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Wyniki wyszukiwania dla: MOLECULAR MODELING,MOLECULES,NEURAL NETWORKS,SOLVENTS,VISCOSITY
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Composite 2D Material-Based Pervaporation Membranes for Liquid Separation: A Review
PublikacjaToday, chemistry and nanotechnology cover molecular separations in liquid and gas states by aiding in the design of new nano-sized materials. In this regard, the synthesis and application of two-dimensional (2D) nanomaterials are current fields of research in which structurally defined 2D materials are being used in membrane separation either in self-standing membranes or composites with polymer phases. For instance, pervaporation...
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A Model of Thermal Energy Storage According to the Convention of Bond Graphs (BG) and State Equations (SE)
PublikacjaThe main advantage of the use of the Bond Graphs method and State Equations for modeling energy systems with a complex structure (marine power plants, hybrid vehicles, etc.) is the ability to model the system components of different physical nature using identical theoretical basis. The paper presents a method of modeling thermal energy storage, which is in line with basic BG theory. Critical comments have been put forward concerning...
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Structural and dynamic properties of water within the solvation layer around various conformations of the glycine-based polypeptide
PublikacjaSeveral conformations of the solvated glycine-based polypeptides were investigated using molecular dynamics simulations. Some properties of water in the neighbouring space around these molecules were investigated. It was found, that water forms a well-defined layer - the first solvation shell - around the peptide molecule, and thickness of this layer is independent of the peptide structure, and it equals to approximately 0.28 nm....
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Molecular basis of the osmolyte effect on protein stability: a lesson from the mechanical unfolding of lysozyme
PublikacjaOsmolytes are a class of small organic molecules that shift the protein folding equilibrium. For this reason, they are accumulated by organisms under environmental stress, and find applications in biotechnology where proteins need to be stabilized or dissolved. However, despite years of research, debate continues over the exact mechanisms underpinning the stabilizing and denaturing effect of osmolytes. Here, we simulated the mechanical...
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Are stabilizing osmolytes preferentially excluded from the protein surface? FTIR and MD studies
PublikacjaInteractions between osmolytes and hen egg white lysozyme in aqueous solutions were studied by means of FTIR spectroscopy and molecular dynamics. A combination of difference spectra method and chemometric analysis of spectroscopic data was used to determine the number of osmolyte molecules interacting with the protein, and the preferential interaction coefficient in presented systems. Both osmolytes – L-proline and trimethylamine-N-oxide...
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Examining Classifiers Applied to Static Hand Gesture Recognition in Novel Sound Mixing System
PublikacjaThe main objective of the chapter is to present the methodology and results of examining various classifiers (Nearest Neighbor-like algorithm with non-nested generalization (NNge), Naive Bayes, C4.5 (J48), Random Tree, Random Forests, Artificial Neural Networks (Multilayer Perceptron), Support Vector Machine (SVM) used for static gesture recognition. A problem of effective gesture recognition is outlined in the context of the system...
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Music Mood Visualization Using Self-Organizing Maps
PublikacjaDue to an increasing amount of music being made available in digital form in the Internet, an automatic organization of music is sought. The paper presents an approach to graphical representation of mood of songs based on Self-Organizing Maps. Parameters describing mood of music are proposed and calculated and then analyzed employing correlation with mood dimensions based on the Multidimensional Scaling. A map is created in which...
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Benchmarking Deep Neural Network Training Using Multi- and Many-Core Processors
PublikacjaIn the paper we provide thorough benchmarking of deep neural network (DNN) training on modern multi- and many-core Intel processors in order to assess performance differences for various deep learning as well as parallel computing parameters. We present performance of DNN training for Alexnet, Googlenet, Googlenet_v2 as well as Resnet_50 for various engines used by the deep learning framework, for various batch sizes. Furthermore,...
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Deep-Learning-Based Precise Characterization of Microwave Transistors Using Fully-Automated Regression Surrogates
PublikacjaAccurate models of scattering and noise parameters of transistors are instrumental in facilitating design procedures of microwave devices such as low-noise amplifiers. Yet, data-driven modeling of transistors is a challenging endeavor due to complex relationships between transistor characteristics and its designable parameters, biasing conditions, and frequency. Artificial neural network (ANN)-based methods, including deep learning...
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Membrane separation processes for the extraction and purification of steviol glycosides: an overview
PublikacjaSteviol glycosides (SGs), as natural sweeteners from Stevia rebaudiana, are currently employed for replacing sugar and its derivatives in several food products and formulations. Such compounds play an essential role in human health. Their usage provides a positive effect on preventing diseases related to sugar consumption, including diabetes mellitus, cancer, and lipid metabolism disorders. The traditional extraction of SGs is...
