jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Monika Kish | Dylan P. Ivory | Jonathan J. Phillips
Source: Journal of the American Chemical Society (article, 2023-12-29)
Field: Chemistry — Spectroscopy

Transient Structural Dynamics of Glycogen Phosphorylase from Nonequilibrium Hydrogen/Deuterium-Exchange Mass Spectrometry It remains a major challenge to ascertain the specific structurally dynamic changes that underpin protein functional switching. There is a growing need in molecular biology and drug discovery to complement structural models with the ability to determine the dynamic structural changes that occur as these proteins are regulated and function. The archetypal allosteric enzyme glycogen phosphorylase is a clinical target of great interest to treat type II diabetes and metastatic cancers. Here, we developed a time-resolved nonequilibrium millisecond hydrogen/deuterium-exchange mass spectrometry (HDX-MS) approach capable of precisely locating dynamic structural changes during allosteric activation and inhibition of glycogen phosphorylase. We resolved obligate transient changes in the localized structure that are absent when directly comparing active/inactive states of the enzyme and show that they are common to allosteric activation by AMP and inhibition by caffeine, operating at different sites. This indicates that opposing allosteric regulation by inhibitor and activator ligands is mediated by pathways that intersect with a common structurally dynamic motif. This mass spectrometry approach uniquely stands to discover local transient structural dynamics and could be used broadly to identify features that influence the structural transitions of proteins. Allosteric regulation ; Chemistry ; Glycogen phosphorylase ; Hydrogen–deuterium exchange ; Biophysics ; Mass spectrometry ; Molecular dynamics ; Enzyme ; Protein dynamics ; Biochemistry ; Protein structure ; Computational chemistry Mass Spectrometry Techniques and Applications ; Protein Structure and Dynamics ; Enzyme Structure and Function
Authors: Zhichen Li | Jing Xu | Lin Zhang | Yiwen Li | Ruisheng Yang | Quanhong Fu | Fuli Zhang | Yuancheng Fan
Source: Annalen der Physik (article, 2023-05-07)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Inverse Design of Dual‐Band Optically Transparent Metasurface Absorbers with Neural‐Adjoint Method Abstract Massive applications of microwave technology have led to a large amount of electromagnetic pollution, which seriously interferes with the normal operation of communication systems in people's daily life. Optically transparent metasurface absorber is emerging as a promising candidate for solving this problem in some specific scenarios. When designing multiband metasurface absorbers, the coupling within the cell structure generally prevents the independent modulation of the absorption effect in each band. The rapid development of deep learning provides a new way for designing high‐performance metasurface. Here, a forward network model is built to predict the absorption spectrum of the metasurface absorber. In the network model, 1D (one‐dimensional) inverse convolution is used as the upsampling layer, which enables the network model to have a good prediction on small data sets while avoiding overfitting on large data sets. Based on the network model, a dual‐band optically transparent metasurface absorber is also designed by employing the neural‐adjoint (NA) method. The results taking advantage of deep learning method for high‐efficiency design of metasurface absorbers without considering the coupling effect, have shown great capability to optimize the absorption efficiency of different frequency bands independently, which may provide an alternative way to design other multiband microwave devices. Computer science ; Overfitting ; Absorption (acoustics) ; Microwave ; Convolution (computer science) ; Upsampling ; Coupling (piping) ; Multi-band device ; Artificial neural network ; Inverse ; Electronic engineering ; Optoelectronics ; Materials science ; Optics ; Physics ; Telecommunications ; Artificial intelligence ; Mathematics ; Engineering ; Image (mathematics) Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Antenna Design and Analysis
Authors: H. Wang | Mengwen Mei | Jiangbo Li
Source: Agriculture (review, 2023-09-19)
Field: Chemistry — Analytical Chemistry

