jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Ivar J. H. G. Wamelink | Joost P.A. Kuijer | Beatriz Padrela | Yi Zhang | Frederik Barkhof | Henk Mutsaerts | Jan Petr | Elsmarieke van de Giessen | Vera C. Keil
Source: Journal of Magnetic Resonance Imaging (article, 2022-05-28)
Field: Materials Science — Materials Chemistry

Reproducibility of <scp>3 T APT‐CEST</scp> in Healthy Volunteers and Patients With Brain Glioma 2 TECHNICAL EFFICACY: Stage 2. Reproducibility ; Glioma ; Medicine ; Nuclear medicine ; Putamen ; Magnetic resonance imaging ; Clinical significance ; Bonferroni correction ; Radiology ; Pathology ; Internal medicine ; Chemistry Lanthanide and Transition Metal Complexes ; Advanced MRI Techniques and Applications ; MRI in cancer diagnosis
Authors: Jinglei Hao | Yongqiang Zhao | Qunnie Peng
Source: Remote Sensing (article, 2022-07-04)
Field: Chemistry — Analytical Chemistry

A Specular Highlight Removal Algorithm for Quality Inspection of Fresh Fruits Nondestructive inspection technology based on machine vision can effectively improve the efficiency of fresh fruit quality inspection. However, fruits with smooth skin and less texture are easily affected by specular highlights during the image acquisition, resulting in light spots appearing on the surface of fruits, which severely affects the subsequent quality inspection. Aiming at this issue, we propose a new specular highlight removal algorithm based on multi-band polarization imaging. First of all, we realize real-time image acquisition by designing a new multi-band polarization imager, which can acquire all the spectral and polarization information through single image capture. Then we propose a joint multi-band-polarization characteristic vector constraint to realize the detection of specular highlight, and next we put forward a Max-Min multi-band-polarization differencing scheme combined with an ergodic least-squares separation for specular highlight removal, and finally, the chromaticity consistency regularization is used to compensate the missing details. Experimental results demonstrate that the proposed algorithm can effectively and stably remove the specular highlight and provide more accurate information for subsequent fruit quality inspection. Besides, the comparison of algorithm speed further shows that our proposed algorithm has a good tradeoff between accuracy and complexity. Specular reflection ; Computer science ; Computer vision ; Specular highlight ; Artificial intelligence ; Polarization (electrochemistry) ; Algorithm ; Optics ; Physics Spectroscopy and Chemometric Analyses ; Color Science and Applications ; Remote Sensing in Agriculture
Authors: Kamil Czwartkowski | Arkadiusz Wierzbic | Wojciech Golimowski
Source: Sustainability (article, 2022-02-05)
Field: Chemistry — Organic Chemistry

Quality, Key Production Factors, and Consumption Volume of Niche Edible Oils Marketed in the European Union Consumer’s awareness of the health-promoting aspects of food and their search for products with high nutritional value is driving increased interest in niche oils. Such oils are produced on a small scale due to limited access to raw material and its low oil content. The aim of this multi-criteria analysis was to position niche oils. Data for the study were collected based on a literature review regarding twenty-three niche oils available on the European Union market. Analysis of quality parameters, key production factors, waste reusability, and average annual consumption volume in 2015–2020 was performed. Based on the research, it was concluded that linseed (flaxseed) oil, hemp oil, mustard oil, raspberry seed oil, and sesame oil should be of the most interest to consumers. They are characterized by the highest content of tocopherols, sterols, polyphenols, and carotenoids, a favorable ratio of mono- and polyunsaturated fatty acids, and pro-ecological and sustainable production technology. Based on the results of the study, the need for empirical research was identified, the key to filling the knowledge gaps in the area of edible niche oils. European union ; Niche market ; Niche ; Business ; Sustainability ; Production (economics) ; Food science ; Raw material ; Biotechnology ; Marketing ; Biology ; Ecology ; Economics Edible Oils Quality and Analysis ; Phytochemicals and Antioxidant Activities ; Nuts composition and effects
Authors: Xihui Bian | Deyun Wu | Kui Zhang | Peng Liu | Huibing Shi | Xiaoyao Tan | Zhigang Wang
Source: Biosensors (article, 2022-08-01)
Field: Chemistry — Analytical Chemistry

