jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Mahmoud Abdulsalam | Usman A. Zahidi | Bradley S. Hurst | Simon Pearson | Grzegorz Cielniak | J. Brown
Source: arXiv (Cornell University) (preprint, 2025-01-06)
Field: Chemistry — Analytical Chemistry

Unsupervised Tomato Split Anomaly Detection using Hyperspectral Imaging and Variational Autoencoders Tomato anomalies/damages pose a significant challenge in greenhouse farming. While this method of cultivation benefits from efficient resource utilization, anomalies can significantly degrade the quality of farm produce. A common anomaly associated with tomatoes is splitting, characterized by the development of cracks on the tomato skin, which degrades its quality. Detecting this type of anomaly is challenging due to dynamic variations in appearance and sizes, compounded by dataset scarcity. We address this problem in an unsupervised manner by utilizing a tailored variational autoencoder (VAE) with hyperspectral input. Preliminary analysis of the dataset enabled us to select the optimal range of wavelengths for detecting this anomaly. Our findings indicate that the 530nm - 550nm range is suitable for identifying tomato dry splits. The proposed VAE model achieved a 97% detection accuracy for tomato split anomalies in the test data. The analysis on reconstruction loss allow us to not only detect the anomalies but also to some degree estimate the anomalous regions. Hyperspectral imaging ; Anomaly detection ; Artificial intelligence ; Anomaly (physics) ; Pattern recognition (psychology) ; Computer science ; Physics Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI
Authors: Retno Damayanti
Source: International Journal of Agriculture and Biology (article, 2025-06-29)
Field: Chemistry — Analytical Chemistry

Image-based ANN Modeling for Nitrogen and Chlorophyll Assessment in Red Betel Leaves using Relief F-selected Texture and Colour Features Accurate and timely detection of chlorophyll and nitrogen content in plants is essential for optimizing nutrient management and crop health monitoring. This study aimed to develop an effective image-based artificial neural network (ANN) model to estimate chlorophyll and nitrogen (N) levels in red betel (Piper crocatum) leaves. Leaf images were captured using standardized digital imaging setups. Color Red Green Blue (RGB) and texture (entropy, homogeneity) features were extracted from these images and analyzed using a carefully optimized ANN model with robust validation techniques to ensure prediction accuracy and generalizability. Results showed that the developed ANN model achieved high accuracy (R² = 0.99), with color intensity and texture parameters strongly correlated to measured chlorophyll and N concentrations. A paired-sample t-test showed no significant difference between ANN-predicted and laboratory Kjeldahl N values (P = 0.12), while SPAD-502 readings differed significantly from the laboratory reference (P &lt; 0.01). Validation errors for chlorophyll and N prediction remained below 4%. These results suggest that an ANN combined with machine vision can provide accurate, real-time, and non-destructive monitoring of plant nutrient status. Biology ; Chlorophyll ; Texture (cosmology) ; Nitrogen ; Botany ; Artificial intelligence ; Pattern recognition (psychology) ; Image (mathematics) ; Computer science ; Chemistry Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Water Quality Monitoring and Analysis
Authors: Boyang Liu | Lijuan Wang
Source: Applied Mathematics (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Crank-Nicolson Finite Difference Scheme for the 3D Allen-Cahn Equation with PINN Comparison In this paper, we derive a second-order Crank-Nicolson finite-difference scheme for the three-dimensional Allen-Cahn equation and present an estimate of the scheme’s truncation error. We prove the existence of the numerical solution and establish stepwise uniqueness, from which the global uniqueness follows given the initial value u 0. We also establish conditional convergence in the L∞ -norm, and demonstrate a discrete maximum principle for the scheme. Numerical Examples 1 and 2 validate the discrete maximum principle, while Numerical Example 3 employs a physics-informed neural network (PINN), using the Crank-Nicolson solution as the reference, to compute the errors between the two approaches in the L2 and L∞ norms. Owing to the high dimensionality of the problem, visualization is performed via isosurface plots on identical time slices; these plots show strong agreement between the Crank-Nicolson and PINN solutions. The numerical results collectively confirm the accuracy and effectiveness of the proposed scheme. Isosurface ; Convergence (economics) ; Curse of dimensionality ; Truncation (statistics) ; Uniqueness ; Truncation error ; Scheme (mathematics) ; Numerical analysis ; Visualization Solidification and crystal growth phenomena ; Model Reduction and Neural Networks ; Numerical methods for differential equations
Authors: Andrea Sama | Sean M. Cahill | Shihong Luo | Abigail Tripka | Yifan Meng | Sarah E. Noll | Richard N. Zare | Pavak K. Shah | Alexandra J. Dickinson
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2025-09-24)
Field: Chemistry — Spectroscopy

