jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ali Berhil | Mahmoud Barati | Yves Bernard | Laurent Daniel
Source: Journal of Intelligent Material Systems and Structures (article, 2022-11-11)
Field: Materials Science — Materials Chemistry

Accurate sensorless displacement control based on the electrical resistance of the shape memory actuator This paper aims to implement the controllable deformation of a structure using Shape Memory Alloys (SMA) actuators. A sensorless displacement estimation method is proposed. This method is tested on a prototype composed of a disc, beams, and SMA actuators. By measuring the variation of electrical resistivity in SMA springs, as a feedback signal in the closed-loop position control, the surface displacement is obtained without any external displacement sensor. The proposed method is validated by comparing the displacement values estimated by the electrical resistivity measurement with those measured by a laser sensor. The estimated displacement and the measured displacement follow the reference displacement with steady-state errors, respectively of 1.14% and 0.42%. Displacement (psychology) ; Actuator ; SMA* ; Shape-memory alloy ; Control theory (sociology) ; Position (finance) ; Materials science ; Electrical resistivity and conductivity ; SIGNAL (programming language) ; Deformation (meteorology) ; Acoustics ; Structural engineering ; Engineering ; Computer science ; Physics ; Electrical engineering ; Composite material ; Control (management) ; Artificial intelligence Shape Memory Alloy Transformations ; Structural Engineering and Vibration Analysis ; Polymer composites and self-healing
Authors: Maura Widyaningsih | Tri Kuntoro Priyambodo | Moh Edi Wibowo | Muhammad Kamal | M Mortatha | S Thabit | H Ameer | R Nuiaa | G Tsagkatakis | A Aidini | K Fotiadou | M Giannopoulos | A Pentari | P Tsakalides | A Shah | J Bangash | A Khan | I Ahmed | U Erkan | S Enginolu | D Thanh | L Hieu | P Srestasathiern | P Rakwatin | A Mitra | S Roy | S Setua | B Desai | S Jha | U Kushwaha | M Alwazzan | M Ismael | A Ahmed | P Dai | H Sheng | J Zhang | L Li | J Wu | M Fan | Z Zou | Shi | A Pour | H Seyedarabi | S Jahromi | A Javadzadeh | G Ulutas | B Ustubioglu | M Lan | Y Zhang | L Zhang | B Du | Y Bengio | A Courville | P Vincent | T Chrisantonius | F Priyambodo | J Raswa | Wang | K Hidjah | M Wibowo | A Harjoko | R Shantiningsih | F Hana | I Maulida | A Pati | S Sagarar | P Rajvanshi | M Veluchamy | B Subramani | X Fu | J Wang | D Zeng | Y Huang | X Ding | R Sabah | R Ngadiran | D Hammood | X Wen | Z Pan | Y Hu | J Liu | C Prema | S Vinsley | S Suresh | S Sinaga | M Kamal | S Tammina | V Badrinarayanan | A Kendall | R Cipolla | Y Ho | S Wookey | D Doggalli | S Kumar | K Ting | M Madni
Source: International journal of intelligent engineering and systems (article, 2022-12-30)
Field: Chemistry — Analytical Chemistry

