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Search results for: MOLECULAR MODELING,MOLECULES,NEURAL NETWORKS,SOLVENTS,VISCOSITY
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Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis
PublicationRenal cell carcinoma is one of the most common cancers in Europe, with a total incidence rate of 18.4 cases per 100 000 population. There is currently significant overdiagnosis (11% to 30.9%) at times of planned surgery based on radiological studies. The purpose of this study was to create an artificial neural network (ANN) solution based on computed tomography (CT) images as an additional tool to improve the differentiation of...
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Processing and Maturation of Cathepsin C Zymogen: A Biochemical and Molecular Modeling Analysis
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Molecular modeling of amphotericin B - ergosterol primary complex in water II
PublicationPrezentowane badania dotyczą oddziaływania antybiotyku polienowego anfoterycyny B (AmB) i ergosterolu (ERG) (typowego sterolu błonowego komórek grzybowych) na poziomie molekularnym. W odróżnieniu od badanego poprzednio kompleksu binarnego analizowany obecnie kompleks AnB/ERG/AmB charakteryzuje się zdecydowanie wiekszą stabilnością i wzglednie sztywną, sandwiczową geometrią. Za trwałość i geometrie kompleksu odpowiedzialne są oddziaływania...
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Determination of Odour Interactions in Gaseous Mixtures Using Electronic Nose Methods with Artificial Neural Networks
PublicationThis paper presents application of an electronic nose prototype comprised of eight sensors, five TGS-type sensors, two electrochemical sensors and one PID-type sensor, to identify odour interaction phenomenon in two-, three-, four- and five-component odorous mixtures. Typical chemical compounds, such as toluene, acetone, triethylamine, α-pinene and n-butanol, present near municipal landfills and sewage treatment plants were subjected...
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When Neural Networks Meet Decisional DNA: A Promising New Perspective for Knowledge Representation and Sharing
PublicationABSTRACT In this article, we introduce a novel concept combining neural network technology and Decisional DNA for knowledge representation and sharing. Instead of using traditional machine learning and knowledge discovery methods, this approach explores the way of knowledge extraction through deep learning processes based on a domain’s past decisional events captured by Decisional DNA. We compare our approach with kNN (k-nearest...
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Identification and molecular modeling of a novel lipase from an Antarctic soil metagenomic library.
PublicationIn this work, we present the construction of a metagenomic library in Escherichia coli using pUC19 vector and environmental DNA directly isolated from Antarctic topsoil and screened for lipolytic enzymes. The screening on agar supplemented with olive oil and rhodamine B revealed one clone with lipolytic activity (Lip1) out of 11,000 E. coli clones. This clone harbored a plasmid, pLip1, which has an insert of 4722 bp that has been...
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Interaction of amphotericin B and its selected derivatives with membranes: molecular modeling studies
PublicationJest to praca przeglądowa obejmująca krytyczną analizę danych dotyczących oddziaływania amfoterycyny B (AmB) i jej wybranych, mniej toksycznych pochodnych, z błonami lipidowymi. Amfoterycyna B jest antybiotykiem przeciwgrzybowym ale ze względu na jej toksyczność trwają prace nad modyfikacjami chemicznymi tego związku. Celem molekularnym dla tego antybiotyku jest błona lipidowa i dlatego różnicowe powinowactwo AmB i jej pochodnych...
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Modeling and Simulation for Exploring Power/Time Trade-off of Parallel Deep Neural Network Training
PublicationIn the paper we tackle bi-objective execution time and power consumption optimization problem concerning execution of parallel applications. We propose using a discrete-event simulation environment for exploring this power/time trade-off in the form of a Pareto front. The solution is verified by a case study based on a real deep neural network training application for automatic speech recognition. A simulation lasting over 2 hours...
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Comparison of selected clustering algorithms of raw data obtained by interferometric methods using artificial neural networks
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Highlights from RNDM 2018 – 10th Anniversary Workshop on Resilient Networks Design and Modeling
PublicationArtykuł prezentujący relację z workshopu RNDM 2018
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Pharmacological Profile and Molecular Modeling of Cyclic Opioid Analogues Incorporating Various Phenylalanine Derivatives
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Modelling relation between oxidation resistance and tribological properties of non-toxic lubricants with the use of artificial neural networks
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Long Short-Term Memory (LSTM) neural networks in predicting fair price level in the road construction industry
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Application of neural networks for identification of forcedness having effect on magnitude of turbine rotor vibration using rotor trajectory.