Computational method for mapping mass signatures along developmental gradients reveals a novel role for a monosaccharide tetrose in maize salt-stress response Metabolic processes are essential for regulating and maintaining developmental transitions, from stem cell quiescence through differentiation. However, the distinct metabolite-driven mechanisms that are critical for development remain poorly characterized due to inherent challenges in measuring their production, localization, and function <i>in situ</i>. We employed desorption electrospray ionization mass spectrometry imaging (DESI-MSI) to map metabolites in the developing maize root, which has a well-characterized longitudinal gradient that encompasses developmental transitions from quiescence through proliferation and maturation. DESI-MSI enables <i>in situ</i> analysis of the chemical composition of tissue sections with high spatial resolution (~50-100 μm). To identify metabolites with specific developmental enrichment patterns, we developed a computational approach called Developmental Imaging Mass Spectrometry Pipeline for Linear Evaluation (DIMPLE). DIMPLE processes mass signatures along linear gradients, generating clusters of metabolites with specific developmental enrichment patterns in the maize root. We employed this method to compare developmental enrichment of metabolites in a salt-resilient maize variety, Oaxacan Green, and a salt-susceptible variety, B73. DIMPLE identifies specific differences in the mass signatures and the overall enrichment patterns between these varieties. DIMPLE also revealed a metabolite, D-erythrose, that had different localization patterns in these varieties. We found that in salt-sensitive maize varieties, treatment with D-erythrose improves stress tolerance by increasing primary root length. Overall, DIMPLE enables comprehensive and rapid analysis of metabolite patterns along a linear gradient, revealing new biology in plant growth and stress response. Mass spectrometry ; Metabolomics ; Mass spectrometry imaging ; Electrospray ionization ; High resolution ; Metabolite ; Stress (linguistics) Mass Spectrometry Techniques and Applications
Authors: Mohamed Abdelkader Aboamer | Abdulrahman Hakami | Meshari Algethami | Ibrahim M. Alarifi | Tarek M. A. A. EL-Bagory | Ahmad Alassaf | Bakheet Awad Alresheedi | Ahmad Khaleel AlOmari | Abdulaziz Abdullah Almazrua | Nader A. Rahman Mohamed
Source: Polymers (article, 2025-04-21)
Field: Materials Science — Polymers and Plastics

Sustainable Medical Materials: AI-Driven Assessment for Mechanical Performance of UVC-Treated Date Palm Epoxy Composites This study investigates the AI-assisted analyses of radiation disinfection effects on the mechanical properties of recycled date kernel powder-epoxy composites for medical applications, utilizing Euclidean distances and the k-nearest neighbor (KNN) algorithm. Tensile and compression tests were conducted on twenty specimens following ASTM standards, with the data analyzed using a <i>t</i>-test to evaluate the impact of the UVC disinfection process on the material's mechanical properties. The application of AI through the KNN algorithm successfully identified the three most representative curves out of five for both tensile and compression tests. This targeted curve selection minimized variability and focused on the most relevant data, enhancing the reliability of the analysis. Following the application of UVC and AI, tensile tests showed a 20-30% increase in ultimate stress. Similarly, compression tests revealed a 25% increase in transition stress, an 18-22% improvement in ultimate stress, and approximately a 12% rise in fracture stress. This research underscores the potential of combining AI, sustainable materials, and UVC technology to develop advanced composites for medical applications. The proposed methodology offers a robust framework for evaluating material performance while promoting the creation of eco-friendly, high-performance materials that meet the stringent standards of medical use. Ultimate tensile strength ; Epoxy ; Materials science ; Composite material ; Tensile testing ; Compression (physics) ; Reliability (semiconductor) Natural Fiber Reinforced Composites ; Textile materials and evaluations ; Date Palm Research Studies
Authors: Ghfran Naif Rahman | Nief Rahman Ahmad
Source: Journal of Ophthalmology Research Reviews & Reports (article, 2025-04-30)
Field: Chemistry — Analytical Chemistry