Optimization Contrast Enhancement and Noise Reduction for Semantic Segmentation of Oil Palm Aerial Imagery Contrast improvement and noise reduction are needed to improve aerial images prone to interference during data collection. Contrast limited adaptive histogram equalization (CLAHE) is a histogram equalization (HE) development method that is commonly used for contrast improvement. Median blur (MB) is one of the methods used for noise reduction. Combining these two techniques helps optimize the preprocessing process before semantic segmentation analysis is carried out in image maps. The results of testing experiments with U-Net VGG-16 and VGG-19 on image maps show a detailed representation of the predicted pixel class. Comparing accuracy with state-of-theart methods shows that contrast enhancement and noise reduction are better than the previous method. The highest average result for combining CLAHE+MB with U-Net VGG-16 was 76.5 and VGG-19 was 73.8, and the highest accuracy for image sample testing was 87.94 with U-net VGG-16. Computer science ; Contrast (vision) ; Palm oil ; Segmentation ; Noise reduction ; Artificial intelligence ; Noise (video) ; Contrast enhancement ; Reduction (mathematics) ; Palm ; Computer vision ; Image (mathematics) ; Environmental science ; Mathematics ; Agroforestry Spectroscopy and Chemometric Analyses ; Industrial Vision Systems and Defect Detection ; Vehicle License Plate Recognition
Authors: Junyun Deng | Wenbo Wang | P. Venugopal | Jelena Popović | Gert Rietveld
Source: 2022 IEEE Energy Conversion Congress and Exposition (ECCE) (article, 2022-10-09)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Knowledge-aware Artificial Neural Network for Loss Modeling of Planar Magnetic Components Artificial neural network (ANN) has emerged as a promising tool for component modeling in power electronics due to its high accuracy and flexibility. However, the availability of large training data is an essential requirement for reliable predictions given by ANN, which is often hard to satisfy in power electronics applications. Therefore, this paper proposes a novel loss modeling approach based on knowledge-aware ANN for planar magnetic components, which is implemented by com-bining small training data with specific domain knowledge. After investigating the principles of ANN, theoretical explanations of knowledge-aware ANN are illustrated and several cases are performed, both of which validate the generalization of the proposed method. Compared with existing modeling tools, the results show that the proposed method realizes an excellent balance between accuracy and computational efficiency. Flexibility (engineering) ; Computer science ; Artificial neural network ; Generalization ; Artificial intelligence ; Domain knowledge ; Component (thermodynamics) ; Power electronics ; Domain (mathematical analysis) ; Electronics ; Data modeling ; Machine learning ; Engineering ; Voltage ; Electrical engineering ; Software engineering Magnetic Properties and Applications ; Electric Motor Design and Analysis ; Induction Heating and Inverter Technology
Authors: Jiaqian Chen | Yan‐Yan Chen | Xia Du | Hui‐Juan Tao | Zong‐Jin Pu | Xu-Qin Shi | Shi‐Jun Yue | Guisheng Zhou | Erxin Shang | Yuping Tang | Jin‐Ao Duan
Source: Chinese Medicine (article, 2022-04-26)
Field: Chemistry — Analytical Chemistry

Fuzzy identification of bioactive components for different efficacies of rhubarb by the back propagation neural network association analysis of UPLC-Q-TOF/MSE and integrated effects Our findings demonstrated that the bioactive components for different efficacies of rhubarb were not exactly the same and can be systematically differentiated by the network-oriented strategy. These efforts will advance our knowledge and understanding of the bioactive components in rhubarb and provide scientific evidence to support the expansion of its use in clinical applications and the further development of some products based on this medicinal herb. Anthraquinones ; Gallic acid ; Radix (gastropod) ; Kaempferol ; High-performance liquid chromatography ; Chemistry ; Chromatography ; Traditional medicine ; Biology ; Quercetin ; Medicine ; Biochemistry ; Botany Chromatography in Natural Products ; Phytochemistry and biological activity of medicinal plants ; Traditional Chinese Medicine Analysis
Authors: Bassey Okon Samuel | Malachy Sumaila | Bashar Dan-asabe
Source: Jurnal Mekanikal (article, 2022-06-22)
Field: Materials Science — Polymers and Plastics

CELLULOSIC FIBER REINFORCED HYBRID COMPOSITE (PxGyEz) OPTIMIZATION FOR LOW WATER ABSORPTION USING THE ROBUST TAGUCHI OPTIMIZATION TECHNIQUE The manufacturing process of a material is a strong determinant of its performance in service. Different applications like ships, wind turbine blades, oil rigs, etc demand materials with low water absorption due to their operational environment. Previous studies have reported the water absorption behavior of cellulosic fiber-reinforced composites but the optimization of the water absorption properties of pineapple leaf/glass fiber hybrid reinforced epoxy composites by optimizing its manufacturing parameters have not been studied even with its possible wide range of application. This paper presents the optimization of the water absorption properties of a material PxGyEz (with x, y, and z representing the volume fraction of pineapple leaf fiber (PALF) (P), the volume fraction of glass fiber (G), and fiber length respectively in an epoxy matrix) using the Taguchi robust optimization technique and statistical analysis. The material at x=15%, y=15%, and z=20mm which is, P15G15E20 was the optimum having the lowest water absorption of 0.2667%. A notable observation was that fiber length had a significant contribution to the water absorption properties of the material. The interaction effect of fiber length with the cellulosic fiber and the glass fiber at mean values was found to be 49.37% and 14.24% respectively. SEM and FTIR analysis showed microstructural and chemical formations that explained the water absorption behavior of the optimized hybrid composite. The water absorption property of the material was modeled and the equations proved to be 95.6% accurate in predicting the water absorption of the material at different combinations. Materials science ; Absorption of water ; Taguchi methods ; Fiber ; Composite material ; Volume fraction ; Absorption (acoustics) ; Epoxy ; Glass fiber ; Composite number ; Cellulose fiber Natural Fiber Reinforced Composites ; Electrospun Nanofibers in Biomedical Applications ; Mechanical Engineering and Vibrations Research
Authors: Arindam Dasgupta | Xiaodong Yang | Jie Gao
Source: Scientific Reports (article, 2022-06-15)
Field: Materials Science — Materials Chemistry

