jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Tanja Vojinović | Zorica Potpara | Mihailo Vukmirovic | Nemanja Turković | Svetlana Ibrić
Source: Acta Poloniae Pharmaceutica - Drug Research (article, 2022-11-21)
Field: Chemistry — Analytical Chemistry

Artificial neural networks and their application in the optimization of carbamazepine solid dispersions The aim of this study was to examine the possibility of using artificial neural networks in the optimization of solid dispersions with carbamazepine. Artificial neural networks of the Generalized regression neural network type with four layers, gave models that describe the effect of components in solid dispersions carbamazepine-Neusilin ® UFL2 (magnesium aluminosilicate)-Collidon ® VA64 (vinylpyrrolidone-vinyl acetate) and dissolved carbamazepine value (%) after 10 (Q10) and 30(Q30) minutes of carbamazepine testing. After the learning process, root mean square error (RMS) values of 0.0029 were obtained for the training data set, and 0.1185 for the test training data, which is an excellent prediction of the neural network. Carbamazepine ; Artificial neural network ; Aluminosilicate ; Mean squared error ; Materials science ; Computer science ; Mathematics ; Chemistry ; Machine learning ; Organic chemistry ; Statistics ; Catalysis ; Medicine Analytical Methods in Pharmaceuticals
Authors: Juan Antonio Fernández Pierna | Philippe Vermeulen | Nicolas Chamberland | Virginie Decruyenaere | Éric Froidmont | Olivier Minet | Bernard Lecler | Vincent Baeten
Source: BASE (article, 2022-01-01)
Field: Chemistry — Analytical Chemistry

Performance of three handheld NIR spectrometers for predicting grass silage quality Description of the subject. Feed is the main variable cost in dairy farming. More efficient use of forage resources is one way to reduce production costs. Improving forage resource efficiency can start with a better assessment of the dry matter content and nutritional value of forages. Currently, analytical process time is often long and analyses are not repeatable while the quality of the fodder changes over time. Being able to analyze forages directly on-farm would make it possible to adapt the animal diet according to forage variability, in order to improve the profitability of the farm. Objectives. To propose in situ rapid analysis solutions to better characterize dry matter content and the chemical composition of fodder for assessing its feeding value. Method. The performance of three recently developed spectroscopic handheld devices, namely the Viavi’s MicroNIR 1700, the Ocean Insight’s FlameNIR and the Malvern Panalytical’s ASD FieldSpec 4, are evaluated to predict dry matter content and the chemical composition of fresh and unground grass silage in the framework of precision feeding and compared to the reference benchtop Foss’s XDS instrument. The conventional global PLS and local PLS are used as multivariate calibration methods. Results. The assessed handheld devices allow the dairy farmer to obtain a relatively precise quantitative prediction of the dry matter and crude fiber content (2.5% and 1.8% respectively on average, in terms of ratios between the local PLS error on fresh forage and the reference method error) in order to adapt the livestock diet. Crude protein, even if the prediction accuracy is lower (6.4%), is still well predicted. Higher errors are obtained for ash (9.2%), crude neutral (6.8%) and acid detergent fiber (6.9%). Conclusions. The studied devices should allow the dairy farmer to obtain a relatively precise quantitative prediction of those quality parameters in order to directly adapt the quantity of forage distributed to the animals. Performances could probably be improved by including more samples/spectra into the databases. Forage ; Silage ; Dry matter ; Fodder ; Neutral Detergent Fiber ; Environmental science ; Agricultural engineering ; Mathematics ; Agronomy ; Engineering ; Biology Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Remote Sensing in Agriculture
Authors: Rahmiati Rahmiati | Suciani Zubair | Baiq Yusmi Aolinnir Rahmah | Ika Mustikasari | Annur Afgoni | Erin Ryantin Gunawan
Source: JURNAL PIJAR MIPA (article, 2022-07-31)
Field: Chemistry — Inorganic Chemistry

