jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Juan Aspromonte | Steven Mascrez | Damien Eggermont | Giorgia Purcaro
Source: Analytical and Bioanalytical Chemistry (review, 2023-11-24)
Field: Chemistry — Spectroscopy

Solid-phase microextraction coupled to comprehensive multidimensional gas chromatography for food analysis Solid-phase microextraction ; Gas chromatography ; Biochemical engineering ; Field (mathematics) ; Quality (philosophy) ; Analyte ; Computer science ; Food quality ; Gas phase ; Milestone ; Chemistry ; Gas chromatography–mass spectrometry ; Chromatography ; Mass spectrometry ; Food science ; Physics ; Engineering ; Mathematics Analytical Chemistry and Chromatography ; Advanced Chemical Sensor Technologies ; Analytical chemistry methods development
Authors: Ayman Ben Mabrouk | Jean‐Luc Putaux | Sami Boufi
Source: Industrial Crops and Products (article, 2023-06-08)
Field: Materials Science — Biomaterials

Valorization of olive leaf waste as a new source of fractions containing cellulose nanomaterials Cellulose ; Biorefinery ; Lignin ; Hemicellulose ; Biomass (ecology) ; Chemistry ; Thermal stability ; Materials science ; Crystallinity ; Chemical engineering ; Pulp and paper industry ; Raw material ; Organic chemistry ; Composite material Advanced Cellulose Research Studies ; Lignin and Wood Chemistry ; Polysaccharides and Plant Cell Walls
Authors: Najmeh Haghbin | Adel Bakhshipour | Hemad Zareiforoush | Sedigheh Mousanejad
Source: Plant Methods (article, 2023-06-02)
Field: Chemistry — Analytical Chemistry

Non-destructive pre-symptomatic detection of gray mold infection in kiwifruit using hyperspectral data and chemometrics Application of hyperspectral imaging (HSI) and data analysis algorithms was investigated for early and non-destructive detection of Botrytis cinerea infection. Hyperspectral images were collected from laboratory-based contaminated and non-contaminated fruits at different day intervals. The spectral wavelengths of 450 nm to 900 nm were pretreated by applying moving window smoothing (MWS), standard normal variates (SNV), multiplicative scatter correction (MSC), Savitzky-Golay 1<sup>st</sup> derivative, and Savitzky-Golay 2<sup>nd</sup> derivative algorithms. In addition, three different wavelength selection algorithms, namely; competitive adaptive reweighted sampling (CARS), uninformative variable elimination (UVE), and successive projection algorithm (SPA), were executed on the spectra to invoke the most informative wavelengths. The linear discriminant analysis (LDA), developed with SNV-filtered spectral data, was the most accurate classifier to differentiate the contaminated and non-contaminated kiwifruits with accuracies of 96.67% and 96.00% in the cross-validation and evaluation stages, respectively. The system was able to detect infected samples before the appearance of disease symptoms. Results also showed that the gray-mold infection significantly influenced the kiwifruits' firmness, soluble solid content (SSC), and titratable acidity (TA) attributes. Moreover, the Savitzky-Golay 1<sup>st</sup> derivative-CARS-PLSR model obtained the highest prediction rate for kiwifruit firmness, SSC, and TA with the determination coefficient (R<sup>2</sup>) values of 0.9879, 0.9644, 0.9797, respectively, in calibration stage. The corresponding cross-validation R<sup>2</sup> values were equal to 0.9722, 0.9317, 0.9500 for firmness, SSC, and TA, respectively. HSI and chemometric analysis demonstrated a high potential for rapid and non-destructive assessments of fungal-infected kiwifruits during storage. Hyperspectral imaging ; Mathematics ; Partial least squares regression ; Linear discriminant analysis ; Second derivative ; Chemometrics ; Pattern recognition (psychology) ; Analytical Chemistry (journal) ; Artificial intelligence ; Chemistry ; Chromatography ; Computer science ; Statistics Spectroscopy and Chemometric Analyses ; Listeria monocytogenes in Food Safety ; Essential Oils and Antimicrobial Activity
Authors: Yifei Hao | Xuegang Chen | Le Zhang | Myung‐Geun Han | Wei Wang | Yue‐Wen Fang | Hanghui Chen | Yimei Zhu | Xia Hong
Source: Nature Communications (article, 2023-12-12)
Field: Materials Science — Materials Chemistry