Determination of Propranolol HCL in Pharmaceutical Preparations and Environmental Wastewater Samples Application to Content Uniformity Testing A Newly developed analysis method for the simple, accurate, precise, rapid, economical and sensitive Ultraviolet spectrophotometric method has been developed for the determination of Propranolol Hydrochloride in pharmaceutical preparations and environmental wastewater samples, which shows maximum absorbance at 290 nm in methanol. Beer's law was obeyed in the range of 2.5 -50 µg/ ml, with molar absorptivity of 5.92×103 L.mol-1.cm1, relative standard deviation of the method was less than 1.5%, and accuracy (average recovery %) was 100 ± 0.9. No interference was observed from common excipients and additives often accompany with Propranolol Hydrochloride in pharmaceutical preparations. The method was successfully applied to the determination of Propranolol Hydrochloride in some pharmaceutical formulations (tablets) and industrial wastewater samples. The proposed method was validated by sensitivity and precision which proves suitability for the routine analysis of Propranolol Hydrochloride in true samples. Propranolol Hydrochloride ; Absorbance ; Relative standard deviation ; Dosage form ; Molar absorptivity ; Wastewater ; Spectrophotometry ; Accuracy and precision Analytical Methods in Pharmaceuticals ; Analytical Chemistry and Chromatography ; Analytical chemistry methods development
Authors: Yanyan Sun | Jun Qi | Yijun Chai | Xiongwei Yang | Yueming Li
Source: Aerospace Research Communications (article, 2025-10-02)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Study on Thermal Cloaks for Hexagon and Dodecahedron With Symmetry The thermal cloak has special thermal insulation performance because of its unique anisotropic thermal conductivity tensor. Constrained by simplistic geometric designs, traditional thermal cloaks face limitations in achieving precise thermal regulation for complex structures with different shapes. The hexagonal and dodecahedral thermal cloaks are quite rare, largely due to their complex transformation equations. In this study, the transformation equations for the hexagonal and dodecahedral cloaks are derived by the rotation matrix, and their thermal conductivity tensors are further obtained according to the theory of transformation thermotics. The derivation method is applicable to any two and three-dimensional thermal invisibility cloaks with geometric symmetry. Furthermore, the numerical verification shows that both hexagonal and dodecahedral thermal cloaks could avoid heat flow in their thermal invisibility region. This proves the correctness of the derivation method and the thermal conductivity tensor calculated. The hexagonal and dodecahedral thermal cloaks obtained in this paper could provide uniform temperature field for different applications preventing the field of non-uniform stress and deformation in actual. Dodecahedron ; Thermal conductivity ; Thermal ; Field (mathematics) ; Anisotropy ; Symmetry (geometry) ; Transformation (genetics) Metamaterials and Metasurfaces Applications ; Quasicrystal Structures and Properties ; Advanced Materials and Mechanics
Authors: M Kucerová
Source: Česká a slovenská farmacie (review, 2025-03-20)
Field: Chemistry — Organic Chemistry

