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Search results for: MOLECULAR MODELING,MOLECULES,NEURAL NETWORKS,SOLVENTS,VISCOSITY
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Water Behavior Near the Lipid Bilayer
PublicationIn this chapter, we focus on the dynamics of water molecules situated in the vicinity of a phospholipid bilayer. Using a molecular dynamics simulation method, we studied interactions between water and the bilayer and tracked trajectories of the water molecules. Based on the hypothesis that molecules trapped inside the bilayer make different motions than the ones which are either attached to the surface or move freely in the water...
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Why is the cubic structure preferred in newly formed ice?
PublicationMolecular dynamics was employed to explain the preference for the cubic structure in newly formed crystals of ice. The results showed that in supercooled liquid water the molecules connected by hydrogen bonds are more likely to adopt relative orientations similar to the ones characteristic for cubic ice. The observed preference for certain relative orientations of molecules in the hydrogen-bonded pairs results in the higher probability...
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Electron impact fragmentation of pyrrole molecules studied by fluorescence emission spectroscopy
PublicationThe fluorescence emission spectroscopy using electron impact excitation technique was employed to study fragmentation processes of the gas phase pyrrole molecules. The following excited fragmentation species were observed by detection of their fluorescence decay: the atomic hydrogen H(n), n = 4-7 and the diatomic CH(A2Δ), CN(B2Σ+), NH(A3Π) and C2(d3Πg) fragments. These atomic and molecular products differ from those previously...
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An Improved Convolutional Neural Network for Steganalysis in the Scenario of Reuse of the Stego-Key
PublicationThe topic of this paper is the use of deep learning techniques, more specifically convolutional neural networks, for steganalysis of digital images. The steganalysis scenario of the repeated use of the stego-key is considered. Firstly, a study of the influence of the depth and width of the convolution layers on the effectiveness of classification was conducted. Next, a study on the influence of depth and width of fully connected...
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Computational intelligence methods in production management
PublicationThis chapter presents a survey of selected computational intelligence methods used in production management. This group of methods includes, among others, approaches based on the artificial neural networks, the evolutionary algorithms, the fuzzy logic systems and the particle swarm optimization mechanisms. From the abovementioned methods particularly noteworthy are the evolutionary and the particle swarm algorithms, which are successfully...
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The POCOBIO Database for Computed Scattering Cross-Sections for Positron Collisions with Biomolecular Systems
PublicationThe design of a database for positron interactions with biomolecular systems is outlined. The database contains only scattering cross sections, which are derived from theory. The data model is defined in a very flexible way, which facilitates the usage of weakly bound clusters of molecules and molecular systems with many tautomeric forms.
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Optymalizacja treningu i wnioskowania sieci neuronowych
PublicationSieci neuronowe są jedną z najpopularniejszych i najszybciej rozwijających się dziedzin sztucznej inteligencji. Ich praktyczne wykorzystanie umożliwiło szersze użycie komputerów w wielu obszarach komunikacji, przemysłu i transportu. Dowody tego są widoczne w elektronice użytkowej, medycynie, a nawet w zastosowaniach militarnych. Wykorzystanie sztucznej inteligencji w wielu przypadkach wymaga jednak znacznej mocy obliczeniowej,...
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Deep eutectic solvents with solid supports used in microextraction processes applied for endocrine-disrupting chemicals
PublicationThe determination of endocrine-disrupting chemicals (EDCs) has become one of the biggest challenges in Analytical Chemistry. Due to the low concentration of these compounds in different kinds of samples, it becomes necessary to employ efficient sample preparation methods and sensitive measurement techniques to achieve low limits of detection. This issue becomes even more struggling when the principles of the Green Analytical Chemistry...
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Assessment and design of greener deep eutectic solvents – A multicriteria decision analysis
PublicationDeep eutectic solvents (DES) are often considered as green solvents because of their properties, such as negligible vapor pressure, biodegradability, low toxicity or natural origin of their components. Due to the fact that DES are cheaper than ionic liquids, they have gained many applications in a short period of time. However, claims about their greenness sometimes seem to be exaggerated. Especially, bearing in mind lots of data...
