jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Qizhao Lin | Tuo He | Yongke Sun | Xin He | Jian Qiu
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2020-06-23)
Field: Chemistry — Organic Chemistry

A Computer-aided Method for Identifying the Presence of Softwood Growth Ring Boundaries ABSTRACT The objective of this study was to develop a computer-aided method to quantify the obvious degree of growth ring boundaries of softwood species, based on data analysis with some image processing technologies. For this purpose, a 5× magnified cross-section color micro-image of softwood was cropped into 20 sub-images, then every image is binarized as a gray image according to an automatic threshold value. After that, the number of black pixels in the gray image was counted row by row and the number of black pixels was binarized to 0 or 100. Finally, a transition band from earlywood to latewood on the sub-image was identified. If this was successful, the growth ring boundaries of the sub-image are distinct, otherwise they were indistinct or absent. If 10 of the 20 sub-images are distinct, with the majority voting method, the growth ring boundaries of softwood are distinct, otherwise they are indistinct or absent. The proposed method has been visualized as a growth-ring-boundary detecting system based on the .NET Framework. A sample of 100 micro-images (Supplementary Images) of softwood cross-sections were selected for evaluation purposes. In short, this detecting system computes the obvious degree of growth ring boundaries of softwood species by image processing involved image importing, image cropping, image reading, image grayscale, image binarization, data analysis. The results showed that the method used avoided mistakes made by the manual comparison method of identifying the presence of growth ring boundaries, and it has a high accuracy of 98%. Softwood ; Pixel ; Artificial intelligence ; Grayscale ; Computer vision ; Image processing ; Image (mathematics) ; Computer science ; Mathematics ; Pattern recognition (psychology) ; Engineering ; Pulp and paper industry Wood and Agarwood Research ; Remote Sensing and LiDAR Applications ; Industrial Vision Systems and Defect Detection
Authors: Shanjun Luo | Yingbin He | Qian Li | Weihua Jiao | Yaqiu Zhu | Xihai Zhao
Source: Research Square (preprint, 2020-09-30)
Field: Chemistry — Analytical Chemistry

Nondestructive estimation of potato yield using relative variables derived from multi-period LAI and hyperspectral data based on weighted growth stage Hyperspectral imaging ; Stage (stratigraphy) ; Yield (engineering) ; Mathematics ; Statistics ; Estimation ; Computer science ; Artificial intelligence ; Materials science ; Geology ; Economics ; Composite material Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Water Quality Monitoring and Analysis
Authors: Luan Pierre Pott | Telmo Jorge Carneiro Amado | Elódio Sebem | Raí Augusto Schwalbert
Source: Revista Engenharia na Agricultura - REVENG (article, 2020-01-29)
Field: Chemistry — Analytical Chemistry

SPECTRAL CURVES FOR IDENTIFICATION OF WEEDS IN WHEAT CROP The principal weeds in wheat cultivation are black oats and ryegrass and their control is generally performed without considering the spatial variability of the density of weed infestation. One way to identify weed species is by analyzing spectral curves of the targets. The objective of this work was to evaluate the spectral curves of wheat, black oats and ryegrass to identify which wavelengths are able to distinguish these species. The experiment was set using the species: black oats, ryegrass and wheat. Each species was sown in individual experimental plots in a completely randomized design with nine replications. HandHeld 2, ASD® spectroradiometer with 325-1075 nm spectral range was used to perform readings at full bloom stage. Then, the reflectance spectral data were grouped into eight spectral bands: violet, blue, green, yellow, orange, red, red edge and near infrared. Descriptive statistics of reflectance of the targets as well as analysis of variance (p&lt;0.05) and test of Tukey for comparison of the means (p&lt;0.01) were performed using the reflectance measurement of each spectral band. The results showed that the yellow and orange spectral bands obtained higher capacities of differentiation of the species under study. It can be concluded that the analysis of spectral curves of target of black oat and ryegrass weeds and wheat crop makes it possible to differentiate species in full bloom stage. Spectroradiometer ; Weed ; Agronomy ; Red edge ; Spectral signature ; Orange (colour) ; Crop ; Lolium multiflorum ; Mathematics ; Biology ; Reflectivity ; Horticulture ; Botany ; Canopy ; Remote sensing ; Physics ; Optics Spectroscopy and Chemometric Analyses ; Date Palm Research Studies ; Insect Pest Control Strategies
Authors: Benoît Rivard | Jilu Feng | Derek A. Russell | Vivek Bushan | Michael Lipsett
Source: Minerals (article, 2020-12-18)
Field: Chemistry — Analytical Chemistry