PublicationW pracy dokonano analizy zastosowania sieci neuronowych do wyznaczenia wartości wymuszeń wpływających na wielkość drgań wirnika używając trajektorii jako parametr określający drgania. Badania przeprowadzono na powietrznej, jednostopniowej turbinie modelowej. Przemieszczenia poziome i pionowe wirnika turbiny mierzono przy pomocy systemu pomiarowego i rejestrowano na oscyloskopie cyfrowym. Przeprowadzono pomiary trajektorii ruchu...
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Age Prediction from Low Resolution, Dual-Energy X-ray Images Using Convolutional Neural Networks
PublicationAge prediction from X-rays is an interesting research topic important for clinical applications such as biological maturity assessment. It is also useful in many other practical applications, including sports or forensic investigations for age verification purposes. Research on these issues is usually carried out using high-resolution X-ray scans of parts of the body, such as images of the hands or images of the chest. In this...
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Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublicationDue to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...
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Sensing Direction of Human Motion Using Single-Input-Single-Output (SISO) Channel Model and Neural Networks
PublicationObject detection Through-the-Walls enables localization and identification of hidden objects behind the walls. While numerous studies have exploited Channel State Information of Multiple Input Multiple Output (MIMO) WiFi and radar devices in association with Artificial Intelligence based algorithms (AI) to detect and localize objects behind walls, this study proposes a novel non-invasive Through-the-Walls human motion direction...
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Molecular dynamics simulation of human neurohypophyseal hormone receptors complexed with oxytocin—modeling of an activated state
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Molecular modeling and evaluation of novel dibenzopyrrole derivatives as telomerase inhibitors and potential drug for cancer therapy
PublicationDuring previous years, many studies on synthesis, as well as on anti-tumor, anti-inflammatory and anti-bacterial activities of the pyrazole derivatives have been described. Certain pyrazole derivatives exhibit important pharmacological activities and have proved to be useful template in drug research. Considering importance of pyrazole template, in current work the series of novel inhibitors were designed by replacing central...
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Free volume in physical absorption of carbon dioxide in ionic liquids: Molecular dynamics supported modeling
PublicationUnderstanding the mechanisms underlying the carbon dioxide (CO2) absorption in ionic liquids (ILs) is the key to their efficient utilization in industrial flue gas treatment. One of the parameters considered substantially important in the process is the Free Volume. In this study, the Fractional Free Volume (FFV) of 73 ILs was calculated using Molecular Dynamics (MD). A quantitative Structure-Property Relationship (QSPR) study...
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Artificial neural networks as a tool for selecting the parameters of prototypical under sleeper pads produced from recycled rubber granulate
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Two- and three-dimensional elastic networks with rigid junctions: modeling within the theory of micropolar shells and solids
PublicationFor two- and three-dimensional elastic structures made of families of flexible elastic fibers undergoing finite deformations, we propose homogenized models within the micropolar elasticity. Here we restrict ourselves to networks with rigid connections between fibers. In other words, we assume that the fibers keep their orthogonality during deformation. Starting from a fiber as the basic structured element modeled by the Cosserat...
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The comparison of semiempirical and ab initio molecular modeling methods in activity and property evaluation of selected antimicrobial sulfonamides
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Application of neural networks for identification of forcedness having effect on magnitude of turbine rotor vibration using pressure distribution in blade tip clearance.
PublicationW pracy sprawdzono, czy zastosowanie sieci neuronowych umożliwia identyfikację wymuszeń powstających w wyniku funkcjonowania maszyny jak i zależnych od jej stanu mechanicznego przy zastosowaniu rozkładu ciśnienia w uszczelnieniu nadbandażowym. Przeprowadzono pomiary rozkładu ciśnienia dla różnych warunków pracy, uwzględniając zmianę mimośrodu oraz zmianę skośnego ustawienia osi wirnika względem osi korpusu. Dokonano analiz przy...
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Flexible Knowledge–Vision–Integration Platform for Personal Protective Equipment Detection and Classification Using Hierarchical Convolutional Neural Networks and Active Leaning
PublicationThis work is part of an effort to develop of a Knowledge-Vision Integration Platform for Hazard Control (KVIP-HC) in industrial workplaces, adaptable to a wide range of industrial environments. The paper focuses on hazards resulted from the non-use of personal protective equipment (PPE). The objective is to test the capability of the platform to adapt to different industrial environments by simulating the process of randomly selecting...
