jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Edward J. Wolfrum | Courtney Payne | Alexa Schwartz | Joshua J. Jacobs | Robert W. Kressin
Source: BioEnergy Research (article, 2020-05-12)
Field: Chemistry — Analytical Chemistry

A Performance Comparison of Low-Cost Near-Infrared (NIR) Spectrometers to a Conventional Laboratory Spectrometer for Rapid Biomass Compositional Analysis Abstract The performance of a conventional laboratory near-infrared (NIR) spectrometer and two NIR spectrometer prototypes (a Texas Instruments NIRSCAN Nano evaluation model (EVM) and an InnoSpectra NIR-M-R2 spectrometer) are compared by collecting reflectance spectra of 270 well-characterized herbaceous biomass samples, building calibration models using the partial least squares (PLS-2) algorithm to predict five constituents of the samples from the reflectance spectra, and comparing the resulting model statistics. The prediction models developed using spectra from the Foss XDS spectrometer were slightly better than the prediction models developed using spectra from either the TI NIRSCAN Nano EVM and the InnoSpectra NIR-M-R2 as measured by the root mean square error (RMSECV) and the correlation coefficient ( R 2 _cv) for “leave-one-out” cross-validation (CV). The models built from the two prototype units were not statistically significantly different from each other ( p = 0.05). The Foss spectrometer has a larger wavelength range (400–2500 nm) compared with the two prototypes (900–1700 nm). When the spectra from the Foss XDS spectrometer were truncated so their wavelength range matched the wavelength range of the two prototype units, the resulting model was not statistically significantly different from the models from either prototype. Spectrometer ; Partial least squares regression ; Near-infrared spectroscopy ; Calibration ; Integrating sphere ; Spectral line ; Wavelength ; Analytical Chemistry (journal) ; Coefficient of determination ; Correlation coefficient ; Optics ; Chemistry ; Remote sensing ; Physics ; Mathematics ; Statistics ; Chromatography ; Geology Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Metabolomics and Mass Spectrometry Studies
Authors: Oliver M. Crook | Aikaterini Geladaki | Daniel J. H. Nightingale | Owen L. Vennard | Kathryn S. Lilley | Laurent Gatto | Paul Kirk
Source: PLoS Computational Biology (article, 2020-11-09)
Field: Chemistry — Spectroscopy

A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection The cell is compartmentalised into complex micro-environments allowing an array of specialised biological processes to be carried out in synchrony. Determining a protein's sub-cellular localisation to one or more of these compartments can therefore be a first step in determining its function. High-throughput and high-accuracy mass spectrometry-based sub-cellular proteomic methods can now shed light on the localisation of thousands of proteins at once. Machine learning algorithms are then typically employed to make protein-organelle assignments. However, these algorithms are limited by insufficient and incomplete annotation. We propose a semi-supervised Bayesian approach to novelty detection, allowing the discovery of additional, previously unannotated sub-cellular niches. Inference in our model is performed in a Bayesian framework, allowing us to quantify uncertainty in the allocation of proteins to new sub-cellular niches, as well as in the number of newly discovered compartments. We apply our approach across 10 mass spectrometry based spatial proteomic datasets, representing a diverse range of experimental protocols. Application of our approach to hyperLOPIT datasets validates its utility by recovering enrichment with chromatin-associated proteins without annotation and uncovers sub-nuclear compartmentalisation which was not identified in the original analysis. Moreover, using sub-cellular proteomics data from Saccharomyces cerevisiae, we uncover a novel group of proteins trafficking from the ER to the early Golgi apparatus. Overall, we demonstrate the potential for novelty detection to yield biologically relevant niches that are missed by current approaches. Computer science ; Proteomics ; Novelty detection ; Computational biology ; Proteome ; Novelty ; Inference ; Bayesian probability ; Annotation ; Artificial intelligence ; Machine learning ; Biology ; Bioinformatics Advanced Proteomics Techniques and Applications ; Mass Spectrometry Techniques and Applications ; Protein Structure and Dynamics
Authors: Hendrik Hotz | Benjamin Kirsch | Jan C. Aurich
Source: Journal of Intelligent Manufacturing (article, 2020-07-22)
Field: Materials Science — Materials Chemistry

