jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Yu Tian | Zidong Lin | Xiangyu Wang | Liangyu Che | Dawei Lu
Source: Acta Physica Sinica (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Experimental progress of quantum machine learning based on spin systems Machine learning is widely applied in various areas due to its advantages in pattern recognition, but it is severely restricted by the computing power of classic computers. In recent years, with the rapid development of quantum technology, quantum machine learning has been verified experimentally verified in many quantum systems, and exhibited great advantages over classical algorithms for certain specific problems. In the present review, we mainly introduce two typical spin systems, nuclear magnetic resonance and nitrogen-vacancy centers in diamond, and review some representative experiments in the field of quantum machine learning, which were carried out in recent years. Quantum ; Quantum machine learning ; Quantum computer ; Computer science ; Spin (aerodynamics) ; Field (mathematics) ; Quantum technology ; Quantum sensor ; Quantum network ; Artificial intelligence ; Open quantum system ; Physics ; Quantum mechanics ; Engineering ; Mathematics ; Mechanical engineering Diamond and Carbon-based Materials Research ; Quantum Computing Algorithms and Architecture ; Machine Learning in Materials Science
Authors: Mario Gabrielli | Vanessa Lançon‐Verdier | Pierre Picouet | Chantal Maury
Source: Chemosensors (article, 2021-04-01)
Field: Chemistry — Analytical Chemistry

Hyperspectral Imaging to Characterize Table Grapes Table grape quality is of importance for consumers and thus for producers. Its objective quality is usually determined by destructive methods mainly based on sugar content. This study proposed to evaluate the possibility of hyperspectral imaging to characterize table grapes quality through its sugar (TSS), total flavonoid (TF), and total anthocyanin (TA) contents. Different data pre-treatments (WD, SNV, and 1st and 2nd derivative) and different methods were tested to get the best prediction models: PLS with full spectra and then Multiple Linear Regression (MLR) were realized after selecting the optimal wavelengths thanks to the regression coefficients (β-coefficients) and the Variable Importance in Projection (VIP) scores. All models were good at showing that hyperspectral imaging is a relevant method to predict sugar, total flavonoid, and total anthocyanin contents. The best predictions were obtained from optimal wavelength selection based on β-coefficients for TSS and from VIPs optimal wavelength windows using SNV pre-treatment for total flavonoid and total anthocyanin content. Thus, good prediction models were proposed in order to characterize grapes while reducing the data sets and limit the data storage to enable an industrial use. Hyperspectral imaging ; Flavonoid ; Anthocyanin ; Partial least squares regression ; Mathematics ; Linear regression ; Sugar ; Table (database) ; Computer science ; Pattern recognition (psychology) ; Statistics ; Artificial intelligence ; Food science ; Chemistry ; Data mining Spectroscopy and Chemometric Analyses ; Horticultural and Viticultural Research ; Phytochemicals and Antioxidant Activities
Authors: Adam J. Simpkin | Jens M. H. Thomas | Ronan M. Keegan | Daniel J. Rigden
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-09-03)
Field: Materials Science — Materials Chemistry

MrParse: Finding homologues in the PDB and the EBI AlphaFold database for Molecular Replacement and more Abstract Crystallographers have an array of search model options for structure solution by Molecular Replacement (MR). Well-established options of homologous experimental structures and regular secondary structure elements or motifs are increasingly supplemented by computational modelling. Such modelling may be carried out locally or use pre-calculated predictions retrieved from databases such as the EBI AlphaFold database. MrParse is a new pipeline to help streamline the decision process in MR by consolidating bioinformatic predictions in one place. When reflection data are provided, MrParse can rank any homologues found using eLLG which indicates the likelihood that a given search model will work in MR. In-built displays of predicted secondary structure, coiled-coil and transmembrane regions further inform the choice of MR protocol. MrParse can also identify and rank homologues in the EBI AlphaFold database, a function that will also interest other structural biologists and bioinformaticians. Pipeline (software) ; Computer science ; Rank (graph theory) ; Data mining ; Process (computing) ; Database ; Computational biology ; Biology ; Mathematics ; Programming language ; Combinatorics Enzyme Structure and Function ; Protein Structure and Dynamics ; RNA and protein synthesis mechanisms
Authors: Gao Shu-min | Cong Cao | Dingyi Hu | Rangwei Xu | Yunjiang Cheng | Hong Chen | Ming Zhu | Shanjun Li
Source: International journal of agricultural and biological engineering (article, 2021-01-01)
Field: Chemistry — Analytical Chemistry

