jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Stéphane Molla | Assefa Asmare Tsegaw | Teshome Mulatie Bogale | Azam Ali | Asmamaw Tegegne Abebe
Source: Preprints.org (review, 2025-07-24)
Field: Materials Science — Polymers and Plastics

Mechanical Strength and Sustainability of Hybrid Sisal-Glass Reinforced HDPE Composites for Automotive Body Applications: A Comprehensive Review Hybrid sisal-Glass Reinforced HDPE composite are emerging as a promising material for automotive body components due to their enhanced mechanical properties and environmental sustainability.This reviews provides a comprehensive investigation into the mechanical strength and potential applications of these composites in automotive parts such as side panels,hoods,and roofing .The study examines key factors influencing the Mechanical properties of hybrid composite s,including fiber content,fiber orientation,and the effect of environmental conditions like moisture, temperature,and UV degradation.The impact of these factors on tensile, flexural,shear,and impact strength is discussed ,along with the balance b/n natural sisal fibers and synthetic glass fibers for optimized performance.Futuremore,the sustainability aspects of these composites,including reduced weight, recyclablitity ,and lower carbin footprint,are highlighted .The review also address es challenges related to interfacial bonding ,durablity,and the optimization of fiber ratios for specific automotive application s.Overall,hybrid sisal-Glass Reinforced HDPE composite present a viable alternative to traditional automotive materials,offering an environmentally friendly ,cost effective solution for the next generation of lightweight vechile design. SISAL ; Automotive industry ; Composite material ; High-density polyethylene ; Materials science ; Sustainability ; Mechanical strength ; Engineering ; Polyethylene ; Aerospace engineering Natural Fiber Reinforced Composites ; Mechanical Engineering and Vibrations Research ; Tribology and Wear Analysis
Authors: Lukáš Maleček | Marek Zemek | Yoshihiro Takeda | Kazuhiko Omote | Peter Oberta | Tomáš Zikmund | Jozef Kaiser
Source: e-Journal of Nondestructive Testing (article, 2025-06-24)
Field: Materials Science — Surfaces, Coatings and Films

Localized Phase Retrieval Application for Analyzing Multi-Material Samples X-ray computed tomography (CT) is a powerful imaging technique that provides three-dimensional insights into the internal structures of objects without mechanical intervention. Initially developed for medical diagnostics, CT has evolved into a versatile tool in various scientific and industrial fields. However, standard absorption-based CT has limitations when imaging materials with low X-ray attenuation or multi-material samples with similar attenuation values, often resulting in insufficient contrast for detailed analysis. To overcome these challenges, phase-contrast CT has emerged as a valuable approach, leveraging changes in the phase of X-rays as they interact with the sample. One of the most accessible phase contrast imaging methods is the propagation-based approach, which typically requires a phase retrieval application. This application increases the contrast of individual structures, but on the other hand, it leads to degradation of the spatial resolution in heterogeneous samples, particularly when high-density particles are present. This paper presents so-called localized phase retrieval, which offers a novel solution to this limitation. Instead of applying the phase retrieval algorithm globally, this method focuses on specific regions within reconstructed tomographic slices, preserving spatial resolution and improving material distinction. This localized approach holds promise for more accurate and efficient analysis of complex multi-material samples, paving the way for advancements in computed tomography applications. Phase (matter) ; Computer science ; Information retrieval ; Materials science ; Chemistry Electron and X-Ray Spectroscopy Techniques
Authors: Dominga C. Aquino | André L. San Lorenzo
Source: Agrotecnia (article, 2025-12-03)
Field: Chemistry — Analytical Chemistry

