jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Dilara Gerdan Koç | Mustafa Vatandaş
Source: Turkish Journal of Agriculture - Food Science and Technology (article, 2021-12-25)
Field: Chemistry — Analytical Chemistry

Classification of Some Fruits using Image Processing and Machine Learning In this study, an image processing algorithm and classification unit were developed to classify the fruits according to their size and color characteristics. For this purpose, a total of 300 fruits (50 fruit samples from each of the Starkrimson Delicious and Golden Delicious apple varieties, Washington Navel and Valencia Midknight orange varieties, Ekmek and Eşme quince varieties) were used in the experiments. The size and color values measured with a caliper and a spectrophotometer were entered in the developed image processing algorithm to determine the success rates of classifying the fruits. The integration of image processing algorithm with the classification unit classified 88%, 100%, 96%, 82%, 86%, respectively. On the other hand, the size and color values read in fruits with the image processing algorithm were evaluated using predictive techniques used in data mining. For this purpose, K Nearest Neighbor (KNN), Decision Tree (DT), Naive Bayes classification and Multilayer Perceptron Neural Network (MLP) algorithms were used. Algorithms were run with 10-fold cross validation method. In the training of artificial classifiers, the success was 93.6% for KNN, 90.3% for DT, 88.3% for Naive Bayes, 92.6% for MLP and 94.3% for RF. Artificial intelligence ; Naive Bayes classifier ; Pattern recognition (psychology) ; Image processing ; Artificial neural network ; Decision tree ; Computer science ; Mathematics ; Machine learning ; Image (mathematics) ; Support vector machine Spectroscopy and Chemometric Analyses
Authors: Kiruba Raji | Thyagharajan K.K | Vignesh T | Kalaiarasi G
Source: KSII Transactions on Internet and Information Systems (article, 2021-10-31)
Field: Chemistry — Analytical Chemistry

Classifying Indian Medicinal Leaf Species Using LCFN-BRNN Model Indian herbal plants are used in agriculture and in the food, cosmetics, and pharmaceutical industries. Laboratory-based tests are routinely used to identify and classify similar herb species by analyzing their internal cell structures. In this paper, we have applied computer vision techniques to do the same. The original leaf image was preprocessed using the Chan-Vese active contour segmentation algorithm to efface the background from the image by setting the contraction bias as (v) -1 and smoothing factor () as 0.5, and bringing the initial contour close to the image boundary. Thereafter the segmented grayscale image was fed to a leaky capacitance fired neuron model (LCFN), which differentiates between similar herbs by combining different groups of pixels in the leaf image. The LFCN's decay constant (f), decay constant (g) and threshold (h) parameters were empirically assigned as 0.7, 0.6 and h=18 to generate the 1D feature vector. The LCFN time sequence identified the internal leaf structure at different iterations. Our proposed framework was tested against newly collected herbal species of natural images, geometrically variant images in terms of size, orientation and position. The 1D sequence and shape features of aloe, betel, Indian borage, bittergourd, grape, insulin herb, guava, mango, nilavembu, nithiyakalyani, sweet basil and pomegranate were fed into the 5-fold Bayesian regularization neural network (BRNN), K-nearest neighbors (KNN), support vector machine (SVM), and ensemble classifier to obtain the highest classification accuracy of 91.19%. Computer science ; Traditional medicine ; Artificial intelligence ; Medicine Spectroscopy and Chemometric Analyses ; Smart Agriculture and AI
Authors: Juan Fernández‐Novales | Ignacio Barrio | María P. Diago
Source: Agronomy (article, 2021-12-13)
Field: Chemistry — Analytical Chemistry

