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Search results for: MOLECULAR MODELING,MOLECULES,NEURAL NETWORKS,SOLVENTS,VISCOSITY
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Computational modeling of molecularly imprinted polymers as a green approach to the development of novel analytical sorbents
PublicationThe development of novel molecularly imprinted polymers (MIP) sorbents for specific chemical compounds require a lot of tedious and time-consuming laboratory work. Significant quantities of solvents and reagents are consumed in the course of the verification of appropriate configurations of polymerization reagents. Implementation of molecular modeling in the MIP sorbent development process appears to provide a solution to this...
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Searching for Solvents with an Increased Carbon Dioxide Solubility Using Multivariate Statistics
PublicationIonic liquids (ILs) are used in various fields of chemistry. One of them is CO2 capture, a process that is quite well described. The solubility of CO2 in ILs can be used as a model to investigate gas absorption processes. The aim is to find the relationships between the solubility of CO2 and other variables—physicochemical properties and parameters related to greenness. In this study, 12 variables are used to describe a dataset...
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Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)
PublicationThe paper presents research on the approximation of variable-order fractional operators by recurrent neural networks. The research focuses on two basic variable-order fractional operators, i.e., integrator and differentiator. The study includes variations of the order of each fractional operator. The recurrent neural network architecture based on GRU (Gated Recurrent Unit) cells functioned as a neural approximation for selected...
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Experimental and Theoretical Insights into the Intermolecular Interactions in Saturated Systems of Dapsone in Conventional and Deep Eutectic Solvents
PublicationSolubility is not only a crucial physicochemical property for laboratory practice but also provides valuable insight into the mechanism of saturated system organization, as a measure of the interplay between various intermolecular interactions. The importance of these data cannot be overstated, particularly when dealing with active pharmaceutical ingredients (APIs), such as dapsone. It is a commonly used anti-inflammatory and...
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Transport properties of aqueous ionic liquid microemulsions: influence of the anion type and presence of the cosurfactant
PublicationTransport properties, viz. specific conductivity, dynamic viscosity and apparent diffusion coefficients, were measured as a function of water content in aqueous ionic liquid microemulsions containing 1-butyl-3- methylimidazolium hexafluorophosphate, [BMIM][PF6] and bis(trifluoromethanesulphonyl)imide, [BMIM][Tf2N], stabilized by the nonionic surfactant TX-100, or its mixture with a cosurfactant, i.e. butanol. The investigation covered...
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Experimental and Theoretical Screening for Green Solvents Improving Sulfamethizole Solubility
PublicationSolubility enhancement of poorly soluble active pharmaceutical ingredients is of crucial importance for drug development and processing. Extensive experimental screening is limited due to the vast number of potential solvent combinations. Hence, theoretical models can offer valuable hints for guiding experiments aimed at providing solubility data. In this paper, we explore the possibility of applying quantum-chemistry-derived...
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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublicationTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
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Thermophysical study of the binary mixtures of triethyl phosphate with N-methylformamide, N,N-dimethylformamide and N,N-dimethylacetamide – Experimental and theoretical approach
PublicationDensities at (293.15, 298.15, 303.15 and 308.15) K, and viscosities and ultrasonic velocities at 298.15 K of binary liquid mixtures of triethyl phosphate with N-methylformamide, N,N-dimethylformamide and N,N-dimethylacetamide have been measured over the entire range of composition at p = 0.1 MPa. From the experimental data, values of excess molar volume, excess isentropic compressibility, viscosity deviation and excess Gibbs energy...
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Chemometrics for Selection, Prediction, and Classification of Sustainable Solutions for Green Chemistry—A Review
PublicationIn this review, we present the applications of chemometric techniques for green and sustainable chemistry. The techniques, such as cluster analysis, principal component analysis, artificial neural networks, and multivariate ranking techniques, are applied for dealing with missing data, grouping or classification purposes, selection of green material, or processes. The areas of application are mainly finding sustainable solutions...
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A dipole-driven path for electron and positron attachments to gas-phase uracil and pyrimidine molecules: a quantum scattering analysis
PublicationElectron and positron scattering processes in the gas-phase are analysed for uracil and pyrimidine molecules using a multichannel quantum approach at energies close to threshold. The special effects on the scattering dynamics induced by the large dipole moments in both molecules on the spatial features of the continuum leptonic wavefunctions are here linked to the possible bound states of the Rydberg-like molecular anions or ‘positroned’...