Record high room temperature resistance switching in ferroelectric-gated Mott transistors unlocked by interfacial charge engineering The superior size and power scaling potential of ferroelectric-gated Mott transistors makes them promising building blocks for developing energy-efficient memory and logic applications in the post-Moore's Law era. The close to metallic carrier density in the Mott channel, however, imposes the bottleneck for achieving substantial field effect modulation via a solid-state gate. Previous studies have focused on optimizing the thickness, charge mobility, and carrier density of single-layer correlated channels, which have only led to moderate resistance switching at room temperature. Here, we report a record high nonvolatile resistance switching ratio of 38,440% at 300 K in a prototype Mott transistor consisting of a ferroelectric PbZr<sub>0.2</sub>Ti<sub>0.8</sub>O<sub>3</sub> gate and an RNiO<sub>3</sub> (R: rare earth)/La<sub>0.67</sub>Sr<sub>0.33</sub>MnO<sub>3</sub> composite channel. The ultrathin La<sub>0.67</sub>Sr<sub>0.33</sub>MnO<sub>3</sub> buffer layer not only tailors the carrier density profile in RNiO<sub>3</sub> through interfacial charge transfer, as corroborated by first-principles calculations, but also provides an extended screening layer that reduces the depolarization effect in the ferroelectric gate. Our study points to an effective material strategy for the functional design of complex oxide heterointerfaces that harnesses the competing roles of charge in field effect screening and ferroelectric depolarization effects. Ferroelectricity ; Materials science ; Optoelectronics ; Transistor ; Field-effect transistor ; Non-volatile memory ; Condensed matter physics ; Dielectric ; Electrical engineering ; Voltage ; Physics Electronic and Structural Properties of Oxides ; Magnetic and transport properties of perovskites and related materials ; Multiferroics and related materials
Authors: Alessia Arangia | Ylenia Marino | Daniela Impellizzeri | Ramona D’Amico | Salvatore Cuzzocrea | Rosanna Di Paola
Source: International Journal of Molecular Sciences (review, 2023-02-04)
Field: Chemistry — Organic Chemistry

Hydroxytyrosol and Its Potential Uses on Intestinal and Gastrointestinal Disease In recent years, the phytoconstituents of foods in the Mediterranean diet (MD) have been the subject of several studies for their beneficial effects on human health. The traditional MD is described as a diet heavy in vegetable oils, fruits, nuts, and fish. The most studied element of MD is undoubtedly olive oil due precisely to its beneficial properties that make it an object of interest. Several studies have attributed these protective effects to hydroxytyrosol (HT), the main polyphenol contained in olive oil and leaves. HT has been shown to be able to modulate the oxidative and inflammatory process in numerous chronic disorders, including intestinal and gastrointestinal pathologies. To date, there is no paper that summarizes the role of HT in these disorders. This review provides an overview of the anti-inflammatory and antioxidant proprieties of HT against intestinal and gastrointestinal diseases. Hydroxytyrosol ; Mediterranean diet ; Polyphenol ; Antioxidant ; Olive oil ; Disease ; Oxidative damage ; Human health ; Gastrointestinal disease ; Biology ; Human studies ; Medicine ; Food science ; Traditional medicine ; Physiology ; Biotechnology ; Biochemistry ; Internal medicine ; Environmental health Edible Oils Quality and Analysis ; Potato Plant Research ; Cholesterol and Lipid Metabolism
Authors: Zahra Lotfi | Mehrdad Khakbiz | Niyousha Davari | Shahin Bonakdar | Javad Mohammadi | Mohammad Ali Shokrgozar | Sara Derhambakhsh
Source: Artificial Organs (article, 2023-03-04)
Field: Materials Science — Biomaterials

Fabrication and multiscale modeling of polycaprolactone/amniotic membrane electrospun nanofiber scaffolds for wound healing This study showed that mixing AM with PCL, a widely used polymer, in different concentrations can overcome PCL disadvantages such as high hydrophobicity and low cellular compatibility. Polycaprolactone ; Electrospinning ; Nanofiber ; Scaffold ; Ultimate tensile strength ; Biomedical engineering ; Viability assay ; Wound healing ; Tissue engineering ; Attenuated total reflection ; Materials science ; Adhesion ; Membrane ; Chemistry ; Fourier transform infrared spectroscopy ; Chemical engineering ; Composite material ; Cell ; Biochemistry ; Surgery Electrospun Nanofibers in Biomedical Applications ; Silk-based biomaterials and applications ; Wound Healing and Treatments
Authors: Moïse Kombolo‐Ngah | Arianna Goi | Matteo Santinello | Nicola Rampado | Stefka Atanassova | Jingjing Liu | Pascal Faure | Laure Thoumy | Alix Neveu | Donato Andueza | Massimo De Marchi | Jean-François J.-F. Hocquette
Source: Meat Science (article, 2023-03-20)
Field: Chemistry — Analytical Chemistry

