jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Y. N. Wang
Source: Highlights in Science Engineering and Technology (article, 2025-12-23)
Field: Materials Science — Materials Chemistry

A High-Order Numerical Scheme for Allen-Cahn Equation via Strang Splitting and Fourier Spectral Method This paper proposes a practical numerical scheme for solving the Allen-Cahn (AC) equation by integrating Strang operator splitting, the Fourier spectral method, and SSP-RK (strong stability-preserving Runge-Kutta) time integration. This approach enhances the stability of phase-field simulations while ensuring computational efficiency by decoupling the treatment of stiff nonlinear terms and linear diffusion terms: the nonlinear reaction term is explicitly advanced using SSP-RK, leveraging its strong stability-preserving properties to control solution boundedness under moderate time step sizes; the linear diffusion term is solved exactly via Fourier spectral differentiation, significantly reducing the iterative cost of traditional implicit schemes. Spatial discretization employs the spectral method, achieving superior interface resolution compared to finite differences in regular domains. Numerical verifications demonstrate that: under a moderate stiffness parameter ( ), when the time step size is refined to 0.00625, the error stably decreases from an initial to , with convergence properties approaching the theoretical second-order accuracy; under strong stiffness regimes ( ), the scheme maintains effective convergence trends, with error reduction magnitudes reaching an order of magnitude. Physical property verifications confirm that the scheme strictly preserves the maximum principle (phase-field values always lie within the [0,1] interval) under two/three-dimensional random initial conditions, and the discrete energy exhibits monotonic decay characteristics consistent with the evolutionary laws of the double-well free energy. Computational efficiency tests show that, for moderate-scale problems, the scheme saves approximately 30–40% of computational time compared to standard implicit schemes. This scheme provides a new option balancing accuracy and efficiency for phase-field modeling, though its strong stiffness adaptability and large-scale scalability still require in-depth study. Discretization ; Nonlinear system ; Spectral method ; Fourier series ; Convergence (economics) ; Reduction (mathematics) ; Numerical analysis ; Fourier transform ; Relaxation (psychology) ; Stability (learning theory) Solidification and crystal growth phenomena ; Advanced Numerical Methods in Computational Mathematics ; Shape Memory Alloy Transformations
Authors: Naoyuki Toyota | Ryo Konno | Shuhei Iwata | Shin Fujita | Yoshio Kodera | Rei Noguchi | Tadashi Kondo | Yusuke Kawashima | Yuki Yoshimatsu
Source: Proteomes (article, 2025-08-12)
Field: Chemistry — Spectroscopy

Identification of Cancer-Associated Proteins in Colorectal Cancer Using Mass Spectrometry Our findings suggest that proteome abundance trends may contribute to the identification of biomarker candidates and therapeutic targets in colorectal cancer. However, given the limited sample size and lack of subtype stratification, further studies using larger, statistically powered cohorts are warranted to establish clinical relevance. These proteins may provide insights into drug resistance and tumor heterogeneity. Limitations of the study include the inability to detect low-abundance proteins and reliance on protein abundance rather than functional activity. Future complementary approaches, such as affinity proteomics, are suggested to address these limitations. Proteomics ; Colorectal cancer ; Proteome ; Cancer ; Biology ; Carcinogenesis ; Disease ; Biomarker ; Computational biology ; Cancer biomarkers ; Biomarker discovery ; Bioinformatics ; Cancer research ; Oncology ; Medicine ; Genetics ; Internal medicine ; Gene Advanced Proteomics Techniques and Applications ; Cancer, Lipids, and Metabolism ; Enzyme Structure and Function
Authors: Soryana Gonçalves Ferreira de Melo | Bruno Gomes de Noronha | Júlia Martins Soares | Denise Cunha Fernandes dos Santos Dias | Laércio Junio da Silva | Anderson Barbosa Evaristo | Marcela Carlota Nery
Source: Journal of Seed Science (article, 2025-01-01)
Field: Chemistry — Analytical Chemistry

