jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Mohammed Abdulla | Meftah Hrairi | Abdul Aabid | Nur Azam Abdullah | Muneer Baig
Source: Actuators (article, 2024-10-02)
Field: Materials Science — Materials Chemistry

Comparative Analysis of Active Bonded Piezoelectric Repair Systems for Damaged Structures under Mechanical and Thermo-Mechanical Loads Active repair systems employing piezoelectric (PZT) patches have emerged as promising solutions for mitigating crack propagation and enhancing structural integrity in various engineering applications. However, the existing literature predominantly focuses on the application of PZT patches for repairing structures under mechanical loading. In this study, a finite element analysis (FEA) is employed to investigate the repair of a centre-cracked aluminium plate under both mechanical and thermo-mechanical loading conditions. This study explores the influence of key parameters, including temperature, PZT patch thickness, type of PZT material, adhesive material, and adhesive thickness, on the structural integrity and crack propagation behaviour. The results reveal significant differences in stress distribution and crack propagation tendencies under varying loading conditions and parameter settings. These findings emphasize the necessity of considering thermo-mechanical loading conditions and parameter variations when designing effective active repair systems. In conclusion, this study provides valuable insights into optimizing PZT patch-based repair strategies for improved structural integrity and crack mitigation in aerospace and other engineering applications under diverse loading scenarios. Piezoelectricity ; Materials science ; Mechanical load ; Structural engineering ; Composite material ; Mechanical system ; Mechanical engineering ; Engineering Structural mechanics and materials ; Ultrasonics and Acoustic Wave Propagation ; Elasticity and Wave Propagation
Authors: Meng Lu | Xuerui Mao | Luca Brandt | Jian Deng
Source: Physical Review Research (article, 2024-10-02)
Field: Materials Science — Surfaces, Coatings and Films

Droplet detachment from a vertical filament with one end clamped Understanding whether a droplet adheres to or detaches from a flexible filament upon axial impact is of significant interest, particularly in the context of raindrop impact on natural surfaces. This process involves dynamic buckling followed by mode coarsening, dissipating the initial droplet kinetic energy and converting the remaining into elastic energy of the filament. To elucidate this phenomenon, we construct two phase diagrams, one while fixing the filament height and the other the droplet diameter. Notably, we observe that the energy conversion rate is inversely proportional to a Cauchy number, defining the transition between attached and detached droplet in the filament length–falling height diagram. This enables us to derive an expression for the critical falling height as a function of the filament parameters, accounting for the energy conversion rate, which emerges as a key factor for droplet detachment. Published by the American Physical Society 2024 Protein filament ; Materials science ; Composite material Surface Modification and Superhydrophobicity ; Fluid Dynamics and Heat Transfer ; Nanomaterials and Printing Technologies
Authors: Linlin Bai | Tao Chen | Junhong Chen | Shuai Yu | Wei Yu
Source: Autex Research Journal (article, 2024-01-01)
Field: Materials Science — Polymers and Plastics

Modeling of virtual clothing and its contact with the human body Abstract Aiming to tackle the issue of virtual fitting, this study proposes an integrated solution encompassing key stages, such as fabric modeling, virtual stitching algorithms, and clothing–body contact mechanisms, with focus on simulating and calculating the clothing pressure. A fabric model based on a particle–spring system is developed, with an emphasis on exploring the relationship between spring coefficients to achieve parametric independence of the virtual fabric. To turn the fabric into clothes, an algorithm for stitch line generation is introduced along with discussions on springs with constraint to improve the rendering accuracy and enhance effects. For simulating the clothing–body contact, a body characterization model consisting of slices is constructed and utilized to compute fabric deformation and its pressure exerted on the human body. Validation tests are conducted by comparing calculated pressures with real measurements obtained from a mannequin, demonstrating an error of 10.9% for the fit size of clothing and below 10% for smaller sizes. These results indicate that the proposed solution not only enables realistic visual effects of virtual clothing but also generates meaningful pressure values based on fabric properties, clothing patterns, and sizes. This lays a solid foundation for the valuable assessment and prediction of clothing pressure in virtual fitting scenarios. Clothing ; Image stitching ; Computer science ; Parametric statistics ; Simulation ; Engineering drawing ; Engineering ; Artificial intelligence ; Mathematics Textile materials and evaluations ; 3D Shape Modeling and Analysis ; Computer Graphics and Visualization Techniques
Authors: S. N. Hettiarachchi | K. Suban | S. Himaanthri | S. D. F. Aththachchi | C. N. Wickramarachchi | T. S. G. Peiris
Source: SLIIT Business Review (article, 2024-02-27)
Field: Chemistry — Inorganic Chemistry