Formulation and antibacterial test traveling paper soap made from virgin coconut oil and durian seeds Soap as a cleaning product has been the primary needs since the spread of Covid-19. Government regulations require people to wash their hands. Hence the demand for soap production is increasing. This study aimed to obtain a Traveling Paper Soap formulation from VCO and durian seeds for antibacterial activity on the skin. The experimental laboratory method uses quantitative and qualitative descriptive analysis. The treatment in this study was the production of Durian Seed Bioethanol with a bioethanol capacity of 19.95% from the hydrolysis of 486 g of Durian Seed flour. The treatment in this study was the manufacture of durian seed bioethanol with a bioethanol content of 19.95% from the hydrolysis of 486 g of durian seed flour. The parameters of the bioethanol viscosity test were 0.7137 cP, and the bioethanol density was 0.9669 g/mL. Based on our research, the best traveling paper soap results are formulation 2 with a water content of 7%, pH value of 10, free alkali content of 0.21%, and antibacterial activity against Staphylococcus Epidermis of 22.3 mm. According to the Indonesian National Standard Mandatory Solid Soap, SNI 3532:1994, it shows that soap complies with the SNI 3532:1994 standard. SOAP ; Biofuel ; Food science ; Pulp and paper industry ; Waste management ; Chemistry ; Mathematics ; Engineering ; Computer science Coconut Research and Applications ; Natural Products and Applications ; Herbal Medicine and Trade Cooperation
Authors: Elke Debrie | Milan Malfait | Ralf Gabriels | Arthur Declerq | Adriaan Sticker | Lennart Martens | Lieven Clement
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2022-11-17)
Field: Chemistry — Spectroscopy

Quality control for the target decoy approach for peptide identification Abstract Reliable peptide identification is key in mass spectrometry (MS) based proteomics. To this end, the target-decoy approach (TDA) has become the cornerstone for extracting a set of reliable peptide-to-spectrum matches (PSMs) that will be used in downstream analysis. Indeed, TDA is now the default method to estimate the false discovery rate (FDR) for a given set of PSMs, and users typically view it as a universal solution for assessing the FDR in the peptide identification step. However, the TDA also relies on a minimal set of assumptions, which are typically never verified in practice. We argue that a violation of these assumptions can lead to poor FDR control, which can be detrimental to any downstream data analysis. We here therefore first clearly spell out these TDA assumptions, and introduce TargetDecoy, a Bioconductor package with all the necessary functionality to control the TDA quality and its underlying assumptions for a given set of PSMs. TOC Graphic False discovery rate ; Decoy ; Identification (biology) ; Bioconductor ; Set (abstract data type) ; Computer science ; Downstream (manufacturing) ; Quality (philosophy) ; Key (lock) ; Data mining ; Data set ; Chemistry ; Artificial intelligence ; Engineering ; Computer security ; Biology Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Identification and Quantification in Food
Authors: Jianfeng Wang | Huo Lin | Di Gai | Jianwei Zhang | Rui Zhao
Source: Highlights in Science Engineering and Technology (article, 2022-11-13)
Field: Materials Science — Materials Chemistry

