jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Frédéric Schmidt | Bikram Koirala | François Andrieu
Source: IEEE Sensors Journal (article, 2024-09-24)
Field: Chemistry — Spectroscopy

Determination of Volumetric Abundance of Intimate Mixture Using Bayesian MCMC The quantitative estimation of volumetric abundance of powder mixture is the basis of quantitative remote sensing analysis. Here, we propose to analyze a unique laboratory measurements set, with precise composition, grain size, and volumetric abundance. We first propose a method to estimate the optical constant of materials, knowing the pure endmember spectra and their grain size. Then, we propose a method to transfer the measurement uncertainties to the volumetric abundance, based on the Bayesian approach and the full Hapke radiative transfer model. Using this approach, we are able to estimate grain size, volumetric abundance, and surface roughness. The results show that this approach is able to well estimate the correct volumetric abundance with an uncertainty of 23% and grain size with a ratio uncertainty of 3.0, i.e., uncertainties in log10 (grain size) = 0.48. The numerical cost of the MCMC is quite large (a few minutes per spectra) but still reasonable to treat a hyperspectral image with the gain of robust handling of nonlinearities and propagating uncertainty. Markov chain Monte Carlo ; Bayesian probability ; Abundance (ecology) ; Statistics ; Computer science ; Environmental science ; Econometrics ; Artificial intelligence ; Mathematics ; Biology ; Ecology Mass Spectrometry Techniques and Applications
Source: Acta Montanistica Slovaca (article, 2024-10-12)
Field: Materials Science — Ceramics and Composites

Investigating cross-docking criteria for raw materials with hybrid MCDM The cross-docking process involves unloading raw materials from incoming vehicles and immediately loading them onto outgoing vehicles. This can greatly improve supply chain operations and expedite transportation to the factory. By minimizing warehouse storage expenses, space requirements, and inventory management, the process can be streamlined effectively. In industries where production profiles need to be responsive to market demands, the location of the cross-docking facility and transportation planning are crucial. This article aims to investigate the criteria for selecting a cross-docking location, using a case study of Arta Profile Company in Ardabil. The research population includes all industrial engineers and production planners in the company, with 10 industry experts selected for this study. The analytic network process (ANP) and grey complex proportional assessment (COPRAS-G) methods were used to compare and prioritize cross-docking locations. Additionally, the fuzzy DEMATEL method was used to determine the strength of connections between different locations. The COPRAS-G approach helps decision-makers make informed decisions by evaluating different options and their importance. The industry experts identified 28 criteria for this study. The results from the network analysis method showed that the most important criterion is the vehicle routing problem (VRP), with a value of 0.46. According to the ANP technique, strategic decision-making is the best option. The fuzzy DEMATEL method revealed that distribution centers are the most important factor, followed by reduced delivery/distribution operations, and finally, the cost of late or early delivery. Multiple-criteria decision analysis ; Docking (animal) ; Biochemical engineering ; Computer science ; Engineering ; Operations research ; Medicine Advanced ceramic materials synthesis ; Iron and Steelmaking Processes ; Recycling and Waste Management Techniques
Authors: Xiaochu Luo | Xiaobing Qi | Luo Zhao | Zhonghao Li | Ruiquan Liao | Xingkai Zhang
Source: Fluid dynamics & materials processing (article, 2024-01-01)
Field: Chemistry — Physical and Theoretical Chemistry

A Novel Method for Determining the Void Fraction in Gas-Liquid Multi-Phase Systems Using a Dynamic Conductivity Probe Conventional conductivity methods for measuring the void fraction in gas-liquid multiphase systems are typically affected by accuracy problems due to the presence of fluid flow and salinity. This study presents a novel approach for determining the void fraction based on a reciprocating dynamic conductivity probe used to measure the liquid film thickness under forced annular-flow conditions. The measurement system comprises a cyclone, a conductivity probe, a probe reciprocating device, and a data acquisition and processing system. This method ensures that the flow pattern is adjusted to a forced annular flow, thereby minimizing the influence of complex and variable gas-liquid flow patterns on the measurement results; Moreover, it determines the liquid film thickness solely according to circuit connectivity rather than specific conductivity values, thereby mitigating the impact of salinity. The reliability of the measurement system is demonstrated through laboratory experiments. The experimental results indicate that, in a range of gas phase superficial velocities 5–20 m/s and liquid phase superficial velocities 0.079–0.48 m/s, the maximum measurement deviation for the void fraction is 4.23%. Conductivity ; Materials science ; Void (composites) ; Fraction (chemistry) ; Two-phase flow ; Liquid phase ; Porosity ; Mechanics ; Physics ; Chromatography ; Thermodynamics ; Chemistry ; Composite material ; Flow (mathematics) Electrostatics and Colloid Interactions
Authors: Bhagwat Prasad | Zubida M. Al‐Majdoub | Christine Wegler | Amin Rostami‐Hodjegan | Brahim Achour
Source: Drug Metabolism and Disposition (review, 2024-05-31)
Field: Chemistry — Spectroscopy