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Vegetable derived-oil facilitating carbon black migration from waste tire rubbers and its reinforcement effect
PublikacjaThree dimensional chemically cross-linked polymer networks present a great challenge for recycling and reutilization of waste tire rubber. In this work, the covalently cross-linked networks of ground tire rubber (GTR) were degraded heterogeneously under 150 °C due to the synergistic effects of the soybean oil and controlled oxidation. The degradation mechanism was discussed using Horikx theory and Fourier transformation infrared...
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MACHINE LEARNING APPLICATIONS IN RECOGNIZING HUMAN EMOTIONS BASED ON THE EEG
PublikacjaThis study examined the machine learning-based approach allowing the recognition of human emotional states with the use of EEG signals. After a short introduction to the fundamentals of electroencephalography and neural oscillations, the two-dimensional valence-arousal Russell’s model of emotion was described. Next, we present the assumptions of the performed EEG experiment. Detail aspects of the data sanitization including preprocessing,...
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Anion–water interactions of weakly hydrated anions: molecular dynamics simulations of aqueous NaBF4 and NaPF6
PublikacjaIn aqueous ionic solutions, both the structure and the dynamics of water are altered dramatically with respect to the pure solvent. The emergence of novel experimental techniques makes these changes accessible to detailed investigations. At the same time, computational studies deliver unique possibilities for the interpretation of the experimental data at the molecular level. Here, using molecular dynamics simulations, we demonstrate...
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Electron-impact dissociation of molecular hydrogen: benchmark cross sections
PublikacjaWe present a joint experimental and theoretical investigation of a fundamental process in atomic and molecular physics: electron impact excitation of molecular hydrogen’s (H2) most dominant transition (X1Σg+ → b3Σu+). Excitation of this state is by far the main channel that causes the dissociation of H2 into H + H atoms at low energies. The Convergent Close-Coupling (CCC) calculations predicted significant, more than factor of...
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Fungal L-Methionine Biosynthesis Pathway Enzymes and Their Applications in Various Scientific and Commercial Fields
PublikacjaL-methionine (L-Met) is one of the nine proteinogenic amino acids essential for humans since, in human cells, there are no complete pathways for its biosynthesis from simple precursors. L-Met plays a crucial role in cellular function as it is required for proper protein synthesis, acting as an initiator. Additionally, this amino acid participates in various metabolic processes and serves as a precursor for the synthesis of S-adenosylmethionine...
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Positron-electron correlation-polarization potentials for the calculation of positron collisions with atoms and molecules
PublikacjaWe present correlation-polarization potentials for the calculation of scattering cross sections of positrons with atoms and molecules. The potentials are constructed from a short-range correlation term and a long-range polarization term. For the short-range correlation term we present four different potentials that are derived from multi-component density functionals. For the long-range polarization term we employ a multi-term...
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Stability and phase transition investigation of olanzapine polymorphs
PublikacjaWe use electrical embedded-fragment QM method with both DFT/ωB97XD/6-31G* and MP2/6-31G* to investigate the phase transformations of olanzapine. Gibbs free energy calculations predict that form I is always the most stable structure and form II is the least stable one, while form IV is more stable than form III below about 200 K but less stable above this temperature, implying a polymorphic phase transformation. This may account...
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Synthesis and polymerisation techniques of molecularly imprinted polymers
PublikacjaMolecularly Imprinted Polymers (MIPs) are materials that has been processed using the molecular imprinting technique which permit to obtain well-defined three-dimensional cavities, with affinity to a template molecule, in the polymer matrix. Technology involves three strategies, i.e., covalent, non-covalent and semi-covalent approach, but the most popular is non-covalent approach. The most important components for the synthesis...
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Molecular hydrogen solvated in water – A computational study
PublikacjaThe aqueous hydrogen molecule is studied with molecular dynamics simulations at ambient temperature and pressure conditions, using a newly developed flexible and polarizable H2 molecule model. The design and implementation of this model, compatible with an existing flexible and polarizable force field for water, is presented in detail. The structure of the hydration layer suggests that first-shell water molecules accommodate the...
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Deep learning in the fog
PublikacjaIn the era of a ubiquitous Internet of Things and fast artificial intelligence advance, especially thanks to deep learning networks and hardware acceleration, we face rapid growth of highly decentralized and intelligent solutions that offer functionality of data processing closer to the end user. Internet of Things usually produces a huge amount of data that to be effectively analyzed, especially with neural networks, demands high...