Study on bird impact response of windshield glass of all general aviation aircraft With the improvement of aircraft flight speed, bird impact is easy to cause serious accidents such as windshield breakdown, aircraft destruction and human death. In order to improve the bird impact resistance of aircraft windshield glass, the dynamic response of windshield glass (YB-3 plexiglass) after bird impact of small general-purpose aircraft flying at cruise speed was studied. By establishing the bird impact windshield glass model and adopting the fixed restraint mode around, the windshield glass is impacted at the speeds of 200km/h, 220km/h and 250km/h and the angles of 30°, 60° and 90°, respectively. The changes of stress-strain, displacement and energy absorption of the windshield glass under the impact of bird body, as well as the effects of different impact speeds and impact angles on the dynamic response of the glass are analyzed. It is found that during the whole impact process, the stress and strain of YB-3 plexiglass will reach the peak in a short time, then oscillate back and forth in a period of time, and the final residual deformation is small. With the increase of impact velocity, the stress, strain and displacement of glass will increase accordingly; With the increase of the impact angle, the energy absorbed by the windshield glass decreases accordingly, and the damage and deformation around the impact point are reduced. By studying the bird impact of the windshield of small general-purpose aircraft, it provides a theoretical basis for the airworthiness certification of general-purpose aircraft and the design optimization of windshield glass. Windshield ; Materials science ; Impact ; Airworthiness ; Deformation (meteorology) ; Impact resistance ; Stress (linguistics) ; Impact energy ; Composite material ; Environmental science ; Forensic engineering ; Structural engineering ; Engineering ; Aerospace engineering ; Certification ; Law High-Velocity Impact and Material Behavior ; Fluid Dynamics Simulations and Interactions ; Transportation Safety and Impact Analysis
Authors: António Lopes | V.A.F. Costa | João S. Amaral
Source: Applied Sciences (article, 2022-06-29)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Thermal Response of Magnetic Refrigerants: Combined Effect of Temperature Dependent Specific Heat and Thermal Conductivity Device optimization plays a paramount role in current research on magnetic refrigeration. Solid state refrigerants have been characterized and numerical simulations assume a critical relevance in the development of magnetocaloric technology to have alternatives to vapour-compression systems whose operating elements have high global warming potential. Experimental studies have shown that the thermal properties of several magnetocaloric materials considerably change around their Curie temperatures (TC) and that this temperature dependency should not be dismissed. Current numerical research does not fully predict the complete thermal response of such materials, due to inaccuracies from neglecting the impact of combining both thermal conductivity (k) and specific heat (Cp) dependence on temperature. In this study, a simple unidimensional model includes k(T) and Cp(T) functions as input parameters, highlighting the relevance of considering temperature dependent thermophysical properties’ inputs when simulating the magnetic refrigerant’s heat transfer processes. The obtained results evidence that neglecting the temperature dependence of the magnetocaloric material thermophysical properties, namely its thermal conductivity and its specific heat, affects its temperature response, what may strongly affect the results after a succession of (hundreds or thousands) cycles. Magnetic refrigeration ; Refrigerant ; Thermal conductivity ; Thermodynamics ; Materials science ; Curie temperature ; Thermal ; Refrigeration ; Heat transfer ; Condensed matter physics ; Magnetic field ; Heat exchanger ; Ferromagnetism ; Magnetization ; Physics Magnetic and transport properties of perovskites and related materials ; Optical properties and cooling technologies in crystalline materials ; Physics of Superconductivity and Magnetism
Authors: Zhanbolat Shakhmov | Shamil Amir
Source: Technobius (article, 2022-03-10)
Field: Materials Science — Materials Chemistry

Nonlinear calculation of beam reinforcement using the finite element method The article is devoted to the research of solution of the actual problem in construction, namely increase of ultimate loads of different kinds of constructions and possibility of effective application of innovative methods of reconstruction of beam constructions. In this work 2 kinds of different composite materials have been applied. The project considers the use of carbon fiber as an external reinforcement material for bridge girders. This study analyzes the performance of the reinforced structure under external loads. With the use of computer modeling of the finite element method, an analysis of the selection of reinforcement schemes, which allows to significantly increase the carrying capacity of reinforced concrete beam structures, is performed. Also, some proposals for the implementation of these experiments on real girder structures and constructions were considered. The data obtained as a result of the work allow the conclusion about the successful application of composite materials as reinforcement structures. Correctly chosen scheme of strengthening, confirmed by calculations allows you to significantly increase the carrying capacity of the beam reinforced concrete structures. Reinforcement ; Finite element method ; Beam (structure) ; Structural engineering ; Girder ; Bridge (graph theory) ; Work (physics) ; Nonlinear system ; Computer science ; Composite number ; Engineering ; Mechanical engineering ; Algorithm Structural mechanics and materials ; Advanced Energy Technologies and Civil Engineering Innovations ; Structural Behavior of Reinforced Concrete
Authors: Małgorzata Matusiak | Otgonsuren Sukhbat
Source: Communications in development and assembling of textile products (article, 2022-09-03)
Field: Materials Science — Polymers and Plastics

Liquid Moisture Transport in Knitted Fabrics in Relaxed and Stretched State The aim of this work was to analyze the influence of stretch on liquid moisture transport through the knitted fabrics for T-shirts. Five variants of cotton and cotton blended fabrics were measured by means of the Moisture Management Tester. Measurements have been performed for samples in the unstretched state and samples stretched by 15%. To precisely stretch the fabrics, the MMT Stretch Fabric Fixture has been applied. The results have been analyzed statistically in order to assess the influence of stretch on the parameters characterizing the moisture transport through the fabrics. Moisture ; Materials science ; Composite material ; Work (physics) ; Fixture ; Mechanical engineering ; Engineering Textile materials and evaluations
Authors: Brad G. Davis | Gregory Langone | Nicholas Reisweber
Source:  (article, 2022-05-25)
Field: Materials Science — Materials Chemistry