Variational Mode Decomposition Weighted Multiscale Support Vector Regression for Spectral Determination of Rapeseed Oil and Rhizoma Alpiniae Offcinarum Adulterants The accurate prediction of the model is essential for food and herb analysis. In order to exploit the abundance of information embedded in the frequency and time domains, a weighted multiscale support vector regression (SVR) method based on variational mode decomposition (VMD), namely VMD-WMSVR, was proposed for the ultraviolet-visible (UV-Vis) spectral determination of rapeseed oil adulterants and near-infrared (NIR) spectral quantification of rhizoma alpiniae offcinarum adulterants. In this method, each spectrum is decomposed into <i>K</i> discrete mode components by VMD first. The mode matrix U<i>k</i> is recombined from the decomposed components, and then, the SVR is used to build sub-models between each U<i>k</i> and target value. The final prediction is obtained by integrating the predictions of the sub-models by weighted average. The performance of the proposed method was tested with two spectral datasets of adulterated vegetable oils and herbs. Compared with the results from partial least squares (PLS) and SVR, VMD-WMSVR shows potential in model accuracy. Rapeseed ; Mathematics ; Partial least squares regression ; Support vector machine ; Mode (computer interface) ; Matrix (chemical analysis) ; Biological system ; Algorithm ; Pattern recognition (psychology) ; Applied mathematics ; Artificial intelligence ; Computer science ; Chemistry ; Statistics ; Chromatography Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Spectroscopy Techniques in Biomedical and Chemical Research
Authors: Agnel Praveen Joseph | Mateusz Olek | Sony Malhotra | Peijun Zhang | Kevin Cowtan | Tom Burnley | Martyn Winn
Source: Acta Crystallographica Section D Structural Biology (article, 2022-01-24)
Field: Materials Science — Materials Chemistry

Atomic model validation using the <i>CCP-EM</i> software suite Recently, there has been a dramatic improvement in the quality and quantity of data derived using cryogenic electron microscopy (cryo-EM). This is also associated with a large increase in the number of atomic models built. Although the best resolutions that are achievable are improving, often the local resolution is variable, and a significant majority of data are still resolved at resolutions worse than 3 Å. Model building and refinement is often challenging at these resolutions, and hence atomic model validation becomes even more crucial to identify less reliable regions of the model. Here, a graphical user interface for atomic model validation, implemented in the CCP-EM software suite, is presented. It is aimed to develop this into a platform where users can access multiple complementary validation metrics that work across a range of resolutions and obtain a summary of evaluations. Based on the validation estimates from atomic models associated with cryo-EM structures from SARS-CoV-2, it was observed that models typically favor adopting the most common conformations over fitting the observations when compared with the model agreement with data. At low resolutions, the stereochemical quality may be favored over data fit, but care should be taken to ensure that the model agrees with the data in terms of resolvable features. It is demonstrated that further re-refinement can lead to improvement of the agreement with data without the loss of geometric quality. This also highlights the need for improved resolution-dependent weight optimization in model refinement and an effective test for overfitting that would help to guide the refinement process. Overfitting ; Suite ; Computer science ; Software ; Software suite ; Data mining ; Range (aeronautics) ; Atomic model ; Resolution (logic) ; Experimental data ; Algorithm ; Artificial intelligence ; Mathematics ; Statistics ; Materials science ; Artificial neural network Enzyme Structure and Function ; Machine Learning in Materials Science ; Protein Structure and Dynamics
Authors: Md. Mazharul Islam | Md. Tanjim Hossain | Md. Reazuddin Repon | Tarikul Islam | Md Golam Kibria | Mohammad Abdul Jalil
Source: Textile & Leather Review (article, 2022-02-20)
Field: Materials Science — Polymers and Plastics

