jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Jian Zhang | Qing Chen | Minghong Shi | Hongping Zhou | Linyun Xu
Source: PLoS ONE (article, 2021-06-17)
Field: Materials Science — Polymers and Plastics

Interaction and influence of a flow field and particleboard particles in an airflow forming machine with a coupled Euler-DPM model Particleboards are widely used in the artificial board market, which can be constructed from a variety of raw materials and require small amounts of energy to be produced. In the particleboard production process, forming machines play an important role as the key equipment for achieving continuous production. In recent years, airflow forming machines have received increasing attention in particleboard production lines because of their strong separation ability and low price. However, the internal flow field is complex and difficult to control, which affects the surface quality and strength of the particleboard. The most pressing technical difficulty is controlling the flow field characteristics of the airflow paver. At present, the research on this subject is conducted primarily through repeated experiments, which entail long research periods and high processing costs. To reduce human and financial costs, in this study, Computational Fluid Dynamics (CFD) is employed to investigate the flow field and the gas-solid two-phase flow field coupled with particle movement of an airflow forming machine. The accuracy of the calculation model is verified by comparing characteristic point velocities obtained from experimental analysis and a simulation. The simulation results show that in practical production, the frequency of a negative pressure fan should be greater than 27 Hz. It is necessary to set the shoulder properly, and the slab smoothness can be improved by moving the shoulder back on the premise of meeting the strength requirements of the box. The distance between the shoulders of the box body should be less than 2570 mm, and particles with uniform diameter should be added to the paving box to reduce the turbulence effect, improve the quality of particle forming and provide actual particleboard production with a solid theoretical foundation. Airflow ; Computational fluid dynamics ; Flow (mathematics) ; Mechanical engineering ; Computer science ; Simulation ; Mechanics ; Process engineering ; Materials science ; Engineering ; Physics Natural Fiber Reinforced Composites ; Cyclone Separators and Fluid Dynamics ; Plant Surface Properties and Treatments
Authors: Jia Liu | Gui Yun Tian | Bin Gao | Kun Zeng | Yongbing Xu | Qianhang Liu
Source: Sensors (article, 2021-03-28)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Time-Response-Histogram-Based Feature of Magnetic Barkhausen Noise for Material Characterization Considering Influences of Grain and Grain Boundary under In Situ Tensile Test Stress is the crucial factor of ferromagnetic material failure origin. However, the nondestructive test methods to analyze the ferromagnetic material properties' inhomogeneity on the microscopic scale with stress have not been obtained so far. In this study, magnetic Barkhausen noise (MBN) signals on different silicon steel sheet locations under in situ tensile tests were detected by a high-spatial-resolution magnetic probe. The domain-wall (DW) motion, grain, and grain boundary were detected using a magneto-optical Kerr (MOKE) image. The time characteristic of DW motion and MBN signals on different locations was varied during elastic deformation. Therefore, a time-response histogram is proposed in this work to show different DW motions inside the grain and around the grain boundary under low tensile stress. In order to separate the variation of magnetic properties affected by the grain and grain boundary under low tensile stress corresponding to MBN excitation, time-division was carried out to extract the root-mean-square (RMS), mean, and peak in the optimized time interval. The time-response histogram of MBN evaluated the silicon steel sheet's inhomogeneous material properties, and provided a theoretical and experimental reference for ferromagnetic material properties under stress. Materials science ; Barkhausen effect ; Grain boundary ; Ferromagnetism ; Magnetic domain ; Ultimate tensile strength ; Tensile testing ; Stress (linguistics) ; Grain size ; Composite material ; Condensed matter physics ; Magnetic field ; Magnetization ; Physics Magnetic Properties and Applications ; Electromagnetic Effects on Materials ; Microstructure and Mechanical Properties of Steels
Authors: Rafael E. Arévalo B. | Nancy Pulido | Juan Felipe Solorzano | Richard Soares | Flavio Ruffinatto | Prabu Ravindran | Alex C. Wiedenhoeft
Source: Colombia Forestal (article, 2021-01-01)
Field: Chemistry — Organic Chemistry