Quantitative Proteomics for Translational Pharmacology and Precision Medicine: State of The Art and Future Outlook Proteomics ; Translational medicine ; Computational biology ; Data science ; Medicine ; Computer science ; Biology ; Pathology ; Biochemistry Advanced Proteomics Techniques and Applications ; Advanced Biosensing Techniques and Applications ; Computational Drug Discovery Methods
Authors: Kiswara Agung Santoso | Ahmad Kamsyakawuni | Siti Virna Rohmatul Izza
Source: Journal of Computers and Digital Business (article, 2024-09-30)
Field: Chemistry — Analytical Chemistry

Comparison Classification Of Tomatoes Ripeness Based On RGB, HSV And CMYK Colors Based On Correlation Coefficient This article discusses the classification of tomato fruit maturity based on color space. Several studies have been conducted to measure maturity levels using RGB and HSV color spaces. In this article, researchers classify the ripeness of tomatoes using the CMYK color space, which researchers have never done before. Next, the classification results of the CMYK color space are compared with the RGB and HSV color spaces. The CMYK color space is a secondary color commonly seen by the human eye. CMYK colors are colors produced from a combination of RGB colors. Comparison of classification results based on CMYK, RGB, and HSV color spaces was carried out using the correlation coefficient and mean square error (MSE). The correlation coefficient is a method that is often used to measure the similarity between 2 images, where the closer to 0 the correlation value, the better Ripeness ; HSL and HSV ; RGB color model ; Correlation coefficient ; Mathematics ; Statistics ; Artificial intelligence ; Computer science ; Food science ; Medicine ; Chemistry Spectroscopy and Chemometric Analyses
Authors: Richard Mcnair | Oliver E. Jensen | Julien R. Landel
Source: Journal of Fluid Mechanics (article, 2024-04-30)
Field: Materials Science — Materials Chemistry