Seam Strength Prediction for Different Stitch Types Considering Stitch Density of Cotton Woven Fabrics Seam strength is critical in achieving the proper and adequate quality seam, which eventually determines the overall quality of any garment. The target of this research was to investigate exactly how different stitch density affected seam strength for different stitch types. Commercially available, 100% cotton plain weave structured woven fabric with mass per unit area of 270 g/m2 was used in this analysis. Two different stitch types, such as lock stitch (ISO#301) and chain stitch (ISO#401), along with four stitch densities like 8, 10, 12 and 14 per inch were utilized. The seam strength of the prepared samples was determined using a tensile strength tester followed by the ASTM D1683 standard procedure. The impact of independent variables on superimposed seam strength was statistically analyzed using a regression correlation with the help of SPSS software to construct a regression equation to predict seam strength before the manufacturing process. The study found a non-linear relationship between seam strength and stitch density. When the stitch density is too low, the seam strength is shown low as well, because the cloth cannot be held under tensile load. In a very compact woven fabric, structural jamming or intrinsic puckering occurs if it is too high. As a result, the best stitch density should be chosen to achieve the best seam strength. This study will help the manufacturers choose a suitable SPI for lock and chain stitches from polynomial regression equations before the sewing production of cotton woven fabric, which was not predicted by any researcher before. Therefore, the optimum stitch density can be chosen using regression equations to get the best result for seam strength. Ultimate tensile strength ; Lock (firearm) ; Linear regression ; Regression analysis ; Structural engineering ; Breaking strength ; Woven fabric ; Composite material ; Engineering ; Materials science ; Mathematics ; Statistics Textile materials and evaluations ; Industrial Vision Systems and Defect Detection ; Ergonomics and Musculoskeletal Disorders
Authors: Xingshuo Cui | Dan Liu | Zanyang Wang | Dengpan Wang | Borui Wu | Guangming Wang | Bin Zheng | Tong Cai
Source: Nanophotonics (article, 2022-11-23)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Wideband and high‐efficiency spin‐locked achromatic meta‐device Achromatic devices present unique capabilities in efficient manipulation of waves and have wide applications in imaging and communication systems. However, the research of achromatic devices is limited by the narrow bandwidth, low efficiency as well as large configurations. In this paper, we propose a general strategy to design spin-locked achromatic metasurface with broadband and high efficiency properties in microwave region. A multi-resonant model is used to control the dispersion within a wide bandwidth by tuning its resonant intensity, resonance numbers as well as resonant frequency. As a proof of the concept, two achromatic meta-devices with ultra-thin profile at microwave frequency are experimentally investigated. The achromatic deflector can reflect the normal incident waves to the same angle within 9.5 to 11.5 GHz, while the other achromatic lens can focus the excitations at the same focal points. The experimentally working efficiency of the meta-devices fluctuates around 71-82% and 57-65% within the target working bandwidth, respectively. Moreover, our meta-devices can preserve the charity of the excitations. The scheme of this research shows great advances in the design of broadband and high-efficiency achromatic devices which can also be applied to other frequency ranges and inspires the realization of ultrabroadband and high-efficiency metadevices. Achromatic lens ; Wideband ; Nanomaterials ; Optoelectronics ; Materials science ; Physics ; Optics ; Nanotechnology Metamaterials and Metasurfaces Applications ; Neural Networks and Reservoir Computing ; Photonic Crystals and Applications
Authors: Xinhao Shao | Christopher Grams | Yu Gao
Source: Journal of Proteome Research (article, 2022-12-13)
Field: Chemistry — Spectroscopy

Sequence Coverage Visualizer: A Web Application for Protein Sequence Coverage 3D Visualization Protein structure defines protein function and plays an extremely important role in protein characterization. Recently, two groups of researchers from DeepMind and the Baker lab have independently published protein structure prediction tools that can help us obtain predicted protein structures for the whole human proteome. This enabled us to visualize the entire human proteome using predicted 3D structures for the first time. To help other researchers best utilize these protein structure predictions in proteomics experiments, we present the Sequence Coverage Visualizer (SCV), http://scv.lab.gy, a web application for protein sequence coverage 3D visualization. Here we showed a few possible usages of the SCV, including the labeling of post-translational modifications and isotope labeling experiments. These results highlight the usefulness of such 3D visualization for proteomics experiments and how SCV can turn a regular proteomics experiment (identified peptide list) into structural insights. Furthermore, when used together with limited proteolysis, we demonstrated that SCV can help to compare different protein structures from different sources, including predicted ones and existing PDB entries. We hope our tool can provide help in the process of improving protein structure prediction accuracy. Overall, SCV is a convenient and powerful tool for visualizing proteomics results in 3D. Visualization ; Proteomics ; Computer science ; Proteome ; Computational biology ; Protein sequencing ; Sequence (biology) ; Sequence database ; Structural bioinformatics ; Protein Data Bank (RCSB PDB) ; Protein structure database ; Protein structure ; Bioinformatics ; Data mining ; Biology ; Peptide sequence ; Genetics ; Biochemistry Advanced Proteomics Techniques and Applications ; Bioinformatics and Genomic Networks ; Genomics and Phylogenetic Studies
Authors: Katja Klinar | Katja Vozel | Timm Swoboda | Tom Sojer | Miguel Muñoz Rojo | Andrej Kitanovski
Source: iScience (article, 2022-01-15)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Ferrofluidic thermal switch in a magnetocaloric device Thermal switches are advanced heat-management devices that represent a new opportunity to improve the energy efficiency and power density of caloric devices. In this study we have developed a numerical model to analyze the operation and the performance of static thermal switches in caloric refrigeration. The investigation comprises a parametric analysis of a realistic ferrofluidic thermal switch in terms of the maximum temperature span, cooling power, and coefficient of performance. The highest achieved temperature span between the heat source and the heat sink was 1.12 K for a single embodiment, which could be further developed into a regenerative system to increase the temperature span. A sensitivity analysis is conducted to correlate the relationship between the input parameters and the results. We show that thermal switches can be used in caloric devices even when switching ratios are small, which greatly extends the possibilities to implement different types of thermal switches. Refrigeration ; Heat sink ; Thermal ; Coefficient of performance ; Span (engineering) ; Thermal analysis ; Parametric statistics ; Magnetic refrigeration ; Materials science ; Power density ; Power (physics) ; Computer science ; Electrical engineering ; Thermodynamics ; Heat exchanger ; Physics ; Heat pump ; Engineering ; Mathematics ; Magnetic field Magnetic and transport properties of perovskites and related materials ; Thermal properties of materials ; Phase Change Materials Research
Authors: Hai Nguyen | Koji Tsuda
Source: The Journal of Chemical Physics (article, 2022-01-11)
Field: Materials Science — Materials Chemistry