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Theoretical designing of selenium heterocyclic non-fullerene acceptors with enhanced power conversion efficiency for organic solar cells: a DFT/TD-DFT-based prediction and understanding
PublicationIn this study, we have designed and explored a new series of non-fullerene acceptors for possible applications in organic solar cells. We have designed four molecules named as APH1 to APH4 after end-capped modification of recently synthesized Y6-Se-4Cl molecule. Density functional theory and time dependent-density functional theory have been employed for computing geometric and photovoltaic parameters of the designed molecules....
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Influence of bulky 3,3′-diphenylalanine enantiomers replacing position 2 of AVP analogues on their conformations: NMR and molecular modeling studies
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Molecular modeling of Gram-positive bacteria peptidoglycan layer, selected glycopeptide antibiotics and vancomycin derivatives modified with sugar moieties
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Intramolecular transformation of an antifungal antibiotic nystatin A1 into its isomer, iso-nystatin A1 - structural and molecular modeling studies
PublicationNystatin A1, a polyene macrolide antifungal antibiotic, in a slightly basic or acidic solution undergoes an intramolecular transformation, yielding a structural isomer, the translactonization product, iso-nystatin A1 with lactone ring diminished by two carbon atoms. Structural evidence is provided by advanced NMR and Mass Spectrometry (MS) studies. Molecular dynamics simulations and quantum mechanics calculations gave the insight...
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Activation maps of convolutional neural networks as a tool for brain degeneration tracking in early diagnosis of dementia in Parkinson's disease based on magnetic resonance imaging
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Screening of potential inhibitors for COVID-19 main protease from phytoconstituents of Tectona grandis Linn: application of molecular modeling studies
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Pharmacological Classification and Activity Evaluation of Furan and Thiophene Amide Derivatives Applying Semi-Empirical ab initio Molecular Modeling Methods
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Imidazolidine-4-one derivatives in the search for novel chemosensitizers of Staphylococcus aureus MRSA: Synthesis, biological evaluation and molecular modeling studies
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Particle swarm optimization–artificial neural network modeling and optimization of leachable zinc from flour samples by miniaturized homogenous liquid–liquid microextraction
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Towards temperature-dependent coarse-grained potentials of side-chain interactions for protein folding simulations. I: Molecular dynamics study of a pair of methane molecules in water at various temperatures
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Molecular modeling study of tectoquinone and acteoside from Tectona grandis linn: a new SARS-CoV-2 main protease inhibitor against COVID-19
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Exploiting the S4–S5 Specificity of Human Neutrophil Proteinase 3 to Improve the Potency of Peptidyl Di(chlorophenyl)-phosphonate Ester Inhibitors: A Kinetic and Molecular Modeling Analysis
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The Ellenbogen's "Matter as Software" Concept for Quantum Computer Implementation: II Bonding Between the C60 and X@C60 Molecules as Available Molecular Building Blocks (MBBs) for Tip-Based Nanofabrication (TBN) of Quantum Computing Devices
PublicationThe binding energy, BE of the X@C60-X@C60 homodimer and the X@C60-Y@C60 heterodimer resulting from the bond formation between the occupied X@C60 MBB and the C60 molecule was studied by means of semiempirical PM7 calculations, where X and Y denote atoms from H to Bi, excluding Tc and lanthanides. All possible combinations of N = 68 guest atoms were considered, which resulted in K = 2346 of different calculated dimers of (X@C60-Y@C60)...
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Solubility Characteristics of Acetaminophen and Phenacetin in Binary Mixtures of Aqueous Organic Solvents: Experimental and Deep Machine Learning Screening of Green Dissolution Media
PublicationThe solubility of active pharmaceutical ingredients is a mandatory physicochemical characteristic in pharmaceutical practice. However, the number of potential solvents and their mixtures prevents direct measurements of all possible combinations for finding environmentally friendly, operational and cost-effective solubilizers. That is why support from theoretical screening seems to be valuable. Here, a collection of acetaminophen...
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Neurocontrolled Car Speed System
PublicationThe features of the synthesis of neural controllers for the car speed control system are considered in this article. The task of synthesis is to determine the weight coefficients of neural networks that provide the implementation of proportional and proportional-integralderivative control laws. The synthesis of controllers is based on an approach that uses a reversed model of the standard. A model of the car speed control system with...
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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’...