Imaged based identification of colombian timbers using the xylotron: a proof of concept international partnership Field deployable computer vision wood identification systems can play a key role in combating illegal logging in the real world. This work used 764 xylarium specimens from 84 taxa to develop an image data set to train a classifier to identify 14 commercial Colombian timbers. We imaged specimens from various xylaria outside Colombia, trained and evaluated an initial identification model, then collected additional images from a Colombian xylarium (BOFw), and incorporated those images to refine and produce a final model. The specimen classification accuracy of this final model was ~ 97%, demonstrating that including local specimens can augment the accuracy and reliability of the XyloTron system. Our study demonstrates the first deployable computer vision model for wood identification in Colombia, developed on a timescale of months rather than years by leveraging international cooperation. We conclude that field testing and advanced forensic and machine learning training are the next logical steps. Identification (biology) ; Classifier (UML) ; Artificial intelligence ; Computer science ; Field (mathematics) ; General partnership ; Proof of concept ; Computer vision ; Pattern recognition (psychology) ; Machine learning ; Engineering ; Mathematics Wood and Agarwood Research ; Remote Sensing and LiDAR Applications ; Industrial Vision Systems and Defect Detection
Authors: J. J. Kas | Fernando D. Vila | C. D. Pemmaraju | Micah P. Prange | Kristin A. Persson | Ruoxi Yang | J. J. Rehr
Source: Computational Materials Science (article, 2021-10-06)
Field: Materials Science — Materials Chemistry

Full spectrum optical constant interface to the Materials Project Workflow ; Python (programming language) ; Computation ; Computer science ; Computational science ; Materials science ; Absorption spectroscopy ; Computational physics ; Optics ; Database ; Physics ; Algorithm Machine Learning in Materials Science ; X-ray Diffraction in Crystallography ; Catalysis and Oxidation Reactions
Authors: Antoni Wibowo | Inten Yasmina
Source: Advances in Science Technology and Engineering Systems Journal (article, 2021-03-01)
Field: Chemistry — Analytical Chemistry

Food Price Prediction Using Time Series Linear Ridge Regression with The Best Damping Factor Forecasting food prices play an important role in livestock and agriculture to maximize profits and minimizing risks. An accurate food price prediction model can help the government which leads to optimization of resource allocation. This paper uses ridge regression as an approach for forecasting with many predictors that are related to the target variable. Ridge regression is an expansion of linear regression. It's fundamentally a regularization of the linear regression model. Ridge regression uses the damping factor () as a scalar that should be learned, normally it will utilize a method called cross-validation to find the value. But in this research, we will calculate the damping factor/ridge regression in the ridge regression (RR) model firsthand to minimize the running time used when using cross-validation. The RR model will be used to forecast the food price time-series data. The proposed method shows that calculating the damping factor/regression estimator first results in a faster computation time compared to the regular RR model and also ANFIS. Series (stratigraphy) ; Ridge ; Regression ; Linear regression ; Time series ; Econometrics ; Regression analysis ; Statistics ; Mathematics ; Economics ; Geology ; Paleontology Spectroscopy and Chemometric Analyses ; Advanced Statistical Methods and Models
Authors: Zhiqiang Dong | Yang Liu | Baoxia Ci | Ming Wen | Minghua Li | Xi Lu | Xiaokang Feng | Shuai Wen | Fuyu Ma
Source: Plant Methods (article, 2021-08-18)
Field: Chemistry — Analytical Chemistry