Confinement-induced drift in Marangoni-driven transport of surfactant: a Lagrangian perspective Successive drops of coloured ink mixed with surfactant are deposited onto a thin film of water to create marbling patterns in the Japanese art technique of Suminagashi. To understand the physics behind this and other applications where surfactant transports adsorbed passive matter at gas–liquid interfaces, we investigate the Lagrangian trajectories of material particles on the surface of a thin film of a confined viscous liquid under Marangoni-driven spreading by an insoluble surfactant. We study a model problem in which several deposits of exogenous surfactant simultaneously spread on a bounded rectangular surface containing a pre-existing endogenous surfactant. We derive Eulerian and Lagrangian formulations of the equations governing the Marangoni-driven surface flow. Both descriptions show how confinement can induce drift and flow reversal during spreading. The Lagrangian formulation captures trajectories without the need to calculate surfactant concentrations; however, concentrations can still be inferred from the Jacobian of the map from initial to current particle position. We explore a link between thin-film surfactant dynamics and optimal transport theory to find the approximate equilibrium locations of material particles for any given initial condition by solving a Monge–Ampère equation. We find that as the endogenous surfactant concentration $\delta$ vanishes, the equilibrium shapes of deposits using the Monge–Ampère approximation approach polygons with corners curving in a self-similar manner over lengths scaling as $\delta ^{1/2}$ . We explore how Suminagashi patterns may be produced by using computationally efficient successive solutions of the Monge–Ampère equation. Marangoni effect ; Pulmonary surfactant ; Marangoni number ; Mechanics ; Eulerian path ; Scaling ; Physics ; Lubrication theory ; Lagrangian ; Classical mechanics ; Materials science ; Thermodynamics ; Lubrication ; Geometry ; Mathematics Pickering emulsions and particle stabilization ; Diffusion and Search Dynamics ; Micro and Nano Robotics
Authors: Jonas B. Profe | Jiawei Yan | Karim Zantout | Philipp Werner | Roser Valentí
Source: TUbilio (Technical University of Darmstadt) (preprint, 2024-10-01)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Multi-orbital two-particle self-consistent approach -- strengths and limitations Extending many-body numerical techniques which are powerful in the context of simple model calculations to the realm of realistic material simulations can be a challenging task. Realistic systems often involve multiple active orbitals, which increases the complexity and numerical cost because of the large local Hilbert space and the large number of interaction terms or sign-changing off-diagonal Green's functions. The two-particle self-consistent approach (TPSC) is one such many-body numerical technique, for which multi-orbital extensions have proven to be involved due to the substantially more complex structure of the local interaction tensor. In this paper we extend earlier multi-orbital generalizations of TPSC by setting up two different variants of a fully self-consistent theory for TPSC in multi-orbital systems. We first investigate the strengths and limitations of the approach analytically and then benchmark both variants against dynamical mean-field theory (DMFT) and D-TRILEX results. We find that the exact behavior of the system can be faithfully reproduced in the weak-coupling regime, while at stronger couplings the performance of the two TPSC variants strongly depends on details of the system. Self consistent ; Particle (ecology) ; Physics ; Statistical physics ; Psychology ; Quantum electrodynamics ; Geology Crystal Structures and Properties
Authors: Tomasz Staśkiewicz | P. Pawłowski | Bartosz Firlik | Marcin Słowiński
Source: Civil-comp conferences (article, 2024-08-27)
Field: Materials Science — Materials Chemistry

Roller Rig for Wheel-Rail Wear Investigations Using Thermal Imaging This paper presents design and measurement results of an experimental roller rig dedicated to wheel-rail wear investigation using thermal imaging.The laboratory test stand is capable of reproducing (in an automatic way) actual wheel-rail movement range and also takes into account the operating conditions such as temperature, humidity and air flow.The rig may also be used for investigations of new wheel and rail materials, friction modifiers and rolling noise emission. Automotive engineering ; Thermal ; Materials science ; Mechanical engineering ; Computer science ; Engineering ; Physics Metal Alloys Wear and Properties ; Welding Techniques and Residual Stresses ; Gear and Bearing Dynamics Analysis
Authors: Thomas Gasperini | A. Pizzi | Luca Olivi | Giuseppe Toscano | Alessio Ilari | Daniele Duca
Source: Energies (article, 2024-12-05)
Field: Chemistry — Analytical Chemistry

Image Processing Technique for Enhanced Combustion Efficiency of Wood Pellets The combustion efficiency of wood pellets is partly affected by their average length. The ISO 17829 standard defines the methodology for assessing the average length of sample pellets, but the method does not always lead to representative data. Furthermore, a standard analysis is time-consuming as it requires manual measurement of the pellets using a caliper. This paper, whilst evaluating the effect of pellet length on combustion efficiency, proposes a pending-patented dimensional image processing method (DIP) for assessing pellet length. DIP allows the dimensional data of grouped and stacked pellets to be obtained by exploiting the shadows produced by pellets when exposed to a light source, assuming that different-sized pellets produce different shadows. Thus, the proposed method allows for the extraction of dimensional information from non-distinct objects, overcoming the reliance of classical image processing methods on object distance for effective segmentation. Combustion tests, carried out using pellets varying only in length, confirmed the influence of length on combustion efficiency. Shorter pellets, compared to longer ones, significantly reduced CO emissions by up to 94% (mg/MJ). However, they exhibited a higher fuel mass consumption rate (kg/h), with an increase of up to 22.8% compared to the longest sample. In addition, longer pellets produced fewer but larger shadows than shorter ones. Further studies are needed to correlate the number and size of shadows with samples’ average length so that DIP could be implemented in stoves and programmed to communicate with the control unit and automatically optimize the setting in order to improve combustion efficiency. Pellets ; Combustion ; Stove ; Pellet ; Process engineering ; Environmental science ; Materials science ; Computer science ; Mathematics ; Waste management ; Chemistry ; Composite material ; Engineering Spectroscopy and Chemometric Analyses ; Thermochemical Biomass Conversion Processes
Authors: Syed Sibghatullah Quadri | Michael T.M. Wang | C. Gomez | Lucy A. Gildea
Source: Journal of Investigative Dermatology (article, 2024-07-19)
Field: Materials Science — Polymers and Plastics