Sensitivity Analysis and Bayesian Calibration of a Holmquist-Johnson-Cook Material Model for Cellular Concrete Subjected to Impact Loading Abstract Periodic updates to small caliber weapon systems and projectiles used in military and law enforcement have resulted in consistently increasing material penetration capabilities. With each new generation, ballistics technology outpaces the lifecycle replacement of live-fire training facilities. For this reason, it is necessary to develop and maintain constitutive material models for use in analyzing the effects new threats will have on existing facilities and for designing new training facilities using numerical methods. This project utilizes material testing data to characterize cellular concretes used in the construction of live-fire training facilities with a 13-parameter Holmquist-Johnson-Cook (HJC) concrete constitutive model. Various statistical tools are used in this analysis to successfully describe the importance of each model parameter and quantify their uncertainty. First, Bayesian linear regression was used to calibrate the parameters in the strength and pressure components of the HJC material model given testing data of cellular concrete. These uncertain parameters were then used to construct computer simulations of penetration and perforation experiments that were previously conducted by Collard and Lanham. Then, Latin Hypercube Sampling of the parameter space was used to generate training data for a Gaussian Process surrogate model of the computer simulation. Using the surrogate model, a global variance-based sensitivity analysis of the material model was completed by computing main and total effect Sobol indices. Finally, a Bayesian calibration of the computer simulation based on the physical experiments was conducted to fully characterize the stochastic behavior of the material subjected to perforation impacts. These approaches can be used to inform decision makers about the potential risk associated with existing facilities and by designers of future live fire training facilities. Latin hypercube sampling ; Surrogate model ; Computer science ; Sensitivity (control systems) ; Gaussian process ; Uncertainty quantification ; Kriging ; Calibration ; Bayesian probability ; Monte Carlo method ; Gaussian ; Engineering ; Machine learning ; Mathematics ; Artificial intelligence ; Statistics ; Physics High-Velocity Impact and Material Behavior ; Structural Response to Dynamic Loads ; Transportation Safety and Impact Analysis
Authors: Katharina Bersching | Thomas Michna | Stefan Tenzer | Stefan Jacob
Source: Journal of Fungi (article, 2022-12-31)
Field: Chemistry — Spectroscopy

Data-Independent Acquisition (DIA) Is Superior for High Precision Phospho-Peptide Quantification in Magnaporthe oryzae The dynamic interplay of signaling networks in most major cellular processes is characterized by the orchestration of reversible protein phosphorylation. Consequently, analytic methods such as quantitative phospho-peptidomics have been pushed forward from a highly specialized edge-technique to a powerful and versatile platform for comprehensively analyzing the phosphorylation profile of living organisms. Despite enormous progress in instrumentation and bioinformatics, a high number of missing values caused by the experimental procedure remains a major problem, due to either a random phospho-peptide enrichment selectivity or borderline signal intensities, which both cause the exclusion for fragmentation using the commonly applied data dependent acquisition (DDA) mode. Consequently, an incomplete dataset reduces confidence in the subsequent statistical bioinformatic processing. Here, we successfully applied data independent acquisition (DIA) by using the filamentous fungus <i>Magnaporthe oryzae</i> as a model organism, and could prove that while maintaining data quality (such as phosphosite and peptide sequence confidence), the data completeness increases dramatically. Since the method presented here reduces the LC-MS/MS analysis from 3 h to 1 h and increases the number of phosphosites identified up to 10-fold in contrast to published studies in <i>Magnaporthe oryzae</i>, we provide a refined methodology and a sophisticated resource for investigation of signaling processes in filamentous fungi. Biology ; Computational biology ; Robustness (evolution) ; Phosphorylation ; Missing data ; Computer science ; Biological system ; Bioinformatics ; Cell biology ; Gene ; Biochemistry ; Machine learning Advanced Proteomics Techniques and Applications ; Fungal and yeast genetics research ; Mass Spectrometry Techniques and Applications
Authors: Canan Demir | Sıddık Keskin
Source: Eastern Journal Of Medicine (article, 2022-01-01)
Field: Chemistry — Analytical Chemistry