Estimation of nitrate nitrogen content in cotton petioles under drip irrigation based on wavelet neural network approach using spectral indices An inexpensive approach consisting of the WNN algorithm and blue edge parameters can be used to enhance the accuracy of NO<sub>3</sub><sup>-</sup>-N content estimation in cotton petioles under drip irrigation. Drip irrigation ; Nitrate ; Wavelet ; Nitrogen ; Artificial neural network ; Environmental science ; Irrigation ; Mathematics ; Agronomy ; Chemistry ; Computer science ; Artificial intelligence ; Biology Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Water Quality Monitoring and Analysis
Authors: Xiaoxia Yang | Ziyu Zhao | Zhongmin Wang | Zhedong Ge | Yucheng Zhou
Source: BioResources (article, 2021-06-07)
Field: Chemistry — Organic Chemistry

Microstructure identification based on vessel pores feature extraction of high-value hardwood species Because of the diversity of vessel pores in different hardwood species, they are important for wood species identification. In this paper, a Micro CT was used to collect wood images. The experiment was based on six wood types, Pterocarpus macrocarpus, Pterocarpus erinaceus, Dalbergia latifolia, Dalbergia frutescens var. tomentosa, Pterocarpus indicus, and Pterocarpus soyauxii. One-thousand cross-sectional images of 2042 px × 1640 px were collected for each species. One pixel represents 1.95 µm of the real physical dimension. The level set geometric active contour model was used to obtain the contour of the vessel pores. Combined with a variety of morphological processing methods, the binary images of the vessel pores were obtained. The features of the binary images were extracted for classification. Classifiers such as BP neural network and support vector machine were used, the number, roundness, area, perimeter, and other characteristic parameters of the vessel pores were classified, and the accuracy rate was more than 98.9%. The distribution and arrangement of the vessel pores of six kinds of hardwood were obtained through the level set geometric active contour model and image morphology. Then BP neural network and support vector machine were used for realizing the classification of hardwood species. Hardwood ; Artificial intelligence ; Artificial neural network ; Pattern recognition (psychology) ; Materials science ; Support vector machine ; Mathematical morphology ; Feature extraction ; Mathematics ; Computer science ; Biological system ; Image processing ; Botany ; Biology ; Image (mathematics) Wood and Agarwood Research ; Image Processing and 3D Reconstruction ; Cultural Heritage Materials Analysis
Authors: Constantinos Valagiannopoulos | Sergei Tretyakov
Source: New Journal of Physics (article, 2021-11-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Stability of active photonic metasurface pairs Abstract Adding active components to a photonic device may dramatically enrich and improve its performance but, at the same time, creates the risk of instability, namely, occurrence of unwanted self-oscillations. Stability considerations are not always given the attention they deserve when setups employing gain media are investigated; thus, the desired effects or reported regimes may not be achievable. In this work, a generic electromagnetic configuration comprising a pair of planar impedance metasurfaces is examined and analytical stability conditions for its operation are derived. The obtained results for the analyzed basic module can shed light on the stability conditions of more complex active systems that incorporate such components and serve a broad range of applications from imaging and polarization engineering to invisibility cloaking and wavefront transformations. Physics ; Cloaking ; Photonics ; Planar ; Wavefront ; Polarization (electrochemistry) ; Stability (learning theory) ; Instability ; Electrical impedance ; Invisibility ; Optics ; Metamaterial ; Computer science ; Mechanics ; Quantum mechanics Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Orbital Angular Momentum in Optics
Authors: Vincenzo Sicari | Mariarosaria Leporini | Rosa Romeo | Marco Poiana | Rosa Tundis | Monica Rosa Loizzo
Source: Foods (article, 2021-07-23)
Field: Chemistry — Organic Chemistry