Covalent drugs Covalent drugs are substances capable of forming a reversible or an irreversible covalent bond with a macromolecular target in the body. Despite the risk of adverse reactions in the organism, the design of such agents has become a trend over the last two decades. Drugs acting by covalent mechanisms from different indication groups are summarized in this article and possibly supported with a reference to the crystallographic structure in the Protein Data Bank. The advantages and the disadvantages of using covalent drugs are also discussed. Covalent bond ; Chemistry ; Organic chemistry Click Chemistry and Applications ; Pharmaceutical studies and practices ; Peptidase Inhibition and Analysis
Authors: Nikolay Padarev
Source: Environment Technology Resources Proceedings of the International Scientific and Practical Conference (article, 2025-06-08)
Field: Materials Science — Materials Chemistry

MATHEMATICAL MODEL FOR CALCULATING THE DISPERSION FLOW RATE OF DECONTAMINATION SOLUTIONS FOR CHEMICAL AND RADIOLOGICAL AGENTS WHEN SPRAYED FROM NOZZLES The mathematical model for calculating the flow rate of fluids when dispersed from nozzles is based on the principles of fluid mechanics, using equations for the velocity of the fluid and the effects of nozzle diameter, pressure, and the dynamic properties of the fluid (density, viscosity). The model includes calculations of the flow rate based on the theoretical exit velocity from the nozzle, along with corrections for pressure losses associated with friction and turbulence. The Reynolds number is used to assess the flow characteristics (laminar or turbulent), which is crucial for optimizing the fluid dispersion. In MATLAB, various plots are generated to show the dependencies between the flow rate, nozzle diameter, and pressure, enabling a deeper understanding of the fluid behaviour during dispersion. The model is applicable to different types of fluids, including solutions with surfactants and hypochlorites, used for disinfection purposes. Human decontamination ; Nozzle ; Radiological weapon ; Volumetric flow rate ; Dispersion (optics) ; Flow (mathematics) ; Materials science ; Chemistry ; Radiochemistry ; Process engineering ; Chemical engineering ; Mechanics ; Waste management ; Engineering ; Mechanical engineering ; Physics ; Optics Graphite, nuclear technology, radiation studies ; Risk and Safety Analysis ; Combustion and Detonation Processes
Authors: Magaly De La Cruz-Noriega | Renny Nazario-Naveda | Santiago M. Benites | Daniel Delfín-Narciso
Source: Proceedings of the International Conference of Theoretical and Applied Nanoscience and Nanotechnology (article, 2025-07-01)
Field: Materials Science — Biomaterials

Bibliometric Analysis of Nanotechnology in Biopolymers for Sustainable Packaging: Trends, Collaborations, and Materials Optimization The study examines the application of nanotechnology in biopolymers for sustainable packaging, offering a key solution to the growing issue of plastic pollution.The research highlights the enhancement of mechanical and functional properties through the incorporation of nanoparticles, resulting in biopolymers that are stronger, biodegradable, and possess antimicrobial activity.The methodology is based on a bibliometric analysis of scientific publications indexed in Scopus between 2003 and 2025, categorizing papers by affiliations, influential authors, leading countries, and predominant keywords.Tools such as VOSviewer were used to visualize collaboration networks and emerging trends.Among the key findings, there is an exponential growth in research on biopolymers reinforced with nanotechnology, with India leading in scientific production and Universiti Putra Malaysia identified as the institution with the highest number of publications.Additionally, the most cited article discusses natural emulsifiers in biopolymers.The study concludes that nanotechnology enhances sustainable packaging materials and that international collaboration is essential for future innovations, underscoring the consolidation of this field in recent years. Nanotechnology ; Materials science biodegradable polymer synthesis and properties
Authors: Anupreet Kaur Sobti
Source: American Journal of Biomedical Science & Research (article, 2025-09-17)
Field: Chemistry — Analytical Chemistry