Natural 2D layered mineral cannizzarite with anisotropic optical responses Cannizzarite is a naturally occurring mineral formed by van der Waals (vdW) stacking of alternating layers of PbS-like and Bi<sub>2</sub>S<sub>3</sub>-like two-dimensional (2D) materials. Although the PbS-type and Bi<sub>2</sub>S<sub>3</sub>-type 2D material layers are structurally isotropic individually, the forced commensuration between these two types of layers while forming the heterostructure of cannizzarite induces strong structural anisotropy. Here we demonstrate the mechanical exfoliation of natural cannizzarite mineral to obtain thin vdW heterostructures of PbS-type and Bi<sub>2</sub>S<sub>3</sub>-type atomic layers. The structural anisotropy induced anisotropic optical properties of thin cannizzarite flakes are explored through angle-resolved polarized Raman scattering, linear dichroism, and polarization-dependent anisotropic third-harmonic generation. Our study establishes cannizzarite as a new natural vdW heterostructure-based 2D material with highly anisotropic optical properties for realizing polarization-sensitive linear and nonlinear photonic devices for future on-chip optical computing and optical information processing. Anisotropy ; Materials science ; Isotropy ; Heterojunction ; Stacking ; Polarization (electrochemistry) ; van der Waals force ; Raman spectroscopy ; Birefringence ; Optoelectronics ; Linear dichroism ; Photonics ; Condensed matter physics ; Optics ; Circular dichroism ; Chemistry ; Crystallography ; Physics ; Nuclear magnetic resonance 2D Materials and Applications ; Perovskite Materials and Applications ; Quantum Dots Synthesis And Properties
Authors: AISWARIYA | B. V. Suma | MEDICHARLA SRI SATYA
Source: International Journal of Current Pharmaceutical Research (article, 2022-07-15)
Field: Chemistry — Organic Chemistry

MOLECULAR DOCKING AND ADMET STUDIES OF BENZOTRIAZOLE DERIVATIVES TETHERED WITH ISONIAZID FOR ANTIFUNGAL ACTIVITY Objective: The incidence of fungal infections is increasing at an alarming rate, presenting an enoromous challenge to health care professionals. This increase is directly related to the growing population of the immunocompromised individuals, resulting from changes in the medical practice such as the use of intensive chemotherapy and immunosuppressive drugs. The ability of many fungi to form biofilms is one of the reasons for the antifungal resistance caused and hence there is an urgent need in the synthesis of new and safer anti-microbial agnets. Benzotriazole is an organic heterocyclic compound with 2 nitrogen atoms in the ring having wide range of biological properties like anti-tubercular, anticancer and anti-microbial etc. isoniazid is the first line drug used to treat tuberculosis. Tethering benzotriazole with isoniazid has shown development of newer compounds that may exhibit better activity on inhibiting the fungal growth and replication and hence has shown a positive effect on the anti-fungal activity. Methods: Affinity between the protein and ligand was found out using rigid docking technique.3D structure of the fungal protein was downloaded from protein data base. The selected ligand molecules are generated using Chem Draw. ADMET studies for the molecules are determined using SWISS-ADMET website. Rigid docking is employed to find the binding affinities between ligand and protein. Results: 4 derivatives of benzotriazole tethered with isoniazid were selected and docking studies were carried out for these compounds with the antifungal protein,14 alfa-demethylase with PDB I. D; 5V5Z,using molecular docking tool PyRx and docking scores were-8.3,-7.6,-9.2,-7.4 respectively when compared with the standard compound Fluconazole (-8.0). ADMET studies of the 4 compounds have shown zero violation to lipinski’s rule. Conclusion: In summary, benzotriazole derivatives tethered with isoniazid exhibits promising results based on in silico studies. ADMET studies showed that the compounds drug likeness parameters are according to lipinski’s rule of five. Docking (animal) ; Benzotriazole ; Chemistry ; Protein Data Bank (RCSB PDB) ; Stereochemistry ; Isoniazid ; Ligand (biochemistry) ; Combinatorial chemistry ; Antifungal ; Active site ; Pharmacology ; Enzyme ; Biochemistry ; Tuberculosis ; Organic chemistry ; Microbiology ; Biology ; Medicine ; Receptor Synthesis and biological activity ; Computational Drug Discovery Methods ; Enzyme function and inhibition
Authors: American Welding Society | KRISHNA SAMPATH
Source: Welding Journal (article, 2022-05-01)
Field: Materials Science — Materials Chemistry

