jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Devon Maywald | Dixon Vimalajeewa
Source: arXiv (Cornell University) (preprint, 2023-12-15)
Field: Chemistry — Analytical Chemistry

Utilizing Wavelet Transform in the Analysis of Scaling Dynamics for Milk Quality Evaluation Food safety and quality are paramount concerns worldwide, especially concerning nutritional quality and its impact on human health. Ensuring the accuracy and efficiency of milk quality assessment is vital for maintaining the quality of dairy farm produce. Milk spectral data, Mid-infrared spectra (MIRS) of milk samples, are frequently employed for milk quality evaluations, encompassing various milk quality parameters. However, conventional milk quality analyses have overlooked the scaling nature, known as stochastic similarity in different scales, inherent in milk spectral data. Wavelet transforms are among the tools used in these analyses, although they are primarily used as data pre-processing techniques without fully realizing their potential in extracting valuable insights. The primary purpose of this study is to demonstrate the importance of accounting for scaling properties in assessing milk quality. A set of 12 descriptors is computed to characterize scaling properties in milk spectral data within the wavelet domain. These descriptors are then assessed for their effectiveness in milk quality assessments utilizing 18 different milk quality parameters. They notably demonstrated comparable performance to existing methods while utilizing fewer features when applied to an MIRS dataset. This innovative approach holds substantial promise for advancing the field of milk quality assessment, offering a means to achieve more accurate and efficient evaluations while shedding light on previously unexplored aspects of milk spectral data. Quality (philosophy) ; Wavelet ; Data quality ; Computer science ; Scaling ; Set (abstract data type) ; Data mining ; Mathematics ; Artificial intelligence ; Engineering Spectroscopy and Chemometric Analyses ; Milk Quality and Mastitis in Dairy Cows ; Meat and Animal Product Quality
Authors: Li He | Keda Wang | Jing Yu | Changjiang Liu | Dong Yuan
Source: Applied Mathematics and Nonlinear Sciences (article, 2023-09-25)
Field: Chemistry — Analytical Chemistry

Application of information fusion technology in maize fertilizer utilization experiments Abstract The article first utilizes the hyperspectral image grayscale, texture information, and reflectance spectral information at characteristic wavelengths to establish the corresponding quantitative analysis models of nutrient content in maize plants using three modeling methods, MLR, PCR, and PLS. Then from the basis of polarized reflection features, it was inferred that the polarization degree features at sensitive wavelengths were extracted using polarized spectra and combined with chemometric techniques to achieve a quantitative analysis of the degree of nutrient stress in maize. Finally, the feature variables extracted on the hyperspectral and polarized-reflection spectral measurement systems were fused with multiple information. A diagnostic evaluation model of fertilizer utilization with polarization-hyperspectral multidimensional light information was established. The results showed that for the new slow-release fertilizers, SF1 and YNPK had higher nitrogen utilization rates, 9.91% and 7.43% higher than N1PK, respectively. And the nitrogen fertilizer utilization rate was correspondingly higher by 6%-7% in 2020 than in 2019 for each fertilizer application treatment. Hyperspectral imaging ; Fertilizer ; Grayscale ; Biological system ; Environmental science ; Wavelength ; Remote sensing ; Computer science ; Artificial intelligence ; Mathematics ; Materials science ; Agronomy ; Geology ; Image (mathematics) ; Optoelectronics Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Smart Agriculture and AI
Authors: Yusuke Yamada | Reìzo Kato | Masahiko Hiraki | Makoto Hikita | Naohiro Matsugaki | Toshiya Senda
Source: Acta Crystallographica Section A Foundations and Advances (article, 2023-08-22)
Field: Materials Science — Materials Chemistry