Prediction of Newhall navel orange internal quality based on digital microscopy The traditional technology for internal quality detection of citrus fruit is believed to be destructive, inefficient, and error-prone. To address these issues, a novel method has been developed to evaluate nondestructively the sugar-acid ratio (SAR) of soluble solids by using the oil glands density (OGD). In this study, a total of 584 samples with different widths were collected. The sample data were correlated that the SAR and OGD decreased with time during storage. The relevance with time was significant between SAR and OGD of citrus positively correlated in the calibration group (R2=0.82), which indicated that OGD could be used to predict the internal quality of citrus. It indicated that a new generation of digital microscopy could provide an alternative to predict nondestructively the internal quality of citrus fruit, as well as some theoretical insight for further studies of online quality detection in the future. Keywords: citrus, nondestructive, oil glands, internal quality, storage, microscopy DOI: 10.25165/j.ijabe.20211406.5996 Citation: Gao S M, Cao C, Hu D Y, Xu R W, Cheng Y J, Chen H, et al. Prediction of Newhall navel orange internal quality based on digital microscopy. Int J Agric & Biol Eng, 2021; 14(6): 222–227. Orange (colour) ; Microscopy ; Navel orange ; Horticulture ; Mathematics ; Materials science ; Chemistry ; Mineralogy ; Food science ; Biology ; Optics ; Physics Spectroscopy and Chemometric Analyses
Authors: Amanda Muyskens | Kathleen Schmidt | Matthew Nelms | Nathan R. Barton | J.N. Florando | Ana Kupresanin | David F. Rivera
Source: Statistical Analysis and Data Mining The ASA Data Science Journal (article, 2021-05-25)
Field: Materials Science — Materials Chemistry

A practical extension of the recursive multi‐fidelity model for the emulation of hole closure experiments Abstract In regimes of high strain rate, the strength of materials often cannot be measured directly in experiments. Instead, the strength is inferred based on an experimental observable, such as a change in shape, that is matched by simulations supported by a known strength model. In hole closure experiments, the rate and degree to which a central hole in a plate of material closes during a dynamic loading event are used to infer material strength parameters. Due to the complexity of the experiment, many computationally expensive, three‐dimensional simulations are necessary to train an emulator for calibration or other analyses. These simulations can be run at multiple grid resolutions, where dense grids are slower but more accurate. In an effort to reduce the computational cost, a combination of simulations with different resolutions can be combined to develop an accurate emulator within a limited training time. We explore the novel design and construction of an appropriate functional recursive multi‐fidelity emulator of a strength model for tantalum in hole closure experiments that can be applied to arbitrarily large training data. Hence, by formulating a multi‐fidelity model to employ low‐fidelity simulations, we were able to reduce the error of our emulator by approximately 81% with only an approximately 1.6% increase in computing resource utilization. Emulation ; Computer science ; Fidelity ; Algorithm ; Grid ; Extension (predicate logic) ; Closure (psychology) ; Computer engineering ; Simulation ; Event (particle physics) ; Computational science ; Mathematics ; Geometry High-Velocity Impact and Material Behavior ; Computational Fluid Dynamics and Aerodynamics ; Granular flow and fluidized beds
Authors: Vahid Bokharaie
Source: The Journal of Open Source Software (article, 2021-02-21)
Field: Materials Science — Materials Chemistry

MiTfAT: A Python-based Analysis Tool for Molecular fMRI Experiments. Functional Magnetic Resonance Imaging, fMRI, is a technique used in neuroscience to measure brain activity based on any signal that can be measured in an MRI scanner. Normally, fMRI is used to detect changes associated with blood flow, but it can also be used to detect changes in concentrations of molecules with different magnetic properties that might be directly injected into the brain of a subject. Python (programming language) ; Computer science ; Programming language ; Psychology ; Natural language processing ; Artificial intelligence Machine Learning in Materials Science ; Functional Brain Connectivity Studies ; Metabolomics and Mass Spectrometry Studies
Authors: Suttikan Sonchai | Chutima Phechkrajang | Piyanuch Rojsanga
Source: Pharmaceutical Sciences Asia (article, 2021-01-01)
Field: Chemistry — Analytical Chemistry

