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Search results for: STRUCTURE PREDICTION
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Deep Learning-based Recalibration of the CUETO and EORTC Prediction Tools for Recurrence and Progression of Non–muscle-invasive Bladder Cancer
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Use of the UNRES force field in template-assisted prediction of protein structures and the refinement of server models: Test with CASP12 targets
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Prediction of Ship Resonant Rolling - Related Dangerous Zones with Regard to the Equivalent Metacentric Height Governing Natural Frequency of Roll
PublicationPotentially dangerous zones corresponding to dynamical stability phenomena, possibly encountered by ships sailing in rough sea, are estimated nowadays with the use of the method recommended by IMO in the guidance coded MSC.1/Circ.1228. In this IMO method the parameter governing the natural period of roll is the initial metacentric height. Some earlier studies revealed that the initial metacentric height...
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Fracture prediction in flat PMMA notched specimens under tension - effectiveness of the equivalent material concept and fictitious material concept
PublicationThe fracture of notched elements under mode I loading (tension) remains an inexhaustible research topic, especially when it comes to the fracture of thermoplastic materials such as polymethylmethacrylate (PMMA), which experience considerable plastic strains under tension. The paper points out that traditional brittle fracture criteria such as mean stress (MS) or maximum tangential stress (MTS) criteria used to predict this phenomenon do...
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Comparative study on total nitrogen prediction in wastewater treatment 1 plant and effect of various feature selection methods on machine learning algorithms performance
PublicationWastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods are used in the pre-processing section for enhancing the model performance. This study aims to evaluate the effect of seven different FS methods (filter, wrapper, and embedded methods) on enhancing the prediction accuracy for total nitrogen (TN) in the WWTP...
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An adaptive-noise Augmented Kalman Filter approach for input-state estimation in structural dynamics
PublicationThe establishment of a Digital Twin of an operating engineered system can increase the potency of Structural Health Monitoring (SHM) tools, which are then bestowed with enhanced predictive capabilities. This is particularly relevant for wind energy infrastructures, where the definition of remaining useful life is a main driver for assessing the efficacy of these systems. In order to ensure a proper representation of the physical...
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Teicoplanin-Modified HPLC Column as a Source of Experimental Parameters for Prediction of the Anticonvulsant Activity of 1,2,4-Triazole-3-Thiones by the Regression Models
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Prediction of skin color, tanning and freckling from DNA in Polish population: linear regression, random forest and neural network approaches
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An asymmetrical λ-foot of condensing steam flow in the IMP PAN nozzle
PublicationIn the present paper we have focused on the precise prediction of the spontaneous condensation phenomena in wet steam flow. Novelty of our approach lies on modelling both the moment of initiation of a phase transition, as well as the moment of its reverse progress - called here re-vaporization of the condensate phase. The practical issue is to elaborate of a model of spontaneous condensation/vaporization of water steam flow...
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Ligand-Modified Boron-Doped Diamond Surface: DFT Insights into the Electronic Properties of Biofunctionalization
PublicationWith the increasing power of computation systems, theoretical calculations provide a means for quick determination of material properties, laying out a research plan, and lowering material development costs. One of the most common is Density Functional Theory (DFT), which allows us to simulate the structure of chemical molecules or crystals and their interaction. In developing a new generation of biosensors, understanding the nature...
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Rapid multi-objective design optimisation of compact microwave couplers by means of physics-based surrogates
PublicationThe authors introduce a methodology for fast multi-objective design optimisation of miniaturised microwave couplers. The approach exploits the surrogate-based optimisation paradigm with an underlying low-fidelity model constructed from an equivalent circuit of the structure under consideration, corrected through implicit and frequency space mapping. A fast prediction tool obtained this way is subsequently optimised by a multi-objective...
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A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification
PublicationThe article concerns the automation of vessel movement anomaly detection for maritime and coastal traffic safety services. Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), were used to solve this problem. Three variants of the datasets, containing samples of vessel traffic routes in relation to the prohibited area in the form of a grayscale image, were generated. 1458 convolutional neural networks with...
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Trends in In Silico Approaches to the Prediction of Biologically Active Peptides in Meat and Meat Products as an Important Factor for Preventing Food-Related Chronic Diseases
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Validation study on a new semi-empirical method for the prediction of added resistance in waves of arbitrary heading in analyzing ship speed trial results
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Modelowanie przepływu wód podziemnych w strefie brzegowej morza - możliwości prognozowania = Groundwater flow modeling in the coastline area - prediction possibilities
PublicationSpecyficzne warunki występowania wód podziemnych w strefie brzegowej morza sprawiają, że ich eksploatacja jest sprawą złożoną i powinna być weryfikowana na modelu numerycznym. Zasadniczym zagrożeniem jest ingresja słonych wód morskich, która może być wzbudzona eksploatacją. Innym czynnikiem, który może przyczynić się do ingresji wód słonych do warstwy wodonośnej może być podniesienie się poziomu morza. W pracy przedstawiono wyniki...