Development of an efficient pipeline from crystallization to structure determination with the Photon Factory macromolecular crystallography beamline, BL-17A Beamline ; Crystallization ; Factory (object-oriented programming) ; Pipeline (software) ; Crystallography ; Materials science ; Physics ; Chemistry ; Computer science ; Engineering ; Optics ; Mechanical engineering ; Programming language ; Thermodynamics ; Beam (structure) Enzyme Structure and Function ; Advanced X-ray Imaging Techniques
Authors: Timon Cheng‐Yi Liu
Source: Theoretical and Natural Science (article, 2023-12-08)
Field: Chemistry — Inorganic Chemistry

Study on the ancient glass composition based on the multivariate statistical analysis method The Silk Road was a channel of cultural exchange between China and the West, and glass was the precious material evidence of early trade. The study of the relationship between the weathering of ancient glass products and glass types and chemical composition contributes to the preservation of ancient cultural relics and promotes the further study of the history of the Silk Road. Based on this, this paper analyzed the surface weathering of cultural relics, and the type, ornamentation, color, and chemical composition of cultural relics, and it was finally found that there is a significant correlation between glass type and surface weathering. Then, discriminant analysis and systematic cluster analysis were applied to establish the classification function for the glass type variables and the chemical composition variables. Finally, gray correlation analysis was used to explore the correlation between each chemical component, and found that SiO2-Al2O3 was the most associated with each other in lead-barium glass, and K2O-CaO was the highest in high potassium glass. Weathering ; Chemical composition ; Composition (language) ; Mineralogy ; Statistical analysis ; Materials science ; Geology ; Chemistry ; Geochemistry ; Mathematics ; Art ; Statistics ; Organic chemistry ; Literature Pigment Synthesis and Properties
Authors: Bishwa Chandra Adhikari | Ketan Bhotkar | Ravindra Patil | Eun Ha Choi | Kyu Chang Park
Source: Research Square (preprint, 2023-06-05)
Field: Materials Science — Materials Chemistry

Optimization of vertically aligned carbon nanotube beam trajectory with the help of focusing electrode in the microchannel plate Abstract The focusing electrode plays an important role to reduce the electron beam trajectory with low dispersion and high brightness. This article summarizes the importance of the vertically aligned multi-walled carbon nanotube effect with the focusing electrode. First of all, the effect of electron beam trajectory is studied with the different heights, hole sizes, and applied voltage of the focusing electrode by the opera 3D simulation. The field emission electron beam spot is captured in the microchannel plate which helps to reduce the signal noise effect and damage of CNT tips by the joule heating effect. The high-dense bright spot is optimized at the focusing electrode hole size of 2 mm, and the height of 1 mm from the gate mesh electrode at the low bias voltage of -200 V without the loss of current. The FWHM of the electron beam is calculated 0.9 mm with its opening angle of 0.9 0 which could be applicable in high-resolution multi-electron beam microscopy and nano-focused X-ray system technology. Materials science ; Carbon nanotube ; Electrode ; Microchannel ; Optics ; Field electron emission ; Cathode ray ; Beam (structure) ; Optoelectronics ; Brightness ; Microchannel plate detector ; Joule heating ; Triode ; Electron ; Voltage ; Nanotechnology ; Physics ; Composite material Carbon Nanotubes in Composites ; Advanced Electron Microscopy Techniques and Applications ; Photocathodes and Microchannel Plates
Authors: Yong Chen | Xujin Yuan
Source: Physica Scripta (article, 2023-12-06)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Reflection modulation generated by scale-free network resonator periodic structure Abstract The pattern of resonator in a periodical array is decisive for its response under impinging electromagnetic wave. A scale-free network resonator is proposed by connecting sub-units in the form of scale free network. Scale-free network resonator array’s reflectivity near resonant frequency could be modulated at arbitrary value between zero and unity, which is different from known resonator array or frequency selective surface. Reflection amplitude modulation could generate rich behaviors, as effective medium property in wide band could be maintained near zero constant, which means zero phase shift and is favorable in radar radome structure. S-parameter analysis indicates amplitude modulation is owing to polarization conversion generated by network links. Scale-free network resonator array has application potentials in future radar radomes, electromagnetic wave lens and microwave antenna panels. Radome ; Resonator ; Optics ; Amplitude ; Amplitude modulation ; Modulation (music) ; Physics ; Acoustics ; Reflection (computer programming) ; Antenna (radio) ; Microwave ; Polarization (electrochemistry) ; Frequency modulation ; Telecommunications ; Computer science ; Radio frequency Metamaterials and Metasurfaces Applications ; Antenna Design and Analysis ; Advanced Antenna and Metasurface Technologies
Authors: Олександр Павлов | Максим Головченко
Source: The Scientific Issues of Ternopil Volodymyr Hnatiuk National Pedagogical University Series pedagogy (article, 2023-01-13)
Field: Chemistry — Analytical Chemistry

