jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Yang Chen | Shilei Li | Jianhua Huang | Teng Hu | Xiaohu Li | Chentao Li | Guang Xian | Changchun Zhou | Hongyuan Fan
Source: REVIEWS ON ADVANCED MATERIALS SCIENCE (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Research on key casting process of high-grade CNC machine tool bed nodular cast iron Abstract The bed structure of high-grade large-scale CNC machine tools is crucial for maintaining their long-term service accuracy. This study focused on the key casting process of large nodular cast iron beds. AnyCasting software was employed to simulate and analyze the casting scheme, and then the mold filling and solidification processes were proposed based on the simulation results. The proposed casting scheme indicates that the designed gating system exhibited excellent filling capability. The dual sprue ceramic pipe bottom pouring technique, in conjunction with the chills, not only improved casting efficiency but also met the requirements of sequential solidification design. The castings possessed a dense microstructure characterized by uniform and stable phase composition, primarily comprising lamellar pearlite, with ≤0.5% of phosphorus eutectic and cementite. Furthermore, the microstructure of these materials displayed favorable graphite morphology with a spheroidization rate exceeding 85% and spheroidization grade of 2–3. This study has important academic and application value for the casting process of producing low-stress, high-grade CNC machine tool bed cast iron materials. Materials science ; Cast iron ; Microstructure ; Casting ; Eutectic system ; Pearlite ; Centrifugal casting (silversmithing) ; Metallurgy ; Machinability ; Cementite ; Graphite ; Sand casting ; Process (computing) ; Austenite ; Mold ; Composite material ; Computer science ; Machining Metal Alloys Wear and Properties ; Aluminum Alloys Composites Properties ; Aluminum Alloy Microstructure Properties
Authors: Zhedong Ge | Ziheng Zhang | Liming Shi | Shuai Liu | Yisheng Gao | Yucheng Zhou | Qiang Sun
Source: Electronics (article, 2023-07-09)
Field: Chemistry — Organic Chemistry

An Algorithm Based on DAF-Net++ Model for Wood Annual Rings Segmentation The semantic segmentation of annual rings is a research topic of interest in wood chronology. To solve the problem of wood annual rings being difficult to segment in dense areas and being greatly affected by defects such as cracks and wormholes, this paper builds a DAF-Net++ model which is based on U-Net whose backbone network is VGG16 and filled with dense jump links, CBAM and DCAM. In this model, VGG16 is used to enhance the extraction ability of image features, dense jump links are used to fuse semantic information of different levels, DCAM provides weighting guidance for shallow features, and CBAM solves the loss of down-sampling information. Taking a Chinese fir wood as the experimental object, 1700 CT images of wood transverse section were obtained by medical CT equipment and 120 of them were randomly selected as the dataset, which was expanded by cropping and rotation, among others. DAF-Net++ was used for training the model and segmentation of the annual rings, and finally the performance of the model was evaluated. The training method is freeze training followed by thaw training, and takes Focal Loss as the loss function, ReLU as the activation function, and Adam as the optimizer. The experimental results show that, in the segmentation of CT images of Chinese fir annual rings, the MIoU of DAF-Net++ is 93.67%, the MPA is 96.76%, the PA is 96.63%, and the Recall is 96.76%. Compared with other semantic segmentation models such as U-Net, U-Net++, DeepLabv3+, etc., DAF-Net++ has better segmentation performance. Segmentation ; Algorithm ; Net (polyhedron) ; Jump ; Artificial intelligence ; Computer science ; Weighting ; Image segmentation ; Pattern recognition (psychology) ; Mathematics ; Geometry ; Physics Wood and Agarwood Research ; Remote Sensing and LiDAR Applications ; Industrial Vision Systems and Defect Detection
Authors: Yiping Zhao | Andrei Galiautdinov | Jingzhi Tie
Source: Preprints.org (preprint, 2023-12-27)
Field: Materials Science — Electronic, Optical and Magnetic Materials

