jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Yanwen Hu | Yaodong Ma | Wen-Ying Zhou | Tingrong Zhang | Qingyang Chen
Source: Journal of Physics D Applied Physics (article, 2024-04-12)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Inverse design of two-function transmission-type reconfigurable polarization control metasurfaces based on deep learning Abstract Compared with single-function metasurfaces, the design difficulty of multi-function metasurfaces increases significantly. This paper introduces an inverse design method based on deep learning to address this challenge. By this method, a transmission-type reconfigurable polarization control metasurface (TRPCM) with two functions is rapidly designed. The network model used in the method consists of an electromagnetic parameter reconstruction network model and an inverse prediction network model. The combination of the two models can solve the problem of difficulty in defining high-dimensional inputs in traditional inverse design, and achieve accurate prediction of metasurface structure parameters under given design targets. To optimize the hyperparameters of the neural network model, a genetic algorithm was introduced. To solve the non-uniqueness problem of inverse design, a method for eliminating similar data by calculating Euclidean Distance was introduced. Both schemes further improve the predictive performance of the proposed network model. Finally, six design targets were set based on the TRPCM. The structural parameters of the metasurface were successfully predicted using two neural network models and achieved the required performance. On this basis, a set of parameters was selected for experimental validation. By controlling the ON or OFF of the PIN diodes, the fabricated metasurface achieves two functions: linear-to-circular polarization conversion and linear polarization maintenance in the range of 2–3.6 GHz. Study results show that the inverse design scheme proposed in the paper is feasible and practical for solving the rapid optimization design of complex multi-function metasurfaces. Inverse ; Polarization (electrochemistry) ; Deep learning ; Computer science ; Materials science ; Mathematics ; Artificial intelligence ; Chemistry ; Geometry Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: José Pedro Santos | Mahmoud Sedahmed | Rodrigo C. V. Coelho | M. M. Telo da Gama
Source: Micromachines (article, 2024-10-26)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Flowing Liquid Crystal Torons Around Obstacles Liquid crystal torons, localized topological structures, are known for their stability and dynamic behaviour in response to external stimuli, making them attractive for advanced material applications. In this study, we investigate the flow of torons in chiral nematic liquid crystals around obstacles. We simulate the fluid flow and director field interactions using a hybrid numerical method combining lattice Boltzmann and finite difference techniques. Our results reveal that the toron dynamical behaviour depends strongly on the impact parameter from the obstacle. At impact parameters smaller than half cholesteric pitch, the flowing toron is destabilized by the interaction with the obstacle; otherwise, the flowing toron follows a trajectory with a deflection which decays exponentially with the impact parameter. Additionally, we explore the scattering of torons by multiple obstacles, providing insights into how the dynamics of these structures respond to complex environments. Lattice Boltzmann methods ; Obstacle ; Liquid crystal ; Deflection angle ; Deflection (physics) ; Scattering ; Lattice (music) ; Mechanics ; Liquid flow ; Physics ; Materials science ; Classical mechanics ; Condensed matter physics ; Optics ; Acoustics Liquid Crystal Research Advancements ; Lattice Boltzmann Simulation Studies ; Micro and Nano Robotics
Authors: Xi Wang | Keren Zhang | Wan He | Luobin Zhang | Biwei Gao | Ruijun Tian | Ruilian Xu
Source: Clinical Proteomics (article, 2024-04-05)
Field: Chemistry — Spectroscopy

Plasma proteomic characterization of colorectal cancer patients with FOLFOX chemotherapy by integrated proteomics technology Our study sheds light on the pathways affected in CRC patients treated with FOLFOX chemotherapy and identifies potential biomarkers that could be valuable for prognosis prediction. Our findings showed the potential of mass spectrometry-based proteomics and machine learning as an unbiased and systematic approach for discovering biomarkers in CRC. FOLFOX ; Colorectal cancer ; Proteomics ; Medicine ; Oncology ; Biomarker ; Oxaliplatin ; Bioinformatics ; Internal medicine ; Cancer ; Biology Advanced Proteomics Techniques and Applications ; S100 Proteins and Annexins ; Machine Learning in Bioinformatics
Authors: Ujjayanta Bhaumik | Laurens Van de Perre | Frédéric Leloup
Source: Journal of Imaging Science and Technology (article, 2024-09-04)
Field: Materials Science — Polymers and Plastics