Research Progress on Non-Destructive Detection of Internal Quality of Fruits with Large Size and Thick Peel: A Review Postharvest quality detection and grading are important factors to improve the commercial value of fruit. The natural biological characteristics bring challenges to the rapid and non-destructive evaluation of the internal quality of fruits with large size and thick peel. A lot of studies have tried to establish a feasible technique to achieve rapid, non-destructive, and accurate detection for this kind of fruit in commercial real-time grading. This article focuses on large-sized and thick-skinned fruits and comprehensively reviews the latest technical progress in the non-destructive detection of internal quality. It can provide a valuable reference for the development of postharvest processing technology for this kind of fruit. Postharvest ; Grading (engineering) ; Quality (philosophy) ; Environmental science ; Agricultural engineering ; Computer science ; Process engineering ; Biochemical engineering ; Engineering ; Biology ; Horticulture ; Civil engineering ; Physics Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; Advanced Chemical Sensor Technologies
Authors: Rweetuparna Guha | Malak Rafik | Anna Gonzàlez‐Rosell | Stacy M. Copp
Source: Chemical Communications (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Heat, pH, and salt: synthesis strategies to favor formation of near-infrared emissive DNA-stabilized silver nanoclusters We present chemical synthesis strategies for DNA-stabilized silver nanoclusters (Ag<sub>N</sub>-DNAs) with near-infrared (NIR) emission in the biological tissue transparency windows. Elevated temperatures can significantly increase chemical yield of near-infrared nanoclusters. In most cases, basic pH favors near-infrared nanoclusters while micromolar amounts of NaCl inhibit their formation. Nanoclusters ; Salt (chemistry) ; Infrared ; Chemistry ; Photochemistry ; DNA ; Inorganic chemistry ; Organic chemistry ; Biochemistry Nanocluster Synthesis and Applications ; Gold and Silver Nanoparticles Synthesis and Applications ; Advanced Nanomaterials in Catalysis
Authors: Corentin Beaumal | Alain Beck | Oscar Hernandez‐Alba | Christine Carapito
Source: PROTEOMICS (article, 2023-05-06)
Field: Chemistry — Spectroscopy

Advanced mass spectrometry workflows for accurate quantification of trace‐level host cell proteins in drug products: Benefits of FAIMS separation and gas‐phase fractionation DIA Therapeutic monoclonal antibodies (mAb) production relies on multiple purification steps before release as a drug product (DP). A few host cell proteins (HCPs) may co-purify with the mAb. Their monitoring is crucial due to the considerable risk they represent for mAb stability, integrity, and efficacy and their potential immunogenicity. Enzyme-linked immunosorbent assays (ELISA) commonly used for global HCP monitoring present limitations in terms of identification and quantification of individual HCPs. Therefore, liquid chromatography tandem mass spectrometry (LC-MS/MS) has emerged as a promising alternative. Challenging DP samples show an extreme dynamic range requiring high performing methods to detect and reliably quantify trace-level HCPs. Here, we investigated the benefits of adding high-field asymmetric ion mobility spectrometry (FAIMS) separation and gas phase fractionation (GPF) prior to data independent acquisition (DIA). FAIMS LC-MS/MS analysis allowed the identification of 221 HCPs among which 158 were reliably quantified for a global amount of 880 ng/mg of NIST mAb Reference Material. Our methods have also been successfully applied to two FDA/EMA approved DPs and allowed digging deeper into the HCP landscape with the identification and quantification of a few tens of HCPs with sensitivity down to the sub-ng/mg of mAb level. Ion-mobility spectrometry ; Chromatography ; Chemistry ; Mass spectrometry ; Fractionation ; Monoclonal antibody ; Tandem mass spectrometry ; Antibody ; Biology Mass Spectrometry Techniques and Applications ; Protein purification and stability ; Analytical Chemistry and Chromatography
Authors: Daniel Sanín-Villa | Oscar Danilo Montoya | Walter Gil-González | Luis Fernando Grisales-Noreña | Alberto-Jesús Perea-Moreno
Source: Energies (article, 2023-05-24)
Field: Materials Science — Materials Chemistry