Near-infrared spectroscopy (NIR) for classifying the physiological quality of canola seeds ABSTRACT: The use of high-quality seeds is essential in production systems. NIR spectroscopy, combined with chemometric methods, is a promising, rapid, nondestructive, and easy-to-use tool for assessing seed physiological potential. This study aimed to analyze the feasibility of NIR spectroscopy coupled with chemometric methods to detect differences in the physiological quality of canola seeds. Seeds from eight lots of the Nuola 300, Hyola 575, and Diamond cultivars underwent initial characterization tests, seedling length tests, and X-ray analysis. For spectral acquisition, random seed samples were selected, with 12 readings taken for each cultivar. The cultivars were categorized as high (C1) and low (C2) vigor. The spectra were preprocessed using methods such as Multiplicative Scattering Correction (MSC), Standard Normal Variance (SNV), and the first and second Savitzky-Golay derivatives. These data were subsequently used to build classification models using Partial Least Squares Discriminant Analysis (PLS-DA). The model demonstrated high accuracy and kappa coefficients, with the SNV method being the best suited for the dataset. The wavelength regions between 1,004-1,064 nm and 1,698-1,907 nm were the most relevant for distinguishing seed quality levels. Analysis of near-infrared (NIR) spectra, subjected to preprocessing based on derivative methods and dispersion correction, demonstrated high efficiency in detecting variations in the physiological quality levels of canola seeds. Canola ; Partial least squares regression ; Cultivar ; Rapeseed ; Linear discriminant analysis ; Chemometrics ; Residual Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Remote Sensing in Agriculture
Authors: Shinta Widyaningtyas | Muhammad Arwani | Sucipto Sucipto | Yusuf Hendrawan
Source: Coffee Science (article, 2025-01-01)
Field: Chemistry — Analytical Chemistry

Improving the accuracy of green bean palm civet coffee purity classification using wrapper feature selection Palm civet coffee, a highly prized specialty coffee, faces counterfeiting due to its limited production. The lack of reliable detection methods necessitates the development of non-destructive sensing techniques. This study investigates the use of machine vision and feature selection to classify the purity of palm civet coffee. A dataset of 101 image features (11 color and 90 textural) was extracted from coffee bean images. A wrapper-based feature selection approach, employing K-Nearest Neighbors (KNN), Random Forest (RF), and Support Vector Machine (SVM) classifiers with four optimization algorithms (Bat Algorithm, Cuckoo Search, Genetic Algorithm, and Grey Wolf Optimizer), was used to identify the most informative features. The results demonstrate that a Random Forest classifier, optimized using Grey Wolf Optimizer with 500 trees, achieved the highest accuracy (0.981) using a subset of five features: Blue_Mean, Hue_Entropy, Gray_Inverse, S_HSL_Correlation, and Green_Cluster. These findings suggest that machine vision, combined with feature selection, holds promise for developing a robust and non-destructive method for detecting palm civet coffee counterfeiting. Key words: Classifier; feature selection; learning algorithm; machine vision; palm civet coffee purity. Palm ; Feature selection ; Selection (genetic algorithm) ; Artificial intelligence ; Pattern recognition (psychology) ; Computer science ; Mathematics ; Physics Spectroscopy and Chemometric Analyses ; Coffee research and impacts ; Coconut Research and Applications
Authors: Vinithaa Raguram | R. Padmanaban
Source: International Journal of Advanced Research in Science Communication and Technology (article, 2025-08-23)
Field: Chemistry — Analytical Chemistry

Optimisation of Acid Yellow Dye Decolourisation using CNS Carbon: A Response Surface Methodology Approach with Exploratory Data Analysis in Jupyter Notebook The current research is focused on the need to develop an efficient adsorbent with low-cost effectiveness and high potentiality for removal of dye from waste water. Cashew nut shell, a solid waste generated in the cashew nut industry is taken as the adsorbent for the decolorization of acid yellow synthetic dye solution. Batch adsorption studies were carried out with the consideration of factors/variables such as dye concentration, adsorbent dosage and contact time. A comparative decolorization study has been done with both commercial activated carbon (CAC) and Cashew nut shell carbon (CNSC). The factors were optimized statistically using Central Composite Design (CCD) in response surface methodology. The characterization of the absorbent was analyzed in FTIR, SEM and XRD. In recent years, the use of interactive computing environments has significantly improved the efficiency of data analysis workflow. This study investigates the effectiveness using Jupyter notebooks in facilitating exploratory data analysis and reproducible research practices. Using the datasets, we conducted a comprehensive analysis involving data cleaning, visualization, and statistical exploration, leveraging Python libraries such as numpy, pandas, seaborn, and matplotlib Response surface methodology ; Exploratory analysis ; Carbon fibers ; Exploratory data analysis ; Environmental science ; Computer science ; Data mining ; Data science ; Machine learning ; Algorithm Dye analysis and toxicity ; Water Quality Monitoring and Analysis
Authors: Sichen Wang | Tingting Xie | Zhiming Du | Qinci Li | Chong Zhang
Source: Research Square (preprint, 2025-05-06)
Field: Chemistry — Inorganic Chemistry