Generating reaction trees with cascaded variational autoencoders To develop useful drugs and materials, chemists synthesize diverse molecules by trying various reactants and reaction routes. Toward automating this process, we propose a deep generative model, called cascaded variational autoencoder (casVAE), for synthesizable molecular design. It generates a reaction tree, where the reactants are chosen from commercially available compounds and the synthesis route is constructed as a tree of reaction templates. The first part of casVAE is designed to generate a molecule called a surrogate product, while the second part constructs a reaction tree that synthesizes it. In benchmarking, casVAE showed its ability to generate reaction trees that yield high-quality and synthesizable molecules. An implementation of casVAE is publicly available at https://github.com/tsudalab/rxngenerator. Autoencoder ; Benchmarking ; Computer science ; Tree (set theory) ; Template ; Product (mathematics) ; Process (computing) ; Yield (engineering) ; Theoretical computer science ; Artificial intelligence ; Combinatorial chemistry ; Algorithm ; Chemistry ; Deep learning ; Mathematics ; Programming language ; Materials science Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Chemical Synthesis and Analysis
Authors: Nathan C. Frey | Vijay Gadepally | Bharath Ramsundar
Source: arXiv (Cornell University) (preprint, 2022-01-28)
Field: Materials Science — Materials Chemistry

FastFlows: Flow-Based Models for Molecular Graph Generation We propose a framework using normalizing-flow based models, SELF-Referencing Embedded Strings, and multi-objective optimization that efficiently generates small molecules. With an initial training set of only 100 small molecules, FastFlows generates thousands of chemically valid molecules in seconds. Because of the efficient sampling, substructure filters can be applied as desired to eliminate compounds with unreasonable moieties. Using easily computable and learned metrics for druglikeness, synthetic accessibility, and synthetic complexity, we perform a multi-objective optimization to demonstrate how FastFlows functions in a high-throughput virtual screening context. Our model is significantly simpler and easier to train than autoregressive molecular generative models, and enables fast generation and identification of druglike, synthesizable molecules. Computer science ; Context (archaeology) ; Autoregressive model ; Set (abstract data type) ; Graph ; Theoretical computer science ; Virtual screening ; Algorithm ; Chemistry ; Mathematics ; Programming language ; Molecular dynamics ; Computational chemistry Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Innovative Microfluidic and Catalytic Techniques Innovation
Authors: Yansong Ji | Xiaoning Zhang | Zhenyu Chen | Yuting Xiao | Shiwei Li | Jie Gu | Hongmei Hu | Guotao Cheng
Source: International Journal of Molecular Sciences (article, 2022-01-31)
Field: Materials Science — Biomaterials

Silk Sericin Enrichment through Electrodeposition and Carbonous Materials for the Removal of Methylene Blue from Aqueous Solution The recycling and reuse of biomass waste for the preparation of carbon-based adsorbents is a sustainable development strategy that has a positive environmental impact. It is well known that a large amount of silk sericin (SS) is dissolved in the wastewater from the silk industry. Utilizing the SS instead of discharging it into the environment without further treatment would reduce environmental and ecological problems. However, effective enrichment of the SS from the aqueous solution is a challenge. Here, with the help of carboxymethyl chitosan (CMCS), which can form a gel structure under low voltage, an SS/CMCS hydrogel with SS as the major component was prepared via electrodeposition at a 3 V direct-current (DC) voltage for five minutes. Following a carbonization process, an SS-based adsorbent with good performance for the removal of methylene blue (MB) from an aqueous solution was prepared. Our results reveal that the SS/CMCS hydrogel maintains a porous architecture before and after carbonization. Such structure provides abundant adsorption sites facilitating the adsorption of MB molecules, with a maximum adsorptive capacity of 231.79 mg/g. In addition, it suggests that the adsorption is an exothermic process, has a good fit with the <i>Langmuir</i> model, and follows the intra-particle diffusion model. The presented work provides an economical and feasible path for the treatment of wastewater from dyeing and printing. Carbonization ; Adsorption ; Aqueous solution ; Methylene blue ; Chemical engineering ; Materials science ; Wastewater ; Sericin ; Langmuir adsorption model ; Activated carbon ; Chitosan ; Chemistry ; SILK ; Organic chemistry ; Composite material ; Environmental engineering ; Catalysis ; Environmental science ; Photocatalysis Silk-based biomaterials and applications ; Biochemical and Structural Characterization ; Protein Hydrolysis and Bioactive Peptides