LB1032 Utilizing Derek Nexus to Predict Skin Sensitization Potential for Cosmetic Ingredients Nexus (standard) ; Skin sensitization ; Sensitization ; Dermatology ; Skin barrier ; Medicine ; Computer science ; Immunology ; Embedded system Textile materials and evaluations ; Color perception and design ; Olfactory and Sensory Function Studies
Authors: Xi Lin | Jens Magelund Tarp | Robin J. Evans
Source: arXiv (Cornell University) (review, 2024-07-01)
Field: Chemistry — Electrochemistry

Data fusion for efficiency gain in ATE estimation: A practical review with simulations The integration of real-world data (RWD) and randomized controlled trials (RCT) is increasingly important for advancing causal inference in scientific research. This combination holds great promise for enhancing the efficiency of causal effect estimation, offering benefits such as reduced trial participant numbers and expedited drug access for patients. Despite the availability of numerous data fusion methods, selecting the most appropriate one for a specific research question remains challenging. This paper systematically reviews and compares these methods regarding their assumptions, limitations, and implementation complexities. Through simulations reflecting real-world scenarios, we identify a prevalent risk-reward trade-off across different methods. We investigate and interpret this trade-off, providing key insights into the strengths and weaknesses of various methods; thereby helping researchers navigate through the application of data fusion for improved causal inference. Estimation ; Fusion ; Computer science ; Sensor fusion ; Artificial intelligence ; Engineering ; Systems engineering ; Philosophy Electrochemical Analysis and Applications ; Non-Destructive Testing Techniques ; Electrical and Bioimpedance Tomography
Authors: Elnur Huseynzade | Hamid Abdullayev
Source: Journal of Materials and Engineering (article, 2024-10-01)
Field: Chemistry — Analytical Chemistry

Infrared Imaging Analysis as Non-Destructive Maintenance of Food Processing Equipment The use of infrared imaging is a recently developed non-destructive tool to assess the safety, quality and efficiency of the food industry. This article explores the application areas and benefits of using infrared imaging in the maintenance of machinery used in the food industry. Applications covered include food quality control, packaging inspection, temperature monitoring and control, hygiene and sanitation control, foreign object detection, energy saving through optimization, baking, as well as cooking process monitoring and research. By using infrared cameras to their full potential, it is possible to reveal defects, check the level of cleanliness, optimize the maintenance of machines, and examine the thermal attributes of food. This article also provides an in-depth analysis of the historical development of infrared imaging technology. We also explore the basic ideas behind infrared image analysis. This includes the Stefan-Boltzmann Law, Planck's Law, and Wien's displacement law. Infrared image analysis has many advantages and some disadvantages. Despite these drawbacks, infrared imaging analysis has continued benefits. It saves costs, ensures equipment longevity and increases productivity. This makes it very important for the safety of food industry machinery. Infrared ; Environmental science ; Computer science ; Optics ; Physics Spectroscopy and Chemometric Analyses ; Advanced Scientific Research Methods ; Food Industry and Aquatic Biology
Authors: Linzhi Ouyang | Yaoyao Wang | Zitong Guo | Zheng Sun | Zhongde Shan
Source: Transactions of the Canadian Society for Mechanical Engineering (article, 2024-09-20)
Field: Materials Science — Polymers and Plastics