Analyzing Colorimetric Characterization Models for Virtual Reality Headsets: A Comparative Study The utility and ubiquitousness of virtual reality make it an extremely popular tool in various scientific research areas. Owing to its ability to present naturalistic scenes in a controlled manner, virtual reality may be an effective option for conducting color science experiments and studying different aspects of color perception. However, head mounted displays have their limitations, and the investigator should choose the display device that meets the colorimetric requirements of their color science experiments. This paper presents a structured method to characterize the colorimetric profile of a head mounted display with the aid of color characterization models. By way of example, two&#xA0;commercially available head mounted displays (Meta Quest 2 and Meta Quest Pro) are characterized using four models (Look-up Table, Polynomial Regression, Artificial Neural Network, and Gain Gamma Offset), and the appropriateness of each of these models is investigated. Virtual reality ; Computer science ; Characterization (materials science) ; Human–computer interaction ; Computer graphics (images) ; Materials science ; Nanotechnology Textile materials and evaluations ; Consumer Perception and Purchasing Behavior ; 3D Shape Modeling and Analysis
Authors: Magdalena Owczarek
Source: Materials (article, 2024-07-01)
Field: Materials Science — Polymers and Plastics

A New Method for Evaluating the Homogeneity within and between Weave Repeats in Plain Fabric Structures Using Computer Image Analysis This article introduces a novel, rapid, and non-destructive method for assessing homogeneity within and between weave repeats in fabric structures, termed intra-repeat (IAR) and inter-repeat (IER) evaluation. The method focuses on structural parameters, including inter-thread pores (ITPs) and warp and weft pitches, using computer image analysis. Each parameter is assigned to a module in the repeat weave pattern, facilitating the sorting of modules in the IAR and IER fabric structure arrangement. The method was verified using artificial images and 30 real plain fabrics with varying degrees of warp grouping, employing the author's proprietary software, MagFABRIC version 2.1The general measurable coefficients of intra- and inter-homogeneity were defined and related to the airflow measurements of these fabrics. Multiple regression models of airflow revealed strong dependencies, particularly for F = 10, with the size, shape, and position of ITPs and warp and weft pitches showing significant correlation. These findings underscore the importance of the new homogeneity parameters in textile structure analysis, including both IAR and IER woven fabric structure homogeneity parameters. The research aims to model specialized fabrics (e.g., barrier, filtration, composite fabrics) to address local changes in fabric structure affecting properties such as filtration efficiency, air permeability, and mechanical properties, especially in applications like composites or medical implants. Homogeneity (statistics) ; Woven fabric ; Airflow ; Fabric structure ; Air permeability specific surface ; Software ; Yarn ; Thread (computing) ; Plain weave ; Composite material ; Weaving ; Structural engineering ; Materials science ; Computer science ; Engineering ; Mechanical engineering Textile materials and evaluations ; Industrial Vision Systems and Defect Detection ; Mechanical Behavior of Composites
Authors: Roman Krzywda | Paweł Gierycz | Łukasz Makowski | Artur Poświata
Source: Energies (article, 2024-11-29)
Field: Chemistry — Analytical Chemistry

Calculation of Crude Oil Processes Using Simplified Model Mixture This paper presents the modeling of the existing crude oil separation process in a system consisting of two rectification columns with side drafts operating at higher pressure. The composition of the crude oil was approximated by a model mixture of hydrocarbons. The installation calculations have been performed for two different model compositions containing 32 and 10 different hydrocarbons. The whole technological process was based on the assumption that the feed stream, containing a model crude oil, was introduced to the first column, and then the other expected products (different petroleum fractions), characterized by their respective boiling points, were collected (side drafts) from the appropriate trays of the distillation columns. The obtained calculation results for both of the model crude oils were compared with the results obtained in the existing petroleum process and discussed from the point of view of their practical applications. The detailed data concerning size, composition, and process parameters for all the streams of the investigated installations, as well as the necessary energy expenditure for each of the columns, have been determined. Moreover, some recommendations are presented for the modeling and optimization of industrial distillation processes of very complex, multi-component systems using simpler model compositions. Crude oil ; Petroleum engineering ; Process engineering ; Environmental science ; Chemistry ; Engineering Petroleum Processing and Analysis ; Phase Equilibria and Thermodynamics ; Process Optimization and Integration
Authors: Shubham Kumar | Piyush Sahu | Surjit Bharatsingh | Gaurav Salwan | Dileep Mampallil
Source: arXiv (Cornell University) (preprint, 2024-07-18)
Field: Materials Science — Surfaces, Coatings and Films