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Novel 2-(2-arylmethylthio-4-chloro-5-methylbenzenesulfonyl)-1-(1,3,5-triazin-2-ylamino)guanidine derivatives: Inhibition of human carbonic anhydrase cytosolic isozymes I and II and the transmembrane tumor-associated isozymes IX and XII, anticancer activity, and molecular modeling studies
PublicationA series of novel 2-(2-arylmethylthio-4-chloro-5-methylbenzenesulfonyl)-1-(6-substituted-4-chloro-1,3,5-triazin-2-ylamino)guanidine derivatives 9–20 have been synthesized by substitution of chlorine atom at the 1,3,5-triazine ring in compounds 5–8 with 3- or 4-aminobenzenesulfonamide and 4-(aminomethyl)benzenesulfonamide hydrochloride. All the synthesized compounds were evaluated for their inhibitory activity toward hCA I, II,...
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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublicationMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
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Enzymatic cross-linking of β-lactoglobulin in solution and at air–water interface: Structural constraints
PublicationEffective and controlled use of cross-linking enzymes in structure engineering of food systems depends on characterization of the favorable conditions for enzyme-substrate complex and the limiting factors for the desired modification. In this respect, we analyzed the susceptibility of bovine β-lactoglobulin (BLG) to enzymatic cross-linking by Trichoderma reesei tyrosinase (TrTyr) and transglutaminase (TG). Changes in BLG molecular...
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A Novel Method of Endotoxins Removal from Chitosan Hydrogel as a Potential Bioink Component Obtained by CO2 Saturation
PublicationThe article presents a new approach in the purification of chitosan (CS) hydrogel in order to remove a significant amount of endotoxins without changing its molecular weight and viscosity. Two variants of the method used to purify CS hydrogels from endotoxins were investigated using the PyroGene rFC Enzymatic Cascade assay kit. The effect of the CS purification method was assessed in terms of changes in the dynamic viscosity of...
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Weakly Hydrated Solute of Mixed Hydrophobic–Hydrophilic Nature
PublicationInfrared (IR) spectroscopy is a commonly used and invaluable tool in studies of solvation phenomena in aqueous solutions. Concurrently, density functional theory calculations and ab initio molecular dynamics simulations deliver the solvation shell picture at the molecular detail level. The mentioned techniques allowed us to gain insights into the structure and energy of the hydrogen bonding network of water molecules around methylsulfonylmethane...
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Topical delivery of pharmaceutical and cosmetic macromolecules using microemulsion systems
PublicationMicroemulsions are transparent, thermodynamically stable colloidal systems. Over the recent years, they have been increasingly investigated due to their potential as skin delivery vehicles for a wide range of drug molecules. The nanoscale particle size and the specificity of microemulsion components are the main features determining the skin permeation process. However, in order to effectively cross the skin barrier, the active...
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Neural Network Subgraphs Correlation with Trained Model Accuracy
PublicationNeural Architecture Search (NAS) is a computationally demanding process of finding optimal neural network architecture for a given task. Conceptually, NAS comprises applying a search strategy on a predefined search space accompanied by a performance evaluation method. The design of search space alone is expected to substantially impact NAS efficiency. We consider neural networks as graphs and find a correlation between the presence...
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Fuzzy Divisive Hierarchical Clustering of Solvents According to Their Experimentally and Theoretically Predicted Descriptors
PublicationThe present study describes a simple procedure to separate into patterns of similarity a large group of solvents, 259 in total, presented by 15 specific descriptors (experimentally found and theoretically predicted physicochemical parameters). Solvent data is usually characterized by its high variability, dierent molecular symmetry, and spatial orientation. Methods of chemometrics can usefully be used to extract and explore accurately...
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Influence of addition of carbon nanotubes on rheological properties of selected liquid lubricants - a computer simulation study
PublicationThis work is motivated by the improvement of anti-friction properties of lubricants by addition of CNTs proved experimentally in literature. In particular, a methodology is developed to compute the shear viscosity of liquid lubricants (Propylene Glycol) based on Molecular Dynamics simulation. Non-Equilibrium molecular dynamics (NEMD) approach is used with a reactive force field ReaxFF implemented in LAMMPS. The simulations are...
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Lignocellulosic waste biosorbents infused with deep eutectic solvents for biogas desulfurization
PublicationThis paper introduces an innovative method for treating biogas streams, employing lignocellulosic biosorbents infused with environmentally friendly solvents known as deep eutectic solvents (DES). The primary focus of this study was the elimination of volatile organosulfur compounds (VSCs) from model biogas. Biosorbents, including energetic poplar wood, antipka tree, corncobs, and beech wood, were used, each with varying levels...