The N-Oscillator Born-Kuhn Model: An In-depth Analysis of Chiro-optical Properties in Complex Chiral Systems A comprehensive theory is developed for the chiral optical response of two configurations of the N-oscillator Born-Kuhn model (NOBK): the helically stacked and the corner stacked models. In the helical NOBK model, there is always a chiral response regardless of the value of N, whereas in the corner NOBK, only configurations with even N demonstrate a chiral response. Generally, the magnitudes of optical rotatory dispersion (ORD) and circular dichroism (CD) increase with N when the parameters of each oscillator are fixed. In cases of weak coupling, the spectral shapes of ORD and CD remain invariant, while strong coupling significantly alters the spectral shapes. For large damping, the spectral amplitude becomes smaller, and the spectral features become broader. In the presence of small damping, strong coupling introduces degeneracy in the coupled oscillator system, leading to multiple spectral features in both ORD and CD across the entire spectral region. This simple model not only can help in the design of tunable chiral metamaterials but also enhance our understanding of chiro-optical responses in structures with different configurations. Circular dichroism ; Physics ; Coupling (piping) ; Invariant (physics) ; Amplitude ; Metamaterial ; Quantum mechanics ; Molecular physics ; Materials science ; Crystallography ; Chemistry Metamaterials and Metasurfaces Applications ; Liquid Crystal Research Advancements ; Molecular spectroscopy and chirality
Authors: Zdravka Ivanova
Source: Biomath Communications (article, 2023-02-10)
Field: Chemistry — Physical and Theoretical Chemistry

Multiphysics Simulations of the Process of Neuromuscular Activation In this Master's thesis, we consider the problem of mathematical modelling and computer simulations of neuromuscular activation. We describe the biological and biochemical processes that result in a muscle contraction. For each of them, we derive a mathematical model, established in the literature. In particular, we consider: the Hodgkin-Huxley model of neural transmission; a reaction-diffusion model for the process of neurotransmitter release in the synaptic gap between a nerve and a muscle cell; an ODE system, based on chemical reaction schemes, proposed by Williams, for the process of calcium dynamics inside the muscle cell; Hill’s model for the generation of muscle force, triggered by calcium dynamics. We study the models numerically to illustrate the behaviour of the model solutions and to interpret them from a biological point of view. For the model of calcium dynamics, we also make qualitative analysis and obtain original results for the asymptotic behaviour of the model solutions. Further, we propose a framework for coupling the models, mentioned above, so that we can obtain new integrated multiphysics simulations of the whole process. Our initial motivation for the study is the future application of the proposed approach for modelling neuromuscular diseases. Therefore, the framework we propose is based on the idea of modelling micro-scale processes and studying their effect on the macro-scale muscle action. Multiphysics ; Computer science ; Process (computing) ; Scale (ratio) ; Mathematical model ; Coupling (piping) ; Biological system ; Mathematics ; Physics ; Finite element method ; Engineering ; Mechanical engineering thermodynamics and calorimetric analyses
Authors: Karunesh K. Shukla | Rahul Nigam | Ajanta Birah | A. K. Kanojia | Anoop Kumar | Bimal K. Bhattacharya | Subhash Chander
Source: Remote Sensing (article, 2023-12-21)
Field: Chemistry — Analytical Chemistry