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Chitin and derivative chitosan-based structures — Preparation strategies aided by deep eutectic solvents: A review
PublicationThe high molecular weight of chitin, as a biopolymer, challenges its extraction due to its insolubility in the solvents. Also, chitosan, as the N-deacetylated form of chitin, can be employed as a primary material for different industries. The low mechanical stability and poor plasticity of chitosan films, as a result of incompatible interaction between chitosan and the used solvent, have limited its industrialization. Deep eutectic...
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Precipitation and Transformation of Vaterite Calcium Carbonate in the Presence of Some Organic Solvents
PublicationIn this paper, the production of CaCO3 particles via the carbonation route in the reaction of CaCl2 and CO2, using NH3 as a promoter of CO2 absorption, was studied. The solvents used as the reaction media for CaCO3 precipitation were aqueous solutions of methanol, isopropanol and dimethyl sulfoxide (DMSO), in a concentration range of 0–20% (v/v). It was found that the presence of an organic additive influenced the precipitation...
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Training of Deep Learning Models Using Synthetic Datasets
PublicationIn order to solve increasingly complex problems, the complexity of Deep Neural Networks also needs to be constantly increased, and therefore training such networks requires more and more data. Unfortunately, obtaining such massive real world training data to optimize neural networks parameters is a challenging and time-consuming task. To solve this problem, we propose an easy-touse and general approach to training deep learning...
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Optical photoluminescent, and electroluminescent properties of organic solids
PublicationThis chapter discusses optical, photoluminescence and electroluminescence properties of organic materials. First, the spectral features of individual molecules and molecular solid states are analysed. Next, the excitonic processes in organic materials are discussed. The chapter reviews experimental methods leading to the determination of basic excitonic parameters. Finally, the electroluminescence phenomena in organic materials...
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Low-energy positron scattering from DNA nucleobases: the effects from permanent dipoles
PublicationAb initio quantum calculations for low-energy positron scattering from gas-phase isolated molecular nucleobases which are part of the DNA structure are presented and discussed over the range of 1 eV to 25 eV. The calculations report the integral cross sections (ICSs) and the momentum-transfer cross sections (MTCSs) for Adenine, Guanine, Thymine and Cytosine. The calculations show very clearly the important role of the dominant...
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Methods of Artificial Intelligence for Prediction and Prevention Crisis Situations in Banking Systems
PublicationIn this paper, a support vector machine has been studied due to prediction of bank crisis. To prevent outcomes of crisis situations, artificial neural networks have been characterized as applied to stock market investments, as well as to test the credibility of the bank's customers. Finally, some numerical experiments have been presented.
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Accurate Modeling of Frequency Selective Surfaces Using Fully-Connected Regression Model with Automated Architecture Determination and Parameter Selection Based on Bayesian Optimization
PublicationSurrogate modeling has become an important tool in the design of high-frequency structures. Although full-wave electromagnetic (EM) simulation tools provide an accurate account for the circuit characteristics and performance, they entail considerable computational expenditures. Replacing EM analysis by fast surrogates provides a way to accelerate the design procedures. Unfortunately, modeling of microwave passives is a challenging...
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User Orientation Detection in Relation to Antenna Geometry in Ultra-Wideband Wireless Body Area Networks Using Deep Learning
PublicationIn this paper, the issue of detecting a user’s position in relation to the antenna geometry in ultra-wideband (UWB) off-body wireless body area network (WBAN) communication using deep learning methods is presented. To measure the impulse response of the channel, a measurement stand consisting of EVB1000 devices and DW1000 radio modules was developed and indoor static measurement scenarios were performed. It was proven that for...
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Deep eutectic solvents – Ideal solution for clean air or hidden danger?