Time Series Model to Forecast Fresh Coconut Exports from Sri Lanka Coconut accounts for approximately 12% of all agricultural produce in Sri Lanka with the total land area under cultivation covering 409, 244 hectares ranking second to rice production. The primary regions for coconut cultivation are the Puttalam and Kurunegala districts in North-Western Province and Gampaha district in the Western Province, forming what is known as the Coconut Triangle. This region accounts for 232,270 hectares (50.94%) of the overall coconut cultivation area. The remaining coconut cultivation areas are found in the Southern Province, specifically in the districts of Galle (13,833 hectares), Matara (14,946 hectares), and Hambantota (25,837 hectares), and in non-traditional regions of the Eastern and Northern provinces. The annual coconut production varies between 2,800 to 3,000 million nuts. Having advanced knowledge of exporting coconuts offers numerous advantages to Sri Lanka, particularly in terms of establishing forward contracts with other countries. Based on secondary data of annual fresh coconut exports from 1981 to 2020 obtained from the Coconut Development Authority (CDA) of Sri Lanka, the paper developed ARIMA (2,1,0) model to forecast export. The model was selected out of three parsimonious models which were identified from the Sample Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) of the stationary series and a comparison of significant parameters and lowest values of Akaike Information Criterion (AIC), Schwarz Bayesian Information Criterion (SBIC) and Hannan-Quinn Information Criterion (HQIC). The errors of the fitted model were found to be random and constant variance. The model was validated using 2021 and 2022 data. The percentage errors for 2021 and 2022 are 20.23% and -29.57% respectively. The predictions for 2023 and 2024 are 14696 and 15052 respectively. The model can be used effectively by the Coconut Development Authority for decision-making. However, it is suggested to develop the model further to reduce the percentage error. Keywords: ARIMA model, Forecast, Fresh Coconut Exports and Validate Hectare ; Autoregressive integrated moving average ; Sri lanka ; Akaike information criterion ; Partial autocorrelation function ; Mathematics ; Agriculture ; Agricultural science ; Geography ; Ranking (information retrieval) ; Statistics ; Toxicology ; Forestry ; Time series ; Biology ; Ecology Coconut Research and Applications
Authors: Tamme Claus | Gaurav Achuda | Jonas Bünger | Silvia Richter | Manuel Torrilhon
Source: Journal of Computational and Theoretical Transport (article, 2024-01-02)
Field: Materials Science — Surfaces, Coatings and Films

An Adjoint Method for High-Resolution EPMA Based on the Spherical Harmonics (PN) Model of Electron Transport Electron Probe Microanalysis (EPMA) is a nondestructive technique to determine the chemical composition of material samples in the micro-to nanometer range. Based on intensity measurements of x-radiation, the reconstruction of the material composition and structure poses an inverse problem. The reconstruction methods currently applied are based on models that assume a homogeneous or a layered structure of the studied material. To increase the spatial resolution of reconstruction in EPMA the combination of a more sophisticated reconstruction method, which is based on a model that allows complex material structure, together with multiple measurements with varying beam configurations is required. We present a deterministic k-ratio model that is based on the P N model, an approximation of the radiative transfer equation for electron transport. Our goal is to approximate a maximum likelihood solution of the inverse problem using gradientbased optimization. We detail the application of the model in the context of algorithmic differentiation, in particular by deriving its continuous adjoint formulation. Algorithmic differentiation provides the flexibility to adapt the reconstruction method to various material parametrizations and thus to regularize and take into account prior knowledge. Through examples, we verify our implementation and demonstrate the flexibility of the reconstruction/ differentiation method. Electron microprobe ; Spherical harmonics ; Harmonics ; Resolution (logic) ; Electron ; Physics ; Computational physics ; Mathematical analysis ; Materials science ; Mathematics ; Computer science ; Nuclear physics ; Quantum mechanics ; Metallurgy Electron and X-Ray Spectroscopy Techniques ; Advancements in Photolithography Techniques ; Advanced Chemical Physics Studies
Authors: Charles Luo
Source: arXiv (Cornell University) (preprint, 2024-12-21)
Field: Materials Science — Materials Chemistry