Impact of the thermomechanical load on subsurface phase transformations during cryogenic turning of metastable austenitic steels Abstract When machining metastable austenitic stainless steel with cryogenic cooling, a deformation-induced phase transformation from γ-austenite to α′-martensite can be realized in the workpiece subsurface. This leads to a higher microhardness and thus improved fatigue and wear resistance. A parametric and a non-parametric model were developed in order to investigate the correlation between the thermomechanical load in the workpiece subsurface and the resulting α′-martensite content. It was demonstrated that increasing passive forces and cutting forces promoted the deformation-induced phase transformation, while increasing temperatures had an inhibiting effect. The feed force had no significant influence on the α′-martensite content. With the proposed models it is now possible to estimate the α′-martensite content during cryogenic turning by means of in-situ measurement of process forces and temperatures. Austenite ; Martensite ; Materials science ; Metastability ; Metallurgy ; Machining ; Indentation hardness ; Phase (matter) ; Deformation (meteorology) ; Austenitic stainless steel ; Composite material ; Microstructure Metal Alloys Wear and Properties ; Microstructure and Mechanical Properties of Steels ; Advanced machining processes and optimization
Authors: Eva H. Dulf | Dan Cristian Vodnar | Alex Ede Danku | Cristina I. Mureşan | O. Crisan
Source: Fractal and Fractional (article, 2020-04-10)
Field: Chemistry — Spectroscopy

Fractional-Order Models for Biochemical Processes Biochemical processes present complex mechanisms and can be described by various computational models. Complex systems present a variety of problems, especially the loss of intuitive understanding. The present work uses fractional-order calculus to obtain mathematical models for erythritol and mannitol synthesis. The obtained models are useful for both prediction and process optimization. The models present the complex behavior of the process due to the fractional order, without losing the physical meaning of gain and time constants. To validate each obtained model, the simulation results were compared with experimental data. In order to highlight the advantages of fractional-order models, comparisons with the corresponding integer-order models are presented. Process (computing) ; Order (exchange) ; Computer science ; Fractional calculus ; Variety (cybernetics) ; Integer (computer science) ; Mathematical model ; Applied mathematics ; Mathematical optimization ; Mathematics ; Artificial intelligence Analytical Chemistry and Chromatography ; Advanced Control Systems Design ; Enzyme Catalysis and Immobilization
Authors: Evgenia D. Spyrelli | Agapi I. Doulgeraki | Anthoula A. Argyri | Chrysoula C. Tassou | Efstathios Ζ. Panagou | George‐John E. Nychas
Source: Microorganisms (article, 2020-04-11)
Field: Chemistry — Analytical Chemistry

Implementation of Multispectral Imaging (MSI) for Microbiological Quality Assessment of Poultry Products The aim of this study was to investigate on an industrial scale the potential of multispectral imaging (MSI) in the assessment of the quality of different poultry products. Therefore, samples of chicken breast fillets, thigh fillets, marinated souvlaki and burger were subjected to MSI analysis during production together with microbiological analysis for the enumeration of Total Viable Counts (TVC) and <i>Pseudomonas</i> spp. Partial Least Squares Regression (PLS-R) models were developed based on the spectral data acquired to predict the "time from slaughter" parameter for each product type. Results showed that PLS-R models could predict effectively the time from slaughter in all products, while the food matrix and variations within and between batches were identified as significant factors affecting the performance of the models. The chicken thigh model showed the lowest RMSE value (0.160) and an acceptable correlation coefficient (r = 0.859), followed by the chicken burger model where RMSE and r values were 0.285 and 0.778, respectively. Additionally, for the chicken breast fillet model the calculated r and RMSE values were 0.886 and 0.383 respectively, whereas for chicken marinated souvlaki, the respective values were 0.934 and 0.348. Further improvement of the provided models is recommended in order to develop efficient models estimating time from slaughter. Mathematics ; Multispectral image ; Partial least squares regression ; Coefficient of determination ; Chicken breast ; Correlation coefficient ; Fillet (mechanics) ; Food science ; Statistics ; Biology ; Computer science ; Artificial intelligence ; Engineering Spectroscopy and Chemometric Analyses ; Meat and Animal Product Quality ; Advanced Chemical Sensor Technologies
Authors: Bing Wu | Walter Chassé | Klaus Zick | Michael D. Mantle | Andreas Heise | Dermot F. Brougham | V. M. Litvinov
Source: Journal of Controlled Release (article, 2020-07-30)
Field: Chemistry — Organic Chemistry