Aplicación de imágenes hiperespectrales en la detección de contaminantes en alimentos: una revisión En los últimos años, las crecientes preocupaciones de salud han resaltado la necesidad urgente de métodos innovadores para garantizar la seguridad alimentaria. La tecnología de imágenes hiperespectrales (HSI, por sus siglas en inglés) ha surgido como una herramienta altamente prometedora y ampliamente reconocida, ofreciendo capacidades de detección no destructivas esenciales para identificar contaminantes en alimentos. Este artículo analiza las principales características de la HSI, su relevancia en la investigación científica y sus avances tecnológicos, en particular su integración con técnicas de aprendizaje automático para mejorar la precisión y eficiencia en la detección de contaminación. Queda claro que la HSI no solo tiene el potencial de revolucionar las prácticas de seguridad alimentaria, sino que también desempeña un papel crítico en la mejora de los procesos de toma de decisiones mediante un análisis de datos preciso. La creciente accesibilidad y aplicación global de esta tecnología, junto con métodos avanzados de procesamiento de datos, posicionan a la HSI como una herramienta clave para abordar los desafíos relacionados con la contaminación de alimentos, ofreciendo beneficios significativos tanto para la industria como para la salud pública. Occupational exposure ; Health surveillance ; Health risk Spectroscopy and Chemometric Analyses ; Melamine detection and toxicity ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Reem Alyaqoubi | Batool Alwerfalli | Shahna Manakat Vakeri | S. L. Haridas | M.A. Qassem | Saed Amer
Source:  (article, 2025-04-07)
Field: Materials Science — Materials Chemistry

Air Quality Monitoring and Risk Prediction System Utilizing Integrated Sensor Network to Create a Safer Work Environment in Foundries This project proposes a novel approach to bolster workplace safety in foundries through the implementation of an integrated sensor network for real-time air quality monitoring and risk prediction. Foundry environments are notorious for their hazardous conditions, primarily due to the emission of harmful particulate matter and gases during metal casting processes. Traditional safety measures often fall short of effectively mitigating these risks. Therefore, our system aims to revolutionize safety protocols by providing continuous, accurate monitoring of air quality parameters such as particulate matter concentration, gas emissions, temperature, and humidity. Leveraging advanced data analytics and machine learning algorithms, the system can predict potential risk events and provide timely alerts to workers and management, enabling proactive intervention strategies. By establishing a safer work environment, this innovative solution not only safeguards the health and well-being of foundry workers but also enhances operational efficiency and productivity. This interdisciplinary endeavor amalgamates expertise in sensor technology, data science, and industrial safety to forge a pathway toward sustainable workplace practices in the foundry industry. SAFER ; Work (physics) ; Wireless sensor network ; Computer science ; Quality (philosophy) ; Air quality index ; Risk analysis (engineering) ; Real-time computing ; Embedded system ; Engineering ; Computer security ; Computer network ; Business ; Mechanical engineering Metal Alloys Wear and Properties
Authors: Tam Le | Truyen Nguyen | Hideitsu Hino | Kenji Fukumizu
Source: ArXiv.org (preprint, 2025-02-02)
Field: Materials Science — Materials Chemistry

Scalable Sobolev IPM for Probability Measures on a Graph We investigate the Sobolev IPM problem for probability measures supported on a graph metric space. Sobolev IPM is an important instance of integral probability metrics (IPM), and is obtained by constraining a critic function within a unit ball defined by the Sobolev norm. In particular, it has been used to compare probability measures and is crucial for several theoretical works in machine learning. However, to our knowledge, there are no efficient algorithmic approaches to compute Sobolev IPM effectively, which hinders its practical applications. In this work, we establish a relation between Sobolev norm and weighted $L^p$-norm, and leverage it to propose a \emph{novel regularization} for Sobolev IPM. By exploiting the graph structure, we demonstrate that the regularized Sobolev IPM provides a \emph{closed-form} expression for fast computation. This advancement addresses long-standing computational challenges, and paves the way to apply Sobolev IPM for practical applications, even in large-scale settings. Additionally, the regularized Sobolev IPM is negative definite. Utilizing this property, we design positive-definite kernels upon the regularized Sobolev IPM, and provide preliminary evidences of their advantages for comparing probability measures on a given graph for document classification and topological data analysis. Scalability ; Sobolev space ; Mathematics ; Graph ; Computer science ; Discrete mathematics ; Pure mathematics Material Properties and Failure Mechanisms
Source:  (article, 2025-01-01)
Field: Materials Science — Materials Chemistry