Water Drop on Thin Viscous Oil Layers: From Stick-Slip Spreading to Dewetting The impact of water droplets on thin layers of immiscible viscous liquids, such as oil films, is commonly encountered across contexts ranging from kitchen activities to industrial processes. In this study, we experimentally investigate the short-term and long-term behavior of water drops spreading on silicone oil-coated surfaces. During the initial spreading, especially towards zero impact energies, the drop edge exhibits stick-slip dynamics, characterized by intermittent stops. The stick-slip behaviour diminishes with increasing spreading energy from impacts, where the drop spreads without noticeably displacing the oil layer. In the long-term dynamics, regardless of whether the spreading is gradual or impact-driven, the drop eventually spreads onto the surface under the oil layer, governed by the dewetting dynamics of the oil. The delay for the second spreading is independent of the Weber number, indicating that the impact initially does not significantly deform the oil layer. Our findings provide new insights into the dynamics of water-oil interactions, with implications for both practical applications and fundamental research. Dewetting ; Drop (telecommunication) ; Materials science ; Slip (aerodynamics) ; Drop impact ; Mechanics ; Petroleum engineering ; Composite material ; Thin film ; Geology ; Nanotechnology ; Wetting ; Mechanical engineering ; Thermodynamics ; Engineering ; Physics Surface Modification and Superhydrophobicity ; Fluid Dynamics and Thin Films ; Electrohydrodynamics and Fluid Dynamics
Authors: Braja Manggala | Chatchawan Chaichana | Mikhail Kornievsky | Nursaadah Syahro Fitriyah | Ramnarong Wanison | Wahyu Nurkholis Hadi Syahputra
Source: AIP conference proceedings (article, 2024-01-01)
Field: Chemistry — Analytical Chemistry

Chlorophyll content detection using a low-cost hyperspectral imaging in Cannabis Sativa L. Cannabis Sativa L. has been clinically proven to be used for antioxidant, anti-inflammatory, antiemetic, parasitic, antibacterial, antiviral, antifungal, antipyretic, painkiller, etc.Consequently, this plant began to be widely produced as an agricultural crop with selling value.More than that, the production of medicinal cannabis products has been permitted in several countries across the world.Furthermore, detecting the chlorophyll content is very important to monitoring the quality of cannabis leaves since the chlorophyll content plays an essential role in determining photosynthetic capacity and plant growth.Chlorophyll content can be assessed using a bench-top method, which might give an accurate and stable result.However, the bench-top method is destructive, costly, and time-consuming.The handheld SPAD chlorophyll meter is widely used nowadays as a non-destructive instrument.Nevertheless, the price of this device is not affordable, especially for small holder.This work aims to develop a relatively cheap, non-invasive, and accurate method for chlorophyll content detection.A low-cost Hyperspectral Imaging (HI) based on the mobile phone was used in this research.Low-cost HI can read reflected values at visible (400 -700 nm) wavelengths by applying digital filters to photographs.The reflectance value at each wavelength was plotted and considered equal with the hyperspectral imaging system method afterward.Then, Artificial Neural Network (ANN) was used to analyze spectral data and generate a model prediction to predict unknown data.The best model predictions were built with 10-and 50layer sizes.The coefficient determination (R 2 ) exhibited acceptable model predictions of 0.785 and 0.8, with root-meansquared deviation (RMSE) of 3.396 and 3.439, respectively.A low-cost HI device has great potential to detect chlorophyll content on the plant; hence pre-processing and resolution quality should be improved. Hyperspectral imaging ; Cannabis sativa ; Chlorophyll ; Remote sensing ; Computer science ; Environmental science ; Mathematics ; Biological system ; Artificial intelligence ; Horticulture ; Biology Spectroscopy and Chemometric Analyses ; Leaf Properties and Growth Measurement ; Remote Sensing in Agriculture
Authors: Renata Regina Pereira da Conceição | Valéria Aparecida Vieira Queiróz | Everaldo S. Medeiros | Joabson Borges de Araújo | Dakson Douglas Araújo | R. de A. Miguel | M. A. R. Stoianoff | M. L. F. Simeone
Source: Brazilian Journal of Biology (article, 2024-01-01)
Field: Chemistry — Analytical Chemistry