Parameter Estimation of a Thermoelectric Generator by Using Salps Search Algorithm Thermoelectric generators (TEGs) have the potential to convert waste heat into electrical energy, making them attractive for energy harvesting applications. However, accurately estimating TEG parameters from industrial systems is a complex problem due to the mathematical complex non-linearities and numerous variables involved in the TEG modeling. This paper addresses this research gap by presenting a comparative evaluation of three optimization methods, Particle Swarm Optimization (PSO), Salps Search Algorithm (SSA), and Vortex Search Algorithm (VSA), for TEG parameter estimation. The proposed integrated approach is significant as it overcomes the limitations of existing methods and provides a more accurate and rapid estimation of TEG parameters. The performance of each optimization method is evaluated in terms of root mean square error (RMSE), standard deviation, and processing time. The results indicate that all three methods perform similarly, with average RMSE errors ranging from 0.0019 W to 0.0021 W, and minimum RMSE errors ranging from 0.0017 W to 0.0018 W. However, PSO has a higher standard deviation of the RMSE errors compared to the other two methods. In addition, we present the optimized parameters achieved through the proposed optimization methods, which serve as a reference for future research and enable the comparison of various optimization strategies. The disparities observed in the optimized outcomes underscore the intricacy of the issue and underscore the importance of the integrated approach suggested for precise TEG parameter estimation. Particle swarm optimization ; Mean squared error ; Ranging ; Generator (circuit theory) ; Standard deviation ; Computer science ; Thermoelectric generator ; Algorithm ; Mathematical optimization ; Mathematics ; Thermoelectric effect ; Statistics ; Power (physics) Advanced Thermoelectric Materials and Devices ; Metaheuristic Optimization Algorithms Research ; Advanced Multi-Objective Optimization Algorithms
Authors: Guangzhen Wang | Fu Dehui | Shuai Yuan | Chenxi Li | Xiao Han | Jinchao Du | Fei Du | Ke Chen
Source: Microwave and Optical Technology Letters (article, 2023-06-19)
Field: Chemistry — Spectroscopy

Rapid detection of dissolved acetylene in oil based on T‐type photoacoustic cell Abstract Aiming at the need of rapid and sensitive detection of acetylene dissolved in oil, a small‐volume T‐type photoacoustic (PA) cell was proposed. By optimizing the design parameters, the volume of the T‐type cell was reduced to 30 mL, which resulted in a significant reduction in the sampling amount of the transformer oil. A laser PA spectroscopy system for dissolved gas analysis was built combined with the headspace degassing method. A near‐infrared tunable laser with wavelength modulation spectroscopy was employed to detect the escaped acetylene gas from oil. Test results show that the detection limit of dissolved acetylene reaches 0.2 μL/L when the sampled oil volume is 50 mL. In addition, the degassing balance time can be shortened to 270 s. This scheme has the superiority of small oil extraction volume, high accuracy, and short response time, providing a new method for analyzing the dissolved characteristic gases in oil. Dissolved gas analysis ; Detection limit ; Acetylene ; Volume (thermodynamics) ; Photoacoustic imaging in biomedicine ; Analytical Chemistry (journal) ; Photoacoustic spectroscopy ; Spectroscopy ; Chemistry ; Laser ; Materials science ; Transformer oil ; Chromatography ; Transformer ; Optics ; Electrical engineering Spectroscopy and Laser Applications ; Analytical Chemistry and Sensors ; Gas Sensing Nanomaterials and Sensors
Authors: Marek Danielak | Krzysztof Przybył | K. Koszela
Source: Sensors (review, 2023-02-05)
Field: Chemistry — Analytical Chemistry

The Need for Machines for the Nondestructive Quality Assessment of Potatoes with the Use of Artificial Intelligence Methods and Imaging Techniques This article describes chemical and physical parameters, including their role in the storage, trade, and processing of potatoes, as well as their nutritional properties and health benefits resulting from their consumption. An analysis of the share of losses occurring during the production process is presented. The methods and applications used in recent years to estimate the physical and chemical parameters of potatoes during their storage and processing, which determine the quality of potatoes, are presented. The potential of the technologies used to classify the quality of potatoes, mechanical and ultrasonic, and image processing and analysis using vision systems, as well as their use in applications with artificial intelligence, are discussed. Quality (philosophy) ; Image processing ; Nondestructive testing ; Artificial intelligence ; Process (computing) ; Computer science ; Food processing ; Machine learning ; Engineering ; Image (mathematics) ; Food science Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Meat and Animal Product Quality
Authors: Ling Wang | Feng Gao | Shu‐Hua Teng | Zhiguo Tan | Xing Zhang | Jun Lou
Source: iScience (article, 2023-11-30)
Field: Materials Science — Electronic, Optical and Magnetic Materials