Firmographica: Knowledge Graph and AI-based Framework for Short-Selling Risk Assessment This study investigates how corporate ownership structures affect short selling in publicly traded banking firms by integrating knowledge graph methodologies with regression analysis.By combining graph-based centrality metrics with traditional indicators like firm size and ownership concentration, we systematically identify and rank the factors that influence shortselling activity.Our results indicate that firm size, the degree of ownership concentration, and PageRank centrality are consistently significant predictors of both the level and intensity of short-selling positions.Additionally, insider trading activity is shown to be a critical determinant of short-selling volatility, suggesting that internal market behaviors provide unique predictive value beyond standard financial metrics.The findings underscore the broader potential for graph analytics and machine learning approaches to enhance financial risk modeling and market surveillance.By providing a richer, network-driven perspective, this research contributes to a better understanding of market dynamics, supports the development of more robust governance frameworks, and informs both regulatory policy and investment strategies aimed at promoting transparency and stability in the financial sector. Computer science ; Knowledge graph ; Graph ; Artificial intelligence ; Business ; Data science ; Theoretical computer science Machine Learning in Materials Science ; Big Data and Business Intelligence
Authors: Waleed Almutairi | Qi‐Huang Zheng | Márk Langer | O.M. Oderinde
Source: Frontiers in Oncology (review, 2025-10-23)
Field: Materials Science — Materials Chemistry

Application of immunoPET imaging to enhance head and neck squamous cell carcinoma clinical management ImmunoPET holds promise for patient stratification and early response monitoring in HNSCC. Evidence remains limited, primarily due to small cohorts, heterogeneous protocols, narrow target diversity, and reliance on long-lived tracers. Future research should broaden the immune target, optimize imaging protocols, and develop short-lived tracers (e.g., <sup>18</sup>F, <sup>68</sup>Ga) for broader clinical integration. Head and neck ; Head and neck squamous-cell carcinoma ; Basal cell ; Cancer imaging ; Risk stratification ; Immune system ; Radiation therapy ; Head and neck cancer Anodic Oxide Films and Nanostructures ; Advanced biosensing and bioanalysis techniques ; CAR-T cell therapy research
Authors: Boyu Zhao | Zhengde Xu | Xue Zhang | Zining Kong | Shuyuan Shi | Zhifeng Zhu
Source: ArXiv.org (preprint, 2025-01-27)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Investigation of Sub-configurations Reveals Stable Spin-Orbit Torque Switching Polarity in Polycrystalline Mn3Sn Previous studies have demonstrated the switching of octupole moment in Mn3Sn driven by spin-orbit torque (SOT). However, they have not accounted for the polycrystalline nature of the sample when explaining the switching mechanism. In this work, we use samples with various atomic orientations to capture this polycrystalline nature. We thoroughly investigate their SOT-induced spin dynamics and demonstrate that the polycrystalline structure leads to distinct outcomes. Our findings reveal that configuration II, where the Kagome plane is perpendicular to the spin polarization, exhibits robust switching with stable polarity, whereas the signals from various sub-configurations in configuration I cancel each other out. By comparing our findings with experimental results, we pinpoint the primary sources contributing to the measured AHE signals. Additionally, we establish a dynamic balance model that incorporates the unique properties of Mn3Sn to elucidate these observations. Our study highlights the essential role of the polycrystalline nature in understanding SOT switching. By clarifying the underlying physical mechanisms, our work resolves the longstanding puzzle regarding the robust SOT switching observed in Mn3Sn. Polarity (international relations) ; Condensed matter physics ; Crystallite ; Torque ; Orbit (dynamics) ; Spin (aerodynamics) ; Physics ; Materials science ; Chemistry ; Engineering ; Quantum mechanics ; Aerospace engineering ; Thermodynamics Heusler alloys: electronic and magnetic properties ; Shape Memory Alloy Transformations ; Magnetic and transport properties of perovskites and related materials
Authors: Juntao Xu | Chenyu Zhu | Yan Pan | Han Zhang | Chao Wu | Hongqiang Li
Source: Micromachines (article, 2025-12-29)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Topology Design of Reconfigurable Intelligent Metasurfaces Based on Equivalent Circuit Model Previous studies on reconfigurable intelligent metasurface (RIS) design have primarily relied on full-wave electromagnetic simulation software, which often incurs high computational costs and lacks clear design direction. The design of multi-bit RIS remains challenging and there is currently no suitable systematic method for selecting the corresponding tuning devices. To overcome these limitations, this article proposes a novel equivalent circuit-based approach to RIS design. In contrast to the conventional approach, where the equivalent circuit model is derived from post-design evaluation of the scattering properties of RIS, our work is entirely driven by the equivalent circuit model from the outset to accomplish the unit cell design. A complete workflow as well as details of each constituent step are presented for the topology design of RIS based on equivalent circuit topology. Building on this circuit topology, a 3-bit reflective phase reconfigurable unit cell is developed based on a tunable band-stop filter circuit. We conducted adjustable phase verification experiments and beam deflection experiments. The consistency between the experimental results and circuit theory demonstrates the feasibility and practicality of the equivalent circuit method of RIS design. This circuit-to-structure methodology provides a physically interpretable and systematic framework for designing RIS with arbitrary electromagnetic responses, offering new insights into RIS design. Equivalent circuit ; Topology (electrical circuits) ; Circuit design ; Workflow ; Network analysis ; Network topology ; Consistency (knowledge bases) ; Circuit extraction Metamaterials and Metasurfaces Applications ; Advanced Wireless Communication Technologies ; Advanced Antenna and Metasurface Technologies
Authors: Ridho Darmawan | Awaly Ilham Dewantoro | Efri Mardawati
Source: International Journal of Applied Sciences and Smart Technologies (article, 2025-12-01)
Field: Chemistry — Inorganic Chemistry