PublicationThe industrial sector is one of the fastest-growing sources of greenhouse gases, due to its excessive energy consumption to meet the rapidly growing demand for energy-intensive products. The use of deep eutectic solvents (DESs) has been studied extensively in order to cope with these harmful gases, but their usage can be an issue in respect to ecological reasons. Do deep eutectic solvents harm the atmosphere? Yes, these solvents...
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Bio‐polyols synthesized by liquefaction of cellulose: Influence of liquefaction solvent molecular weight
PublicationCurrently, the plastics industry including polyurethanes is based on the use of petrochemicals. For this reason, scientists are looking for new types of renewable resources for the substitution of petrochemical substances. This work aims to evaluate the effect of polyethylene glycols (PEG) with different molecular mass impact on properties of bio-based polyols synthesized via biomass liquefaction of cellulose. To date, research...
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Deep eutectic solvents – A new platform in membrane fabrication and membrane-assisted technologies
PublicationDeep eutectic solvents (DESs) are a new class of solvents that can offset some of the primary drawbacks of typical solvents and ionic liquids (ILs). Since DESs fall into the guidelines of “Twelve Principles of Green Chemistry”, their implementation in several types of applications has exponentially increased over the last years. The usage of DESs has been directed to the designing, manufacture and purification of new materials...
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Path Loss Modelling for Location Service Applications
PublicationThe aim of this paper is the path loss modeling for the radiolocation services in radiocommunication networks, particularly in cellular networks. The main results of the measurements obtained in the physical layer of the UMTS are introduced. A new method for the utilization of the multipath propagation phenomenon to improve the estimation of the distance between the mobile station (MS) and the base station (BS) is outlined. This...
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Experience-Based Cognition for Driving Behavioral Fingerprint Extraction
PublicationABSTRACT With the rapid progress of information technologies, cars have been made increasingly intelligent. This allows cars to act as cognitive agents, i.e., to acquire knowledge and understanding of the driving habits and behavioral characteristics of drivers (i.e., driving behavioral fingerprint) through experience. Such knowledge can be then reused to facilitate the interaction between a car and its driver, and to develop better and...
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Road traffic can be predicted by machine learning equally effectively as by complex microscopic model
PublicationSince high-quality real data acquired from selected road sections are not always available, a traffic control solution can use data from software traffic simulators working offline. The results show that in contrast to microscopic traffic simulation, the algorithms employing neural networks can work in real-time, so they can be used, among others, to determine the speed displayed on variable message road signs. This paper describes...
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Performance of the AMOEBA Water Model in the Vicinity of QM Solutes: A Diagnosis Using Energy Decomposition Analysis
PublicationThe importance of incorporating solvent polarization effects into the modeling of solvation processes has been well-recognized, and therefore a new generation of hybrid quantum mechanics/molecular mechanics (QM/MM) approaches that accounts for this effect is desirable. We present a fully self-consistent, mutually polarizable QM/MM scheme using the AMOEBA force field, in which the total energy of the system is variationally minimized...
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Latest Insights on Novel Deep Eutectic Solvents (DES) for Sustainable Extraction of Phenolic Compounds from Natural Sources
PublicationPhenolic compounds have long been of great importance in the pharmaceutical, food, and cosmetic industries. Unfortunately, conventional extraction procedures have a high cost and are time consuming, and the solvents used can represent a safety risk for operators, consumers, and the environment. Deep eutectic solvents (DESs) are green alternatives for extraction processes, given their low or non-toxicity, biodegradability, and reusability....
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Optoelectronic system for investigation of cvd diamond/DLC layers growth
PublicationDevelopment of the optoelectronic system for non-invasive monitoring of diamond/DLC (Diamond-Like-Carbon) thin films growth during μPA ECR CVD (Microwave Plasma Assisted Electron Cyclotron Resonance Chemical Vapour Deposition) process is described. The system uses multi-point Optical Emission Spectroscopy (OES) and long-working-distance Raman spectroscopy. Dissociation of H2 molecules, excitation and ionization of hydrogen atoms...