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From Linear Classifier to Convolutional Neural Network for Hand Pose Recognition
PublicationRecently gathered image datasets and the new capabilities of high-performance computing systems have allowed developing new artificial neural network models and training algorithms. Using the new machine learning models, computer vision tasks can be accomplished based on the raw values of image pixels instead of specific features. The principle of operation of deep neural networks resembles more and more what we believe to be happening...
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Spectroscopic and photophysical properties of ZNTPP in a room temperature ionic liquid
PublicationThe steady-state absorption and emission spectra and the time-resolved Soret- and Q-band excited fluorescence profiles of the model metalloporphyrin, ZnTPP, have been measured in a highly purified sample of the common room temperature ionic liquid, [bmim][PF(6)]. S(2)-S(0) emission resulting from Soret-band excitation behaves in a manner completely consistent with that of molecular solvents of the same polarizability. The ionic...
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Electron impact iozization of CCl4 and SF6 embedded in superfluid helium droplets
PublicationElectron impact ionization of helium nano-droplets containing several 104 He atoms and doped with CCl4 or SF6 molecules is studied with high-mass resolution. The mass spectra show significant clustering of CCl4 molecules, less so for SF6 under our experimental conditions. Positive ion efficiency curves as a function of electron energy indicate complete immersion of the molecules inside the helium droplets in both cases. For CCl4...
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Identyfikacja instrumentu muzycznego z nagrania fonicznego za pomocą sztucznych sieci neuronowych
PublicationCelem rozprawy jest zbadanie algorytmów do identyfikacji instrumentów występujących w sygnale polifonicznym z wykorzystaniem sztucznych sieci neuronowych. W części teoretycznej przywołano podstawy przetwarzania sygnałów fonicznych w kontekście ekstrakcji parametrów sygnałów wykorzystywanych w treningu sieci neuronowych. Dodatkowo dokonano analizy rozwoju metod uczenia maszynowego z uwzględnieniem podziału na sieci neuronowe pierwszej,...
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Selection of an artificial pre-training neural network for the classification of inland vessels based on their images
PublicationArtificial neural networks (ANN) are the most commonly used algorithms for image classification problems. An image classifier takes an image or video as input and classifies it into one of the possible categories that it was trained to identify. They are applied in various areas such as security, defense, healthcare, biology, forensics, communication, etc. There is no need to create one’s own ANN because there are several pre-trained...
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Open-Set Speaker Identification Using Closed-Set Pretrained Embeddings
PublicationThe paper proposes an approach for extending deep neural networks-based solutions to closed-set speaker identification toward the open-set problem. The idea is built on the characteristics of deep neural networks trained for the classification tasks, where there is a layer consisting of a set of deep features extracted from the analyzed inputs. By extracting this vector and performing anomaly detection against the set of known...
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Positron binding to alkali-metal hydrides: The role of molecular vibrations
PublicationThe bound vibrational levels for J=0 have been computed for the series of alkali-metal hydride molecules from LiH to RbH, including NaH and KH. For all four molecules the corresponding potential-energy curves have been obtained for each isolated species and for its positron-bound complex (e+XH). It is found that the calculated positron affinity values strongly depend on the molecular vibrational state for which they are obtained...
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Neural Network-Based Sequential Global Sensitivity Analysis Algorithm
PublicationPerforming global sensitivity analysis (GSA) can be challenging due to the combined effect of the high computational cost, but it is also essential for engineering decision making. To reduce this cost, surrogate modeling such as neural networks (NNs) are used to replace the expensive simulation model in the GSA process, which introduces the additional challenge of finding the minimum number of training data samples required to...
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Novel “acid tuned” deep eutectic solvents based on protonated L-proline
PublicationThe paper presents new types of deep eutectic solvents (DESs) based on L-proline protonated using three different acids (hydrochloric, sulfuric and phosphoric)and playing the role of a hydrogen bond acceptor(HBA). Glucose and xylitol were used as hydrogen bond donors (HBD). A series of deep eutectic solvents with various mole ratios were obtained for the systems L-proline: glucose and L-proline: xylitol. Density, melting point,...
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Magnetic deep eutectic solvents – Fundamentals and applications
PublicationMagnetic deep eutectic solvents (MDES), a relatively new subclass of conventional deep eutectic solvents (DES) containing additional paramagnetic components in their structure. MDES exhibit a strong response toward external magnetic fields, thus they can improve many industrial and analytical applications. In addition, this new group of solvents present unique physicochemical properties that can be easily tuned by selecting the...