Terahertz tunable vanadium dioxide metasurface for dynamic illusion and cloaking Realizing camouflage by illusion and cloaking based on the metasurface has received widespread attention recently. However, existing metasurface-based illusion and cloaking devices are valid for the incident wave with a specific frequency, angle, or polarization, or exhibit a single function. Therefore, a terahertz tunable vanadium dioxide (VO<sub>2</sub>) metasurface carpet cloak is proposed for dynamic illusion and cloaking. Simulation results show that by controlling the state of the VO<sub>2</sub>, the metasurface carpet cloak can simultaneously achieve illusion and cloaking functions, working at 0.45 THz and 0.6 THz, and is effective for orthogonal circularly polarized waves with different incidence angles. That is the function, frequency, incident angle, and polarization of the metasurface carpet cloak are dynamically adjustable. Besides, the metasurface carpet cloak is robust to the incident angle and is capable of polarization angle stability. This work has potential value in the real-life application of metasurface-based illusion and cloaking devices. Cloaking ; Camouflage ; Terahertz radiation ; Vanadium dioxide ; Illusion ; Optics ; Polarization (electrochemistry) ; Optoelectronics ; Metamaterial ; Materials science ; Physics ; Nanotechnology ; Computer science ; Thin film ; Chemistry ; Physical chemistry ; Artificial intelligence Metamaterials and Metasurfaces Applications ; Advanced Antenna and Metasurface Technologies ; Polydiacetylene-based materials and applications
Authors: Liang Xu | Lingfeng Lai | Yaqi Wen | Jia Lin | Beibei Chen | Yazhi Zhong | Yan Cheng | Xiaolei Zhang | Jitian Guan | David J. Mikulis | Yan Lin | Gen Yan | Renhua Wu
Source: ACS Chemical Neuroscience (article, 2023-01-04)
Field: Materials Science — Materials Chemistry

Angiopep-2, an MRI Biomarker, Dynamically Monitors Amyloid Deposition in Early Alzheimer’s Disease The reliable and dynamic detection of amyloid β-protein (Aβ) deposition using imaging technology is necessary for preclinical Alzheimer's disease (AD), which may significantly improve prognosis. The present study aimed to evaluate the feasibility of applying angiopep-2 (ANG), a chemical exchange saturation transfer-magnetic resonance imaging (CEST-MRI) biomarker, for monitoring Aβ deposition in vivo. ANG exerted a good chemical exchange saturation transfer (CEST) effect and displayed a moderate binding affinity to Aβ1-42 in vitro. Six-month-old mice with AD injected with ANG exhibited a significantly enhanced CEST effect than controls in vivo; this effect gradually became more apparent at 8, 10, and 12 months. Spatial learning impairment caused by abundant Aβ deposition (representing mild cognitive impairment in AD patients) develops at 12 months in APPswe/PSEN1dE9 (line 85) AD mice. To conclude, the CEST of ANG could display very earlier age-related Aβ pathological progress in mice with AD, consistent with immunohistochemistry. ANG has extraordinary potential for clinical transformation as an imaging biomarker to diagnose early AD and track its progress dynamically and nonradiationally. Biomarker ; Magnetic resonance imaging ; In vivo ; Amyloid β ; Pathology ; Chemistry ; Imaging biomarker ; Disease ; Medicine ; Neuroscience ; Cancer research ; Psychology ; Biology ; Biochemistry ; Radiology Lanthanide and Transition Metal Complexes ; Advanced MRI Techniques and Applications ; MRI in cancer diagnosis
Authors: Afifah Mohd Asri | Siti Rohaidah Ahmad | Nurhafizah Moziyana Mohd Yusop
Source: International Journal of Advanced Computer Science and Applications (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Feature Selection using Particle Swarm Optimization for Sentiment Analysis of Drug Reviews Feature selection (FS) is an essential classification pre-processing task that eliminates irrelevant, redundant, and noisy features. The primary benefits of performing this task include enhanced model performance, reduced computational expense, and modified “curse of dimensionality”. The goal of performing FS is to find the best feature group that can be used to build an effective pattern recognition model. Drug reviews play a significant role in delivering valuable medical care information, such as the efficacy, side effects, and symptoms of drug use, facilities, drug pricing, and personal drug usage experience to healthcare providers and patients. FS can be used to obtain relevant and valuable information that can produce an optimal subset of features to help obtain accurate results in the classification of drug reviews. The FS approach reduces the number of input variables by eliminating redundant or irrelevant features and narrowing the collection of features to those most significant to the machine learning model. However, the high dimensionality of the feature vector is a major issue that reduces the accuracy of sentiment classification, making it challenging to find the best feature subset. Thus, this article presents a perceptive method to perform FS by gathering information from the potential solutions generated by a particle swarm optimization (PSO) algorithm. This research aimed to apply this algorithm to identify the optimal feature subset of drug reviews to improve the classification accuracy of sentiment analysis. The experimental results showed that PSO provided a better classification performance than a genetic algorithm (GA) and ant colony optimization (ACO) in most datasets. The results showed that PSO demonstrated the highest levels of performance, with an average of 49.3% for precision, 73.6% for recall, 59% for F-score, and 57.2% for accuracy. Computer science ; Feature selection ; Particle swarm optimization ; Curse of dimensionality ; Artificial intelligence ; Feature (linguistics) ; Machine learning ; Data mining ; Task (project management) ; Feature vector ; Pattern recognition (psychology) Machine Learning in Materials Science ; Computational Drug Discovery Methods ; Sentiment Analysis and Opinion Mining
Authors: Kamrul Hasan | Md. Toriqule Islam | Tusdid Sabur Tohfa | Fadzil Mat Yahaya
Source: CONSTRUCTION (article, 2023-04-27)
Field: Materials Science — Polymers and Plastics