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A Novel IoT-Perceptive Human Activity Recognition (HAR) Approach Using Multi-Head Convolutional Attention
PublicationTogether with fast advancement of the Internet of Things (IoT), smart healthcare applications and systems are equipped with increasingly more wearable sensors and mobile devices. These sensors are used not only to collect data, but also, and more importantly, to assist in daily activity tracking and analyzing of their users. Various human activity recognition (HAR) approaches are used to enhance such tracking. Most of the existing...
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Machine Learning Algorithm-Based Tool and Digital Framework for Substituting Daylight Simulations In Early- Stage Architectural Design Evaluation
PublicationThe aim of this paper is to examine the new method of obtaining the simulation-based results using backpropagation of errors artificial neural networks. The primary motivation to conduct the research was to determine an alternative, more efficient and less timeconsuming method which would serve to achieve the results of daylight simulations. Three daylight metrics: Daylight Factor, Daylight Autonomy and Daylight Glare Probability have...
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Widespread theta synchrony and high-frequency desynchronization underlies enhanced cognition
PublicationThe idea that synchronous neural activity underlies cognition has driven an extensive body of research in human and animal neuroscience. Yet, insufficient data on intracranial electrical connectivity has precluded a direct test of this hypothesis in a whole-brain setting. Through the lens of memory encoding and retrieval processes, we construct whole-brain connectivity maps of fast gamma (30-100 Hz) and slow theta (3-8 Hz) spectral...
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Creating a radiological database for automatic liver segmentation using artificial intelligence.
PublicationImaging in medicine is an irreplaceable stage in the diagnosis and treatment of cancer. The subsequent therapeutic effect depends on the quality of the imaging tests performed. In recent years we have been observing the evolution of 2D to 3D imaging for many medical fields, including oncological surgery. The aim of the study is to present a method of selection of radiological imaging tests for learning neural networks.
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Resource constrained neural network training
PublicationModern applications of neural-network-based AI solutions tend to move from datacenter backends to low-power edge devices. Environmental, computational, and power constraints are inevitable consequences of such a shift. Limiting the bit count of neural network parameters proved to be a valid technique for speeding up and increasing efficiency of the inference process. Hence, it is understandable that a similar approach is gaining...
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High frequency oscillations in human memory and cognition: a neurophysiological substrate of engrams?
PublicationDespite advances in understanding the cellular and molecular processes underlying memory and cognition, and recent successful modulation of cognitive performance in brain disorders, the neurophysiological mechanisms remain underexplored. High frequency oscillations beyond the classic electroencephalogram spectrum have emerged as a potential neural correlate of fundamental cognitive processes. High frequency oscillations are detected...
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New Two-center Ellipsoidal Basis Function Neural Network for Fault Diagnosis of Analog Electronic Circuits
PublicationIn the paper a new fault diagnosis-oriented neural network and a diagnostic method for localization of parametric faults in Analog Electronic Circuits (AECs) with tolerances is presented. The method belongs to the class of dictionary Simulation Before Test (SBT) methods. It utilizes dictionary fault signatures as a family of identification curves dispersed around nominal positions by component tolerances of the Circuit Under Test...
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WYKORZYSTANIE SIECI NEURONOWYCH DO SYNTEZY MOWY WYRAŻAJĄCEJ EMOCJE
PublicationW niniejszym artykule przedstawiono analizę rozwiązań do rozpoznawania emocji opartych na mowie i możliwości ich wykorzystania w syntezie mowy z emocjami, wykorzystując do tego celu sieci neuronowe. Przedstawiono aktualne rozwiązania dotyczące rozpoznawania emocji w mowie i metod syntezy mowy za pomocą sieci neuronowych. Obecnie obserwuje się znaczny wzrost zainteresowania i wykorzystania uczenia głębokiego w aplikacjach związanych...