The effect of hydrogen bonding on diffusion and permeability in UV-cured Polyacrylate-based networks for controlled release Polyacrylates are important polymers widely used in pharmaceutical industry such as drug coatings due to their low cost, processability and ease of functionalisation. Chemical functionalities (e.g. H-bonding) can be easily included to modulate the transport of low molecular weight drug-like entities through the network. Understanding how such microscopic structural modifications determine macroscopic diffusion is critical for designing next generation responsive polymers. In this study pulsed field gradient (PFG) <sup>1</sup>H NMR measurements of the self-diffusion of a dye molecule (Eosin Y) in a series of polyacrylate networks with differing H-bonding strength were undertaken; it was found that the diffusion of Eosin Y is significantly reduced in networks with H-bonding. Detailed analyses by <sup>1</sup>H NMR relaxometry and double quantum (DQ) NMR show that H-bonding can also reduce polymer chain mobility. Furthermore, DSC thermoporometry showed a significant increase in the average network mesh size potentially due to the pre-organization of H-bonding containing monomer during network curing. By introducing the H-bonding disrupter, LiClO<sub>4</sub>, it was found that the diffusivity of solute becomes positively correlated to the average mesh size across the series of networks. Hence, a modified diffusion model based on hydrodynamic theory is proposed to separate the direct (solute-network) H-bonding contribution to solute diffusion from the indirect contribution arising from monomer pre-ordering induced mesh size reduction. Finally, it is shown that the same direct and indirect contributions to microscopic diffusivity, arising from the H-bond strength of the co-monomers, also contribute significantly to the macroscopic membrane permeability which is similarly subject to H-bond disruption. Monomer ; Diffusion ; Polymer ; Hydrogen bond ; Thermal diffusivity ; Chemistry ; Pulsed field gradient ; Chemical engineering ; Molecule ; Polymer chemistry ; Organic chemistry ; Thermodynamics Advanced Polymer Synthesis and Characterization ; Surfactants and Colloidal Systems ; Polymer composites and self-healing
Authors: Lina Yan | Lei Hou | Shengtong Sun | Peiyi Wu
Source: Industrial & Engineering Chemistry Research (article, 2020-04-03)
Field: Chemistry — Analytical Chemistry

Dynamic Diffusion of Disperse Dye in a Polyethylene Terephthalate Film from an Infrared Spectroscopic Perspective The diffusion behavior of a typical disperse dye, disperse red 9 (DR 9), in the polyethylene terephthalate (PET) film at different temperatures was investigated by attenuated total reflection–Fourier transform infrared spectroscopy and 2D correlation spectroscopy (2Dcos) analyses. According to the Fickian diffusion model, the calculated diffusion coefficients of DR 9 in the PET film at different temperatures were observed to increase with temperature, which might be attributed to the increased free volume and thermal motion in the PET matrix and the rapid movement of DR 9 molecules at higher temperatures. In-detail analysis of the diffusion spectra discerned various kinds of molecular interactions, that is, intramolecular hydrogen bonding interactions of DR 9 and dipole–dipole and π–π interactions between DR 9 and PET. Among these, the dipole–dipole interactions between C═O groups of DR 9 and PET occurred first and played a vital role during the diffusion process of DR 9, as deduced from the sequence order of group motions in 2Dcos analysis. Polyethylene terephthalate ; Diffusion ; Intramolecular force ; Dipole ; Infrared ; Fourier transform infrared spectroscopy ; Hydrogen bond ; Infrared spectroscopy ; Molecule ; Materials science ; Attenuated total reflection ; Analytical Chemistry (journal) ; Spectroscopy ; Chemistry ; Nuclear magnetic resonance ; Organic chemistry ; Thermodynamics ; Optics ; Composite material ; Physics Spectroscopy and Chemometric Analyses ; Dye analysis and toxicity ; Electrochemical Analysis and Applications
Authors: Smriti Thakur | Sanjay K. Mandal
Source: ACS Omega (article, 2020-06-29)
Field: Materials Science — Materials Chemistry