Coconut Shell-Based Briquettes for Sustainable Energy: A Bibliometric Study on Biomass Mixtures and Binder Materials Coconut shell is one of the potential biomass resources that has been widely developed as a raw material for briquettes to support renewable energy initiatives and circular economy practices. This study aimed to explore the development, research focus, and future directions of cocomut shell briquette through a systematic literature review. The Methodi Ordinatio approach was employed for analysis, resulting in a final portfolio of 134 selected documents, which were the further examined to identify trends and research gaps. The findings showed that mixturing coconut shell with other biomass such as from wood-based and agricultural-based residues could enhance the briquette performance. Moreover, alternative binders such as lignocellulosic carbohydrate and its derivatives, plant sap, and waste cooking oil offered promising subsitutes for food-based materials. Oily biomass, such as eucalyptus wastes and pine resin, was also found to improve briquette performance due to its volatile content. In addition, the integration of automation technologies based on microcontrolers and the Internet of Things (IoT) began to applied to improve production efficiency and consistency. It is expected that the findings of this study can serve as a foundation for future development focused on material formulation and technological innovations for coconut shell-based briquette production that are more efficient, sustainable, and responsive to future energy needs. Briquette ; Raw material ; Biomass (ecology) ; Renewable energy ; Biofuel ; Renewable resource ; Production (economics) Coconut Research and Applications ; Thermochemical Biomass Conversion Processes
Authors: Sachin Lonare
Source: International Journal For Multidisciplinary Research (review, 2025-06-15)
Field: Materials Science — Materials Chemistry

