics ; Chemical physics ; Materials science ; Photochemistry ; Green fluorescent protein ; Biology ; Physics ; Evolutionary biology ; Optics ; Biochemistry Photochromic and Fluorescence Chemistry ; Photoreceptor and optogenetics research ; Photosynthetic Processes and Mechanisms
Authors: Rokhsana Mohammed Ismail | Fatima Sahleh Nagi
Source: Electronic Journal of University of Aden for Basic and Applied Sciences (article, 2020-12-30)
Field: Chemistry — Analytical Chemistry

COMPARATIVE EVALUATION OF PHYSICAL PROPERTIES OF SOME YEMENI CRUDE AND FUEL OIL Due to the high significance of crude oil to modern society as a source of energy and as raw material for a wide chemical and petrochemical industries; in this study, we evaluate the characteristics of certain Yemeni crude, and fuel oils specifically Mareb crude oil blend, Masila crude oil blend plus two samples from Sounah and Hijah oil fields in Masila basin. The general specifications of these crudes and fuel oils are determined and compared with some other regional and international types including Brent and West Texas benchmark crudes using the published data in the specialized literature. It is revealed that Mareb crude oil blend is the lightest and sweetest crude oil followed by Sounah crude while Masila is considered Medium crude and Hijah field is the heaviest with medium sulfur content. Mareb, Masila blends, and Sounah field fuel oils are considered low sulfur fuel oils with sulfur content below the 1% standard marketable fuels; while the Hijah fuel oil slightly above, and this is absorbed within the marketable blend. Crude oil ; Petrochemical ; Fuel oil ; Petroleum ; Raw material ; Sulfur ; Environmental science ; Pulp and paper industry ; Energy source ; Petroleum product ; Oil field ; Synthetic crude ; Waste management ; Chemistry ; Petroleum engineering ; Shale oil ; Engineering ; Organic chemistry ; Environmental engineering Petroleum Processing and Analysis
Authors: David L. Mainka | Jörg Schwarz | Ulrich Girreser
Source: ARKIVOC (article, 2020-05-11)
Field: Chemistry — Organic Chemistry

Temperature dependent analysis of Octenidine (N,N´-(decane-1,10-diyldipyridin-1-yl-4-ylidene)dioctan-1-amine) dihydrochloride by NMR and NIR spectroscopy Octenidine dihydrochloride is one of the most common active pharmaceutical incredients with a disinfectant effect on superficial wounds. In this paper we describe the mesomeric behaviour of Octenidine dihydrochloride by comparison with 1 H, 13 C and 15 N NMR shift data. With various NMR experiments, the possible mesomeric structures are studied and it is shown that an E/Z-isomerization plays a role, corresponding to a hindered rotation of the heteroaromatic pyridine ring. In this context, NIR spectroscopy and principal component analysis emphasize the occurrence of a modified temperature-dependent spectral behaviour of Octenidine dihydrochloride. In addition, we made a detailed study of the NMR-characteristics of Octenidine dihydrochloride using 1D-and 2D-experiments. Chemistry ; Decane ; Spectroscopy ; Nuclear magnetic resonance spectroscopy ; Amine gas treating ; Medicinal chemistry ; Physical chemistry ; Computational chemistry ; Organic chemistry Synthesis and biological activity ; Synthesis and Characterization of Heterocyclic Compounds ; Quinazolinone synthesis and applications
Authors: Amélie Chatelain | Giuseppe Luca Tommasone | Laurent Daudet | Iacopo Poli
Source: arXiv (Cornell University) (preprint, 2020-06-15)
Field: Chemistry — Spectroscopy

Online Change Point Detection in Molecular Dynamics With Optical Random Features Proteins are made of atoms constantly fluctuating, but can occasionally undergo large-scale changes. Such transitions are of biological interest, linking the structure of a protein to its function with a cell. Atomic-level simulations, such as Molecular Dynamics (MD), are used to study these events. However, molecular dynamics simulations produce time series with multiple observables, while changes often only affect a few of them. Therefore, detecting conformational changes has proven to be challenging for most change-point detection algorithms. In this work, we focus on the identification of such events given many noisy observables. In particular, we show that the No-prior-Knowledge Exponential Weighted Moving Average (NEWMA) algorithm can be used along optical hardware to successfully identify these changes in real-time. Our method does not need to distinguish between the background of a protein and the protein itself. For larger simulations, it is faster than using traditional silicon hardware and has a lower memory footprint. This technique may enhance the sampling of the conformational space of molecules. It may also be used to detect change-points in other sequential data with a large number of features. Observable ; Computer science ; Identification (biology) ; Molecular dynamics ; Change detection ; Biological system ; Dynamics (music) ; Footprint ; Statistical physics ; Point (geometry) ; Function (biology) ; Algorithm ; Exponential function ; Physics ; Artificial intelligence ; Chemistry ; Mathematics ; Computational chemistry ; Biology Mass Spectrometry Techniques and Applications ; Machine Learning in Materials Science ; Gene Regulatory Network Analysis
Authors: Shujun Liu | Yuanyuan Xie | Xi‐Ming Song
Source: Scientific Reports (article, 2020-04-02)
Field: Chemistry — Analytical Chemistry

Accurate and rapid discrimination of cigarette and household decoration material ash residues by negative chemical ionization TOFMS via acid-enhanced evaporation The detection and identification of cigarette ash in fire debris can be meaningful in fire investigations caused by burning cigarettes. In this work, a novel analytical method based on negative chemical ionization time-of-flight mass spectrometry (NCI/TOFMS) combined with a phosphoric-acid-enhanced evaporation strategy has been developed for the discrimination of cigarette ash samples (CAs) and common household decoration material ash samples (CHDMAs). A series of characteristic ions representing the acidified products HNCO and formic acid in the CAs were achieved, whose signal responses were enhanced with the help of mechanical agitation operation. To account for both the signal responses of the characteristic ions and acid corrosion of the ion source, the dynamic-purge gas was chosen to be 200 mL/min. The whole time for analysis was only 5 min, which is suitable for high-throughput measurements of large quantities of fire debris. As a result, a preliminary discrimination was achieved between the CAs and CHDMAs by virtue of the chemometric tool of principal components analysis (PCA) based on intensity differences of the characteristic ions. The results are encouraging and highlight the potential of NCI/TOFMS without complicated sample preparation steps for the accurate and high-throughput identification of cigarette ash on substrates in fire debris. Evaporation ; Ionization ; Materials science ; Environmental chemistry ; Chemistry ; Environmental science ; Organic chemistry ; Ion ; Geography Analytical chemistry methods development ; Advanced Chemical Sensor Technologies ; Analytical Chemistry and Chromatography