Determination of fumonisin content in maize using near-infrared hyperspectral imaging (NIR-HSI) technology and chemometric methods Maize (Zea mays L.) is of socioeconomic importance as an essential food for human and animal nutrition. However, cereals are susceptible to attack by mycotoxin-producing fungi, which can damage health. The methods most commonly used to detect and quantify mycotoxins are expensive and time-consuming. Therefore, alternative non-destructive methods are required urgently. The present study aimed to use near-infrared spectroscopy with hyperspectral imaging (NIR-HSI) and multivariate image analysis to develop a rapid and accurate method for quantifying fumonisins in whole grains of six naturally contaminated maize cultivars. Fifty-eight samples, each containing 40 grains, were subjected to NIR-HSI. These were subsequently divided into calibration (38 samples) and prediction sets (20 samples) based on the multispectral data obtained. The averaged spectra were subjected to various pre-processing techniques (standard normal variate (SNV), first derivative, or second derivative). The most effective pre-treatment performed on the spectra was SNV. Partial least squares (PLS) models were developed to quantify the fumonisin content. The final model presented a correlation coefficient (R2) of 0.98 and root mean square error of calibration (RMSEC) of 508 µg.kg-1 for the calibration set, an R2 of 0.95 and root mean square error of prediction (RMSEP) of 508 µg.kg-1 for the test validation set and a ratio of performance to deviation of 4.7. It was concluded that NIR-HSI with partial least square regression is a rapid, effective, and non-destructive method to determine the fumonisin content in whole maize grains. Hyperspectral imaging ; Partial least squares regression ; Calibration ; Mean squared error ; Coefficient of determination ; Fumonisin B1 ; Multivariate statistics ; Multispectral image ; Fumonisin ; Correlation coefficient ; Mycotoxin ; Biology ; Mathematics ; Biological system ; Statistics ; Food science ; Artificial intelligence ; Computer science Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Mycotoxins in Agriculture and Food
Authors: Rafael Pessoa Santos Brochado | Thiago de Alencar Neves | Thiago Bressani Ribeiro | Lariza Azevedo | Carolina Gemelli Carneiro | R. Martijn Wagterveld | Doekle Yntema | Klaas Jan Agema | Luewton L. F. Agostinho
Source: Water (article, 2024-12-27)
Field: Chemistry — Analytical Chemistry

Real-Time Determination of Total Suspended Solids in Activated Sludge’s Carousel Using a Single Emitter Ultrasonic Sensor Sludge management is a very relevant aspect in the operation of Wastewater Treatment Plants (WWTPs). In activated sludge systems, it is common to have daily (or continuous) monitoring of total suspended solids in the aeration tank (MLSS). If such control is not properly performed, it can cause solids to wash out in the secondary sedimentation tank or significantly impact BOD (Biochemical Oxygen Demand) and nitrogen removal. There are many commercially available systems which can provide real-time monitoring of solids (mainly optical or ultrasound sensors). Even though commercially available (usually with a high cost), there are still issues related to the use of such sensors. The most important one is the progressive accumulation of solids, which cause measurement errors. In this work, the authors investigated the application of a low-cost US sensor for MLSS (mixed-liquor suspended solids) monitoring in two full-scale activated sludge WWTPs. The tested sensor was similar to a previously described device, which had been previously employed in a pilot-scale UASB reactor in Brazil. The main differences were related to an integrated treatment and acquisition system which allowed real-time treatment of the US wave as well as data acquisition at a predefined time. The values generated by the sensor were compared with a commercial optical sensor installed in the same WWTP and double-checked with periodic gravimetric tests. The results at a Leeuwarden WWTP showed that the measurements of the US sensor, the optical sensor, and gravimetric test did not present significant differences during the test period at a significance level of 5%. Absolute errors were on average 0.04% (US sensor) and 0.03% (optic sensor) of MLSS compared to the gravimetric test. Although the use of the tested US sensor for monitoring solids in WWTP is promising, there are still several improvements that need to be made to the sensor. These include implementing a more precise calibration frequency, establishing a cleaning routine, and preventing sensor fouling. Furthermore, the sensor still needs a more thorough cost–benefit analysis, which would help assess the practicality of implementing this technology in various WWTPs. Ultrasonic sensor ; Activated sludge ; Common emitter ; Suspended solids ; Environmental science ; Materials science ; Acoustics ; Environmental engineering ; Sewage treatment ; Wastewater ; Optoelectronics ; Physics Spectroscopy and Chemometric Analyses ; Water Quality Monitoring and Analysis ; Advanced Chemical Sensor Technologies
Authors: Pritam Meshram | Kishan Singh Rawat | Vinod Kumar Tripathi
Source: Environment and Ecology (article, 2024-12-01)
Field: Chemistry — Analytical Chemistry