Shelf-Life Evaluation of “San Marzano” Dried Tomato Slices Preserved in Extra Virgin Olive Oil Since ancient times, vegetables have been preserved in oil, to be consumed throughout the year, and not just during the period in which they were harvested. Dried tomato slices in Extra Virgin Olive Oil (EVOO) are one of the most famous Italian preserves. This is the first study which aimed to investigate the shelf-life parameters of this preserve during the 12 months of storage in both light and dark conditions. For this purpose, quality and CIELab color parameters were analysed in EVOO alone and as preserving liquid; total phenols and carotenoids content as well as β-carotene and lycopene content, a fatty acids profile, and antioxidant activities were examined. Results showed that samples stored in the dark are protected against degradative processes. Moreover, after 6 months of storage, the EVOO used as preserving liquid is enriched by the phytochemicals contained in dried tomato slices. This enrichment of EVOO by tomato bioactive compounds is reflected in the increase in the antioxidant activity of the oil independently by the presence of light during storage. Lycopene ; Carotenoid ; Olive oil ; Phenols ; Shelf life ; Food science ; Chemistry ; Antioxidant ; Botany ; Biology ; Biochemistry Edible Oils Quality and Analysis ; Phytochemicals and Antioxidant Activities ; Antioxidant Activity and Oxidative Stress
Authors: Niklas König | Yannik Carbon | Matthias Nienhaus | Emanuele Grasso
Source: Energies (article, 2021-10-15)
Field: Materials Science — Electronic, Optical and Magnetic Materials

A Self-Sensing Method for Electromagnetic Actuators with Hysteresis Compensation Self-sensing techniques are a commonly used approach for electromagnetic actuators since they allow the removal of position sensors. Thus, costs, space requirements, and system complexity of actuation systems can be reduced. A widely used parameter for self-sensing is the position-dependent incremental inductance. Nevertheless, this parameter is strongly affected by electromagnetic hysteresis, which reduces the performance of self-sensing. This work focuses on the design of a hysteresis-compensated self-sensing algorithm with low computational effort. In particular, the Integrator-Based Direct Inductance Measurement (IDIM) technique is used for the resource-efficient estimation of the incremental inductance. Since the incremental inductance exhibits a hysteresis with butterfly characteristics, it first needs to be transformed into a B-H curve-like hysteresis. Then, a modified Prandtl–Ishlinskii (MPI) approach is used for modeling this hysteretic behavior. By using a lumped magnetic circuit model, the hysteresis of the iron core can be separated from the air gap, thus allowing a hysteresis-compensated estimation of the position. Experimental studies performed on an industrial switching actuator show a significant decrease in the estimation error when the hysteresis model is considered. The chosen MPI model has a low model order and therefore allows a computationally lightweight implementation. Therefore, it is proven that the presented approach increases the accuracy of self-sensing on electromagnetic actuators with remarkable hysteresis while offering low computational effort which is an important aspect for the implementation of the technique in cost-critical applications. Hysteresis ; Control theory (sociology) ; Inductance ; Actuator ; Computer science ; Position (finance) ; Integrator ; Compensation (psychology) ; Electronic engineering ; Control engineering ; Engineering ; Physics ; Electrical engineering ; Voltage ; Control (management) ; Bandwidth (computing) Magnetic Properties and Applications ; Piezoelectric Actuators and Control ; Electric Motor Design and Analysis
Authors: Ramadan Fayez Ewaida | Nissar Rasool Wani | Yasin Khan | Abdulrahman Ali Al-Arainy
Source: Energies (article, 2021-01-08)
Field: Materials Science — Materials Chemistry