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Abdominal Aortic Aneurysm segmentation from contrast-enhanced computed tomography angiography using deep convolutional networks
PublicationOne of the most common imaging methods for diagnosing an abdominal aortic aneurysm, and an endoleak detection is computed tomography angiography. In this paper, we address the problem of aorta and thrombus semantic segmentation, what is a mandatory step to estimate aortic aneurysm diameter. Three end-to-end convolutional neural networks were trained and evaluated. Finally, we proposed an ensemble of deep neural networks with underlying...
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Poly-L-Lysine-modified boron-doped diamond electrodes for the amperometric detection of nucleic acid bases
PublicationBoron-doped diamond (BDD) is a very promising supporting material used in the construction of biosensors for molecular recognition. The direct immobilization of structurally-organized huge molecules, such as poly-L-Lysine (PLL) provides the possibility of determining organic molecules, e.g. nucleic acid bases (e.g. adenine, guanine) or peptides and proteins. This paper describes the direct method for chemical and electrochemical...
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OBTAINING FLUID FLOW PATTERN FOR TURBINE STAGE WITH NEURAL MODEL.
PublicationIn the paper possibility of applying neural model to obtaining patterns of proper operation for fluid flow in turbine stage for fluid-flow diagnostics is discussed. Main differences between Computational Fluid Dynamics (CFD) solvers and neural model is given, also limitations and advantages of both are considered. Time of calculations of both methods was given, also possibilities of shortening that time with preserving the accuracy...
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Analyzing the Effectiveness of the Brain–Computer Interface for Task Discerning Based on Machine Learning
PublicationThe aim of the study is to compare electroencephalographic (EEG) signal feature extraction methods in the context of the effectiveness of the classification of brain activities. For classification, electroencephalographic signals were obtained using an EEG device from 17 subjects in three mental states (relaxation, excitation, and solving logical task). Blind source separation employing independent component analysis (ICA) was...
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Adsorption-assisted transport of water vapour in super-hydrophobic membranes filled with multilayer graphene platelets
PublicationThe effects of confinement of multilayer graphene platelets in hydrophobic microporous polymeric membranes are here examined. Intermolecular interactions between water vapour molecules and nanocomposite membranes are envisaged to originate assisted transport of water vapour in membrane distillation processes when a suitable filler-polymer ratio is reached. Mass transport coefficients are estimated under different working conditions,...
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ABSORPCJA, METABOLIZM I ROLA BIOLOGICZNA KWASÓW NUKLEINOWYCH OBECNYCH W ŻYWNOŚCI
PublicationKwasy nukleinowe należą do niedocenianych składników żywności, szczególnie surowej lub nisko przetworzonej. W niniejszej publikacji skupiono się na omówieniu przemian, jakim podlegają kwasy nukleinowe w przewodzie pokarmowym człowieka, procesie absorpcji nukleotydów oraz nukleozydów z przewodu pokarmowego, a także przedstawiono podstawowe etapy ich metabolizmu w komórkach organizmu. Produkty trawienia kwasów nukleinowych stanowią...
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Towards neural knowledge DNA
PublicationIn this paper, we propose the Neural Knowledge DNA, a framework that tailors the ideas underlying the success of neural networks to the scope of knowledge representation. Knowledge representation is a fundamental field that dedicates to representing information about the world in a form that computer systems can utilize to solve complex tasks. The proposed Neural Knowledge DNA is designed to support discovering, storing, reusing,...
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Data augmentation for improving deep learning in image classification problem
PublicationThese days deep learning is the fastest-growing field in the field of Machine Learning (ML) and Deep Neural Networks (DNN). Among many of DNN structures, the Convolutional Neural Networks (CNN) are currently the main tool used for the image analysis and classification purposes. Although great achievements and perspectives, deep neural networks and accompanying learning algorithms have some relevant challenges to tackle. In this...
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Studies of the Interaction Dynamics in Albumin-Chondroitin Sulfate Systems by Recurrence Method
PublicationThe physicochemical basis of lubrication of articular cartilage is still not fully understood. However, the synergy between components of the synovial fluid can be a crucial factor that could explain this phenomenon. This work presents a nonlinear data analysis technique named the recurrence method, applied to the system involving two components of synovial fluid: albumin and chondroitin sulfate (CS) immersed in a water environment....
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Rheology of potato starch chemically modified with microwave-assisted reactions
PublicationNative potato starch was sulfated, selenated, borated, silicated and zincatated by means of microwave-assisted reactions with varying doses of relevant reagents. Resulting products were characterized involving rheological behavior of pastes, their weight-average molecular weight (Mw), and radius of gyration (Rg). Most of the pastes showed shear-thinning behavior, with the flow behavior index (n) below unity. The pastes of starch...