Detection of Aphid-Infested Mustard Crop Using Ground Spectroscopy Timely detection of pest infestation in agricultural crops plays a pivotal role in the planning and execution of pest management interventions. In this study, a ground measured electromagnetic spectrum through hyperspectral sensing (400–2500 nm) was conducted in healthy and aphid-infested mustard crops in different regions of the Bharatpur district of Rajasthan state, India. The ground measured hyperspectral reflectance and its derivatives during the mustard aphid infestation period were used to identify the sensitive spectral regions in the electromagnetic spectrum concerning Aphid Infestation Severity Grade (AISG) to discriminate Lipaphis-infested mustard crops from the healthy ones. Further Principal Component Analysis (PCA) and Partial Least Square Regression (PLSR) were utilized to identify specific spectral bands to differentiate the healthy from aphid-infested crops. The spectral regions of 493–497 nm (blue), 509–515 nm (green), 690–714 nm (red), 717–721 nm (red edge), and 752–756 nm (NIR) showed high correlation with AISG for reflectance, first and second order derivatives. Further analysis of the spectra using PCA and PLSR indicated that spectral bands of 679 nm, 746 nm, and 979 nm had high sensitivity for discriminating aphid-infested crops from the healthy ones. Average reflectance and various spectral indices such as ratio spectral index (RSI), difference spectral index (DSI), and normalized difference spectral index (NDSI) of identified spectral regions and absolute reflectance of identified specific spectral bands were used for predicting AISG. Several regression models, including PCR and PLSR, were examined to predict the AISG. PLSR was found to better predict infestation grade with RMSE of 0.66 and r2 0.71. Our outcomes counseled that hyperspectral reflectance data have the ability to detect aphid-infested severity in mustard. Infestation ; Aphid ; Hyperspectral imaging ; Environmental science ; VNIR ; Partial least squares regression ; Principal component analysis ; Spectral bands ; Crop ; Remote sensing ; Veterinary medicine ; Agronomy ; Mathematics ; Biology ; Statistics ; Medicine ; Geography Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Essential Oils and Antimicrobial Activity
Authors: Emilio Castillo-Ibarra | Marco A. Alsina | César A. Astudillo | Ignacio Fuenzalida-Henríquez
Source: Mathematics (article, 2023-10-03)
Field: Chemistry — Analytical Chemistry

PFA-Nipals: An Unsupervised Principal Feature Selection Based on Nonlinear Estimation by Iterative Partial Least Squares Unsupervised feature selection (UFS) has received great interest in various areas of research that require dimensionality reduction, including machine learning, data mining, and statistical analysis. However, UFS algorithms are known to perform poorly on datasets with missing data, exhibiting a significant computational load and learning bias. In this work, we propose a novel and robust UFS method, designated PFA-Nipals, that works with missing data without the need for deletion or imputation. This is achieved by considering an iterative nonlinear estimation of principal components by partial least squares, while the relevant features are selected through minibatch K-means clustering. The proposed method is successfully applied to select the relevant features of a robust health dataset with missing data, outperforming other UFS methods in terms of computational load and learning bias. Furthermore, the proposed method is capable of finding a consistent set of relevant features without biasing the explained variability, even under increasing missing data. Finally, it is expected that the proposed method could be used in several areas, such as machine learning and big data with applications in different areas of the medical and engineering sciences. Imputation (statistics) ; Missing data ; Computer science ; Dimensionality reduction ; Cluster analysis ; Artificial intelligence ; Unsupervised learning ; Feature selection ; Data mining ; Machine learning ; Curse of dimensionality ; Data set ; Nonlinear system ; Pattern recognition (psychology) Spectroscopy and Chemometric Analyses ; Face and Expression Recognition ; Gene expression and cancer classification
Authors: Karunesh K. Shukla | Ajanta Birah | Rahul Nigam | A. K. Kanojia | M. K. Khokhar | Bimal K. Bhattacharya | Subhash Chander
Source: Journal of Agrometeorology (article, 2023-05-25)
Field: Chemistry — Analytical Chemistry

Selection of sensitive bands for assessing Alernaria blight diseased severity grades in mustard crops using hyperspectral reflectance Recent development in remote sensing technology using hyperspectral reflectance or spectroscopic data was enabled the rapid and ongoing progression of monitoring, mapping, and surveillance/detection of insects tools for better crop management. This study describes a spectroscopic based methodology to escalation the efficiency of present surveillance practices (insect traps and human examinations) for detection pest infestation (e.g., Alternaria blight in mustard crop). The methodology uses ground based hyperspectral data across the spectral bands 350-2500nm at 1 nm interval. Three different statistical procedures such as correlation (between reflectance, 1st and 2nd derivatives with diseased severity grades), continuum removal analysis was implemented for selection of sensitive bands. In this method, we explore the combinations of different selected sensitive spectral bands and regions to separate diseased crops. The objectives of this research is to develop a novel methodology for selection of sensitive bands to Alternaria blight diseased crops. The development of such methodology would provide researchers, Agronomist, and remote sensing practitioners reliable and stable method to achieve faster technique with higher accuracy to mapping of Alternaria blight diseased crops. Hyperspectral imaging ; Blight ; Multispectral image ; Alternaria ; Reflectivity ; Remote sensing ; Selection (genetic algorithm) ; Crop ; Environmental science ; Agronomy ; Computer science ; Biology ; Botany ; Artificial intelligence ; Geography Spectroscopy and Chemometric Analyses ; Fungal Plant Pathogen Control ; Insect Pest Control Strategies
Authors: Aris Munandar | Sri Mulyati | H Hasanuddin | Zulfahrizal Zulfahrizal
Source: International Journal of Design & Nature and Ecodynamics (article, 2023-10-31)
Field: Chemistry — Analytical Chemistry