Collaborative control of circumferential yarn implantation system for large-scale 3D braiding equipment using fast nonsingular terminal sliding mode To ensure high performance collaborative control of the circumferential yarn implantation system for a specific large-scale 3D braiding equipment, a multi-motor fast nonsingular terminal sliding mode (FNTSM) controller is proposed using time-delay estimation (TDE) and deviation coupling control (DCC). Then, comparative experiments were conducted among our proposed TDE-based FNTSM controller and PD controller and TDE-based PD controller. As shown in the experimental results, the root-mean-square error (RMSE) and maximum absolute error (MAE) ensured by our FNTSM controller tracking sine signal have decreased by 89.4% and 67.1% compared with the ones by PD controller, while the RMSE of our FNTSM controller tracking slope signal is ensured within 0.03°. Meanwhile, the RMSE and MAE of our FNTSM controller tracking sine signals have been reduced by 48.2% and 56.9% due to DCC, respectively. Afterwards, less than 3% error fluctuation has been observed with load using our FNTSM controller. High control performance and strong robustness have been experimentally observed. Yarn ; Terminal (telecommunication) ; Invertible matrix ; Scale (ratio) ; Mode (computer interface) ; Materials science ; Mechanical engineering ; Computer science ; Engineering ; Physics ; Operating system ; Telecommunications Textile materials and evaluations
Authors: Arkadiusz Urzędowski | Andrzej Sachajdak | Arkadiusz Syta | Jacek Zaburko
Source: Energies (article, 2024-12-30)
Field: Materials Science — Materials Chemistry

CFD and Statistical Analysis of the Impact of Surface Physical Parameters on the Thermal Resistance of Layered Partitions in ETICS Systems In the article, the authors attempted to analyze the impact of such materials factors as surface emissivity, surface roughness, air gap thickness, and type of concrete on heat transport in the microstructure of vertical multilayer building walls. The surface analysis conducted using three-dimensional modeling tools provided information about the formation of its microstructure before and after the application of a reflection-smoothing coating, which has a direct impact on the emissivity of the surface and was reduced from 0.93 to 0.29. Thermal analyses demonstrated that after applying the reflective coating, thermal resistance increased significantly in the air gap, by approximately 86%, which resulted in a 28% improvement of the evaluated walls samples. The studies have shown that increasing the gap thickness between concrete and thermal insulation results in a thermal resistance increase. It is feasible to enhance the thermal insulation of walls while simultaneously reducing their thickness, a development that holds significant potential for application in the production of prefabricated sandwich panels. The statistical analyzes performed showed significant differences between the analyzed configurations. Computational fluid dynamics ; Surface (topology) ; Materials science ; Thermal ; Thermal resistance ; Mechanics ; Thermodynamics ; Mathematics ; Physics ; Geometry Thermal properties of materials ; Radiative Heat Transfer Studies ; Building Energy and Comfort Optimization
Authors: Wei Li | Qiaohua Wang | Yingli Wang
Source: Foods (article, 2024-06-13)
Field: Chemistry — Analytical Chemistry

Non-Destructive Inspection of Physicochemical Indicators of Lettuce at Rosette Stage Based on Visible/Near-Infrared Spectroscopy Lettuce is a globally important cash crop, valued by consumers for its nutritional content and pleasant taste. However, there is limited research on the changes in the growth indicators of lettuce during its growth period in domestic settings. Quality assessment primarily relies on subjective evaluations, resulting in significant variability. This study focused on hydroponically grown lettuce during the rosette stage and investigated the patterns of changes in the indicators and spectral curves over time. By employing spectral preprocessing and selecting characteristic wavelengths, three models were developed to predict the indicators. The results showed that the optimal model structures were S_G-UVE-PLSR (SSC and vitamin C) and Nor-CARS-PLSR (moisture content). The PLSR models achieved prediction set correlation coefficients of 0.8648, 0.8578, and 0.8047, with residual prediction deviations of 1.9685, 1.9568, and 1.6689, respectively. The optimal models were integrated into a portable device, using real-time analysis software written in Matlab2021a, for the prediction of the physicochemical indicators of lettuce during the rosette stage. The results demonstrated prediction set correlation coefficients of 0.8215, 0.8472, and 0.7671, with root mean square errors of prediction of 0.5348, 1.5813, and 2.3347 for a sample size of 180. The small discrepancies between the predicted and actual values indicate that the developed device can meet the requirements for real-time detection. Partial least squares regression ; Residual ; Biological system ; Near-infrared spectroscopy ; Mathematics ; Rosette (schizont appearance) ; Statistics ; Environmental science ; Biology Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Leaf Properties and Growth Measurement