Has LLM Reached the Scaling Ceiling Yet? Unified Insights into LLM Regularities and Constraints Large Language Models (LLMs) have demonstrated remarkable capabilities, yet their scalability raises a critical question: Have we reached the scaling ceiling? This paper addresses this pivotal question by developing a unified theoretical framework that integrates mathematical and statistical insights to explain the scaling dynamics of LLMs. We present: 1. Central Limit Theorem (CLT) for Hidden Representations: We show that noise in hidden representations scales inversely with context size, explaining stabilization effects and the limits of context length improvements. 2. Bias-Variance Decomposition: We decompose next-token prediction loss into irreducible entropy, capacity-driven bias, and finite sample variance, revealing trade-offs where scaling yields diminishing returns. 3. Emergent SNR Thresholds: By defining signal-to-noise ratio (SNR), we quantify how capabilities emerge abruptly once SNR surpasses a threshold, offering insights into when scaling becomes less effective. Through this framework, we conclude that while LLMs have not reached an absolute scaling ceiling, practical constraints are increasingly prominent: diminishing returns, resource inefficiencies, and data limitations. Future progress will require a shift from brute-force scaling to innovations in architecture, data quality, and training paradigms. This work provides a roadmap for guiding the efficient development of next-generation LLMs and advancing the field beyond traditional scaling strategies. Keywords: Large Language Models; Scaling Ceiling; Central Limit Theorem; Bias-Variance Trade-Off; Signal-to-Noise Ratio; Emergent Capabilities Ceiling (cloud) ; Scaling ; Glass ceiling ; Computer science ; Political science ; Engineering ; Mathematics ; Geometry ; Structural engineering Fusion materials and technologies ; Metallurgy and Material Forming ; Tunneling and Rock Mechanics
Authors: Vitor Hugo de Souza | Adriano Mendonça Souza | Cláudia Aline de Souza Ramser
Source: Revista de Economia e Sociologia Rural (article, 2024-01-01)
Field: Chemistry — Analytical Chemistry

Temperature and relative humidity dynamic effect inside a soybean metal silos storage: evidence from Brazil Abstract The research main purpose is to realize a short-term forecast temperature values inside metal soybean storage silos using the variables temperature and relative humidity, to predict and analyze the impulse response using vector autoregressions (VAR) with the Seemingly estimator. Unrelated Regression (SUR). The soybean storage silo is considered a multivariate system, as inside the metallic structure there are several temperature and relative humidity sensors, both located internally and externally. As a multivariate system, equations were adjusted using the vector autoregressive methodology, to capture external shocks and their influence on each variable and, determine how long this impact will take effect on the system. The forecast and response impulse show in advance the moment in which that the aeration process must be started. The system of equations points out that the prototype's external variables represented by temperature 7 (T7) and humidity (U7) directly influence other variables. After the occurrence of an external shock, endogenous variables take 4 periods of time to stabilize. An external action, whether naturally or through aeration, will take around eight hours to have an effective change in temperature and humidity. The forecast provides advance knowledge to carry out aeration in the silo, in order to keep the temperature and relative humidity controlled. As 6 periods of time are needed for the response to be carried out, ranging from hours to 12 hours, given that the observations were collected every 2 hours, this time was necessary to stabilize the variables. Keep these variables at target values to add commercial value to the product. Silo ; Relative humidity ; Information silo ; Environmental science ; Humidity ; Econometrics ; Mathematics ; Meteorology ; Engineering ; Geography ; Mechanical engineering Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Food Drying and Modeling
Authors: Joven C. Serato | Jojames Arnaldo G. Gaddi | Emelyn S. Digal | Mary Jane C. Labor | Miamie C. Villa | Queenie L. Bermudez
Source: Current Journal of Applied Science and Technology (article, 2024-02-16)
Field: Chemistry — Inorganic Chemistry