Thermoelasticity in Modern Materials: A Review of Linear and Nonlinear Mathematical Models Thermoelasticity, the mathematical study of the interaction between mechanical deformations and thermal effects in solids, plays a foundational role in modeling the behavior of advanced engineering systems and materials. This review presents a comparative analysis of linear and nonlinear thermoelastic models, emphasizing their mathematical formulations, physical assumptions, and practical applications. Linear thermoelasticity is explored in the context of classical elasticity theory, with governing equations derived under small strain and constant material property assumptions. Nonlinear thermoelasticity is then examined as a generalization that incorporates large deformations, temperature-dependent parameters, and thermal memory effects. Key developments in theoretical approaches, including micropolar continua, fractal models, and hybrid data-driven frameworks, are discussed with reference to recent literature. Applications in structural engineering, MEMS/NEMS, aerospace systems, and smart materials are used to highlight the advantages and limitations of each modeling regime. The paper concludes by outlining challenges in computational efficiency, experimental validation, and multiphysics integration, offering future directions for research at the intersection of applied mathematics and material science. Multiphysics ; Nonlinear system ; Thermoelastic damping ; Context (archaeology) ; Aerospace ; Computer science ; Computational Science and Engineering ; Mathematical model ; Thermal ; Mechanical engineering ; Applied mathematics ; Mathematics ; Finite element method ; Engineering ; Structural engineering ; Physics ; Aerospace engineering Nonlocal and gradient elasticity in micro/nano structures ; Thermoelastic and Magnetoelastic Phenomena ; Heat Transfer and Optimization
Authors: Humeera Tazeen | Anne Joice | Talha Tufaique | C. Igathinathane | Ademola Ajayi-Banji | Zhao Zhang | Craig W. Whippo | Drew A. Scott | John Hendrickson | David W. Archer | Lester O. Pordesimo | S. Sokhansanj
Source: AgriEngineering (article, 2025-06-16)
Field: Chemistry — Analytical Chemistry

Jasmine Flower Color Degradation User-Coded Computer Vision Image Analysis Tool and Kinetics Modeling Jasmine (Jasminum sambac (L.) Ait.) flowers, valued for their fragrance and essential oils, are extensively used in the flavor, cosmetics, and pharmaceutical industries. However, their useful life is short due to rapid color degradation and browning caused by photo-oxidative stress induced by environmental factors like light, temperature, and humidity. Therefore, the significant reduction in the visual appeal, quality, and economic value necessitates the measurement of temporal color degradation to evaluate the shelf life for jasmine flowers. A developed open-source ImageJ plugin program quantified the color degradation of jasmine petals and pedicles over 25 h. Petal area (&gt;19 mm2) cutoff separated the pedicles. Color degradation kinetics models, including zeroth-order, first-order, exponential decay, Page, and Peleg, using several color indices, were developed, and their performances were evaluated. VEG, hue, chroma, COM, and CIVE color indices were found suitable for kinetics modeling. Peleg and Page models (R2≥0.99) are suitable for petals and pedicles, respectively. Jasmine petals retained their color integrity for longer periods than pedicles. This study underscores the potential of computer vision analysis and kinetic modeling for evaluating flower quality after harvest. The color degradation dynamics were accurately characterized by the kinetic models, which provide actionable insights for optimizing storage and handling practices. Degradation (telecommunications) ; Computer science ; Image (mathematics) ; Computer vision ; Artificial intelligence ; Computer graphics (images) ; Telecommunications Spectroscopy and Chemometric Analyses ; Leaf Properties and Growth Measurement ; Remote Sensing and Land Use
Authors: O.I. Kit | E. M. Frantsiyants | И. П. Кодониди | I.V. Kaplieva | E.K. Alekseev | А. А. Глушко | P.S. Kachesova | S. Yu. Filippova | Irina V. Mezhevova | A.S. Chiryapkin | Alla I. Shikhlya­rova | E. V. Shalashnaya | Viktoriya L. Volkova
Source: Современные проблемы науки и образования (Modern Problems of Science and Education) (article, 2025-01-01)
Field: Chemistry — Organic Chemistry

ANTITUMOR ACTIVITY OF A NOVEL PYRIMIDIN-4(1H)-ONE DERIVATIVE IN NON-SMALL CELL LUNG CANCER MODELS IN VITRO -4(1H)- INVITRO .. 1 , .. 1 , .. 2 , .. 1 , .. 1 , .. 2 , .. 1 , .. 1 , .. 1 , .. 2 , .. 1 , .. 1 , In vitro ; Derivative (finance) ; Lung cancer ; Cancer ; Cancer research ; Chemistry ; Computational biology ; Medicine ; Oncology ; Biology ; Internal medicine ; Biochemistry Synthesis and biological activity ; Synthesis and Reactions of Organic Compounds ; Multicomponent Synthesis of Heterocycles