Optimization System Development and Application for Characteristic Volume in Flow Field of In-Situ Leaching of Uranium Uranium ; In situ ; Leaching (pedology) ; Field (mathematics) ; Volume (thermodynamics) ; Materials science ; Environmental science ; Metallurgy ; Soil science ; Chemistry ; Mathematics ; Physics ; Thermodynamics Radioactive element chemistry and processing ; Minerals Flotation and Separation Techniques ; Extraction and Separation Processes
Authors: Sami Berrais | Sabiha Tekili | Abdelaziz Nehal | Youcef Khadri
Source: Research on Engineering Structures and Materials (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Thermo-mechanical behavior of a symmetric single-walled carbon nanotube/polymer reinforced beam laminate The symmetrical laminates reinforced with carbon nanotubes (CNTs) offer exceptional performance,due to their high specific stiffness, low density, and excellent fracture toughness. Through theunderstanding of their thermo-mechanical behavior under various stresses and temperature is essential for their design. Moreover, if the distribution and orientation of CNTs are adjusted and their agglomeration is avoided, their integration into a polymer matrix allows the macroscopic application of their exceptional characteristics in different fields. This work provides a micromechanical modeling approach to predict the effective thermo-elasticbehavior ofnanocomposites. In order to determine these effective parameters,the Mori-Tanaka homogenization approach is used.with a volume fraction equal or less thanten percent which, modify significantly thermo-elastic properties of the composite and also, a simplified model where CNTs are modeled as hollow cylindrical shells.These effective properties are combined via MATLAB for ensuring a structural analysis based on the classical laminate theory and first-order shear deformation theory to examine the mechanical behavior and the classical laminate theory to evaluate the thermal behavior of symmetric laminated nanocomposite beams. The model focuses particularly on the thickness distribution of normal as in-plane and out-of-plane shear stresses that vary over thickness and stresses, deformations due to the temperature variation. The resultsshow the need to capture shear deformation effects and indicate the validity ofproposed model for analyzing stress continuity and identifying critical locations in nanocomposite laminates and so how each ply reacts to a temperature variation despite an overall geometry without curvature. Homogenization (climate) ; Volume fraction ; Carbon nanotube ; Micromechanics ; Nanocomposite ; Composite number ; Composite laminates ; Shear (geology) ; Timoshenko beam theory Carbon Nanotubes in Composites ; Nonlocal and gradient elasticity in micro/nano structures ; Composite Structure Analysis and Optimization
Authors: Yeong Hwan Ko | Robert Magnusson
Source: Photonics (article, 2025-04-22)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Dynamically Tunable Singular States Through Air-Slit Control in Asymmetric Resonant Metamaterials This study presents a novel method for dynamically tuning singular states in one-dimensional (1D) photonic lattices (PLs) using air-slit-based structural modifications. Singular states, arising from symmetry-breaking-induced resonance radiation, generate diverse spectral features through interactions between resonance modes and background radiation. By strategically incorporating air slits to break symmetry in 1D PLs, we demonstrated effective control of resonance positions, enabling dual functionalities including narrowband band pass and notch filtering. These singular states originate from asymmetric guided-mode resonances (aGMRs), which can be interpreted by analytical modeling of the equivalent slab waveguide. Moreover, the introduction of multiple air slits significantly enhances spectral tunability by inducing multiple folding behaviors in the resonance bands. This approach allows for effective manipulation of optical properties through simple adjustments of air-slit displacements. This work provides great potential for designing multifunctional photonic devices with advanced metamaterial technologies. Slit ; Metamaterial ; Optics ; Materials science ; Optoelectronics ; Physics Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: Lu Liu | Songlin Guo | Zhaoyu Xing | Xianjun Yu | Wenbo Mi | Jiule Ding | Jie Chen | Xing Wei | Liang Pan
Source: Abdominal Radiology (review, 2025-05-31)
Field: Materials Science — Materials Chemistry