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Improvement of speech intelligibility in the presence of noise interference using the Lombard effect and an automatic noise interference profiling based on deep learning
PublikacjaThe Lombard effect is a phenomenon that results in speech intelligibility improvement when applied to noise. There are many distinctive features of Lombard speech that were recalled in this dissertation. This work proposes the creation of a system capable of improving speech quality and intelligibility in real-time measured by objective metrics and subjective tests. This system consists of three main components: speech type detection,...
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Wireless Link Selection Methods for Maritime Communication Access Networks—A Deep Learning Approach
PublikacjaIn recent years, we have been witnessing a growing interest in the subject of communication at sea. One of the promising solutions to enable widespread access to data transmission capabilities in coastal waters is the possibility of employing an on-shore wireless access infrastructure. However, such an infrastructure is a heterogeneous one, managed by many independent operators and utilizing a number of different communication...
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Position Estimation in Mixed Indoor-Outdoor Environment Using Signals of Opportunity and Deep Learning Approach
PublikacjaTo improve the user's localization estimation in indoor and outdoor environment a novel radiolocalization system using deep learning dedicated to work both in indoor and outdoor environment is proposed. It is based on the radio signatures using radio signals of opportunity from LTE an WiFi networks. The measurements of channel state estimators from LTE network and from WiFi network are taken by using the developed application....
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Membrane Sterols Modulate the Binding Mode of Amphotericin B without Affecting Its Affinity for a Lipid Bilayer
PublikacjaMembrane-active antibiotics are known to selectively target certain pathogens based on cell membrane properties, such as fluidity, lipid ordering, and phase behavior. These are in turn modulated by the composition of a lipid bilayer and in particular by the presence and type of membrane sterols. Amphotericin B (AmB), the golden standard of antifungal treatment, exhibits higher activity toward ergosterol-rich fungal membranes, which...
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Liquefaction of alder wood as the source of renewable and sustainable polyols for preparation of polyurethane resins
PublikacjaLiquefaction of wood-based biomass gives different polyol properties depending on the reagents used. In this article, alder wood sawdust was liquefied with glycerol and poly(ethylene glycol) solvents. Liquefaction reactions were carried out at temperatures of 120, 150 and 170 °C. The obtained bio-polyols were analyzed in order to establish the process efficiency, hydroxyl number, acid value, viscosity and structural characteristics...
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RNDM 2016 Workshop and 2nd Meeting of COST CA15127-RECODIS: Highlights from the Resilience Week in Halmstad, Sweden
PublikacjaLeading network resilience researchers took part in the Resilience Week on Sept. 12-15, 2016 at Halmstad University, SE by Prof. Magnus Jonsson from the Centre for Research on Embedded Systems (CERES), Halmstad University, SE, and Prof. Jacek Rak from Gdansk University of Technology, PL. It included two major events: - The 2nd Meeting of COST CA15127–RECODIS Action (Resilient Communication Services Protecting End-user Applications...
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Optical Sensor Based Gestures Inference Using Recurrent Neural Network in Mobile Conditions
PublikacjaIn this paper the implementation of recurrent neural network models for hand gesture recognition on edge devices was performed. The models were trained with 27 hand gestures recorded with the use of a linear optical sensor consisting of 8 photodiodes and 4 LEDs. Different models, trained off-line, were tested in terms of different network topologies (different number of neurons and layers) and different effective sampling frequency...
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Projektowanie i eksploatacja dróg szynowych z wykorzystaniem mobilnych pomiarów satelitarnych
PublikacjaNiniejsza monografia zawiera szczegółowy opis aktywnych sieci geodezyjnych GNSS oraz modelowania dokładności określania pozycji w pomiarach satelitarnych. Omówiono również opracowaną technikę mobilnych pomiarów satelitarnych toru kolejowego oraz aplikacje związane z jej zastosowaniem w projektowaniu i eksploatacji dróg szynowych. Autorzy zawarli w pracy wyniki swoich badań, wykonywanych na przestrzeni lat 2009–2015. Badania przeprowadzono...
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Mutual Coupling Reduction in Antenna Arrays Using Artificial Intelligence Approach and Inverse Neural Network Surrogates
PublikacjaThis paper presents a novel approach to reduce undesirable coupling in antenna arrays using custom-designed resonators and inverse surrogate modeling. To illustrate the concept, two stand-ard patch antenna cells with 0.07λ edge-to-edge distance are designed and fabricated to operate at 2.45 GHz. A stepped-impedance resonator is applied between the antennas to suppress their mutual coupling. For the first time, the optimum values...