Hyperspectral Characteristics of Oil Sand, Part 2: Prediction of Froth Characteristics from Measurements of Froth This is the second part of a study of predictive models of oil sand ore and froth characteristics using infrared hyperspectral data as a potential new means for process control. In Alberta, Canada, bitumen in shallow oil sands deposits is accessed by surface mining and then extracted from ore using flotation processes. The ore displays variability in the clay, bitumen, and fines content and this variability affects the separability and product quality in flotation units. Flotation experiments were performed on a set of ore samples of different types to generate froth and determine the ore processability (e.g., separation performance) and froth characteristics (bitumen and solids content, fines distribution). We show that point spectra and spectral imagery of good quality can be acquired rapidly (&lt;1 s and &lt;15 s, respectively) and these capture spectral features diagnostic of bitumen and solids. Ensuing models can predict the solids/bitumen (r2 = 0.88) and the %fines and ultrafines (particle passing at 3.9 and 0.5 µm) content of froth (r2 = 0.8 and 0.9, respectively). The latter model could be used to reject froth with a high solids content. Alternately, the strength of the illite-smectite absorption observed in froth could be used to retain all the samples above a pre-defined processability. Given that point spectrometers can currently be acquired for less than half the cost of an imaging system, we recommend the use of the former for future trials in operating environments. Asphalt ; Oil sands ; Hyperspectral imaging ; Illite ; Environmental science ; Mineralogy ; Geology ; Materials science ; Clay minerals ; Remote sensing ; Composite material Spectroscopy and Chemometric Analyses ; Minerals Flotation and Separation Techniques ; Mineral Processing and Grinding
Authors: Hsin‐Yung Yen | Idlir Liko | Joseph Gault | Di Wu | Weston B. Struwe | Carol V. Robinson
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2020-04-24)
Field: Chemistry — Spectroscopy

Correlating glycoforms of DC-SIGN with stability using a combination of enzymatic digestion and ion mobility MS Abstract The immune scavenger protein DC-SIGN interacts with glycosylated proteins and has a putative role in facilitating viral infection. How these recognition events take place with different viruses is not clear and the effects of glycosylation on the folding and stability of DC-SIGN have not been reported. Here, we develop and apply a mass spectrometry-based approach to both uncover and characterise the effects of O-glycans on the stability of DC-SIGN. We first quantify the Core 1 &amp; 2 O-glycan structures on the carbohydrate recognition and extracellular domains of the protein via sequential exoglycosidase sequencing. We then use ion mobility mass spectrometry to show how specific O-glycans, and/or single monosaccharide substitutions, alter both the overall collision cross section and the gas-phase stability of the glycoprotein isoforms of DC-SIGN. We find that rather than the mass or length of glycoprotein modifications, the stability of DC-SIGN is better correlated with the number of glycosylation sites. Collectively, our results exemplify a combined multi-dimensional MS approach, proficient in evaluating protein stability in response to both glycoprotein macro- and micro-heterogeneity and adding structural detail to the infection enhancer DC-SIGN. Exoglycosidase ; DC-SIGN ; Glycoprotein ; Glycosylation ; Glycan ; Chemistry ; Ion-mobility spectrometry ; Biochemistry ; Mass spectrometry ; Biophysics ; Immune system ; Biology ; Chromatography Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Eduardo Gessel Pacheco-Venegas | Isabel Israde-Alcántara | Josué Álvarez-Borrego
Source: IEEE Access (article, 2020-01-01)
Field: Materials Science — Biomaterials