Precursor- and Time-Dependent Morphological Evolution of ZnO Nanostructures for Comparative Photocatalytic Activity and Adsorption Dynamics with Methylene Blue Dye Diverse ZnO nanostructures were successfully fabricated at 700 °C by direct annealing of 1D Zn(II) coordination polymer precursors, namely, [Zn<sub>2</sub>(bpma)<sub>2</sub>(adc)<sub>2</sub>] <sub><i>n</i></sub> , [Zn<sub>2</sub>(bpea)<sub>2</sub>(adc)<sub>2</sub>] <sub><i>n</i></sub> , and {[Zn<sub>2</sub>(bpta)<sub>2</sub>(adc)<sub>2</sub>]·2H<sub>2</sub>O} <sub><i>n</i></sub> . The effect of sacrificial ligands present in the precursors as well as a variation in the retention time (6-24 h) during their synthesis resulted in 0D nanospheres, 1D microrods, and 3D polyhedra (with a diamond-like structure) of ZnO. The as-synthesized ZnO nanostructures were characterized by field-emission scanning electron microscopy, transmission electron microscopy, X-ray diffractometry, diffuse reflectance spectroscopy, and Raman spectroscopy. The hexagonal crystal structure was confirmed for all the ZnO samples. A lattice spacing of 0.22 nm has been observed for nanospheres, whereas a lattice spacing of 0.26 nm has been observed for the polyhedra. Their Raman spectra confirm the wurtzite phase of ZnO. UV-vis spectra of ZnO nanostructures exhibit broad peaks in the range of 350-370 nm, and the band gap energies are found to be in the range of 3.02-3.20 eV. Based on the photoluminescence spectra photocatalytic activities of the as-synthesized ZnO nanostructures calcined for 12 h were tested with methylene blue (MB) as a contaminant in an aqueous solution. These results demonstrate that the photocatalytic efficiency of polyhedra is higher than those of nanospheres and microrods. The adsorption kinetics of MB dye by these nanostructures were studied by three different kinetic models-Elovich's, intraparticle, and pseudo-second-order. The maximum rate of adsorption was observed with the intraparticle diffusion model. Wurtzite crystal structure ; Photocatalysis ; Materials science ; Raman spectroscopy ; Photoluminescence ; Cathodoluminescence ; Nanostructure ; Diffuse reflectance infrared fourier transform ; Spectroscopy ; Nanotechnology ; Analytical Chemistry (journal) ; Zinc ; Chemistry ; Luminescence ; Catalysis ; Organic chemistry ZnO doping and properties ; Metal-Organic Frameworks: Synthesis and Applications ; Ga2O3 and related materials
Authors: Chenglang Xiang | Hui Liu | Jie Mu | Zhihui Lang | Haining Wang | Rongshan Nie | Fanyu Kong
Source: ACS Omega (article, 2020-08-04)
Field: Materials Science — Materials Chemistry

Thermodynamic Model and Kinetic Compensation Effect of Spontaneous Combustion of Sulfur Concentrates The spontaneous combustion of the sulfur concentrate is the main hazard faced in ore storage bins. To understand the thermodynamic characteristics of spontaneous combustion of the sulfur concentrate and test whether the kinetic compensation effects are present in the spontaneous combustion process of the sulfur concentrate, typical sulfur concentrate samples were selected as the research object, and thermogravimetric experiments were carried out under an air atmosphere at heating rates of 5, 10, and 15 K/min. On this basis, the contributions of different reaction models to the mass change during the spontaneous combustion of the sulfur concentrate, as well as the thermodynamic model and kinetic compensation effect, are analyzed. The results show that solid-phase combustion contributes the most to mass loss among different mechanisms of the reaction between the sulfur concentrate and oxygen. The contributions of reaction models to mass loss are affected by the different heating rates, and the contribution of solid-phase combustion to mass loss increases with increasing heating rates. The Malek method is used to obtain the kinetic model of the spontaneous combustion of the sulfur concentrate, and its mechanism function changes from a chemical reaction model to a three-dimensional diffusion model. There is a kinetic compensation effect in the spontaneous combustion process of the sulfur concentrate, and the level of the kinetic compensation line may be one of the bases for distinguishing the spontaneous combustion tendency of the sulfur concentrate. Combustion ; Sulfur ; Spontaneous combustion ; Chemistry ; Thermodynamics ; Kinetic energy ; Organic chemistry Thermal and Kinetic Analysis ; Coal Properties and Utilization ; Combustion and Detonation Processes
Authors: Wararat Montha | Weerakanya Maneeprakorn | I‐Ming Tang | Weeraphat Pon‐On
Source: RSC Advances (article, 2020-01-01)
Field: Materials Science — Biomaterials

