jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Lynn Mouawad | Georges Istamboulié | Gaëlle Catanante | Thierry Noguer
Source: Foods (article, 2023-12-30)
Field: Chemistry — Analytical Chemistry

Acetylcholinesterase- and Butyrylcholinesterase-Based Biosensors for the Detection of Quaternary Ammonium Biocides in Food Industry A sensitive and robust electrochemical cholinesterase-based sensor was developed to detect the quaternary ammonium (QAs) biocides most frequently found in agri-food industry wash waters: benzalkonium chloride (BAC) and didecyldimethylammonium chloride (DDAC). To reach the maximum residue limit of 28 nM imposed by the European Union (EU), two types of cholinesterases were tested, acetylcholinesterase (AChE, from <i>Drosophila melanogaster</i>) and butyrylcholinesterase (BChE, from horse serum). The sensors were designed by entrapping AChE or BChE on cobalt phthalocyanine-modified screen-printed carbon electrodes. The limits of detection (LOD) of the resulting biosensors were 38 nM for DDAC and 320 nM for BAC, using, respectively, AChE and BChE. A simple solid-phase extraction step was used to concentrate the samples before biosensor analysis, allowing for the accurate determination of DDAC and BAC in tap water with limits of quantification (LOQ) as low as 2.7 nM and 5.3 nM, respectively. Additional assays demonstrated that the use of a phosphotriesterase enzyme allows for the total removal of interferences due to the possible presence of organophosphate insecticides in the sample. The developed biosensors were shown to be stable during 3 months storage at 4 °C. Butyrylcholinesterase ; Detection limit ; Chemistry ; Biosensor ; Paraoxon ; Acetylcholinesterase ; Organophosphate ; Chromatography ; Biocide ; Ammonium ; Benzalkonium chloride ; Nerve agent ; Biochemistry ; Enzyme ; Aché ; Organic chemistry ; Pesticide ; Biology Analytical chemistry methods development ; Electrochemical sensors and biosensors ; Environmental Chemistry and Analysis
Authors: Jakub Czyżycki | Lidia Marciniak-Podsadna | Paweł Twardowski
Source: Advances in Science and Technology – Research Journal (article, 2023-11-21)
Field: Materials Science — General Materials Science

Classification of Deflections of Thin-Walled Elements Made of EN AW-7075A Aluminum Alloy During Milling The aim of the research is to classify and evaluate the size of deformations appearing during milling of thin-walled elements representing a pocket form made of aluminum alloy AW-7075A. Finishing, which is the purpose of the research, was carried out at the full depth of cut ap = 15 mm, milling the entire height of the wall in one pass. Deformations during machining were correlated with the geometric accuracy of the workpieces after machining. During the tests, deformations were measured with a laser displacement sensor, and the temperature of the samples was measured using a resistance temperature sensor. The tests made it possible to identify deformations occurring during the milling of thin-walled elements. The course of deformation during milling was analyzed, from which the value of deformation caused by milling, the reaction to this deformation and its time were extracted, additionally, permanent distortion of the workpiece was detected. The results show the effect of the ratio of the height to the thickness of the thin-walled element on its geometric accuracy after machining in the form of straightness and flatness of the samples. The test results were compared to the tests carried out on the Ti6Al4V titanium alloy, which confirmed the influence of the material selection on the course of deformations during milling. Alloy ; Materials science ; Aluminium ; Metallurgy Material Properties and Applications ; Engineering Technology and Methodologies ; Aluminum Alloy Microstructure Properties
Authors: Vijay Chandan | Rajesh Mishra | Viktor Kolář | Petr Jirků | Miroslav Müller | Hafsa Jamshaid
Source: Materials (article, 2023-07-08)
Field: Materials Science — Polymers and Plastics