МОДИФІКОВАНИЙ МЕТОД ПОБУДОВИ БАГАТОВИМІРНОЇ ЛІНІЙНОЇ РЕГРЕСІЇ, ЗАДАНОЇ НАДЛИШКОВИМ ОПИСОМ A number of scientific works of Prof. O. A. Pavlov and his disciples is devoted to the development of an original method of efficient estimation of coefficients at nonlinear terms of multivariate polynomial regression given by a redundant description under the conditions of an active experiment. The solution of the formulated problem is reduced to the sequential construction of univariate polynomial regressions (finding efficient estimates for the coefficients at nonlinear terms) and solving the corresponding systems of linear nondegenerate equations, the variables of which are the estimates for coefficients at nonlinear terms of the multivariate polynomial regression given by the redundant description. Thus, the problem was reduced to the estimation of the coefficients at linear terms of a multivariate linear regression given by a redundant description in the conditions of an active experiment. We have proposed an original method of its solution that uses a cluster analysis algorithm. The algorithm’s implementation significantly reduces the enumeration of partial descriptions of multivariate linear regression followed by the finding of the residual sum of squares for each of them. This allows using the chi-squared criterion to build a linguistic variable which value gives a qualitative assessment (high reliability, acceptable reliability, low reliability, unreliability) to the obtained result. The analysis of the computational experiments made it possible to modify the proposed method, which significantly increased its efficiency, first of all, of finding a reliable structure of the sought multivariate linear regression given by the redundant description. The method modification, in particular, has reduced the enumeration of partial descriptions and has led to a more efficient use of the general procedure of the least squares method. Polynomial regression ; Multivariate statistics ; Univariate ; Enumeration ; Linear predictor function ; Polynomial ; Bayesian multivariate linear regression ; Proper linear model ; Linear regression Spectroscopy and Chemometric Analyses ; Advanced Statistical Methods and Models ; Statistical and Computational Modeling
Authors: Sadataka Furui
Source: arXiv (Cornell University) (preprint, 2023-10-12)
Field: Chemistry — Spectroscopy

On the Quadratic Phase Quaternion Domain Fourier Transform and on the Clifford algebra of $R^{3,1}$ We study application of the Clifford algebra and the Grassmann algebra to image recognitions in $(3+1)D$ using quaternions. Following S.L.Adler, we construct a quaternion-valued wave function model with fermions and bosons of equal degrees of freedom, similar to Cartan's supersymmetric model. The Clifford algebra ${\mathcal A}_{3,1}$ is compared with ${\mathcal A}_{2,1}$ and the model applied to the $(2+1)D$ non-destructive testing is extended. The fixed point lattice actions are calculated for 7 paths in $(3+1)D$ space with lengths less than or equal to 8 lattice units. Comparison with the quaternion time approach of Ariel, quaternion Fourier transform of Hitzer and the tensor renormalization group approach to classical lattice models are also discussed. Quaternion ; Clifford algebra ; Quaternion algebra ; Mathematics ; Lattice (music) ; Fourier transform ; Algebra over a field ; Pure mathematics ; Mathematical physics ; Physics ; Mathematical analysis ; Filtered algebra ; Division algebra ; Geometry Advanced NMR Techniques and Applications ; Algebraic and Geometric Analysis ; Medical Imaging Techniques and Applications
Authors: Xin Du | Eric R. Weeks
Source: arXiv (Cornell University) (preprint, 2023-02-11)
Field: Materials Science — Materials Chemistry