Using Basalt Fiber Reinforced Polymer as Steel Reinforcement - Review The production of affordable, lightweight polymers using sustainable composites reinforced with natural, eco-friendly fibers has recently attracted a lot of attention from both the research and manufacturing realms. Future construction of buildings must have the least negative impact on the environment while also being long-lasting. Basalt is the best material to utilize as reinforcement among natural fibers (animal, vegetable, or mineral) because of its advantageous qualities. The superior features of basalt rebar, such as its high tensile strength, low young's modulus, and corrosion-inhibiting properties, contribute to its operational excellence. This article summarizes the previous studies to investigate the use of basalt fiber-reinforced polymer (BFRP) bars as a substitute for steel reinforcement, emphasizing flexural strength, serviceability, and durability. That fits with the objective of this study, which is to analyse the most updated available data, compile the findings, and then identify any knowledge gaps that warrant future investigation. Moreover, the authors concluded following the review that basalt rebar might be used in construction as a more environmentally friendly and sustainable substitute for steel reinforcement. Basalt fiber ; Reinforcement ; Serviceability (structure) ; Durability ; Environmentally friendly ; Materials science ; Composite material ; Rebar ; Ultimate tensile strength ; Basalt ; Civil engineering ; Fiber ; Engineering ; Geology Natural Fiber Reinforced Composites ; Structural Behavior of Reinforced Concrete ; Innovative concrete reinforcement materials
Authors: Joel B. Johnson | Aimen El Orche | Janice S. Mani | Abderrahmane Aït‐Kaddour | Kerry B. Walsh | Mani Naiker
Source: Applied Sciences (article, 2023-04-20)
Field: Chemistry — Analytical Chemistry

Prediction of Phytochemical Constituents in Cayenne Pepper Using MIR and NIR Spectroscopy The aim of the present study was to evaluate the potential of handheld near-infrared (NIR) and benchtop mid-infrared (MIR) spectroscopy for the rapid prediction of antioxidant capacity, dry matter, and total phenolic contents in cayenne pepper (Capsicum annuum ‘Cayenne’). Using NIR spectroscopy, the best-performing model for dry matter had an R2pred = 0.74, RMSEP = 0.38%, and RPD of 2.02, exceeding the best results previously reported in the literature. This was also the first study to predict dry matter content from the mid-infrared spectra, although with lower accuracy (R2pred = 0.54; RMSEP = 0.51%, RPD 1.51). The models for antioxidant capacity and total phenolic content did not perform well using NIR or MIR spectroscopy (RPD values &lt; 1.5), indicating that further optimization is required in this area. Application of support vector regression (SVR) generally gave poorer results compared to partial least squares regression (PLSR). NIR spectroscopy may be useful for in-field measurement of dry matter in the chili crop as a proxy measure for fruit maturity. However, the lower accuracy of MIR spectroscopy is likely to limit its use in this crop. Near-infrared spectroscopy ; Dry matter ; Partial least squares regression ; Pepper ; Chemistry ; Spectroscopy ; Phytochemical ; Food science ; Horticulture ; Mathematics ; Botany ; Biology ; Statistics ; Biochemistry ; Physics Spectroscopy and Chemometric Analyses ; Phytochemicals and Antioxidant Activities ; Essential Oils and Antimicrobial Activity