Numerical and Experimental Analysis of Mechanical Properties in Hybrid Epoxy–Basalt Composites Partially Reinforced with Cellulosic Fillers The current work is focused on numerical and experimental studies of woven fabric composites modified by hybridisation with biological (cellulosic) filler materials. The mechanical performance of the composites is characterized under tensile, bending and impact loads and the effect of hybridisation is observed with respect to pure and nonhybrid composites. Numerical models are developed using computational tools to predict mechanical performance under tensile loading. The computational prediction results are compared and validated with relevant experimental results. This research is aimed at understanding the mechanical performance of basalt-epoxy composites partially reinforced with micro-/nano-sized bio-fillers from cellulose and intended for various application areas. Different weave structures, e.g., plain, twill, matt, etc., were investigated with respect to the mechanical properties of the hybrid composites. The effects of hybridizing with cellulose particles and different weave patterns of the basalt fabric are studied. In general, the use of high-strength fibres such as basalt along with cellulosic fillers representing up to 3% of the total weight improves the mechanical performance of the hybrid structures. The thermomechanical performance of the hybrid composites improved significantly by using basalt fabric as well as by addition of 3% weight of cellulosic fillers. Results reveal the advantages of hybridisation and the inclusion of natural cellulosic fillers in the hybrid composite structures. The material developed is suitable for high-end applications in components for construction that demand advanced mechanical and thermomechanical performance. Furthermore, the inclusion of biodegradable fillers fulfills the objectives of sustainable and ecological construction materials. Composite material ; Materials science ; Ultimate tensile strength ; Epoxy ; Filler (materials) ; Basalt fiber ; Composite number ; Plain weave ; Bending ; Fiber ; Yarn Natural Fiber Reinforced Composites ; Additive Manufacturing and 3D Printing Technologies ; Innovations in Concrete and Construction Materials
Authors: Juho Son | Seungjin Na | Eunok Paek
Source: Analytical Chemistry (article, 2023-07-17)
Field: Chemistry — Spectroscopy

DbyDeep: Exploration of MS-Detectable Peptides via Deep Learning Predicting peptide detectability is useful in a variety of mass spectrometry (MS)-based proteomics applications, particularly targeted proteomics. However, most machine learning-based computational methods have relied solely on information from the peptide itself, such as its amino acid sequences or physicochemical properties, despite the fact that peptides detected by MS are dependent on many factors, including protein sample preparation, digestion, separation, ionization, and precursor selection during MS experiments. DbyDeep (Detectability by Deep learning) is an innovative end-to-end LSTM network model for peptide detectability prediction that incorporates sequence contexts of peptides and their cleavage sites (by protease). Utilizing the cleavage site contexts could improve the performance of prediction, and DbyDeep outperformed existing methods in predicting peptides recognizable from multiple MS/MS data sets with diverse species and MS instruments. We argue for the necessity of a learning model that encompasses several contexts associated with peptide detection, as opposed to depending just on peptide sequences. There is a Python implementation of DbyDeep at https://github.com/BISCodeRepo/DbyDeep. Chemistry ; Peptide ; Bottom-up proteomics ; Proteomics ; Python (programming language) ; Computational biology ; Mass spectrometry ; Deep learning ; Peptide sequence ; Amino acid ; Artificial intelligence ; Cleavage (geology) ; Machine learning ; Tandem mass spectrometry ; Chromatography ; Computer science ; Biochemistry ; Protein mass spectrometry Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Ibrahim A. Darwısh | Zongzhi Wang | Ryhan J. Darling | Nourah Z. Alzoman
Source: RSC Advances (article, 2023-01-01)
Field: Chemistry — Analytical Chemistry