Across countries implementation of handheld near-infrared spectrometer for the on-line prediction of beef marbling in slaughterhouse Only few studies have used Near-Infrared (NIR) spectroscopy to assess meat quality traits directly in the chiller. The aim of this study was therefore to investigate the ability of a handheld NIR spectrometer to predict marbling scores on intact meat muscles in the chiller. A total of 829 animals from 2 slaughterhouses in France and Italy were involved. Marbling was assessed according to the 3G (Global Grading Guaranteed) protocol using 2 different scores. NIR measurements were collected by performing 5 scans at different points of the Longissimus thoracis. An average MSA marbling score of 330-340 was obtained in the two countries. The prediction models provided a R<sup>2</sup> in external validation between 0.46 and 0.59 and a standard error of prediction between 83.1 and 105.5. Results did provide a moderate prediction of the marbling scores but can be useful in the European industry context to predict classes of MSA marbling. Marbled meat ; Line (geometry) ; Mobile device ; Spectrometer ; Infrared ; Environmental science ; Computer science ; Mathematics ; Animal science ; Biology ; Optics ; Physics ; World Wide Web Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Advanced Chemical Sensor Technologies
Authors: Chinmay Kurade | Maninder Meenu | Sahil Kalra | Ankur Miglani | Bala Chakravarthy Neelapu | Yong Yu | Hosahalli S. Ramaswamy
Source: Foods (article, 2023-03-16)
Field: Chemistry — Analytical Chemistry

An Automated Image Processing Module for Quality Evaluation of Milled Rice The paper demonstrates a low-cost rice quality assessment system based on image processing and machine learning (ML) algorithms. A Raspberry-Pi based image acquisition module was developed to extract the structural and geometric features from 3081 images of eight different varieties of rice grains. Based on features such as perimeter, area, solidity, roundness, compactness, and shape factor, an automatic identification system is developed to segment the grains based on their types and classify them by using seven machine learning algorithms. These ML models are trained using the images and are compared using different ML models. ROC curves are plotted for each model for quantitative analysis to assess the model's performance. It is concluded that the random forest classifier presents an accuracy of 77 percent and is the best-performing model for the classification of rice varieties. Furthermore, the same algorithm is efficiently employed to determine the price of adulterated rice samples based upon the market price of individual rice. Artificial intelligence ; Solidity ; Roundness (object) ; Random forest ; Image processing ; Classifier (UML) ; Computer science ; Pattern recognition (psychology) ; Machine vision ; Identification (biology) ; Perimeter ; Mathematics ; Machine learning ; Image (mathematics) Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI ; GABA and Rice Research
Authors: Recep Adiyaman | Nicholas S. Edmunds | Ahmet G Genc | Shuaa M. A. Alharbi | Liam J. McGuffin
Source: Bioinformatics Advances (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Improvement of protein tertiary and quaternary structure predictions using the ReFOLD refinement method and the AlphaFold2 recycling process Supplementary data are available at <i>Bioinformatics Advances</i> online. Quaternary ; Protein quaternary structure ; Process (computing) ; Chemistry ; Computer science ; Geology ; Paleontology ; Programming language ; Biochemistry Enzyme Structure and Function ; Protein Structure and Dynamics ; RNA and protein synthesis mechanisms
Authors: Shunan Feng | Jing Shang | Tao Tan | Qingchun Wen | Qinglong Meng
Source: Scientific Reports (article, 2023-08-14)
Field: Chemistry — Analytical Chemistry