Binary Masks of Concentric Rings as a Method to Approximate Identification of Diatoms Using Images Diatoms are currently being used in different fields, and their application as bioindicators is one of their main benefits. Their identification is carried out by specialists, the main difficulty being the wide variety of existing species and the great similarity between some of them. In recent years attempts have been made to create an automatic identification system with the collaboration of experts in areas of pattern recognition. In this research we analyzed the use of binary masks of rings in images as a method to automatically identify diatoms, or render an approximative identification. Among the advantages of the proposed method is its invariance regarding the different positions in which the diatoms can be found. Invariance to illumination changes is achieved by means of different transforms, such as the power law transform. The image databases used to develop the algorithms were diatom images taken from samples collected at springs in Lake Patzcuaro, Michoacan, Mexico, at the San Lazaro basin, Baja California Sur, Mexico and from the public image database of ADIAC. In morphological and textural descriptors, the background of the image must be eliminated in order to classify the diatoms, whereas in the proposed methodology this is not necessary. The obtained results reach over than 90% even when the diatoms in the images are broken. Computer science ; Identification (biology) ; Artificial intelligence ; Binary image ; Diatom ; Binary number ; Image (mathematics) ; Pattern recognition (psychology) ; Similarity (geometry) ; Pixel ; Image processing ; Computer vision ; Geology ; Mathematics ; Ecology ; Arithmetic Diatoms and Algae Research ; Identification and Quantification in Food
Authors: Beatriz García-Castellanos | Osney Pérez Ones | Lourdes Zumalacárregui de Cárdenas | Idania Blanco-Carvajal | Luis Eduardo López-de-la-Maza
Source: Revista Facultad de Ingeniería (article, 2020-02-22)
Field: Chemistry — Analytical Chemistry

Neural Model for the Prediction of Volume Losses in the Aging Process of Rums The rum aging process shows volume losses, called wastage. The numerical operation variables: product, boardwalk, horizontal and vertical positions, date, volume, alcoholic degree, temperature, humidity and aging time, recorded in databases, contain valuable information to study the process. MATLAB 2017 software was used to estimate volume losses. In the modeling of the rum aging process, the multilayer perceptron neuronal network with one and two hidden layers was used, varying the number of neurons in these between 4 and 10. The Levenberg-Marquadt (LM) and Bayesian training algorithms were compared (Bay) The increase in 6 consecutive iterations of the validation error and 1,000 as the maximum number of training cycles were the criteria used to stop the training. The input variables to the network were: numerical month, volume, temperature, humidity, initial alcoholic degree and aging time, while the output variable was wastage. 546 pairs of input/output data were processed. The statistical Friedman and Wilcoxon tests were performed to select the best neural architecture according to the mean square error (MSE) criteria. The selected topology has a 6-4-4-1 structure, with an MSE of 2.1∙10-3 and a correlation factor (R) with experimental data of 0.9898. The neural network obtained was used to simulate thirteen initial aging conditions that were not used for training and validation, detecting a coefficient of determination (R2) of 0.9961. Artificial neural network ; Volume (thermodynamics) ; Mean squared error ; Multilayer perceptron ; Computer science ; Process (computing) ; Statistics ; MATLAB ; Algorithm ; Simulation ; Mathematics ; Artificial intelligence Spectroscopy and Chemometric Analyses ; Sensory Analysis and Statistical Methods ; Meat and Animal Product Quality
Authors: JSC " | И. А. Хабаров | В.В. Журов | А.N. Zhabayeva | С. М. Адекенов
Source: Bulletin of the Karaganda University Chemistry series (article, 2020-12-30)
Field: Chemistry — Analytical Chemistry