Development of two highly sensitive and selective sensor-assisted fluorescence immunoassays for trace determination of copper residues in food samples This study describes the development of two highly sensitive and selective sensor-assisted fluorescence immunoassays for the trace determination of copper ions, Cu(ii) residues, in food samples. These assays were the microwell-based fluoroimmuoassay (FIA) and the kinetic exclusion assay (KinExA). FIA and KinExA were assisted by a microplate reader and a KinExA™ 3200 immunosensor, respectively. Both FIA and KinExA were developed utilizing the same antibody, capturing reagent, and fluorescence signal-generating reagent. The antibody was a mouse monoclonal antibody, designated as 8D66, that specifically recognized the Cu(ii)-ethylenediaminetetraacetic acid complex (Cu(ii)-EDTA) but did not recognize Cu(ii)-free EDTA. The capturing reagent was Cu(ii)-EDTA covalently linked to bovine serum albumin protein (Cu(ii)-EDTA-BSA). The fluorescence-generating reagent was an anti-mouse IgG conjugated with fluorescein isothiocyanate (IgG-FITC). Both FIA and KinExA involved competitive binding reactions between Cu(ii)-EDTA complexes, formed in the sample solution, and Cu(ii)-EDTA-BSA conjugate which has been immobilized onto microwell fluorescence assay plates (in FIA) or polymethylmethacrylate beads (in KinExA) for a limited quantity of binding sites of 8D66 antibody. The conditions of both FIA and KinExA were investigated, and the optimum procedures were established. Both FIA and KinExA were validated, and all validation parameters were acceptable. Many different metal ions that are commonly encountered in food samples did not interfere with Cu(ii) analysis by both FIA and KinExA. Both assays were applied to the determination of Cu(ii) in food samples with satisfactory accuracy and precision. Both assays were compared favorably with inductively coupled plasma atomic emission spectroscopy. Comparative evaluation of FIA and KinExA revealed that KinExA had higher sensitivity and better precision than FIA, whereas, both assays had comparable accuracy. Both FIA and KinExA were superior to the existing atomic spectrometric methods for Cu(ii). The proposed FIA and KinExA are anticipated to effectively contribute to assessing Cu(ii) concentrations and controlling the exposure of humans to its potential toxicities. Chemistry ; Reagent ; Ethylenediaminetetraacetic acid ; Chromatography ; Fluorescence ; Conjugate ; Bovine serum albumin ; Metal ions in aqueous solution ; Fluorescein ; Detection limit ; Immunoassay ; Copper ; Chelation ; Metal ; Inorganic chemistry ; Antibody ; Organic chemistry Analytical chemistry methods development ; Electrochemical Analysis and Applications ; Advanced biosensing and bioanalysis techniques
Authors: Yaoyao Hu | Jun Chang | Yiting Li | Wenchao Zhang | Xiaoxiao Lai | Quanquan Mu
Source: Journal of Spectroscopy (article, 2023-01-01)
Field: Chemistry — Analytical Chemistry

High Zoom Ratio Foveated Snapshot Hyperspectral Imaging for Fruit Pest Monitoring Snapshot hyperspectral imaging technology is increasingly used in agricultural product monitoring. In this study, we present a 9× local zoom snapshot hyperspectral imaging system. Using commercial spectral sensors with spectrally resolved detector arrays, we achieved snapshot hyperspectral imaging with 14 wavelength bands and a spectral bandwidth of 10–15 nm. An experimental demonstration was performed by acquiring spatial and spectral information about the fruit and Drosophila . The results show that the system can identify Drosophila and distinguish well between different types of fruits. The results of this study have great potential for online fruit classification and pest identification. Hyperspectral imaging ; Snapshot (computer storage) ; Spectral imaging ; Zoom ; Remote sensing ; Full spectral imaging ; Computer vision ; Computer science ; Imaging spectrometer ; Artificial intelligence ; Optics ; Spectrometer ; Geography ; Physics Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Remote-Sensing Image Classification
Authors: Ignacio Fdez. Galván | Roland Lindh
Source: ChemRxiv (preprint, 2023-04-06)
Field: Chemistry — Spectroscopy