Hyperthermia evaluation and drug/protein-controlled release using alternating magnetic field stimuli-responsive Mn–Zn ferrite composite particles Drug delivery particles in which the release of biomolecules is triggered by a magnetic simulant have attracted much attention and may have great potential in the fields of cancer therapy and tissue regenerative medicine. In this study, we have prepared magnetic Mn-Zn ferrite ((Mn,Zn)Fe<sub>2</sub>O<sub>4</sub>) (MZF) nanoparticles coated with chitosan-<i>g-N</i>-isopropylacrylamide (Chi-<i>g</i>-NIPAAm) polymer (MZF@Chi-<i>g</i>-NIPAAm) to deliver the anticancer drug (Doxorubicin, DOX) and bioactive proteins (Bone morphogenic protein (BMP-2)-immobilized bovine serum albumin (BSA)) (P//MZF@Chi-<i>g</i>-NIPAAm) and be used as chemo-hyperthermia and vector delivering biomolecules. For these purposes, we first show that the as-prepared MZF@Chi-<i>g</i>-NIPAAm particles exhibit super paramagnetic behavior and under certain conditions, they can act as a heat source with a specific absorption rate (SAR) of 34.88 W g<sup>-1</sup>. Under acidic conditions and in the presence of AMF, the fast release of DOX was seen at around 58.9% within 20 min. <i>In vitro</i> evaluations indicated that concurrent thermo-chemotherapy treatment by DOX-MZF@Chi-<i>g</i>-NIPAAm using AMF had a better antitumor effect, compared with those using either DOX or DOX-MZF@Chi-<i>g</i>-NIPAAm without AMF (89.02% of cells were killed as compared to 71.82% without AMF exposure). Up to 28.18% of the BSA (used as the model protein to determine the controlled release) is released from the P//MZF@Chi-<i>g</i>-NIPAAm particles under AMF exposure for 1 h (only 17.31% was released without AMF). These results indicated that MZF@Chi-<i>g</i>-NIPAAm particles could be used to achieve hyperthermia at a precise location, effectively enhancing the chemotherapy treatments, and have a promising future as drug or bioactive delivering molecules for cancer treatment and cartilage or bone regenerative applications. Doxorubicin ; Ferrite (magnet) ; Materials science ; Composite number ; Hyperthermia ; Bovine serum albumin ; Drug delivery ; Nuclear chemistry ; Nuclear magnetic resonance ; Biophysics ; Chemistry ; Chemotherapy ; Nanotechnology ; Medicine ; Surgery ; Biochemistry ; Composite material ; Internal medicine ; Biology Nanoparticle-Based Drug Delivery ; Blood properties and coagulation ; Characterization and Applications of Magnetic Nanoparticles
Authors: Ghadah M. Al‐Senani | Nada S. Al‐Kadhi
Source: Applied Sciences (article, 2020-07-14)
Field: Materials Science — Materials Chemistry

The Synthesis and Effect of Silver Nanoparticles on the Adsorption of Cu2+ from Aqueous Solutions The adsorption of Cu2+ ions from an aqueous solution using AgNPs synthesized from Convolvulus arvensis leaf extract was investigated. The characterization of AgNPs was investigated before and after the adsorption of Cu2+ ions via Fourier-transform infrared spectroscopy (FTIR), energy-dispersive X-ray spectroscopy (EDS), and scanning electron microscopy (SEM) analyses. The adsorbent contained various functional groups in addition to the AgNPs, which contributed to the Cu2+ ions adsorption. The silver nanoparticle surface consisted of spherical particles and deep pores, which adsorbed numerous Cu2+ ions. The influences of dosage, pH, and contact time on adsorption of 10 and 50 mg/L Cu2+ at 298 K, and initial Cu2+ concentrations at 298 and 323 K were studied. It was found that the highest percentage of Cu2+ ions adsorbed from an aqueous solution was 98.99%; the aqueous solution had 10 mg/L of Cu2+ ions and 0.2 g of AgNPs, at pH 12 and 298 K. A pseudo-second kinetics model offered the most accurate description of the process of adsorption. The process of Cu2+ adsorption more resembled a Langmuir rather than a Freundlich isotherm model, including chemical and physical mixed adsorption (mixed adsorption) processes, and was exothermic and spontaneous. Adsorption ; Aqueous solution ; Chemistry ; Freundlich equation ; Fourier transform infrared spectroscopy ; Langmuir adsorption model ; Langmuir ; Inorganic chemistry ; Silver nanoparticle ; Ion ; Nuclear chemistry ; Nanoparticle ; Materials science ; Chemical engineering ; Physical chemistry ; Organic chemistry ; Nanotechnology Nanoparticles: synthesis and applications ; Adsorption and biosorption for pollutant removal ; Graphene and Nanomaterials Applications
Authors: Thomas Themelis | Ali Amini | Jelle De Vos | Sebastiaan Eeltink
Source: Analytica Chimica Acta (review, 2020-12-29)
Field: Chemistry — Spectroscopy

Towards spatial comprehensive three-dimensional liquid chromatography: A tutorial review Chemistry ; Dimension (graph theory) ; Space (punctuation) ; Chromatography ; Product (mathematics) ; Two-dimensional chromatography ; Separation (statistics) ; Separation method ; Process engineering ; High-performance liquid chromatography ; Biological system ; Analytical Chemistry (journal) ; Machine learning ; Computer science Analytical Chemistry and Chromatography ; Microfluidic and Capillary Electrophoresis Applications ; Nanopore and Nanochannel Transport Studies