Rearrangements during slow compression of a jammed two-dimensional emulsion As amorphous materials get jammed, both geometric and dynamic heterogeneity are observed. We investigate the correlation between the local geometric heterogeneity and local rearrangements in a slowly compressed bidisperse quasi-two-dimensional emulsion system. The compression is driven by evaporation of the continuous phase, and causes the area packing fraction to increase from 0.88 to 0.99. We quantify the structural heterogeneity of the system using the radical Voronoi tessellation following the method of [Rieser et al., Phys. Rev. Lett. 116, 088001 (2016)]. We define two structural quantities characterizing local structure, the first which considers nearest neighbors and the second of which includes information from second nearest neighbors. We find that droplets in heterogeneous local regions are more likely to have local rearrangements. These rearrangements are generally T1 events where two droplets converge toward a void, and two droplets move away from the void to make room for the converging droplets. Thus the presence of the voids tends to orient the T1 events. The presence of a correlation between the structural quantities and the rearrangement dynamics remains qualitatively unchanged over the entire range of packing fractions observed. Atomic packing factor ; Voronoi diagram ; Local Void ; Amorphous solid ; Void (composites) ; Local structure ; Statistical physics ; Emulsion ; Molecular dynamics ; Materials science ; Chemical physics ; Physics ; Crystallography ; Mathematics ; Chemistry ; Mechanics ; Geometry ; Two-phase flow ; Composite material Pickering emulsions and particle stabilization ; Material Dynamics and Properties ; Theoretical and Computational Physics
Authors: Giuseppe Montanaro | Angelo Petrozza | Laura Rustioni | Francesco Cellini | Antonio Carlomagno | Vitale Nuzzo
Source:  (article, 2023-11-06)
Field: Chemistry — Analytical Chemistry

Measuring fruit quality traits in olive through RGB imaging and artificial neural networks: opportunities and limitations Imaging is an emerging contact-less high-throughput technology employed to retrieve quantitative and qualitative plant traits. In addition, it is often combined with artificial neural networks (ANNs) to further improve the reliability of image-based digital proxies. The olive oil industry is expanding globally as olive oil is increasingly recognized as a functional food. Fast and reliable determination of fruit quality traits is challenging in the agricultural sector. This study summarizes recent advances in the use of RGB-based imaging combined with ANNs to (i) predict oil and phenol concentrations in olive fruit and (ii) classify fruit at harvest according to colour and defects. Opportunities and limitations are also discussed. Artificial neural network ; Artificial intelligence ; RGB color model ; Quality (philosophy) ; Computer science ; Pattern recognition (psychology) ; Machine learning ; Computer vision Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Date Palm Research Studies
Authors: Mahantesh Sajjan | Lingangouda Kulkarni | Basavaraj S. Anami | Nijagunadev B. Gaddagimath | Liset Sulay Rodriguez Baca
Source: International Journal of Image Graphics and Signal Processing (article, 2023-11-29)
Field: Chemistry — Analytical Chemistry