Introduction of Nonlinear Principal Component Analysis with an Application in Health Science Data Nonlinear Principal Component Analysis is one of the explanatory dimension reducing technique and presents numerical and graphical results for variable set included linear or nonlinear relationships. In this study, Nonlinear Principal Component Analysis was introduced and the relationship between students' sexual and physical trauma stories and demographic characteristics was examined with this method. In the study, the relationship between trauma and 9 variables obtained by questionnaire from 548 students was evaluated by Nonlinear Principal Component Analysis. The eigenvalue of first dimension has been found to be 1.766 and the eigenvalue of second dimension has been found to be 1.504 The variance explanation rate of these eigenvalues are 17.656% and 15.044% respectfully. The total explained variance is seen as 28.550%. With Nonlinear Principal Component Analysis, categorical variables are scaled to the desired size in the most appropriate way, and thus, nonlinear relationships can be modeled as well as linear relationships between variables. With this analysis, gender, age, marital status and suicide variables were found to be effective on trauma. Medicine ; Principal component analysis ; Component (thermodynamics) ; Nonlinear system ; Health science ; Data science ; Artificial intelligence ; Medical education ; Computer science Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Seval Uyanık | Mehmet Merkepçi
Source: Çukurova Üniversitesi Mühendislik Fakültesi Dergisi (article, 2022-03-29)
Field: Materials Science — Polymers and Plastics

Çeşitli Örme Kumaşlarda Farklı Tekniklerle Gözenekliliğin Belirlenmesi ve Hava Geçirgenliği için Optimum Tekniğin Tespiti Üzerine Bir Çalışma Geçirgenlik özellikleri kumaş gözenekliliğinden doğrudan etkilenir. Tekstil malzemelerinin gözenekliliğini belirlemek için teorik ve deneysel birçok yöntem vardır. Bu çalışma, görüntü işleme tekniği ve geometri modelleme kullanarak askılı örme kumaşların gözenekliliğini belirlemeyi ve hava geçirgenliği açısından kumaş gözenekliliğini belirlemek için hangi tekniğin daha uygun olduğunu ortaya koymayı amaçlamaktadır. Çalışma sonuçları, optik gözenekliliği belirleyen görüntü analizinin, bu yöntem sadece gözenek boyutuna odaklandığından geometri modellemeye göre daha uygun olduğunu kanıtlamıştır. Ayrıca örme kumaşlarda ilmeklerin konumuna göre gözenek boyutları değiştiği için hava geçirgenlik değerleri beklenmedik bir şekilde ilmek sayısı ile paralel değildir.. Physics ; Mathematics Textile materials and evaluations ; Color perception and design ; Dyeing and Modifying Textile Fibers
Authors: Desi Puspita
Source: Indonesian Journal of Computer Science (article, 2022-12-31)
Field: Chemistry — Inorganic Chemistry

Implementasi Learning Vector Quantization untuk Klasifikasi Jenis Buah Kelapa menggunakan Image Processing Coconut fruit is a versatile plant because all parts from the stem to the coconut fruit have their benefits. Coconut fruit is the most valuable part of the economy. The problem so far that has occurred is that the process of classifying coconut species is still done manually and has not been computerized, namely the classification of coconut types is still based on experience, color, and shape of the coconut. This of course takes a long time and errors still occur frequently. So this research can help classify coconuts with Learning Vector Quantization (LVQ). The purpose of this research is to organize the types of coconuts with image processing and Learning Vector Quantization (LVQ) by using mean extraction from RGB (Red, Green, Blue) and standard deviation from RGB (Red, Green, Blue). The results of the study were taken from 2 different types of coconuts against the 80 training data, the accuracy of the training data was 83.75%. The evaluation results with the Confusion Matrix with a test accuracy value of 90% of the 20 test data. Learning vector quantization ; RGB color model ; Artificial intelligence ; Confusion matrix ; Confusion ; Mathematics ; Computer science ; Pattern recognition (psychology) ; Vector quantization Coconut Research and Applications ; Food and Agricultural Sciences ; Agricultural and Biological Research