Acceptability of Coconut Meat Sisig Recipe in St. Paul University Surigao, Philippines This study aimed to assess the acceptability of the Coconut Meat Sisig Recipe among Senior High School teachers. We employed a descriptive research design and utilized a survey technique for data collection. The data were collected through an adapted and modified questionnaire. We used Frequency Count and Percentage Distribution, Mean and Standard Deviation, and Analysis of Variance (ANOVA) as statistical tools. The results indicated that the Coconut Meat Sisig recipe is highly acceptable in appearance, color, aroma, taste, and texture. The innovative incorporation of coconut meat as the primary ingredient received a positive reception, demonstrating the dish's potential for favorable adoption in the culinary preferences of this target group. Furthermore, the Coconut Meat Sisig recipe enjoyed universal acclaim, with slight variations in perception related to educational backgrounds concerning texture. Given its broad acceptance among Senior High School teachers, it is recommended to promote the Coconut Meat Sisig recipe as an innovative and attractive option for school canteens. Recipe ; Ingredient ; Aroma ; Descriptive statistics ; Taste ; Mathematics ; Food science ; Agricultural science ; Biotechnology ; Geography ; Statistics ; Biology Coconut Research and Applications
Authors: Qiangbo Zhang | Zeqing Yu | Mengguang Wang | Yiyang Liu | Changwei Zhang | Chang Wang | Zhenrong Zheng
Source: arXiv (Cornell University) (preprint, 2024-04-04)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Centimeter-Scale Achromatic Hybrid Metalens Design: A New Paradigm Based on Differentiable Ray Tracing in the Visible Spectrum Single metalenses are limited by their physical constraints, precluding themselves from achieving high numerical aperture across a wide visible spectral band in large-aperture applications. A hybrid system that integrates a metalens with a refractive lens can address this issue, yet previous designs lacked sufficient flexibility. Here, by reanalyzing the generalized Snell's law, we introduce a new paradigm for the hybrid metalens design based on differentiable ray tracing. Through joint optimization of the phase distribution of the metalens and refractive lens parameters, our system achieves achromatic performance within the broad spectral range of 440-700 nm, with an aperture of 1 cm and an f-number of 1.4. Owing to the differentiable nature of the proposed system, it can be seamlessly integrated as the optical front-end into any differentiable computational imaging system. Our system offers unprecedented opportunities for the advancement of metalenses in innovative optical design and computational imaging domains. Achromatic lens ; Centimeter ; Differentiable function ; Tracing ; Ray tracing (physics) ; Scale (ratio) ; Spectrum (functional analysis) ; Optics ; Physics ; Computer science ; Mathematics ; Mathematical analysis ; Astronomy ; Quantum mechanics Metamaterials and Metasurfaces Applications ; Photonic Crystals and Applications ; Modular Robots and Swarm Intelligence
Authors: Günter Gauglitz | Michael Bodensteiner | Pascal Bohleber | David Clases | Marcel Dahms | Carsten Engelhard | Markus Haider | Heiko Hayen | Regine Herbst‐Irmer | Martin Jäger | Annemarie E. Kramell | Robin Legner | Frank‐Michael Matysik | Alexander Pöthig | Matthias Rädle | Stephan Seifert | Georg Steinhauser | Kathrin Wolter
Source: Nachrichten aus der Chemie (article, 2024-03-29)
Field: Chemistry — Analytical Chemistry

Trendbericht Analytische Chemie 2024 Abstract Mehrdimensionale Trenntechniken sowie Kopplungstechniken verbessern weiter die Auflösung in der Analytik. In der Elementanalytik beeindrucken neue Entwicklungen der Massenspektrometrie mit induktiv gekoppeltem Plasma, in der Archäometrie zerstörungsfreie In‐situ‐Analysen. Der 3‐D‐Druck treibt die elektroanalytische Forschung voran, und die Prozessanalytik setzt auf Lab‐on‐a‐Chip und vermeldet Neues bei der Raman‐Spektroskopie mit Flüssigkernlichtleitern. Chemistry Analytical chemistry methods development ; Mass Spectrometry Techniques and Applications ; Various Chemistry Research Topics
Authors: Zakaria Bouhoun | Ahmed Allalı | Riccardo Cocci | Mohamad Assaad | Alexandra Plancon | Frederic Godest | K. Kondratenko | Julien Rodriguez | Francesco Vitillo | Olivier Malhomme | Lies Benmiloud Bechet | R. Plana
Source: EPJ Web of Conferences (article, 2024-01-01)
Field: Materials Science — Materials Chemistry