Estimating Gurjun Oil Adulteration in Aceh Patchouli Oil Using NIRS and Multivariate Analysis Indonesia, a leading supplier of patchouli oil globally, produces a significant proportion of this high-value commodity in Aceh.Given the high economic value of patchouli oil, adulteration practices with less expensive oils, such as palm, gurjun, and turpentine oil, are commonplace.These adulterations not only degrade the quality of the oil but also pose potential safety risks, health hazards, and non-compliance with natural attributes.Among the adulterants, gurjun oil is frequently used due to its blendability and similarity in color and aroma to patchouli oil.This study was designed to develop a quantification model to estimate the gurjun oil content adulterating Aceh patchouli oil.The model employed near-infrared reflectance spectroscopy (NIRS) technology in combination with multivariate analysis methods, specifically principal component regression (PCR) and partial least squares (PLS) regression.To enhance the accuracy level of the NIRS calibration model, mean normalization (MN) and de-trending (DT) spectrum pretreatments were applied.The findings indicate that the application of NIRS technology coupled with multivariate analysis can effectively address the issue of gurjun oil adulteration in patchouli oil.Moreover, the PLS calibration method was shown to outperform PCR.The residual predictive deviation (RPD) index for the PLS model was found to be 2.34, compared to 1.85 for the PCR model.Spectrum pretreatments successfully enhanced the performance of the model, with calibration RPD indices for the PLS-MN and PLS-DT models registering at 2.98 and 2.59, respectively.In general, both models were deemed viable for application as the PLS-MN and PLS-DT models, after validation, yielded range to error ratio (RER) values of 3.39 and 3.60, respectively.Thus, this study underscores the potential of employing NIRS technology and multivariate analysis to combat the prevalent issue of patchouli oil adulteration. Patchouli ; Multivariate statistics ; Multivariate analysis ; Environmental science ; Mathematics ; Statistics ; Food science ; Biology ; Essential oil Spectroscopy and Chemometric Analyses ; Natural product bioactivities and synthesis
Authors: Ozan Çiftçi | Niels Wagemaker | Adrienne Mertens | Peter M. van Bodegom | Walter Pirovano | Barbara Gravendeel
Source: BMC Ecology and Evolution (article, 2023-02-06)
Field: Materials Science — Biomaterials

Genotyping by sequencing for estimating relative abundances of diatom taxa in mock communities Our results suggest that GBS is a reliable method to estimate the relative abundances of the N. palea taxa analyzed in this study and outperformed traditional light microscopy in terms of accuracy. GBS provides increased taxonomic resolution compared to currently available quantitative molecular approaches, and it is more scalable in the number of species that can be analyzed in a single run. Hence, this is a significant step forward in developing automated, high-throughput molecular methods specifically designed for the quantification of [diatom] communities for freshwater quality assessments. Diatom ; Relative species abundance ; Taxon ; Biology ; Abundance (ecology) ; Bioindicator ; Ecology Diatoms and Algae Research ; Environmental DNA in Biodiversity Studies ; Microbial Community Ecology and Physiology
Authors: Yuki Hata | Yaoshu Xie | Kiyou Shibata | Teruyasu Mizoguchi
Source: Journal of the Ceramic Society of Japan (article, 2023-09-30)
Field: Materials Science — Materials Chemistry