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Badanie dynamiki platform pływających morskich turbin wiatrowych z zastosowaniem metod numerycznej mechaniki płynów
PublicationPraca dotyczy badania ruchu platform pływających pod morskie turbiny wiatrowe. Przedstawiono w niej główne metody obliczeń i przedyskutowano ich zastosowanie. Na przykładzie koncepcji konstrukcji 3-kolumnowej platformy typu Spar przedstawiono metodykę wykonywania obliczeń z zastosowaniem programu AQWA opartego na metodzie dyfrakcyjnej, rozszerzonego o współczynniki wynikające z lepkości wyznaczone za pomocą obliczeń RANSE-CFD....
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Deep eutectic solvents for the food industry: extraction, processing, analysis, and packaging applications – a review
PublicationFood factories seek the application of natural products, green feedstock and eco-friendly processes, which minimally affect the properties of the food item and products. Today, water and conventional polar solvents are used in many areas of food science and technology. As modern chemistry evolves, new green items for building eco-friendly processes are being developed. This is the case of deep eutectic solvents (DESs), named the...
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Instability of 2,2-di(pyridin-2-yl)acetic acid. Tautomerization versus decarboxylation
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Molecular dynamics simulations of the growth of poly(chloro-para-xylylene) films
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A unified coarse-grained model of biological macromolecules based on mean-field multipole–multipole interactions
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Study of the Interactions between Neurophysin II and Dipeptide Ligand by Means of Molecular Dynamics
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Ab initio study of phenyl benzoate: structure, conformational analysis, dipole moment, IR and Raman vibrational spectra
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Molecular dynamics study of 4-OH-phenylacetyl- D -Y(Me)FQNRPR-NH 2 selectivity to V1a receptor
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A hypothesis for GPCR activation
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Attaching an alkali metal atom to an alkaline earth metal oxide (BeO, MgO, or CaO) yields a triatomic metal oxide with reduced ionization potential and redirected polarity
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Functionalization of the transition metal oxides FeO, CoO, and NiO with alkali metal atoms decreases their ionization potentials by 3–5 eV
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Computational studies of intermolecular interactions in aqueous solutions of poly(vinylmethylether)
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On the origin of surface imposed anisotropic growth of salicylic and acetylsalicylic acids crystals during droplet evaporation
PublicationIn this paper droplet evaporative crystallization of salicylic acid (SA) and acetylsalicylic acid (ASA) crystals on different surfaces, such as glass, polyvinyl alcohol (PVA), and paraffin was studied. The obtained crystals were analyzed using powder X-ray diffraction (PXRD) technique. In order to better understand the effect of the surface on evaporative crystallization, crystals deposited on glass were scraped off. Moreover,...
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Exploring the cocrystallization potential of urea and benzamide
PublicationThe cocrystallization landscape of benzamide and urea interacting with aliphatic and aromatic carboxylic acids was studied both experimentally and theoretically. Ten new cocrystals of benzamide were synthesized using an oriented samples approach via a fast dropped evaporation technique. Information about types of known bi-component cocrystals augmented with knowledge of simple binary eutectic mixtures was used for the analysis...
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Polymerization of chloro-p-xylylenes, quantum-chemical study
PublicationThe p-xylylene monomers of parylene N, C and D have similar high polymerization reactivity. For effective copolymerization processes this fact is basically a draw- back and for instance the copolymerization with styrene doesn't go at all (Corley et al. J Pol Sc 13(68):137156, 1954). Substitution of terminal hydrogen atoms by chlorine atoms reduces reactivity dramatically. 7,7,8,8-tetrachloro-p- xylylene and 2,5,7,7,8,8-hexachloro-p-xylylene...
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A first-principles study of electronic and magnetic properties of 4d transition metals doped in Wurtzite GaN for spintronics applications
PublicationWe studied the electronic and magnetic properties of wurtzite GaN (w-GaN) doped with different concentrations of the 4d transition metal ions Nb, Mo, and Ru. We incorporated spin-polarized plane-wave density functional theory within an ultrasoft pseudopotential formalism. The 4d transition metals were doped at different geometrical sites to determine the geometry with the lowest total energy and the one that induced the largest...