HPLC and chemometrics-assisted spectroscopic methods used for determination of dissolution of paracetamol and orphenadrine citrate in a combination tablet Paracetamol (4-acetamidophenol) is an effective analgesic and antipyretic for treatment of minor, noninflammatory conditions 1 . Orphenadrine citrate ((RS)-(dimethyl-2-(2-methylbenz-hydroxy) ethyl) amine citrate) is employed as skeletal muscle relaxant 2 . Thus, tablets containing paracetamol (PAR) and orphenadrine citrate (OPC) show combined analgesic, antipyretic and skeletal muscle relaxing actions. The structures of PAR and OPC are displayed in Figure Chemometrics ; Chromatography ; High-performance liquid chromatography ; Dissolution ; Chemistry ; Organic chemistry Analytical Methods in Pharmaceuticals ; Analytical Chemistry and Chromatography ; Chemical Thermodynamics and Molecular Structure
Authors: Д.В. Мамаев | S.A. Merkuryev | О. V. Malyshkina
Source: Physical and Chemical Aspects of the Study of Clusters Nanostructures and Nanomaterials (article, 2021-12-23)
Field: Chemistry — Analytical Chemistry

PORE PERCENTAGE ESTIMATION OF PIEZOELECTRIC CERAMICS USING CCANN AND IMAGE MADE WITH SEM Авторами получены образцы пьезоэлектрической керамики ниобата калия натрия с концентрацией пор 10,25 и 40 объемных %. Разработана капсульная свёрточная искусственная нейронная сеть для определения процентного содержания пор по изображению. С помощью растрового электронного микроскопа получено обучающее множество примеров (фотографии поверхности и сколов подготовленных образцов). Разработка и апробация капсульной свёрточной искусственной нейронной сети осуществлена в несколько этапов. На первом проведено ее обучение с помощью метода обратного распространения ошибки. На втором - тестирование на проверочном множестве. На заключительном этапе проведено сравнение полученных результатов с результатами метода сравнения плотности материала. Показано, что данный метод можно использовать для решения задачи определения процентного содержания пор в KNN, поскольку полученные результаты сопоставимы с результатами, полученными другим методом. Установлено, что в образцах, в которых не были специально добавлены поры, также присутствуют поры (порядка 5 %). The authors synthesized samples of piezoelectric potassium sodium niobate ceramics of 10,25 and 40 pore percentage by volume. Capsule convolutional artificial neural network has been developed for estimation of the pore percentage in images. Using the scanning electron microscopy, f learning massive of examples was formed (photographs of surface and edges of so-synthesized samples). Development and approbation of the capsule convolutional artificial neural network was completed in a few stages. During the first stage, the network was trained using a backpropagation method. Secondly, it was tested by a testing set. At the final stage we made a comparison of the acquired results with the results of the density comparing method. The article shows that this method can be used the pore percentage estimation in sodium niobate ceramics because the acquired results are comparable with the results of other methods. It was found that the samples where the pores were not made also have some pore percentage (about 5 %). Scanning electron microscope ; Backpropagation ; Materials science ; Ceramic ; Convolutional neural network ; Artificial neural network ; Piezoelectricity ; Mineralogy ; Artificial intelligence ; Composite material ; Computer science ; Chemistry Spectroscopy and Chemometric Analyses ; Industrial Vision Systems and Defect Detection ; Ultrasonics and Acoustic Wave Propagation
Authors: Korkut Açikalin | Gözde Gözke
Source: Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi (article, 2021-05-27)
Field: Materials Science — Materials Chemistry

Kavun çekirdeği pirolizine ait kinetik parametrelerin ve termodinamik özelliklerin belirlenmesi Bu almann amac, kavun ekirdei pirolizinin davrann incelemek ve kinetik parametreleri ile termodinamik zelliklerini hesaplamaktr. Termogravimetrik analiz deneyleri azot atmosferinde evre scaklndan 800C'ye 5, 10, 20 ve 40C/dk stma hzlarnda allmtr. Piroliz prosesinin, ikinci ve nc basamaklar aktif piroliz basama olan drt basamakta gerekletii tespit edilmitir Thermogravimetric analysis ; Gibbs free energy ; Pyrolysis ; Kinetic energy ; Enthalpy ; Activation energy ; Nitrogen ; Thermodynamics ; Chemistry ; Materials science ; Analytical Chemistry (journal) ; Physical chemistry ; Physics ; Organic chemistry Thermal and Kinetic Analysis ; Thermochemical Biomass Conversion Processes ; Chemical Thermodynamics and Molecular Structure
Authors: Hiroshi Nada | A. A. Arafa | Ibrahim F. Tarrad | M. Ashour
Source: International Journal of Computer Applications (article, 2021-09-18)
Field: Chemistry — Analytical Chemistry