A guideline for searching for stable grain boundary structure by utilizing crystallographic information: A method based on non-identical termination Determining the stable atomic structure of grain boundaries (GBs) is one of the most important tasks for computational materials science to comprehensively understand the structure-property relationship of GBs in real polycrystalline materials. In this paper, we revisit a proposed method (PM) that was thought to be ineffective in determining the stable GB structures based on sampling non-identical terminating crystal planes of the two adjoining crystals forming the GB. In contrast to the previous conclusion, we found that the PM is effective regarding both the reproducibility of stable structures and calculation cost. This method could determine the most stable GB structures and energies of not only elemental materials of face-centered-cubic and body-centered-cubic metals, including Cu and Mo, but also a binary ceramic material, MgO. We show that the PM can greatly reduce the number of necessary candidate structures calculated to determine the stable GB structures compared with other brute-force methods sampling the rigid body translation between the two adjoining crystals. We demonstrated that sampling GB structures made of non-identical termination combinations is a useful and effective method to determine the stable GB structures of various materials. Crystallite ; Materials science ; Grain boundary ; Crystal structure ; Translation (biology) ; Binary number ; Sampling (signal processing) ; Cubic crystal system ; Caesium ; Ceramic ; Crystallography ; Optics ; Mathematics ; Physics ; Composite material ; Chemistry ; Metallurgy ; Microstructure ; Inorganic chemistry ; Detector Microstructure and mechanical properties ; Metal and Thin Film Mechanics ; Magnesium Alloys: Properties and Applications
Authors: Yordan Kyosev
Source: Materials research proceedings (article, 2023-04-13)
Field: Materials Science — Polymers and Plastics

Forming of textile fabrics with additively assembled protective elements on the human body Abstract. Stab protective clothing is used in a wide range of applications, including military and police applications, but is also becoming increasingly important for civilian users. A relatively new way of manufacturing personal protective equipment is additive manufacturing. This makes it possible to produce new types of stab protection geometries by applying polymer layers to textiles. Such composite structures represent a mechanical system of rigid bodies with constraints, especially with large continuous protective surfaces. As a result, the wearing comfort is limited. This paper presents two methods for numerically simulating the forming of reinforced textiles with solid polymer elements over the body as part of the development and optimization process of such garments. Clothing ; Textile ; Stab ; Process (computing) ; Computer science ; Mechanical engineering ; Manufacturing engineering ; Materials science ; Engineering drawing ; Composite material ; Engineering Textile materials and evaluations ; Advanced Theoretical and Applied Studies in Material Sciences and Geometry ; Structural Analysis and Optimization
Authors: M.K. Karazhanova | L.B. Zhetekova | S. V. Abbasova | K. K. Aghayeva | G. Sabyrbaeva
Source: NEWS of National Academy of Sciences of the Republic of Kazakhstan (article, 2023-02-18)
Field: Chemistry — Analytical Chemistry

STUDY OF INTERRELATIONS BETWEEN COMPOSITION AND PROPERTIES OF HIGH-VISCOUS OIL , , , , , Composition (language) ; Chemistry ; Petroleum engineering ; Materials science ; Environmental science ; Geology ; Art ; Literature Petroleum Processing and Analysis ; Coal and Coke Industries Research ; Engineering Diagnostics and Reliability
Authors: Katerina Danko | Л. Г. Данилов | Anna Malashicheva | Arseniy Lobov
Source: Biological Communications (article, 2023-05-02)
Field: Chemistry — Spectroscopy

Comparative analysis of methods for batch correction in proteomics — a two-batch case A proper study design is vital for life science. Any effects unrelated to the studied ones (batch effects) should be avoided. Still, it is not always possible to exclude all batch effects in a complicated omics study. Here we discuss an appropriate way for analysis of proteomics data with an enormous technical batch effect. We re-analyzed the published dataset (PXD032212) with two batches of samples analyzed in two different years. Each batch includes control and differentiated cells. Control and differentiated cells form separate clusters with 209 differentially expressed proteins (DEPs). Nevertheless, the differences between the batches were higher than between the cell types. Therefore, the analysis of only one of the batches gives 276 or 290 DEPs. Then we compared the efficiency of five methods for batch correction. ComBat was the most effective method for batch effect correction, and the analysis of the corrected dataset revealed 406 DEPs. Batch processing ; Computer science ; Proteomics ; Data mining ; Chemistry ; Biochemistry Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies ; Bioinformatics and Genomic Networks