Non-Invasive Monitoring of Berry Ripening Using On-the-Go Hyperspectral Imaging in the Vineyard Hyperspectral imaging offers enormous potential for measuring grape composition with a high degree of representativity, allowing all exposed grapes from the cluster to be examined non-destructively. On-the-go hyperspectral images were acquired using a push broom hyperspectral camera (400–100 nm) that was mounted in the front part of a motorized platform moving at 5 km/h in a commercial Tempranillo vineyard in La Rioja, Spain. Measurements were collected on three dates during grape ripening in 2018 on the east side of the canopy, which was defoliated in the basal fruiting zone. A total of 144 grape clusters were measured for Total soluble solids (TSS), Titratable acidity (TA), pH, Tartaric and Malic acid, Anthocyanins and Total polyphenols, using standard wet chemistry reference methods, throughout the entire experiment. Partial Least Squares (PLS) regression was used to build calibration, cross validation and prediction models for the grape composition parameters. The best performances returned determination coefficients values of external validation (R2p) of 0.82 for TSS, 0.81 for Titratable acidity, 0.61 for pH, 0.62 for Tartaric acid, 0.84 for Malic acid, 0.88 for Anthocyanins and 0.55 for Total polyphenols. The promising results exposed in this work disclosed a notable methodology on-the-go for the non-destructive, in-field assessment of grape quality composition parameters along the ripening period. Vineyard ; Titratable acid ; Ripening ; Hyperspectral imaging ; Malic acid ; Partial least squares regression ; Polyphenol ; Tartaric acid ; Chemistry ; Berry ; Canopy ; Horticulture ; Food science ; Botany ; Mathematics ; Remote sensing ; Biology ; Citric acid ; Geography Spectroscopy and Chemometric Analyses ; Horticultural and Viticultural Research ; Fermentation and Sensory Analysis
Authors: Luke Reilly | Lirong Peng | Erika Lara | Daniel M. Ramos | Michael S. Fernandopulle | Caroline B. Pantazis | Julia T. Stadler | Marianita Santiana | Anant Dadu | James Iben | Faraz Faghri | Mike A. Nalls | Steven L. Coon | Priyanka Narayan | Andrew Singleton | Mark Cookson | Michael E. Ward | Yue Qi
Source: bioRxiv (Cold Spring Harbor Laboratory) (preprint, 2021-11-25)
Field: Chemistry — Spectroscopy

A fully automated FAIMS-DIA proteomic pipeline for high-throughput characterization of iPSC-derived neurons Abstract Fully automated proteomic pipelines have the potential to achieve deep coverage of cellular proteomes with high throughput and scalability. However, it is important to evaluate performance, including both reproducibility and ability to provide meaningful levels of biological insight. Here, we present an approach combining high field asymmetric waveform ion mobility spectrometer (FAIMS) interface and data independent acquisition (DIA) proteomics approach developed as part of the induced pluripotent stem cell (iPSC) Neurodegenerative Disease Initiative (iNDI), a large-scale effort to understand how inherited diseases may manifest in neuronal cells. Our FAIMS-DIA approach identified more than 8000 proteins per mass spectrometry (MS) acquisition as well as superior total identification, reproducibility, and accuracy compared to other existing DIA methods. Next, we applied this approach to perform a longitudinal proteomic profiling of the differentiation of iPSC-derived neurons from the KOLF2.1J parental line used in iNDI. This analysis demonstrated a steady increase in expression of mature cortical neuron markers over the course of neuron differentiation. We validated the performance of our proteomics pipeline by comparing it to single cell RNA-Seq datasets obtained in parallel, confirming expression of key markers and cell type annotations. An interactive webapp of this temporal data is available for aligned-UMAP visualization and data browsing ( https://share.streamlit.io/anant-droid/singlecellumap ). In summary, we report an extensively optimized and validated proteomic pipeline that will be suitable for large-scale studies such as iNDI. Pipeline (software) ; Computer science ; Proteomics ; Ion-mobility spectrometry ; Proteome ; Computational biology ; Induced pluripotent stem cell ; Chemistry ; Bioinformatics ; Mass spectrometry ; Biology ; Embryonic stem cell ; Gene Advanced Proteomics Techniques and Applications ; Single-cell and spatial transcriptomics ; Mass Spectrometry Techniques and Applications
Authors: Feng Xu | Lingyu Mo | Hong Chen | Jiaming Zhu
Source: Frontiers in Physics (article, 2021-02-17)
Field: Materials Science — Polymers and Plastics

RETRACTED: Genetic Algorithm to Optimize the Design of High Temperature Protective Clothing Based on BP Neural Network For the clothing design for high-temperature operation, the theory or method such as partial differential, nonlinear programming and finite difference method was first applied to construct the overall heat transfer model of “high temperature environment--clothing--air layer--skin” and draw the temperature distribution map. Secondly, according to the human body burn model, the optimal parameters of fabric thickness are obtained preliminarily. Finally, the weights and thresholds of BP neural network were optimized by genetic algorithm, and these optimized values were assigned to the optimized BP neural network, and the nonlinear thickness function was approximated and optimized with MATLAB. MATLAB ; Artificial neural network ; Clothing ; Nonlinear system ; Genetic algorithm ; Algorithm ; Computer science ; Function (biology) ; Artificial intelligence ; Machine learning ; Physics Textile materials and evaluations ; Infrared Thermography in Medicine ; Thermoregulation and physiological responses
Authors: Cheng Li | Bangsong Su | Tianlun Zhao | Cong Li | Jinhong Chen | Shuijin Zhu
Source: Journal of Cotton Research (article, 2021-05-07)
Field: Chemistry — Analytical Chemistry