Non-destructive Detection for Irradiated Apple using Image Processing This paper proposes a nondestructive method for detecting irradiated apple rather than the previous destructive method known before such as analytical methods; Chemical, Physical and Biological methods. Image processing technique was applied for rapid and nondestructive detection of irradiated apples. Color intensities, smoothness and uniformities were extracted and analyzed to correlate these color features of apple samples with its values before radiation. ANOVA analysis showed significant differences between both irradiated and un-irradiated apples sample. Linear discriminant analysis (LDA) was utilized for HSV data analysis. Results indicated that it was possible to detect irradiated food with good accuracy using imaging processing technique with an overall success rate of approximately 85%. The proposed method is cheap and less complicated which in turn saves time and effort. Consequently, it overcome the disadvantages of other analytical methods that are complex, costly and destructing the samples. Computer science ; Image (mathematics) ; Image processing ; Computer vision ; Artificial intelligence ; Computer graphics (images) Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Industrial Vision Systems and Defect Detection
Authors: Małgorzata Rabiej | Stanisław Rabiej
Source: Acta Crystallographica Section A Foundations and Advances (article, 2021-09-24)
Field: Materials Science — Materials Chemistry

The role of an objective function in the mathematical modelling of wide-angle X-ray diffraction curves of semi-crystalline polymers To decompose a wide-angle X-ray diffraction (WAXD) curve of a semi-crystalline polymer into crystalline peaks and amorphous halos, a theoretical best-fitted curve, i.e. a mathematical model, is constructed. In fitting the theoretical curve to the experimental one, various functions can be used to quantify and minimize the deviations between the curves. The analyses and calculations performed in this work have proved that the quality of the model, its parameters and consequently the information on the structure of the investigated polymer are considerably dependent on the shape of an objective function. It is shown that the best models are obtained employing the least-squares method in which the sum of squared absolute errors is minimized. On the other hand, the methods in which the objective functions are based on the relative errors do not give a good fit and should not be used. The comparison and evaluation were performed using WAXD curves of seven polymers: isotactic polypropylene, polyvinylidene fluoride, cellulose I, cellulose II, polyethylene, polyethylene terephthalate and polyamide 6. The methods were compared and evaluated using statistical tests and measures of the quality of fitting. Materials science ; Tacticity ; Polymer ; Diffraction ; Amorphous solid ; Polyethylene ; Curve fitting ; Composite material ; Crystallography ; Optics ; Mathematics ; Statistics ; Physics ; Chemistry X-ray Diffraction in Crystallography ; Cultural Heritage Materials Analysis ; Composite Material Mechanics
Authors: Abdullah Beyaz
Source: Turkish Journal of Agricultural Engineering Research (article, 2021-12-01)
Field: Chemistry — Analytical Chemistry

LabVIEW Based Real-time Color Measurement System Colorimetry is of paramount importance to the agricultural industry. Colorimetry refers to the processing of agricultural products for consumer needs from a marketing point of view, and therefore the agricultural industry spends a lot of money and time classifying each product. In the past, agricultural professionals had to use program codes that are difficult to learn, and even the most basic image analysis for agricultural product classification required mastering different program libraries. Today, the LabVIEW platform offers a flexible, fast, easy-to-learn, and complete image analysis infrastructure with various useful modules. For this reason, in this study, a method analysis for color perception with a simple USB webcam and software developed for real-time color analysis on the LabVIEW platform is presented and its success in the basic color analysis is tried to be revealed. The basic application developed for this purpose in LabVIEW v2019 using NI Vision Development Module v19 and NI IMAQ v19 modules. The basic fact that is the LabVIEW application is the idea that LabVIEW can only be analyzed with expensive IEEE 1394, but it should be known that these analyzes can be done with USB webcams. For this purpose, the application includes a USB webcam driver that can be stacked seamlessly. USB Webcam and colorimeter measurement-based results of ƔR factors for each of RGB color channels are 1.161232, 0.506287, 0.432229; ƔG factors for each of RGB color channels are 0.519619, 1.025383, 1.201444; at last ƔB factors for each of RGB color channels are 0.600362, 0.714016, 1.413406, respectively. USB ; RGB color model ; Colorimeter ; Computer science ; Colorimetry ; Computer graphics (images) ; Computer hardware ; Artificial intelligence ; Computer vision ; Embedded system ; Software ; Multimedia ; Operating system Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Advanced Chemical Sensor Technologies
Authors: Lars Kolbowski | Swantje Lenz | Lutz Fischer | Ludwig Sinn | Francis J. O’Reilly | Juri Rappsilber
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-11-23)
Field: Chemistry — Spectroscopy