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Comparative molecular modelling of biologically active sterols
PublikacjaMembrane sterols are targets for a clinically important antifungal agent – amphotericin B. The relatively specific antifungal action of the drug is based on a stronger interaction of amphotericin B with fungal ergosterol than with mammalian cholesterol. Conformational space occupied by six sterols has been defined using the molecular dynamics method to establish if the conformational features correspond to the preferential interaction...
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ortho-Fluorobenzanilides and ortho-fluorothiobenzanilides: Molecular conformations and crystal packing
PublikacjaSeries of 2-fluoro and 2,6-difluorobenzanilides and their thiobenzanilide analogs have been synthesized to investigate the influence of the fluorine atom on their crystal structures and self-assembly in the crystal lattice. The X-ray analysis of the single crystal revealed that the synthesized molecules adopt a geometry being deflected from planarity. The deflection was investigated by analysis of dihedral angles between mean planes...
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Structural and Dynamic Properties of Water within the Solvation Layer around Various Conformations of the Glycine-based Polypeptide
PublikacjaSeveral conformations of the solvated glycine-based polypeptides were investigated using molecular dynamics simulations. Some properties of water in the neighboring space around these molecules were investigated. It was found that water forms a well-defined layer—the first solvation shell—around the peptide molecule, and thickness of this layer is independent of the peptide structure and is equal to approximately 0.28 nm. Within...
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Solvation of ionic liquids based on N-methyl-N-alkyl morpholinium cations in dimethylsulfoxide – volumetric and compressibility studies
PublikacjaThe density and sound velocity of the solutions of ionic liquids based on N-alkyl-N-methyl-morpholinium cations, N-ethyl-N-methylmorpholinium bis(trifluoromethanesulfonyl)imide, N-butyl-N-methylmorpholinium bis(trifluoromethanesulfonyl)imide, N-methyl-N-octyl-morpholinium bis(trifluoromethanesulfonyl)imide and N-decyl-N-methylmorpholinium bis(trifluoromethanesulfonyl)imide in dimethylsulfoxide were measured at T = (298.15 to 318.15)...
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Interpretable Deep Learning Model for the Detection and Reconstruction of Dysarthric Speech
PublikacjaWe present a novel deep learning model for the detection and reconstruction of dysarthric speech. We train the model with a multi-task learning technique to jointly solve dysarthria detection and speech reconstruction tasks. The model key feature is a low-dimensional latent space that is meant to encode the properties of dysarthric speech. It is commonly believed that neural networks are black boxes that solve problems but do not...
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Comparison of Deep Neural Network Learning Algorithms for Mars Terrain Image Segmentation
PublikacjaThis paper is dedicated to the topic of terrain recognition on Mars using advanced techniques based on the convolutional neural networks (CNN). The work on the project was conducted based on the set of 18K images collected by the Curiosity, Opportunity and Spirit rovers. The data were later processed by the model operating in a Python environment, utilizing Keras and Tensorflow repositories. The model benefits from the pretrained...
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Residual MobileNets
PublikacjaAs modern convolutional neural networks become increasingly deeper, they also become slower and require high computational resources beyond the capabilities of many mobile and embedded platforms. To address this challenge, much of the recent research has focused on reducing the model size and computational complexity. In this paper, we propose a novel residual depth-separable convolution block, which is an improvement of the basic...
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Fragmentation of Hydrographic Big Data Into Subsets During Reduction Process
PublikacjaThe article presented problems of fragmentation of hydrographic big data into smaller subsets during reduction process. Data reduction is a processing of reduce the value of the data set, in order to make them easier and more effective for the goals of the analysis. The main aim of authors is to create new reduction method. The article presented the first stage of this method – fragmentation of bathymetric data into subsets. It...
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Effects of UV light irradiation on fluctuation enhanced gas sensing by carbon nanotube networks
PublikacjaThe exceptionally large active surface-to-volume ratio of carbon nanotubes makes it an appealing candidate for gas sensing applications. Here, we studied the DC and low-frequency noise characteristics of a randomly oriented network of carbon nanotubes under NO2 gas atmosphere at two different wavelengths of the UV light-emitting diodes. The UV irradiation allowed to sense lower concentrations of NO2 (at least 1 ppm) compared to...
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Fault detection in measuring systems of power plants
PublikacjaThis paper describes possibility of forming diagnostic relations based on application of the artifical neural networks (ANNs), intended for the identifying of degradation of measuring instruments used in developed power systems. As an example a steam turbine high-power plant was used. And, simulative calculations were applied to forming diagnostic neural relations. Both degradation of the measuring instruments and simultaneously...