Metallurgical Design Rules for High-Strength Steel Weld Metals A review of a dilatometric analysis of selected Fe-C-Mn high-strength steel shielded metal arc weld metals showed that balanced Ti, B, Al, O, and N additions reduced the austenite-to-ferrite transformation-start (TS) temperature. These microalloy additions must match the following aim levels for composition control: Ti at 400 ppm (0.04 wt-%), B at 40 ppm (0.004 wt-%), Al at 200 ppm (0.020 wt-%), O at 400 ppm (0.04 wt-%), and N preferably below 80 ppm (0.008 wt-%) to ensure effective deoxidation, form complex inclusions, and distribute them to enable development of highly fracture-resistant refined weld metal microstructures. It may be wiser to avoid the rich and lean ends for these microalloy additions, except N, which should be held at the lean end, preferably much below 80 ppm (0.008 wt-%). The balanced Ti, B, Al, O, and N additions offered nearly a 100°C shift in lowering the Charpy V-notch (CVN) test temperature for either 28 or 100 J absorbed energy. Dilatometric evaluations of reheated weld metals showed that 1) the balanced Ti, B, Al, O, and N additions lowered the actual TS temperature by about 60°C compared to the calculated austenite-to-ferrite transformation temperature obtained from the constitutional equation; 2) N with more than 100 ppm (0.010 wt-%) effectively nullified the beneficial effects of Ti, B, and Al additions in lowering the transformation temperature; and 3) at N content much below 80 ppm (0.008 wt-%), both a lower TS temperature and a narrow start-to-finish (TS–Tf) temperature range helped in achieving exceptional weld metal CVN impact toughness. Charpy impact test ; Metallurgy ; Austenite ; Materials science ; Welding ; Ferrite (magnet) ; Microstructure ; Acicular ferrite ; Metal ; Bainite ; Composite material Metal Alloys Wear and Properties ; Welding Techniques and Residual Stresses ; Microstructure and Mechanical Properties of Steels
Authors: P. Arunachalam | N. Janakiraman | Junaid Rashid | Jungeun Kim | Sovan Samanta | Usman Naseem | Arun Kumar Sivaraman | A. Balasundaram
Source: Computers, materials & continua/Computers, materials & continua (Print) (article, 2022-01-01)
Field: Chemistry — Analytical Chemistry

Effective Classification of Synovial Sarcoma Cancer Using Structure Features and Support Vectors In this research work, we proposed a medical image analysis framework with two separate releases whether or not Synovial Sarcoma (SS) is the cell structure for cancer. Within this framework the histopathology images are decomposed into a third-level sub-band using a two-dimensional Discrete Wavelet Transform. Subsequently, the structure features (SFs) such as Principal Components Analysis (PCA), Independent Components Analysis (ICA) and Linear Discriminant Analysis (LDA) were extracted from this sub-band image representation with the distribution of wavelet coefficients. These SFs are used as inputs of the Support Vector Machine (SVM) classifier. Also, classification of PCA + SVM, ICA + SVM, and LDA + SVM with Radial Basis Function (RBF) kernel the efficiency of the process is differentiated and compared with the best classification results. Furthermore, data collected on the internet from various histopathological centres via the Internet of Things (IoT) are stored and shared on blockchain technology across a wide range of image distribution across secure data IoT devices. Due to this, the minimum and maximum values of the kernel parameter are adjusted and updated periodically for the purpose of industrial application in device calibration. Consequently, these resolutions are presented with an excellent example of a technique for training and testing the cancer cell structure prognosis methods in spindle shaped cell (SSC) histopathological imaging databases. The performance characteristics of cross-validation are evaluated with the help of the receiver operating characteristics (ROC) curve, and significant differences in classification performance between the techniques are analyzed. The combination of LDA + SVM technique has been proven to be essential for intelligent SS cancer detection in the future, and it offers excellent classification accuracy, sensitivity, specificity. Linear discriminant analysis ; Support vector machine ; Artificial intelligence ; Pattern recognition (psychology) ; Computer science ; Receiver operating characteristic ; Principal component analysis ; Kernel (algebra) ; Wavelet ; Mathematics ; Data mining ; Machine learning Spectroscopy and Chemometric Analyses ; AI in cancer detection ; Smart Agriculture and AI
Authors: Bruno Zêzere | Inês Portugal | José R. B. Gomes | Carlos M. Silva
Source: Materials (article, 2022-09-15)
Field: Chemistry — Spectroscopy