Defect Localization Inside Simulated MV Switchgear Based on Cumulative Energy Curve Using Transient Earth Voltage Sensors The partial discharge (PD) leads to catastrophic failure of the medium voltage (MV) switchgear insulation. Determination of the PD source (defect) location in high voltage (HV) equipment is very important in the maintenance procedures and in isolating the root cause of PD generation. In this paper, the transient earth voltage (TEV) detection method was used to acquire defect-initiated PD signals in a simulated MV switchgear model. An array of four TEV sensors were placed on the surface walls outside an MV switchgear tank to acquire the PD signals generated from the known location(s)/coordinates of sharp needle type defect inside the tank. The time difference of arrival (TDOA) between signals that are captured by the TEV sensors array was critically analyzed. Estimating the TDOA between PD signals generated by PD source at a known location with high accuracy is of great importance for accurate defect localization. The cumulative energy method (CEM) is used to estimate the onset time point of each TEV signal. The estimated TDOA by the cumulative energy method is compared with actual and expected TDOA based on known coordinates of PD source and TEV sensors. Experimental data are used as a basis for determining the TEV method accuracy for PD source localization. Experimental results show the average error of time difference is about 1.34 ns, which is equivalent to the propagation distance of 0.4 m. Switchgear ; Multilateration ; Voltage ; Transient (computer programming) ; Energy (signal processing) ; Partial discharge ; SIGNAL (programming language) ; Acoustics ; Electrical engineering ; Computer science ; Engineering ; Physics ; Mathematics ; Statistics High voltage insulation and dielectric phenomena ; Geophysical Methods and Applications ; Underwater Vehicles and Communication Systems
Authors: Ibukun O. Adebolu | Hirokazu Masui | Mengu Cho
Source: Shock and Vibration (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Quantitative Evaluation of SRS Similarity for Aerospace Testing Applications The similarity between a shock response spectrum (SRS) and a target shock specification is essential in evaluating the success of a qualification test of a space component. Qualification testing facilities often utilize shock response databases for rapid testing. Traditionally, the comparison of two shocks (SRS) depends on visual evaluation, which is, at best, subjective. This paper compares five different quantitative methods for evaluating shock response similarity. This work aims to find the most suitable metric for retrieving an SRS from a pyroshock database. The five methods are the SRS difference, mean acceleration difference, average SRS ratio, dimensionless SRS coefficients, and mean square goodness‐of‐fit method. None of the similarity metrics account for the sign of the deviation between the target SRS and database SRS, making it challenging to satisfy the criteria for a good shock test. We propose a metric (the weighted distance) for retrieving the most similar SRS to a target SRS specification from a shock database in this work. The weighted distance outperforms the mean square goodness‐of‐fit and other metrics in database SRS retrieval for rapid qualification testing. Aerospace ; Similarity (geometry) ; Engineering ; Computer science ; Reliability engineering ; Aerospace engineering ; Artificial intelligence High-Velocity Impact and Material Behavior ; Nuclear Physics and Applications ; Graphite, nuclear technology, radiation studies
Authors: Edy Eime ́Pereira Baraúna | Patrícia Hellenn Stallbaun | Thiago Campos Monteiro | Thiago Cardoso Silva | Talita Baldin | Fernando Colen | Marina Donária Chaves Arantes
Source: BioResources (article, 2021-10-06)
Field: Chemistry — Organic Chemistry

The effect of carbonization on the wood anatomy of Sclerolobium paniculatum Vogel Considering the extraordinary diversity of the Brazilian Cerrado and the difficulties related to the inspection of environmental crimes, knowing the wood and charcoal anatomy of widely exploited species is important. Thus, this study aimed to verify the anatomical characteristics of the wood and charcoal of Sclerolobium paniculatum. Therefore, anatomical characterizations of the wood and the charcoal produced were performed in order to compare the characteristics of both materials and observe any possible changes in the anatomical properties after carbonization. The results exposed that the qualitative anatomical characteristics of S. paniculatum wood can be maintained after the carbonization process. However, quantitatively, the carbonization increased the vessel frequency value and height and width of rays, despite reducing the frequency of rays. The diameter of the vessels was not altered by carbonization. This characterization of the species can then serve as a database for future identification of charcoal produced with this wood. In addition, it can encourage increasing the quality of inspection and consequently reducing the illegal exploitation of the species in natural environments. Carbonization ; Charcoal ; Materials science ; Pulp and paper industry ; Environmental science ; Composite material ; Scanning electron microscope ; Engineering ; Metallurgy Wood and Agarwood Research ; Agricultural and Food Sciences ; Cultural Heritage Materials Analysis