Smooth Things Come in Threes: A Diabatic Surrogate Model for Conical Intersection Optimization The optimization of conical intersection structures is complicated by the non-differentiability of the adiabatic potential energy surfaces. In this work, we build a pseudo-diabatic surrogate model, based on Gaussian process regression, formed by three smooth and differentiable surfaces that can adequately reproduce the adiabatic surfaces. Using this model with the restricted variance optimization method results in a notable decrease of the overall computational effort required to obtain minimum energy crossing points. Diabatic ; Conical intersection ; Adiabatic process ; Intersection (aeronautics) ; Conical surface ; Surrogate model ; Differentiable function ; Gaussian process ; Gaussian ; Potential energy ; Variance (accounting) ; Work (physics) ; Mathematical optimization ; Mathematics ; Physics ; Mathematical analysis ; Classical mechanics ; Geometry ; Engineering ; Quantum mechanics ; Aerospace engineering Mass Spectrometry Techniques and Applications ; Machine Learning in Materials Science ; Advanced Multi-Objective Optimization Algorithms
Authors: Qinyi Liao | Ludovic Berthier | Haijun Zhou | Ning Xu
Source: Proceedings of the National Academy of Sciences (article, 2023-06-20)
Field: Materials Science — Materials Chemistry

Dynamic Gardner cross-over in a simple glass The criticality of the jamming transition responsible for amorphous solidification has been theoretically linked to the marginal stability of a thermodynamic Gardner phase. While the critical exponents of jamming appear independent of the preparation history, the pertinence of Gardner physics far from equilibrium is an open question. To fill this gap, we numerically study the nonequilibrium dynamics of hard disks compressed toward the jamming transition using a broad variety of protocols. We show that dynamic signatures of Gardner physics can be disentangled from the aging relaxation dynamics. We thus define a generic dynamic Gardner cross-over regardless of the history. Our results show that the jamming transition is always accessed by exploring increasingly complex landscape, resulting in anomalous microscopic relaxation dynamics that remains to be understood theoretically. Jamming ; Statistical physics ; Relaxation (psychology) ; Phase transition ; Amorphous solid ; Criticality ; Non-equilibrium thermodynamics ; Simple (philosophy) ; Glass transition ; Variety (cybernetics) ; Dynamic relaxation ; Physics ; Theoretical physics ; Condensed matter physics ; Computer science ; Chemistry ; Thermodynamics ; Quantum mechanics ; Polymer ; Psychology ; Epistemology Material Dynamics and Properties ; Phase Equilibria and Thermodynamics ; Theoretical and Computational Physics
Authors: Hans‐Jörg Wittsack | Karl Ludger Radke | Julia Stabinska | Alexandra Ljimani | Anja Müller‐Lutz
Source: Journal of Medical Systems (article, 2023-03-24)
Field: Materials Science — Materials Chemistry

calf – Software for CEST Analysis with Lorentzian Fitting Analysis of chemical exchange saturation transfer (CEST) MRI data requires sophisticated methods to obtain reliable results about metabolites in the tissue under study. CEST generates z-spectra with multiple components, each originating from individual molecular groups. The individual lines with Lorentzian line shape are mostly overlapping and disturbed by various effects. We present an elaborate method based on an adaptive nonlinear least squares algorithm that provides robust quantification of z-spectra and incorporates prior knowledge in the fitting process. To disseminate CEST to the research community, we developed software as part of this study that runs on the Microsoft Windows operating system and will be made freely available to the community. Special attention has been paid to establish a low entrance threshold and high usability, so that even less experienced users can successfully analyze CEST data. Health informatics ; Computer science ; Software ; Medicine ; Pathology ; Programming language Lanthanide and Transition Metal Complexes ; Advanced MRI Techniques and Applications ; Medical Imaging Techniques and Applications
Authors: Chengfeng Wu | Ming Jiang | Yingying Lu | Hongjian Qu | Hongyan Li | Shaoqing Hu
Source: Materials (article, 2023-10-15)
Field: Materials Science — Materials Chemistry