Modeling Tracer Diffusion Coefficients of Any Type of Solutes in Polar and Non-Polar Dense Solvents In this work, a simple two-parameters correlation based on the Rice and Gray, Lennard-Jones, and Stockmayer theories was devised for the calculation of binary diffusion coefficients (D12) of any type of solutes at infinite dilution in polar and non-polar solvents. This equation can be relevant for systems with polar solvents, since most models in the literature fail when strong intermolecular forces predominate in solution. The new correlation embodies the Stockmayer potential without requiring the dipole moments of any component, which significantly enlarges its application. It was validated with the largest D12 database of polar and non-polar dense systems, with 8812 data points (NDP) spanning 553 systems, of which 133 have water as solvent (NDP = 1266), 89 contain polar solvents excluding water (NDP = 1405), 177 have supercritical carbon dioxide (SC-CO2) as solvent (NDP = 5028), and 154 have non-polar or weakly polar solvents excluding SC-CO2 (NDP = 1113). Overall, the model achieved an average deviation of only 3.43%, with accurate and unbiased behavior even for polar systems. Polar ; Chemical polarity ; Solvent ; Chemistry ; Thermodynamics ; Dipole ; Dilution ; Supercritical fluid ; Intermolecular force ; Diffusion ; Molecule ; Organic chemistry ; Physics Diffusion Coefficients in Liquids ; Phase Equilibria and Thermodynamics ; Thermodynamic properties of mixtures
Authors: Jian Song | Changbin Yu
Source: Bioinformatics (article, 2022-01-03)
Field: Chemistry — Spectroscopy

Alpha-Tri: a deep neural network for scoring the similarity between predicted and measured spectra improves peptide identification of DIA data The original datasets for benchmarks are downloaded from the ProteomeXchange with the identifiers PXD005573, PXD000954 and PXD002952. Source code is available at https://github.com/YuAirLab/Alpha-Tri. Similarity (geometry) ; Fragment (logic) ; Pattern recognition (psychology) ; Ion ; Spectral line ; Artificial neural network ; Matching (statistics) ; Identification (biology) ; Artificial intelligence ; Spectrum (functional analysis) ; Physics ; Intensity (physics) ; Chemistry ; Computer science ; Mathematics ; Algorithm ; Statistics ; Biology ; Optics Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Identification and Quantification in Food
Authors: Xueting Ma | Huaping Luo | Jiean Liao | Li‐Xia Zhu | Jinfei ZHAO | Feng GAO
Source: Food Science and Technology (article, 2022-11-04)
Field: Chemistry — Analytical Chemistry

Study on the detection of apple soluble solids based on fractal theory and hyperspectral imaging technology To explore a new method for the detection of soluble solids content (SSC) in apples, the reflectance spectra of apples with different SSC were obtained based on hyperspectral imaging technology in this paper, and fractal measurement of the reflection spectrum curve was carried out based on fractal theory, for using fractal dimension to quantitatively reflect its SSC. The results show that the samples with different SSC have little difference in fractal dimension, and are not sensitive to the change of apple SSC, which cannot show an obvious linear relationship. It can be considered to conduct a study on discrimination with obvious differences between spectral curves, such as variety discrimination and damage discrimination. Hyperspectral imaging ; Fractal ; Fractal dimension ; Dimension (graph theory) ; Mathematics ; Artificial intelligence ; Spectrum (functional analysis) ; Fractal analysis ; Reflection (computer programming) ; Biological system ; Optics ; Remote sensing ; Pattern recognition (psychology) ; Computer science ; Physics ; Mathematical analysis ; Biology ; Geology ; Pure mathematics Spectroscopy and Chemometric Analyses ; Remote Sensing and Land Use ; Remote Sensing in Agriculture