Bibliometric Mapping and In Silico ADME Profiling of Bioactive Compounds in Germinated Oats with Antidiabetic Potential Type 2 Diabetes Mellitus (T2DM) is a growing global health burden, where dietary interventions play a crucial role in prevention and management.Oats (Avena sativa), known for their -glucan, phenolic compounds, and GABA content, exhibit glycaemic-regulating effects.Germination enhances the bioactive profile of oats, yet limited studies explore its impact on pharmacological properties relevant to diabetes.An integrative bibliometric and in silico pharmacokinetic analysis was conducted to explore the therapeutic potential of germinated oat compounds in diabetes management.VOSviewer software was used for bibliometric co-occurrence analysis of keywords related to oats, germination, and diabetes.Germination-enhanced compounds--glucan, avenanthramides, ferulic acid, and Gamma-Aminobutyric Acid (GABA), were analysed using SwissADME software for solubility, GI absorption, Blood-Brain Barrier (BBB) permeability, drug-likeness, and bioavailability.The bibliometric map revealed a lack of focused research connecting germinated oats and glycaemic control.Among the compounds, ferulic acid showed high oral bioavailability and BBB permeability.Avenanthramides had favourable drug-likeness and absorption.GABA demonstrated good solubility and GI absorption, while -glucan showed poor oral bioavailability but potential enzyme inhibition activity.Germinated oats are underexplored in the context of diabetes.Ferulic acid and avenanthramides promise as antidiabetic agents, while -glucan and GABA may support functional food or enzyme-targeted applications. In silico ; ADME ; Profiling (computer programming) ; Germination Spectroscopy and Chemometric Analyses ; Food Science and Nutritional Studies ; Food Industry and Aquatic Biology
Authors: Moshe Avraham | Mikhail Klinov | Yael Nemirovsky
Source:  (article, 2025-11-07)
Field: Materials Science — Electronic, Optical and Magnetic Materials

CMOS-Compatible Narrow Bandpass MIM Metamaterial Absorbers for Spectrally Selective LWIR Thermal Sensors The growing demand for compact, low-power infrared (IR) sensors necessitates advanced solutions for on-chip spectral selectivity, particularly for integration with Thermal Metal-Oxide-Semiconductor (TMOS) devices. This paper investigates the design and analysis of CMOS-compatible metal–insulator–metal (MIM) metamaterial absorbers tailored for selective absorption in the long-wave infrared (LWIR) region. We present a design methodology utilizing an equivalent-circuit model, which provides intuitive physical insight into the absorption mechanism and significantly reduces computational costs compared to full-wave electromagnetic simulations. An important rule in this design methodology is demonstrating how the resonance wavelength of these absorbers can be precisely tuned across the LWIR spectrum by engineering the geometric parameters of the top metallic patterns and, critically, by optimizing the dielectric substrate’s refractive index and thickness, which assist in designing small period MIM absorber units which are important in infrared thermal sensor pixels. Our results demonstrate that the resonance wavelength of these absorbers can be precisely tuned across the LWIR spectrum by engineering the geometric parameters of the top metallic patterns and by optimizing the dielectric substrate’s refractive index and thickness. Specifically, the selection of silicon as the dielectric material, owing to its high refractive index and low losses, facilitates compact designs with high-quality factors. The transmission line model provides intuitive insight into how near-perfect absorption is achieved when the absorber’s input impedance matches the free-space impedance. This work presents a new approach for the methodology of designing MIM absorbers in the mid-infrared and long-wave infrared (LWIR) regions, utilizing the intuitive insights provided by equivalent circuit modeling. This study validates a highly efficient design approach for high-performance, spectrally selective MIM absorbers for LWIR radiation, paving the way for their monolithic integration with TMOS sensors to enable miniaturized, cost-effective, and functionally enhanced IR sensing systems. Metamaterial ; Refractive index ; Dielectric ; Absorption (acoustics) ; Infrared ; Thermal ; Wavelength ; Transmission line Metamaterials and Metasurfaces Applications ; Thermal Radiation and Cooling Technologies ; Electromagnetic wave absorption materials