Experimental and Numerical Investigation into the Mechanical Behavior of Composite Solid Propellants Subject to Uniaxial Tension To further explore the quasi-static mechanical characteristics of composite solid propellants at low strain rates, an investigation was conducted on the mechanical behavior and damage mechanisms of a four-component hydroxy-terminated polybutadiene (HTPB) propellant by means of experiments and numerical simulation. A uniaxial tensile test and scanning electron microscope (SEM) characterization experiment were carried out. A microstructural model, which accurately represents the mesoscopic structure, was developed via the integration of micro-CT scanning and image-processing techniques. The constructed microstructural model was utilized to conduct a numerical simulation of the mechanical behavior. The experimental results demonstrated that the maximum tensile strength increases with increasing strain rate, and the primary cause of propellant failure at low strain rates is the dewetting phenomenon occurring at the interface between the larger particles and the matrix. The maximum tensile strength is 0.48 MPa when the strain rate is 0.00119 s<sup>-1</sup>, and the maximum tensile strength is 0.37 MPa when the strain rate is 0.000119 s<sup>-1</sup>. The simulation results indicated a consistent trend in variation when comparing the simulation and experimental curves. This suggested that the established model exhibits a high level of reliability, and provides a promising approach for carrying out microstructural simulations of heterogeneous propellants in future. The mechanical behavior of the propellant can be effectively described by utilizing a mesoscopic finite element model that incorporates the superelastic constitutive model of the matrix and the bilinear cohesive model. This framework facilitates the representation of mesoscopic damage evolution, which consequently provides insights into the damage mechanism. Additionally, the utilization of such models assists in compensating for the limitations of damage evolution characterization experiments. Materials science ; Ultimate tensile strength ; Propellant ; Composite material ; Strain rate ; Scanning electron microscope ; Composite number ; Mesoscopic physics ; Dewetting ; Tensile testing ; Tension (geology) High-Velocity Impact and Material Behavior ; Energetic Materials and Combustion ; Polymer crystallization and properties
Authors: Zhongyi Hu | Zhenzhen Luo | Yanli Wang | Qiuju Zhou | Shuangyan Liu | Qiang Wang
Source: Foods (article, 2023-06-24)
Field: Chemistry — Analytical Chemistry

Texture Feature Extraction from 1H NMR Spectra for the Geographical Origin Traceability of Chinese Yam Adulteration is widespread in the herbal and food industry and seriously restricts traditional Chinese medicine development. Accurate identification of geo-authentic herbs ensures drug safety and effectiveness. In this study, 1H NMR combined intelligent “rotation-invariant uniform local binary pattern” identification was implemented for the geographical origin confirmation of geo-authentic Chinese yam (grown in Jiaozuo, Henan province) from Chinese yams grown in other locations. Our results showed that the texture feature of 1H NMR image extracted with rotation-invariant uniform local binary pattern for identification is far superior compared to the original NMR data. Furthermore, data preprocessing is necessary. Moreover, the model combining a feature extraction algorithm and support vector machine (SVM) classifier demonstrated good robustness. This approach is advantageous, as it is accurate, rapid, simple, and inexpensive. It is also suitable for the geographical origin traceability of other geographical indication agricultural products. Traceability ; Local binary patterns ; Pattern recognition (psychology) ; Support vector machine ; Artificial intelligence ; Preprocessor ; Feature extraction ; Computer science ; Classifier (UML) ; Mathematics ; Data mining ; Image (mathematics) ; Statistics Spectroscopy and Chemometric Analyses ; Metabolomics and Mass Spectrometry Studies ; Identification and Quantification in Food
Authors: Calvin Fai | Charles J. Hages | Anthony J. C. Ladd
Source: PRX Energy (article, 2023-09-01)
Field: Materials Science — Materials Chemistry

Rapid Optoelectronic Characterization of Semiconductors by Combining Bayesian Inference with Metropolis Sampling Extraction of material parameters from experimental time-resolved photoluminescence measurements can be problematic; here, a Bayesian inference approach, with Metropolis Monte Carlo sampling, is demonstrated to quickly and accurately infer essential optoelectronic parameters from the characterization measurements. Characterization (materials science) ; Bayesian inference ; Inference ; Sampling (signal processing) ; Monte Carlo method ; Bayesian probability ; Metropolis–Hastings algorithm ; Computer science ; Photoluminescence ; Gibbs sampling ; Bayesian statistics ; Optoelectronics ; Statistical inference ; Materials science ; Markov chain Monte Carlo ; Artificial intelligence ; Statistics ; Mathematics ; Nanotechnology ; Computer vision Machine Learning in Materials Science ; Electron and X-Ray Spectroscopy Techniques ; Semiconductor materials and devices