Chemical exchange saturation transfer magnetic resonance imaging of the kidney: applications and challenges The kidney plays a crucial role in regulating the acid-base balance of the body. The development of kidney diseases is often accompanied by changes in the renal PH, protein, glucose, urea, and other metabolites. Chemical exchange saturation transfer (CEST) imaging is a new magnetic resonance imaging (MRI) technique based on the chemical exchange between solute and water protons. The potential of CEST imaging in renal metabolic imaging stems from its ability to provide image contrast based on specific molecular compositions at relevant millimolar physiological concentrations. In this article, we briefly introduce the fundamental principles of CEST imaging and its applications in various renal disorders, including acute kidney injury, chronic kidney disease, renal tumors, and renal allograft rejection. Finally, we discuss the challenges and prospects of CEST imaging in the field of kidney diseases. Hepatology ; Magnetic resonance imaging ; Medicine ; Nuclear magnetic resonance ; Saturation (graph theory) ; Internal medicine ; Radiology ; Physics Lanthanide and Transition Metal Complexes ; Advanced MRI Techniques and Applications ; MRI in cancer diagnosis
Authors: Fendy Prasetyawan | Yuneka Saristiana | Mihdzar Abdul Kadir | Lisa Savitri | Novyananda Salmasfattah | Muhammad Nurul Fadel | Emma Jayanti Besan
Source: Journal of Engineering Science and Technology Management (JES-TM) (article, 2025-03-16)
Field: Chemistry — Analytical Chemistry

Description of Absorption Distribution Metabolism Excretion Toxicity (ADMET) of Nuciferine from Terate Flowers (Nymphaea spp.) using pkCSM Technology This study evaluates the ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) profile of nuciferine to assess its potential as a drug candidate. Based on in silico analysis, nuciferine demonstrates favorable oral absorption and extensive systemic distribution, including its capability to cross the blood-brain barrier into the central nervous system. Regarding metabolism, the compound acts as a substrate for CYP2D6 and CYP3A4 enzymes while serving as an inhibitor of CYP1A2 and CYP2D6, which may lead to drug-drug interactions. In terms of excretion, nuciferine displays moderate clearance values and utilizes renal transporter OCT2. However, toxicological evaluations suggest potential risks, including mutagenicity (positive AMES test), hepatotoxicity, and inhibition of hERG II potassium channels, which are associated with cardiotoxicity risks. Despite its favorable bioavailability and distribution properties, concerns about chronic toxic effects and metabolic interaction risks underscore the need for careful consideration in its development. Further research is necessary to validate its safety and efficacy for therapeutic applications. Excretion ; Absorption (acoustics) ; Toxicity ; Metabolism ; Distribution (mathematics) ; Chemistry ; Botany ; Biology ; Biochemistry ; Organic chemistry ; Materials science ; Mathematics Chromatography in Natural Products ; Morinda citrifolia extract uses ; Spectroscopy and Chemometric Analyses
Authors: P Viji | Senapathi Sireesha | Jesmi Debbarma | Madhusudana Rao Badireddy | J. Bindu
Source: Fishery Technology (article, 2025-10-31)
Field: Materials Science — Biomaterials

Healthy Coating for Fish Nuggets: Effects of Millet Batter on Coating Performance and Nutritional Composition The present study investigated the effects of substituting refined wheat flour (RFW) in conventional batter with different millet flours on the coating performance and nutritional quality of fish nuggets. Among the different millets used (pearl millet, sorghum and little millet), substitution of RWF with pearl millet flour significantly (p &lt; 0.05) reduced the lightness (L*) and yellowness score (b*) of batter. At 20% substitution, the coating pick-up of millet batters was comparable (40.62 to 43.82%) to that of conventional batter (43.90%), but the pickup ratio decreased as the level of substitution increased up to 50%, regardless of the millets used (38.76-41.54%). The cooking yield of coated nuggets increased proportionally with the addition of millet flour in the batter. Substitution of maida with millet flour in the batter significantly enhanced the nutritional components, including protein and fat. However, the oil absorption by millet batters (285 to 667%) was significantly (p &lt; 0.05) higher than that of the conventional batter (334%). Overall, the results of the study revealed that maida in conventional batter can be substituted with millet flour to enhance the coating performance and the nutritional quality of coated products. Coating ; Fish <Actinopterygii> ; Wheat flour ; Sorghum ; Lightness ; Composition (language) Nanocomposite Films for Food Packaging ; Food composition and properties ; Microencapsulation and Drying Processes
Authors: C. T. Chen | Dingfeng Shi | An Huang | Sen Ai | Rantong Niu | Ting Jiao | Zhenyu Xu
Source: Photonics (article, 2025-04-18)
Field: Chemistry — Spectroscopy