Modeling the extraction process of medicinal raw materials The review considers 26 mathematical models of the process of biologically active substances extraction from medicinal plant raw materials, taking into account factors affecting the extraction process: diffusion coefficient, particle size, layer porosity, extractant feed rate, raw material grinding method, pressure, temperature and duration of extraction, individual characteristics of raw materials (content of the target component) and technological equipment. In general, these models fall into four important groups: empirical models, models based on heat transfer analogies, a shrinking core model, and models based on differential mass bal-ance. Here were described problems that occur in the selection of mathematical models, first of all, associated with the imperfect behavior of the flows of extraction liquids, and the inhomogeneous cross-section of the extraction apparatus. It was shown that first of all the extraction process modeling requires mathematical models to describe the mass transfer inside solid particles. It is also important to take into account the solubility of the target substances when simulating. It is shown that for describing the extraction processes, the optimal models are Naik and Lentz, Esquivel, diffusion, H. Sovová mass transfer, damaged and undamaged cells for calculating the main factors of extraction processes. Mass transfer ; Raw material ; Extraction (chemistry) ; Process (computing) ; Diffusion ; Process engineering ; Mathematical model ; Biological system ; Component (thermodynamics) ; Computer science ; Mass transfer coefficient ; Materials science ; Mechanics ; Chromatography ; Chemistry ; Mathematics ; Thermodynamics ; Engineering ; Physics ; Statistics Chromatography in Natural Products ; Mining and Gasification Technologies ; Field-Flow Fractionation Techniques
Authors: Sameer Singh
Source: Scholarworks (University of Massachusetts Amherst) (article, 2020-06-26)
Field: Materials Science — Materials Chemistry

Scaling MCMC Inference and Belief Propagation to Large, Dense Graphical Models This Open Access Dissertation is brought to you for free and open access by the Dissertations and Theses at ScholarWorks@UMass Amherst. It has Graphical model ; Inference ; Markov chain Monte Carlo ; Belief propagation ; Computer science ; Scaling ; Artificial intelligence ; Mathematics ; Algorithm ; Bayesian probability Machine Learning in Materials Science ; Graph Theory and Algorithms ; Machine Learning and Algorithms
Authors: Bernard Adaramola | Daniel Danjuma Chirpyen
Source: Global Journal of Engineering and Technology Advances (article, 2020-11-30)
Field: Materials Science — Materials Chemistry

Experimental investigation of insulation resistance for turbo generator digital protection Insulation of all electrical machinery is practically in the form of organic compounds that contain water as part of their make-up. Excessive temperature tends to dehydrate and oxidize the insulation and make it become brittle and disintegrate under vibration and shock. The insulation lifespan of turbo generators deteriorates slowly at low temperatures and more rapidly at high temperature. Economic factors, such as initial cost, replacement cost, obsolescence, and maintenance, are of prime importance when determining the years of useful service desired for the electrical insulation. Generator digital protection- fault diagnosis test was carried out to find out the cause of insulation breakdown on the turbo generator unit 411G3. The experimental procedure consists of an insulation resistance test, meggering (time-resistance absorption test), and pendulum over-speed test. A thorough investigation was conducted to identify all the stator bars that constituted the Red phase and other connections. Voltage drops on these stator bars were measured and values were used to detect ground faults which were rectified via an intelligent protection scheme. Stator ; Turbo generator ; Dynamic insulation ; Electric generator ; Generator (circuit theory) ; Electrical engineering ; Structural engineering ; Automotive engineering ; Materials science ; Composite material ; Engineering ; Nuclear engineering ; Thermal insulation ; Vacuum insulated panel High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Non-Destructive Testing Techniques
Authors: А.Б. Белая | А.Ю. Яковлев
Source: МОРСКИЕ ИНТЕЛЛЕКТУАЛЬНЫЕ ТЕХНОЛОГИИ (article, 2020-08-13)
Field: Materials Science — General Materials Science