Chilli Dryness and Ripening Stages Assessment Using Machine Vision The quality of chilli is prime concern for farmers, traders and chilli processing industries. The effective determination of chilli dryness and ripening stages are important factors in determining its quality and chilli shelf life with respect to manual estimation of ripening/dryness that are complex and time consuming. Chilli dryness and ripeness prediction at post-harvest stage by non-destructive machine vision technologies have potential of fair valuation for chilli produce for the chilli stalk holders. Chilli pericarp color values calculated from RGB, HSV and CIE-L*a*b* color space, texture properties using edge-wrinkles parameters are described by histogram of oriented gradients (HOG). LDA(linear discriminant analysis), RF(random-forest) and SVM(support vector machine) classifiers are analysed for performance accuracy for chilli dryness identification and chilli ripening stages using the machine vision. The chilli dryness identification accuracies of 83%, 85.4% and 83.5% are achieved using chilli color and HOG features with LDA, Random Forest and SVM classifiers respectively. Chilli ripening stage identification with combined chilli feature set of {color, HOG, SURF and LBP} using Support Vector Machine (SVM) average classifier accuracy is 90.56% across four chilli ripening stages. This work is simple with rapid, intelligent and high accuracy of chilli dryness and ripening identification by using machine vision approach has prospect in real-time chilli quality monitoring and grading. The results yielded were promising quality measurements compared previous studies. Ripening ; Dryness ; Support vector machine ; Ripeness ; Artificial intelligence ; Linear discriminant analysis ; Mathematics ; Pattern recognition (psychology) ; Computer science ; Food science ; Biology Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Date Palm Research Studies
Authors: Yekaterinburg Regional Branch of Central Expert-Criminalistic Customs Administration | A. S. Mukhametganeva | А. R. Bayguzina
Source: Analitika i kontrolʹ (article, 2023-01-01)
Field: Chemistry — Spectroscopy

Hard- and Soft-PLS-DA methods in the identification of petroleum products on the basis of gas chromatography data Customs examination for the identification of general or various group affiliation of petroleum products for the purposes of the Commodity Nomenclature of Foreign Economic Activity of the Eurasian Economic Union (THE CUSTOMS CODE OF THE EAEU) is an important task, and the use of a chemometric approach in the study of chemical composition provides additional opportunities for interpretation of the chromatographic data obtained. Proposed identification technique is based on preliminary separation of main components by gas-liquid chromatography and processing the obtained data using a chemometric analysis method – discriminant analysis using regression on latent structures (PLS-DA). The article demonstrates the appropriateness and effectiveness of applying chemometric methods for solving identification problems at the level of establishing the general group affiliation of petroleum products. The PLS-DA method is clear for visual assessment and grouping of objects with similar component composition indicators. Application of the Soft-PLS-DA method in performeing a comparative study of 31 analytes (petroleum product samples: automotive gasoline of different brands, gas condensate distillates, aromatic hydrocarbon fractions) using gas chromatography with a flame-ionization detector (GC-FID) is considered. The obtained model allows identifying samples of petroleum products if the data on the corresponding sets of samples (collections) are available. The obtained model was tested by including two additional samples (outliers) in the set, which differ in composition (characteristics) from other objects, and the reliability and stability of the model was demonstrated. The results of the analysis confirmed the prospects for using chemometric approach for primary identification and grouping of petroleum product samples on the basis of GC-FID results using the Soft-PLS-DA method in expert applications. Identification (biology) ; Gas chromatography ; Chromatography ; Chemistry ; Biology ; Botany Analytical Chemistry and Chromatography
Authors: Vitalii Lozovan
Source:  (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Diagnostic Algorithm Quality of the State of Underground Metal Structures the Using Neural Networks The underground metal structures function in specific conditions of the soil environment and cyclic mechanical loads. It is necessary to conduct a detailed analysis of underground metal structures and monitor their technical condition, since damage and destruction of structural elements during operation can lead to dangerous and/or catastrophic consequences. Intelligent monitoring systems are able to control the life cycle of underground pipelines based on a comprehensive analysis of their current state, operating loads and the results of interaction with the environment. Pipeline transport ; Artificial neural network ; Computer science ; Lead (geology) ; State (computer science) ; Function (biology) ; Quality (philosophy) ; Algorithm ; Engineering ; Environmental science ; Structural engineering ; Geology ; Mechanical engineering ; Artificial intelligence Material Properties and Failure Mechanisms ; Industrial Engineering and Technologies ; Engineering Diagnostics and Reliability