Feasibility study on the use of near-infrared spectroscopy for rapid and nondestructive determination of gossypol content in intact cottonseeds Abstract Background Gossypol found in cottonseeds is toxic to human beings and monogastric animals and is a primary parameter for the integrated utilization of cottonseed products. It is usually determined by the techniques relied on complex pretreatment procedures and the samples after determination cannot be used in the breeding program, so it is of great importance to predict the gossypol content in cottonseeds rapidly and nondestructively to substitute the traditional analytical method. Results Gossypol content in cottonseeds was investigated by near-infrared spectroscopy (NIRS) and high-performance liquid chromatography (HPLC). Partial least squares regression, combined with spectral pretreatment methods including Savitzky-Golay smoothing, standard normal variate, multiplicative scatter correction, and first derivate were tested for optimizing the calibration models. NIRS technique was efficient in predicting gossypol content in intact cottonseeds, as revealed by the root-mean-square error of cross-validation (RMSECV), root-mean-square error of prediction (RMSEP), coefficient for determination of prediction ( R p 2 ), and residual predictive deviation (RPD) values for all models, being 0.05∼0.07, 0.04∼0.06, 0.82∼0.92, and 2.3∼3.4, respectively. The optimized model pretreated by Savitzky-Golay smoothing + standard normal variate + first derivate resulted in a good determination of gossypol content in intact cottonseeds. Conclusions Near-infrared spectroscopy coupled with different spectral pretreatments and partial least squares (PLS) regression has exhibited the feasibility in predicting gossypol content in intact cottonseeds, rapidly and nondestructively. It could be used as an alternative method to substitute for traditional one to determine the gossypol content in intact cottonseeds. Gossypol ; Partial least squares regression ; Coefficient of determination ; Cottonseed ; Chemistry ; Monogastric ; Mathematics ; Standard error ; Content (measure theory) ; Correlation coefficient ; Analytical Chemistry (journal) ; Chromatography ; Food science ; Nitrogen ; Statistics ; Biochemistry ; Plant nutrition Spectroscopy and Chemometric Analyses ; Research in Cotton Cultivation ; Rice Cultivation and Yield Improvement
Authors: Harun Taş | Jörg Adams | Jan C. Namyslo | Andreas Schmidt
Source: RSC Advances (article, 2021-01-01)
Field: Chemistry — Spectroscopy

Zn<sup>2+</sup> detection of a benzimidazole 8-aminoquinoline fluorescent sensor by inhibited tautomerization A new fluorescent chemosensor based on 8-aminoquinoline L1 bearing a benzimidazole moiety was synthesized, which exists as two predominant tautomers L1A and L1B in diluted DMSO-d<sub>6</sub> solution. Among various metal ions, L1 showed a highly selective and sensitive turn-on fluorescence response to the presence of Zn<sup>2+</sup> ions in methanol. The detection limit for Zn<sup>2+</sup> by L1 was calculated to be 1.76 × 10<sup>-7</sup> M. The 1 : 1 complexation ratio of the L1-Zn complex was confirmed through Job plot measurements. Complexation studies were performed by FT-IR, NMR and HR-ESI MS measurements and DFT calculations. With the gained insight, it was possible to successfully apply L1 in water sample analysis. Benzimidazole ; Tautomer ; Fluorescence ; Chemistry ; Medicinal chemistry ; Organic chemistry ; Physics Molecular Sensors and Ion Detection ; Electrochemical Analysis and Applications ; Luminescence and Fluorescent Materials
Authors: Susana Velasco‐Lozano | Silvia Alonso‐de Castro | Carlos Sánchez-Cano | Ana I. Benítez‐Mateos | Fernando López‐Gallego | Luca Salassa
Source: Chemical Science (article, 2021-11-29)
Field: Materials Science — Biomaterials