Forecasting of modern propeller characteristics by OpenFoam Применение CFD-пакетов для моделирования работы гребных винтов является одним из современных направлений исследований. Несмотря на достигнутые успехи, имеют место расхождения результатов, получаемых разными исследователями. С целью преодоления этих трудностей на международном уровне был проведен ряд сопоставительных расчетов гребных винтов. В данной работе представлена схема расчета силовых и кавитационных характеристик гребного винта в пакете OpenFOAM. Валидация расчетной схемы осуществляется на примере сопоставительных расчетов выполненных в рамках симпозиума SMP’11 и под эгидой пропульсивного комитета ITTC. Показано, что предложенная схема расчета не уступает аналогам в части расчета кривых действия модели гребного винта, оценке ее кавитационных характеристик и прогнозирования характеристик натурного гребного винта. Так же показано, что принципиальным для получения достоверных результатов является правильное построение сетки, имеющей высокое разрешение. The use of CFD packages for modeling the operation of propellers is one of the modern research areas. Despite the success achieved, there are discrepancies in the results obtained by different researchers. In order to overcome these difficulties, a number of comparative calculations of propellers have been made at the international level. This paper presents a scheme for calculating the thrust, torque and cavitation characteristics of a propeller in the OpenFOAM package. Validation of the calculation scheme is carried out on the example of comparative calculations performed in the framework of the SMP’11 Symposium and under the auspices of the ITTC propulsive Committee. It is shown that the proposed calculation scheme is not inferior to its analogues in terms of calculating the action curves of the propeller model, evaluating its cavitation characteristics and predicting the characteristics of a full-scale propeller. It is also shown that the principle for obtaining reliable results is the correct construction of a high-resolution grid. Propeller ; Thrust ; Computational fluid dynamics ; Marine engineering ; Torque ; Scheme (mathematics) ; Scale (ratio) ; Computer science ; Propulsor ; Grid ; Engineering ; Aerospace engineering ; Mathematics ; Physics Material Properties and Applications
Authors: Özge Ural | Tuba Vural
Source: TEKSTİL VE KONFEKSİYON (article, 2020-03-10)
Field: Materials Science — Polymers and Plastics

MEASUREMENT CONTROL OF READY-MADE GARMENTS WITH IMAGE ANALYSIS METHODS In the ready-made clothing industry accurate garment measurement is one of the most important points for the right fitting of the apparel. Garments should be produced to the determined size by the customer or the enterprise. Although, the measurement control of the final product is made by trained operator, the factors such as gradually loose of attention, fatigue and stress could cause faults that could lead to lack of quality and waste of time. In this sense, developing and using objective, fast and economic measurement control systems in terms of both cost effectiveness and the reliability of the controls has become a must. The purpose of the study is to design a system and develop an algorithm to control the measurements of garments automatically. This study, which is determined that image analysis method can be used in measurement control of ready-made garments, will be a new measurement control method in the literature and an example for similar studies. By benefiting from the image analysis methods, measurement mistakes likely to result from the operator will be prevented and the results will be made more reliable. Clothing ; Control (management) ; Reliability (semiconductor) ; Quality (philosophy) ; Operator (biology) ; Computer science ; Product (mathematics) ; Reliability engineering ; Manufacturing engineering ; Industrial engineering ; Risk analysis (engineering) ; Engineering drawing ; Operations management ; Engineering ; Business ; Artificial intelligence ; Mathematics Textile materials and evaluations ; Advanced Vision and Imaging ; Industrial Vision Systems and Defect Detection
Authors: Yusuke Matsui | Yuichi Abe | Kohei Uno | Satoru Miyano
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2020-12-23)
Field: Chemistry — Spectroscopy

RoDiCE: Robust differential protein co-expression analysis for cancer complexome Abstract Motivation The full spectrum of abnormalities in cancer-associated protein complexes remains largely unknown. Comparing the co-expression structure of each protein complex between tumor and healthy cells may provide insights regarding cancer-specific protein dysfunction. However, the technical limitations of mass spectrometry-based proteomics, including contamination with biological protein variants, causes noise that leads to non-negligible over- (or under-) estimating co-expression. Results We propose a robust algorithm for identifying protein complex aberrations in cancer based on differential protein co-expression testing. Our method based on a copula is sufficient for improving identification accuracy with noisy data compared to conventional linear correlation-based approaches. As an application, we use large-scale proteomic data from renal cancer to show that important protein complexes, regulatory signaling pathways, and drug targets can be identified. The proposed approach surpasses traditional linear correlations to provide insights into higher order differential co-expression structures. Availability and Implementation https://github.com/ymatts/RoDiCE . Computational biology ; Proteomics ; Protein expression ; Biology ; Computer science ; Genetics ; Gene Advanced Proteomics Techniques and Applications ; Bioinformatics and Genomic Networks ; Statistical Methods in Clinical Trials