Reconstruction Algorithm of Absorption Spectral Field Distribution Based on a Priori Constrained Bivariate Polynomial Model Computed Tomography–Tunable Diode Laser Absorption Spectroscopy (CT-TDLAS) is an effective diagnostic method for analyzing combustion flow fields within engines. This study proposes an adaptive reconstruction algorithm utilizing constrained polynomial fitting within the CT-TDLAS framework. Based on existing polynomial fitting models, the proposed algorithm integrates physical boundary constraints on temperature and concentration fields, optimizing integrated absorbance errors. This method significantly enhances reconstruction accuracy and computational efficiency, while also lowering computational complexity. The adaptive strategy dynamically adjusts the polynomial order, effectively mitigating issues of overfitting or underdetermination typically associated with fixed polynomial orders. Numerical simulations demonstrate reduced temperature reconstruction errors of 2%, 1.6%, and 2% for single-peak, dual-peak, and mixed distribution flow fields, respectively. Corresponding concentration errors were 2%, 1.8%, and 2.6%, which are all improvements over those achieved by the Algebraic Reconstruction Technique (ART). Experimental results using a McKenna flat-flame burner revealed an average reconstruction error of only 0.3% compared to thermocouple measurements for high-temperature regions (&gt;1000 K), with a minimal central temperature difference of 6 K. For lower-temperature peripheral regions, the average error was 188 K, illustrating the practical applicability of the proposed algorithm. Bivariate analysis ; A priori and a posteriori ; Algorithm ; Field (mathematics) ; Computer science ; Absorption (acoustics) ; Distribution (mathematics) ; Polynomial ; Optics ; Mathematics ; Physics ; Mathematical analysis Spectroscopy and Laser Applications ; Photoacoustic and Ultrasonic Imaging ; Optical Systems and Laser Technology
Authors: B. Tu | Yueting Zhang | Yongjie Zheng | Xinliang Liu | Yanfang Wu
Source: American journal of biochemistry & biotechnology/American journal of biochemistry and biotechnology (article, 2025-01-01)
Field: Chemistry — Analytical Chemistry

Near Infrared Spectroscopy Identification Method for Five Chemical Types of <i>Cinnamomum camphora</i> To more quickly and accurately identify the five chemical types of Cinnamomum camphora, a desktop and portable near-infrared spectrometer was used to collect the near-infrared spectra of the leaves of the five chemical types of C. camphora. Combined with chemometric methods, the near-infrared spectra of different chemical types of C. camphora were discriminated and analyzed. Using a desktop near-infrared spectrometer in the 1000-2000 nm wavelength range, we applied dg2 and SNV preprocessing techniques, combined with the SIMCA algorithm, to build a model. This model successfully identified the three chemical types- Linalool, Borneol, and Camphor-with 100% accuracy. Only two samples of Cineol and Iso-nerolidol were not correctly identified. In the wavelength range of 1600-2400 nm, the portable near-infrared spectrometer was pretreated with S-G smoothing and SNV pretreatment. The optimal model was established after spectral matching and the sample recognition rate of the model was as high as 99.73%. A sample of Cineol and Iso-nerolidol was incorrectly identified. In terms of the external verification test, the recognition rates of the two models reached 99.20 and 98% respectively, showing high recognition ability. This study provides a robust and efficient method for the rapid, field-based identification of five different chemotypes of C. camphora, which could significantly benefit practical applications in the field. Cinnamomum camphora ; Cinnamomum ; Identification (biology) ; Infrared spectroscopy ; Infrared ; Spectroscopy ; Analytical Chemistry (journal) ; Chemistry ; Botany ; Chromatography ; Physics ; Biology ; Optics ; Medicine ; Organic chemistry Spectroscopy and Chemometric Analyses