Nondestructive quality assessment and maturity classification of loquats based on hyperspectral imaging The traditional method for assessing the quality and maturity of loquats has disadvantages such as destructive sampling and being time-consuming. In this study, hyperspectral imaging technology was used to nondestructively predict and visualise the colour, firmness, and soluble solids content (SSC) of loquats and discriminate maturity. On comparison of the performance of different feature variables selection methods and the calibration models, the results indicated that the multiple linear regression (MLR) models combined with the competitive adaptive reweighting algorithm (CARS) yielded the best prediction performance for loquat quality. Particularly, CARS-MLR models with optimal prediction performance were obtained for the colour (R<sup>2</sup><sub>P</sub> = 0.96, RMSEP = 0.45, RPD = 5.38), firmness (R<sup>2</sup><sub>P</sub> = 0.87, RMSEP = 0.23, RPD = 2.81), and SSC (R<sup>2</sup><sub>P</sub> = 0.84, RMSEP = 0.51, RPD = 2.54). Subsequently, distribution maps of the colour, firmness, and SSC of loquats were obtained based on the optimal CARS-MLR models combined with pseudo-colour technology. Finally, on comparison of different classification models for loquat maturity, the partial least square discrimination analysis model demonstrated the best performance, with classification accuracies of 98.19% and 97.99% for calibration and prediction sets, respectively. This study demonstrated that the hyperspectral imaging technique is promising for loquat quality assessment and maturity classification. Hyperspectral imaging ; Computer science ; Maturity (psychological) ; Quality (philosophy) ; Quality assessment ; Artificial intelligence ; Nondestructive testing ; Pattern recognition (psychology) ; Medicine ; Radiology ; Pathology ; Physics ; Psychology ; External quality assessment Spectroscopy and Chemometric Analyses ; Phytochemicals and Antioxidant Activities ; Essential Oils and Antimicrobial Activity
Authors: Peng Jin | Jintu Fan | Rong Zheng | Qing Chen | Le Liu | Runtian Jiang | Hui Zhang
Source: Sustainability (article, 2023-01-09)
Field: Materials Science — Polymers and Plastics

Design and Research of Automatic Garment-Pattern-Generation System Based on Parameterized Design Personalization in the apparel industry shows importance and the potential for demand, but the existing personalization has unreasonable time cost, labor cost, and resource waste. To solve the problems of the waste of resources as well as both time and labor cost caused by manual pattern making in clothing personalization, a method of automatic garment pattern generation based on a parametric formula and the Python language was proposed. Based on the classification of common curves in patterns, three curve fitting algorithms based on different parameters were derived and combined with the Python language to achieve personalized generation of different patterns by classifying the parameters in the system into key parameters, secondary parameters, and variable parameters. Three different methods for verifying the accuracy of the garment patterns were proposed based on curve fitting similarity and three-dimensional virtual modeling, and the accuracy of the proposed system was verified. The results show that the accuracy and comfort of the patterns generated via the system were high. Meanwhile, the Python-language-based system fits well with the production system of enterprises, which can improve the rapid response capability of garment personalization, greatly save the time cost and labor cost of enterprises, reduce resource loss, and contribute to the sustainable development of the garment industry. Personalization ; Python (programming language) ; Parameterized complexity ; Computer science ; Parametric statistics ; Industrial engineering ; Clothing ; Simulation ; Data mining ; Engineering ; Algorithm ; Operating system ; World Wide Web ; Mathematics Textile materials and evaluations ; 3D Shape Modeling and Analysis ; Color perception and design
Authors: Zhengmao Yang | Wenhao Li | Yang Chen | Wu Zeng | Wenbo Chen | Xueqiang Cao
Source: International Journal of Fatigue (article, 2023-04-05)
Field: Materials Science — Ceramics and Composites

Life assessment of thermomechanical fatigue in a woven SiC/SiC ceramic matrix composite with an environmental barrier coating at elevated temperature Materials science ; Composite material ; Ceramic matrix composite ; Composite number ; Softening ; Tension (geology) ; Ceramic ; Coating ; Modulus ; Compression (physics) Advanced ceramic materials synthesis ; Aluminum Alloys Composites Properties ; Mechanical Behavior of Composites
Authors: Xiangrui Wang | Wen‐Xiong Wang
Source: Aggregate (article, 2023-06-14)
Field: Materials Science — Materials Chemistry