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SiMiSnoRNA: Collection of siRNA, miRNA, and snoRNA database for RNA Interference
PublikacjaObjective:The discovery of sequence specific gene silencing which occurs due to the presence of double-stranded RNAs has considerable impact on biology, revealing an unknown level of regulation of gene expression. This process is known as RNA interference (RNAi) or RNA silencing in which RNA molecules inhibit gene expression, typically by causing the destruction of specific mRNA molecule. Two types of small RNA molecules - small...
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Interactions of protons with furan molecules studied by collision-induced emission spectroscopy at the incident energy range of 50–1000 eV
PublikacjaInvestigations of the ion-molecule reactions provide insight into many fields ranging from the stellar wind interaction with interstellar media, up to medicine and industrial applications. Besides the applications, the understanding of these processes is itself a problem of fundamental importance. Thus, interactions of protons with the gas-phase furan molecules have been investigated for the first time in the energy range of 50–1000...
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Hydration of amino acids: FTIR spectra and molecular dynamics studies
PublikacjaThe hydration of selected amino acids, alanine, glycine, proline, valine, isoleucine and phenylalanine, has been studied in aqueous solutions by means of FTIR spectra of HDO isotopically diluted in H2O. The difference spectra procedure and the chemometric method have been applied to remove the contribution of bulk water and thus to separate the spectra of solute-affected HDO. To support interpretation of obtained spectral results,...
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Unique agreement of experimental and computational infrared spectroscopy: a case study of lithium bromide solvation in an important electrochemical solvent
PublikacjaInfrared (IR) spectroscopy is a widely used and invaluable tool in the studies of solvation phenomena in electrolyte solutions. Using state-of-the-art chemometric analysis of a spectral series measured in a concentration-dependent manner, the spectrum of the solute-affected solvent can be extracted, providing a detailed view of the structural and energetic states of the solvent molecules influenced by the solute. Concurrently,...
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Natural Deep Eutectic Solvents as Agents for Improving Solubility, Stability and Delivery of Curcumin
PublikacjaPurpose Study on curcumin dissolved in natural deep eutectic solvents (NADES) was aimed at exploiting their beneficial properties as drug carriers. Methods The concentration of dissolved curcumin in NADES was measured. Simulated gastrointestinal fluids were used to determine the concentration of curcumin and quantum chemistry computations were performed for clarifying the origin of curcumin solubility enhancement in NADES. Results NADES...
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Urban scene semantic segmentation using the U-Net model
PublikacjaVision-based semantic segmentation of complex urban street scenes is a very important function during autonomous driving (AD), which will become an important technology in industrialized countries in the near future. Today, advanced driver assistance systems (ADAS) improve traffic safety thanks to the application of solutions that enable detecting objects, recognising road signs, segmenting the road, etc. The basis for these functionalities...
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LDRAW based positional renders of LEGO bricks
Dane Badawcze243 different LEGO bricks renders of size 250x250 in 5 colors in 120 viewing angles stored as JPEG images. The renders are used to train neural networks for bricks recognition. All images were generated using L3P (http://www.hassings.dk/l3/l3p.html) and POV-Ray (http://www.povray.org/) tools and were based on the 3D models from LDraw (https://www.ldraw.org/)...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublikacjaDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Experimental and Machine-Learning-Assisted Design of Pharmaceutically Acceptable Deep Eutectic Solvents for the Solubility Improvement of Non-Selective COX Inhibitors Ibuprofen and Ketoprofen
PublikacjaDeep eutectic solvents (DESs) are commonly used in pharmaceutical applications as excellent solubilizers of active substances. This study investigated the tuning of ibuprofen and ketoprofen solubility utilizing DESs containing choline chloride or betaine as hydrogen bond acceptors and various polyols (ethylene glycol, diethylene glycol, triethylene glycol, glycerol, 1,2-propanediol, 1,3-butanediol) as hydrogen bond donors. Experimental...
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Categorization of emotions in dog behavior based on the deep neural network
PublikacjaThe aim of this article is to present a neural system based on stock architecture for recognizing emotional behavior in dogs. Our considerations are inspired by the original work of Franzoni et al. on recognizing dog emotions. An appropriate set of photographic data has been compiled taking into account five classes of emotional behavior in dogs of one breed, including joy, anger, licking, yawning, and sleeping. Focusing on a particular...
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Bio-Based Polyurethane Networks Derived from Liquefied Sawdust
PublikacjaThe utilization of forestry waste resources in the production of polyurethane resins is a promising green alternative to the use of unsustainable resources. Liquefaction of wood-based biomass gives polyols with properties depending on the reagents used. In this article, the liquefaction of forestry wastes, including sawdust, in solvents such as glycerol and polyethylene glycol was investigated. The liquefaction process was carried...