Sentinel-1A Data Analysis for Rice Classification Utilizing Random Forests and Support Vector Machine Rice is known to be one of the most important crops in India and many other nations, particularly in Asia, therefore accurate rice area estimation has an important role in many activities, ranging from human nutrition to environmental concerns. As a result, the determination of cultivation area remains a hot topic among researchers from numerous disciplines, planners, and decision makers. Using Sentinel-1A SAR (Synthetic Aperture Radar) satellite data, this study attempts to evaluate the effectiveness of random forest (RF) and support vector machines (SVM) algorithms for rice crop classification. According to the findings, rice fields can easily be distinguished from other crops in the research area by using the temporal characteristics of the rice crop as reflected in the VH backscatter patterns. The total precision and Kappa coefficient produced by RF showed 85.7% and 0.74, respectively, when the classification outcomes were compared to the ground reference data. These values were somewhat higher than those obtained by SVM (81.2% overall accuracy and 0.68 Kappa coefficient). The government’s rice area statistics were used to compare the analysis results; the relative difference in rice area for RF and SVM, respectively, came out to be +1.40% and -4.63%. In summary, the RF algorithm is highly recommended for the accurate differentiation of rice fields from neighbouring classes in conditions of identical climate, soil, and topography with similar methods of cultivation. On the other hand, Sentinel-1A SAR provides a valuable data set at cost-free for similar studies. Random forest ; Support vector machine ; Agroforestry ; Environmental science ; Computer science ; Machine learning Spectroscopy and Chemometric Analyses
Authors: Ruhuan Deng | Xinhao Wang | Yi Zuo | Zhen Liu | Feifan Wang | Chao Peng | Tongyu Li | Wenzhe Liu | Xiaohan Liu | Lei Shi
Source: Advanced Optical Materials (article, 2024-04-20)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Broadband Complete Polarization Control via Inverse‐Designed Photonic Crystal Slabs Abstract Polarization is a crucial characteristic of electromagnetic fields, and the ability to fully control it has many useful applications. While novel nanophotonic devices have been designed to achieve unprecedented capability to manipulate light on demand, their usage in the complete control of polarization states for the transmitted light has been relatively limited, and traditional design methods always produce devices with narrow operation bandwidths. In this work, a two‐phase topology optimization strategy is proposed in conjunction with adjoint method to inverse design photonic crystal slabs capable of complete polarization control. It successfully produces devices operating over a broad bandwidth that is significantly larger than the current state‐of‐the‐art designs, and their performances are also robust to material loss. This is also find that the C 2 v symmetry of the structure can regularize the problem, so that less simulation time and faster convergence can be obtained without compromising performance. This study demonstrates the power of the inverse design method, which can be further applied to achieve more complex polarization control and beyond. Broadband ; Polarization (electrochemistry) ; Inverse ; Nanophotonics ; Photonic crystal ; Materials science ; Photonics ; Optics ; Computer science ; Topology optimization ; Bandwidth (computing) ; Optoelectronics ; Topology (electrical circuits) ; Electronic engineering ; Physics ; Telecommunications ; Electrical engineering ; Mathematics ; Engineering ; Finite element method Metamaterials and Metasurfaces Applications ; Photonic Crystals and Applications ; Thermal Radiation and Cooling Technologies