CurieLM: Enhancing Large Language Models for Nuclear Domain Applications Large Language Models (LLMs), such as the Mistral model, have exhibited remarkable performance across diverse tasks. However, their efficacy in nuclear applications remains constrained by a lack of domain-specific knowledge and an inability to effectively leverage that knowledge. Nuclear-related tasks, including safety assessments and requirement analyses, pose unique challenges due to the intricate domain expertise and diverse constraints involved. To address these limitations, we introduce CurieLM, an LLM specifically tailored for the nuclear domain. CurieLM builds upon the Mistral model, enhancing its capabilities through domain-specific fine-tuning. Our team of nuclear engineers overcame the initial hurdle of accessing high-quality nuclear data, enabling CurieLM to comprehend and accurately respond to nuclear-specific instructions. This manuscript outlines the development and optimization process of CurieLM, marking a significant step toward enhancing nuclear-related natural language processing tasks. Experimental results demonstrate a 13% performance improvement over base LLMs, underscoring the effectiveness of our approach. Domain-specific LLMs like CurieLM hold a great potential across various applications, and this study sets the stage for further exploration in this emerging field. Domain (mathematical analysis) ; Computer science ; Mathematics Graphite, nuclear technology, radiation studies ; Photovoltaic Systems and Sustainability ; Nuclear and radioactivity studies
Authors: Leheng Cai | Qirui Hu
Source: arXiv (Cornell University) (preprint, 2024-01-31)
Field: Materials Science — Materials Chemistry

From Sparse to Dense Functional Data: Phase Transitions from a Simultaneous Inference Perspective We aim to develop simultaneous inference tools for the mean function of functional data from sparse to dense. First, we derive a unified Gaussian approximation to construct simultaneous confidence bands of mean functions based on the B-spline estimator. Then, we investigate the conditions of phase transitions by decomposing the asymptotic variance of the approximated Gaussian process. As an extension, we also consider the orthogonal series estimator and show the corresponding conditions of phase transitions. Extensive simulation results strongly corroborate the theoretical results, and also illustrate the variation of the asymptotic distribution via the asymptotic variance decomposition we obtain. The developed method is further applied to body fat data and traffic data. Perspective (graphical) ; Inference ; Computer science ; Artificial intelligence Machine Learning in Materials Science
Authors: Xingting Liu | Haiqi Wang | Zhuo Gao | Xutao Han
Source: Frontiers in Energy Research (article, 2024-11-20)
Field: Materials Science — Materials Chemistry

Research on fault localization of distribution transformers based on frequency response analysis and support vector machine (SVM) Distribution transformers are vital to the stability of the power system, but long-term operation and environmental factors can cause distribution transformers to discharge, posing a potential threat. The impulse voltage withstand test rigorously evaluates the insulation of the transformer windings, to prevent accidents caused by insulation breakdown. However, due to the small size of distribution transformers, impulse voltage withstand test breakdown usually cause less damage, and it is challenging to locate the point of failure using traditional methods such as spatial positioning or disassembly. Therefore, the study of the discharge location method based on the characteristic value of the frequency response waveform is of great significance to find and deal with potential faults. This paper discusses the waveform characteristics of different discharge signals transmitted from different positions of the winding to the end. By analyzing the frequency response of different breakdown current signals measured at the end of the transformer winding, support vector machine is used to identify the breakdown position of the distribution transformer. The approximate location of the fault was identified with more than 80% accuracy. The feasibility and effectiveness of this localization method are verified by experiments. Waveform ; Transformer ; Distribution transformer ; Electromagnetic coil ; Support vector machine ; Engineering ; Voltage ; Impulse (physics) ; Electronic engineering ; Electrical engineering ; Reliability engineering ; Computer science ; Artificial intelligence ; Physics High voltage insulation and dielectric phenomena ; Power Transformer Diagnostics and Insulation ; Electrical Fault Detection and Protection