Metal substrate catalysis in the confined space for platinum drug delivery Catalysis-based approaches for the activation of anticancer agents hold considerable promise. These principally rely on the use of metal catalysts capable of deprotecting inactive precursors of organic drugs or transforming key biomolecules available in the cellular environment. Nevertheless, the efficiency of most of the schemes described so far is rather low, limiting the benefits of catalytic amplification as strategy for controlling the therapeutic effects of anticancer compounds. In the work presented here, we show that flavin reactivity within a hydrogel matrix provides a viable solution for the efficient catalytic activation and delivery of cisplatin, a worldwide clinically-approved inorganic chemotherapy agent. This is achieved by ionically adsorbing a flavin catalyst and a Pt(iv) prodrug as substrate into porous amino-functionalized agarose beads. The hydrogel chassis supplies high local concentrations of electron donating groups/molecules in the surrounding of the catalyst, ultimately boosting substrate conversion rates (TOF >200 min<sup>-1</sup>) and enabling controlled liberation of the drug by light or chemical stimuli. Overall, this approach can afford platforms for the efficient delivery of platinum drugs as demonstrated herein by using a transdermal diffusion model simulating the human skin. Platinum ; Catalysis ; Substrate (aquarium) ; Drug delivery ; Nanotechnology ; Materials science ; Space (punctuation) ; Combinatorial chemistry ; Metal ; Chemical space ; Drug ; Chemical engineering ; Chemistry ; Computer science ; Organic chemistry ; Drug discovery ; Metallurgy ; Engineering ; Pharmacology ; Medicine ; Biochemistry Nanoparticle-Based Drug Delivery ; Innovative Microfluidic and Catalytic Techniques Innovation ; Nanomaterials for catalytic reactions
Authors: Xanel Vecino | Mónica Reig | César Valderrama | José Luis Cortina
Source: Water (article, 2021-06-02)
Field: Materials Science — Biomaterials

Ion-Exchange Technology for Lactic Acid Recovery in Downstream Processing: Equilibrium and Kinetic Parameters The downstream processing for the separation and purification of lactic acid is a hot research area in the bio-refinery field due to its continuous growing market in different sectors, such as the food, cosmetic and pharmaceutical sectors. In this work, the use of ion-exchange technology for lactic acid recovery is proposed. For that, four anion exchange resins with different polymer structures and functional groups were tested (A100, MN100, A200E and MP64). The sorption process was optimized by the Box–Behnken factorial design, and the experimental data obtained in the sorption process were analyzed by using the response surface methodology and fitted at different isotherms and kinetics models. Moreover, regenerant type, contact time and solid/liquid ratio were evaluated in the desorption process. Results showed that the best resin for lactic acid removal was A100, at pH = 4, with a resin/lactic acid solution ratio of 0.15 g/mL during a maximum of 1 h, achieving 85% of lactic acid removal. Moreover, equilibrium data sorption of lactic acid onto A100 resin was fitted by a Langmuir isotherm and by a kinetic model of a pseudo-second order. In addition, in the desorption process, it was stablished that a resin/regenerant ratio of 0.15 g/mL during 30 min with 0.1 M of NaOH solution provided the best results (4.45 ± 0.08 mg/g). Lactic acid ; Sorption ; Desorption ; Ion-exchange resin ; Ion exchange ; Chemistry ; Chromatography ; Downstream processing ; Factorial experiment ; Chemical engineering ; Nuclear chemistry ; Ion ; Adsorption ; Organic chemistry ; Computer science biodegradable polymer synthesis and properties ; Biofuel production and bioconversion ; Protein purification and stability
Authors: Christian Beck | Marco Grimaldo | Michal K. Braun | Lena Bühl | Olga Matsarskaia | Niina Jalarvo | Fajun Zhang | Felix Roosen‐Runge | Frank Schreiber | Tilo Seydel
Source: Soft Matter (article, 2021-01-01)
Field: Materials Science — Materials Chemistry

Temperature and salt controlled tuning of protein clusters The formation of molecular assemblies in protein solutions is of strong interest both from a fundamental viewpoint and for biomedical applications. While ordered and desired protein assemblies are indispensable for some biological functions, undesired protein condensation can induce serious diseases. As a common cofactor, the presence of salt ions is essential for some biological processes involving proteins, and in aqueous suspensions of proteins can also give rise to complex phase diagrams including homogeneous solutions, large aggregates, and dissolution regimes. Here, we systematically study the cluster formation approaching the phase separation in aqueous solutions of the globular protein BSA as a function of temperature (<i>T</i>), the protein concentration (<i>c</i><sub>p</sub>) and the concentrations of the trivalent salts YCl<sub>3</sub> and LaCl<sub>3</sub> (<i>c</i><sub>s</sub>). As an important complement to structural, <i>i.e.</i> time-averaged, techniques we employ a dynamical technique that can detect clusters even when they are transient on the order of a few nanoseconds. By employing incoherent neutron spectroscopy, we unambiguously determine the short-time self-diffusion of the protein clusters depending on <i>c</i><sub>p</sub>, <i>c</i><sub>s</sub> and <i>T</i>. We determine the cluster size in terms of effective hydrodynamic radii as manifested by the cluster center-of-mass diffusion coefficients <i>D</i>. For both salts, we find a simple functional form <i>D</i>(<i>c</i><sub>p</sub>, <i>c</i><sub>s</sub>, <i>T</i>) in the parameter range explored. The calculated inter-particle attraction strength, determined from the microscopic and short-time diffusive properties of the samples, increases with salt concentration and temperature in the regime investigated and can be linked to the macroscopic behavior of the samples. Salt (chemistry) ; Nanotechnology ; Chemical physics ; Protein crystallization ; Chemistry ; Materials science ; Physical chemistry ; Crystallization ; Organic chemistry Enzyme Structure and Function ; Protein Structure and Dynamics ; Protein purification and stability
Authors: Rafaela Q. C. Melo | Marcus Vinícius Lia Fook | Antônio Gilson Barbosa de Lima
Source: Polymers (article, 2021-02-28)
Field: Materials Science — Polymers and Plastics