Improved peptide backbone fragmentation is the primary advantage of MS-cleavable crosslinkers Abstract Proteome-wide crosslinking mass spectrometry studies have coincided with the advent of MS-cleavable crosslinkers that can reveal the individual masses of the two crosslinked peptides. However, recently such studies have also been published with non-cleavable crosslinkers suggesting that MS-cleavability is not essential. We therefore examined in detail the advantages and disadvantages of using the most popular MS-cleavable crosslinker, DSSO. Indeed, DSSO gave rise to signature peptide fragments with a distinct mass difference (doublet) for nearly all identified crosslinked peptides. Surprisingly, we could show that it was not these peptide masses that proved the main advantage of MS-cleavability of the crosslinker, but improved peptide backbone fragmentation that allowed for more confident peptide identification. We also show that the more intricate MS3-based data acquisition approaches lack sensitivity and specificity, causing them to be outperformed by the simpler and faster stepped HCD method. This understanding will guide future developments and applications of proteome-wide crosslinking mass spectrometry. Peptide ; Proteome ; Fragmentation (computing) ; Chemistry ; Mass spectrometry ; Combinatorial chemistry ; Computational biology ; Chromatography ; Biochemistry ; Computer science ; Biology Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Tarso Rudiana | Elda Suci Yala Merru | Hendrawati Hendrawati | Dede Sukandar
Source: EduChemia (Jurnal Kimia dan Pendidikan) (article, 2021-12-30)
Field: Chemistry — Organic Chemistry

Characterization and Anticancer Activity from Gaharu (Aquilaria malaccensis) Stem Bark Extract Aquilaria malaccensis is a plant species from the Thymeleaceae family. A. malaccensis contains secondary metabolites of phenolic groups, namely benzophenone, chromone, coumarin, xanthone, and flavonoids with various biological activities such as antioxidants and anticancer. This study aims to determine the potential of A. malaccensis stem bark extract as an anticancer and to determine the characteristics of secondary metabolite compounds contained in A. malaccensis stem bark extract. Extraction of the stem bark of A. malaccensis by maceration method in stages using n -hexane, ethyl acetate and methanol as solvents. The anticancer activity test used the microculture tetrazolium (MTT) assay against Murine Leukemia P-388 cells. Compound separation using thin layer chromatograph (TLC) and gravity column chromatography (CC) methods. Determination of chemical compounds using liquid chromatography mass spectroscopy/mass spectroscopy (LCMS/MS). The extracts of n -hexane, ethyl acetate, and methanol each had anticancer activity which was classified as active with an IC 50 value of 20.64, 26.61, and 14.49 µg/mL. Based on the results of separation and identification of compounds in methanol extract with TLC, CC, and LCMS/MS, methanol extract contains acetaminophen, aminosamptothesin, isophorone, diethyl phthalate, 3-hydroxy-6H-benzochromen-6-one, isolongifolenic, 2-(2-phenethyl) chromone, 4′,7-dihydroxy-2′,5-dimethoxyisoflavone, 4-hydroxy-3-(1-phenylpropyl)-2H-chromone-2-one; 6-methylchromone-2-carboxylic acid; 3,4-dimethyl-2- phenylmorpholine; and β-calacoren compounds. Chemistry ; Chromone ; Chromatography ; Ethyl acetate ; Xanthone ; Maceration (sewage) ; Column chromatography ; Soxhlet extractor ; Coumarin ; Organic chemistry ; Extraction (chemistry) Wood and Agarwood Research ; Identification and Quantification in Food