Cellular journey of nanomaterials: Theories, trafficking, and kinetics Abstract Engineered nanomaterials (NMs) are increasingly fabricated in various fields involving consumer goods, waste management, and biomedical applications such as drug delivery, diagnosis, and treatment of pathological conditions. While these NMs are intentionally or unexpectedly in contact with the human body, there are growing concerns about their intracellular journey, especially considering the therapeutic or deleterious effects after they cross the cell membrane. In this review, the cellular journey of NMs including internalization, intracellular trafficking, and deposition/exocytosis is systematically discussed. This work highlights the accumulation of NMs in cells not only depends on the moment of NMs crossing the cell membrane but also at the following trafficking and exocytosis process. A deeper understanding of the cellular journey of NMs implies that an alternative strategy to fabricate specific targeting NMs is to bypass a few pathways of intracellular trafficking to achieve potent therapeutic effects with minimal toxicity. After comprehensively reviewing the cellular journey of NMs, current progress and application scenarios of kinetic models are discussed. Finally, this review focuses on the bottleneck problems and the corresponding solution technologies for studying the cellular journey of NMs. Recent progresses on the cellular journey of NMs provide new insights into the fabrication of biomedical NMs and facilitate technology development for probing the nano‐cell interaction with high temporal‐spatial resolution. Internalization ; Intracellular ; Exocytosis ; Nanotechnology ; Cell biology ; Cell ; Chemistry ; Biology ; Materials science ; Membrane Nanoparticles: synthesis and applications ; Graphene and Nanomaterials Applications ; Nanoparticle-Based Drug Delivery
Authors: Sarah Brajkovic | Nils Rugen | Carlos Agius | Nicola Berner | Stephan Eckert | Amirhossein Sakhteman | Claus Schwechheimer | Bernhard Küster
Source: Nutrients (article, 2023-02-03)
Field: Chemistry — Spectroscopy

Getting Ready for Large-Scale Proteomics in Crop Plants Plants are an indispensable cornerstone of sustainable global food supply. While immense progress has been made in decoding the genomes of crops in recent decades, the composition of their proteomes, the entirety of all expressed proteins of a species, is virtually unknown. In contrast to the model plant <i>Arabidopsis thaliana</i>, proteomic analyses of crop plants have often been hindered by the presence of extreme concentrations of secondary metabolites such as pigments, phenolic compounds, lipids, carbohydrates or terpenes. As a consequence, crop proteomic experiments have, thus far, required individually optimized protein extraction protocols to obtain samples of acceptable quality for downstream analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS). In this article, we present a universal protein extraction protocol originally developed for gel-based experiments and combined it with an automated single-pot solid-phase-enhanced sample preparation (SP3) protocol on a liquid handling robot to prepare high-quality samples for proteomic analysis of crop plants. We also report an automated offline peptide separation protocol and optimized micro-LC-MS/MS conditions that enables the identification and quantification of ~10,000 proteins from plant tissue within 6 h of instrument time. We illustrate the utility of the workflow by analyzing the proteomes of mature tomato fruits to an unprecedented depth. The data demonstrate the robustness of the approach which we propose for use in upcoming large-scale projects that aim to map crop tissue proteomes. Proteome ; Computational biology ; Proteomics ; Biology ; Arabidopsis ; Tandem mass spectrometry ; Biotechnology ; Chemistry ; Mass spectrometry ; Chromatography ; Computer science ; Biochemistry Advanced Proteomics Techniques and Applications ; Biosensors and Analytical Detection ; Mass Spectrometry Techniques and Applications
Authors: Jiaxuan Li | Rui Gao | Yan Zhang | Shuqing Wang | Lei Zhang | Wangbao Yin | Suotang Jia
Source: Chemosensors (article, 2023-06-28)
Field: Chemistry — Analytical Chemistry

Coal Calorific Value Detection Technology Based on NIRS-XRF Fusion Spectroscopy Calorific value is an important index for evaluating coal quality, and it is important to achieve the rapid detection of calorific value to improve production efficiency. In this paper, a calorific value detection method based on NIRS-XRF fusion spectroscopy is proposed, which utilizes NIRS to detect organic functional groups and XRF to detect inorganic ash-forming elements in coal. NIRS, XRF and NIRS-XRF fusion spectrum were separately used to establish partial least squares (PLS) regression models for coal calorific value, and better prediction performance was obtained by using fusion spectrum (the determination coefficient of calibration set (R2) was 0.98, the root mean square error of prediction set (RMSEP) was 0.19 MJ/kg, the average relative deviation for prediction (MARDP) was 0.95%). The variable selection is very important for model performance. The effective variables were extracted using Pearson correlation coefficients to further optimize the prediction model, and the evaluation indexes of the optimized model are R2 = 0.99, RMSEP = 0.16 MJ/kg and MARDP = 0.70%. In addition, the repeatability of the proposed method was briefly evaluated. The results show that the proposed method is an effective analysis method to detect the calorific value of coal, which provides a new idea and technique for coal quality detection. Heat of combustion ; Partial least squares regression ; Coal ; Repeatability ; Fusion ; Mean squared error ; Coefficient of determination ; Correlation coefficient ; Mathematics ; Calibration ; Environmental science ; Statistics ; Chemistry ; Combustion Spectroscopy and Chemometric Analyses ; Mineral Processing and Grinding ; Metal Extraction and Bioleaching