Non-Fickian Moisture Absorption in Vegetable Fiber Reinforced Polymer Composites: The Effect of the Mass Diffusivity This article aims to study the non-Fickian water absorption process in vegetable fiber-reinforced polymer composite using the Langmuir-type model, evaluating the influence of mass diffusivity on the process. The numerical solutions of the governing equations were obtained using the finite-volume method. Transient results of the local and average moisture content, free and entrapped water molecules concentration considering the constant diffusivity and as a function of the average and local moisture content were presented and analyzed. It was observed that the mass diffusivity effectively influences the water absorption behavior, especially in the initial time of the process, where higher differences in the water migration rates into the material are found. The largest free and entrapped water molecule concentration gradients were found close to the composite surface, especially when considering constant mass diffusivity. Thermal diffusivity ; Mass diffusivity ; Fick's laws of diffusion ; Materials science ; Composite material ; Absorption of water ; Absorption (acoustics) ; Moisture ; Fiber ; Water content ; Composite number ; Diffusion ; Mass transfer ; Volume (thermodynamics) ; Thermodynamics ; Chemistry ; Chromatography Natural Fiber Reinforced Composites ; Textile materials and evaluations ; Acoustic Wave Phenomena Research
Authors: Enas Abd Dleam | Sameer H. Kareem
Source: Baghdad Science Journal (article, 2021-01-12)
Field: Materials Science — Materials Chemistry

Mesoporous Silica Nanoparticles as a System for Ciprofloxacin Drug Delivery; Kinetic of Adsorption and Releasing Mesoporous silica (MPS) nanoparticle was prepared as carriers for drug delivery systems by sol–gel method from sodium silicate as inexpensive precursor of silica and Cocamidopropyl betaine (CABP) as template. The silica particles were characterized by SEM, TEM, AFM, XRD, and N2adsorption–desorption isotherms. The results show that the MPS particle in the nanorange (40-80 nm ) with average diameter equal to 62.15 nm has rods particle morphology, specific surface area is 1096.122 m2/g, pore volume 0.900 cm3/g, with average pore diameter 2.902 nm, which can serve as efficient carriers for drugs. The adsorption kinetic of Ciprofloxacin (CIP) drug was studied and the data were analyzed and found to match well with pseudo-first order kinetic model. The CIP drug-loaded mesoporous silica (CIP-mSiO2) nanoparticles has capacity of about 16.3 mg drug/ mg mSiO2 were achieved, and capable of releasing 26% and 98.6% of their drug content after 90 min in water and PBS solution(pH,7.4) respectively. In-vitro controlled release studies of CIP in Simulated Body Fluid were carried out under stirring conditions. A study on release kinetics and mechanism using Koresmeyer-Pepps model, first order kinetic, and kopcha model shows that the Korsmeyer-Peppas and Kopcha models, both conform more closely to the release data. Mesoporous silica ; Adsorption ; Materials science ; Drug delivery ; Chemical engineering ; Mesoporous material ; Nanoparticle ; Particle size ; Particle (ecology) ; Kinetics ; Desorption ; Sodium silicate ; Chromatography ; Nanotechnology ; Nuclear chemistry ; Chemistry ; Organic chemistry ; Composite material ; Catalysis Mesoporous Materials and Catalysis ; Nanoparticle-Based Drug Delivery ; Advanced Drug Delivery Systems
Authors: Donatela Sadriaj | Gert Desmet | Deirdre Cabooter
Source: Journal of Chromatography A (article, 2021-12-26)
Field: Chemistry — Spectroscopy

Taylor-Aris methodology for the experimental determination of molecular diffusion coefficients: Tutorial with focus on large biomolecules Chemistry ; Diffusion ; Analyte ; Taylor dispersion ; Chromatography ; Variance (accounting) ; Analytical Chemistry (journal) ; Biological system ; Thermodynamics Diffusion Coefficients in Liquids ; Analytical Chemistry and Chromatography ; Thermodynamic properties of mixtures