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Prognostic and diagnostic capabilities of OOBN in assessing investment risk of complex construction projects
PublicationModelling decision problems using Bayesian networks is extremely valuable especially in case of issues related to uncertainty; it is also very helpful in constructing and understanding visual representation of the elements and their relations. This approach facilitates subsequent application of Bayesian networks, however there can be situations where using simple Bayesian networks is impractical or even ineffective. The aim of...
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Perspectives on the replacement of harmful organic solvents in analytical methodologies: a framework toward the implementation of a generation of eco-friendly alternatives
PublicationVolatile organic solvents derived from non-renewable fossil feedstocks are commonplace in analytical laboratories. In spite of their convenient performance in countless unit operations, their environmental, health and safety issues represent a major area of concern. The progressive replacement of organic solvents obtained from fossil resources by eco-friendly alternatives would involve remarkable advances within the framework of...
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Machine Learning Applied to Aspirated and Non-Aspirated Allophone Classification—An Approach Based on Audio "Fingerprinting"
PublicationThe purpose of this study is to involve both Convolutional Neural Networks and a typical learning algorithm in the allophone classification process. A list of words including aspirated and non-aspirated allophones pronounced by native and non-native English speakers is recorded and then edited and analyzed. Allophones extracted from English speakers’ recordings are presented in the form of two-dimensional spectrogram images and...
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TOXIC GASES IDENTIFICATION USING SINGLE ELECTROCATALYTIC SENSOR RESPONSES AND ARTIFICIAL NEURAL NETWORK
PublicationThe need for precise detection of toxic gases drives development of new gas sensors structures and methods of processing the output signals from the sensors. In literature, artificial neural networks are considered as one of the most effective tool for the analysis of gas sensors or sensors arrays responses. In this paper a method of toxic gas components identification using a electrocatalytic gas sensor as a detector and an artificial...
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Neural network training with limited precision and asymmetric exponent
PublicationAlong with an extremely increasing number of mobile devices, sensors and other smart utilities, an unprecedented growth of data can be observed in today’s world. In order to address multiple challenges facing the big data domain, machine learning techniques are often leveraged for data analysis, filtering and classification. Wide usage of artificial intelligence with large amounts of data creates growing demand not only for storage...
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Magnetic deep eutectic solvents as efficient media for extraction of furfural and 5-hydroxymethylfurfural from aqueous samples
PublicationThe extraction of furfural (FF) and 5-hydroxymethylfurfural (HMF) from hydrolysates is currently one of the main challenges in bio-refinery. In this work, the separation of FF and HMF from the aqueous phase was carried out using a new type of green solvents – Magnetic Deep Eutectic Solvents (MDES). A conductor-like screening model for realistic solvents (COSMO-RS) was used for the preselection of 400 MDES. MDES which exhibit the...
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Removal of Siloxanes from Model Biogas by Means of Deep Eutectic Solvents in Absorption Process
PublicationThe paper presents the screening of 20 deep eutectic solvents (DESs) composed of tetrapropylammonium bromide (TPABr) and glycols in various molar ratios, and 6 conventional solvents as absorbents for removal of siloxanes from model biogas stream. The screening was achieved using the conductor-like screening model for real solvents (COSMO-RS) based on the comparison of siloxane solubility in DESs. For the DES which was characterized...
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Green adsorbents and solvents in food analysis
PublicationGreen analytical chemistry aims to minimize the negative impact of analytical procedures on the environment and human health. This can be achieved through the use of non-toxic and environmentally friendly reagents. Classical green solvents include water, ethanol, acetone, and supercritical fluids. Water has been used for the extraction of water-soluble compounds (sugars, amino acids). Ethanol and acetone have been used for the...
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Organic solvents aggregating and shaping structural folding of protein, a case study of the protease enzyme
PublicationLow solubility of reactants or products in aqueous solutions can result in the enzymatic catalytic reactions that can occur in non-aqueous solutions. In current study we investigated aqueous solutions containing different organic solvents / deep eutectic solvents (DESs) that can influence the protease enzyme's activity, structural, and thermal stabilities. Retroviral aspartic protease enzyme is responsible for the cleavage of the...
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Interactions of positrons with atoms and molecules
PublicationThe positron is the antiparticle of the electron. It has the same mass as the electron, but opposite charge. The understanding of the interactions of positrons with normal matter, like atoms and molecules, is of interest in various scientific fields, like nuclear medicine, plasma physics and astronomy. In this talk we will give a short introduction to some theoretical methods to describe the interactions of positrons with atoms...