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Prediction of maximum tensile stress in plain-weave composite laminates with interacting holes via stacked machine learning algorithms: A comparative study
PublicationPlain weave composite is a long-lasting type of fabric composite that is stable enough when being handled. Open-hole composites have been widely used in industry, though they have weak structural performance and complex design processes. An extensive number of material/geometry parameters have been utilized for designing these composites, thereby an efficient computational tool is essential for that purpose. Different Machine Learning...
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On adaptive covariance and spectrum estimation of locally stationary multivariate processes
PublicationWhen estimating the correlation/spectral structure of a locally stationary process, one has to make two important decisions. First, one should choose the so-called estimation bandwidth, inversely proportional to the effective width of the local analysis window, in the way that complies with the degree of signal nonstationarity. Too small bandwidth may result in an excessive estimation bias, while too large bandwidth may cause excessive...
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Modeling protein structures with the coarse-grained UNRES force field in the CASP14 experiment
PublicationThe UNited RESidue (UNRES) force field was tested in the 14th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP14), in which larger oligomeric and multimeric targets were present compared to previous editions. Three prediction modes were tested (i) ab initio (the UNRES group), (ii) contact-assisted (the UNRES- contact group), and (iii) template-assisted (the UNRES-template...
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Market Price Prediction of Property Rights from Gas Fired Plants or Plants with Total Installed CHP Source Capacity Below 1 MW until 2025
PublicationThe resolution on the Polish Energy Policy until 2030 (PEP-30) was adopted by the Council of Ministers on 10 November 2009. The document specifies the combined electricity and heat generation as a direction of pursuing the goals of energy efficiency, fuel and energy supply security, competitive fuel and energy markets development, and reduction of the energy sector’s environmental impact. PEP-30 assumes that electricity generation...
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Chemometric analysis of bio-inspired micellar electrokinetic chromatographic systems – modelling of retention mechanism and prediction of biological properties using bile salts surfactants
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Toxicity of the New Psychoactive Substance (NPS) Clephedrone (4-Chloromethcathinone, 4-CMC): Prediction of Toxicity Using In Silico Methods for Clinical and Forensic Purposes
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Potential of Serum Proteome Patterns Analysis by MALDI-TOF Mass Spectrometry for Prediction of Acute Radiation Injury Response in Head and Neck Cancers Patients
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Drug affinity to human serum albumin prediction by retention of cetyltrimethylammonium bromide pseudostationary phase in micellar electrokinetic chromatography and chemically advanced template search descriptors
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Polybrominated diphenyl ether (PBDE) concentrations in dust from various indoor environments in Gdańsk, Poland: Prediction of concentrations in indoor air and assessment of exposure of adults
PublicationMonitoring of polybrominated diphenyl ethers (PBDEs) in indoor environments involves the determination of their concentrations in air, airborne particles, and settled dust. Each of these is a source of human exposure to PBDEs. In this study, we attempted to model PBDEs concentrations in various typical indoor environments on the basis of real PBDEs measurements in dust collected from them. The analytical procedure for determining...
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Towards an Understanding of the Stability Assessment of Floating Buildings
PublicationOne of the most important aspects of the design of floating facilities such as ships, floating offshore structures or floating houses is stability. Its impact on both general safety and operational aspects renders it a fundamental consideration already in preliminary design stages. Usually, the concept of sufficient stability of floating buildings is associated with the ability to keep an allowed heel angle and residual freeboard,...
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Comparative Study of Pavement Rehabilitation Using Hot in-Place Recycling and Hot-Mix Asphalt: Performance Evaluation, Pavement Life Prediction, and Life Cycle Cost Analysis
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Analiza porównawcza metod predykcji chwili zgodności fazowejw automatycznym synchronizatorze prądnic = Comparison of the methods of prediction time phase coincidence in automatic synchronizer of power generators
PublicationW artykule porównano dokładność wybranych metod realizacji warunku fazowego podczas synchronizacji obiektów elektroenergetycznych. Do porównania wybrano trzy metody: liniową, wielomianową oraz metodę adaptacyjnej synchronizacji prądnic z ekstrapolacją funkcją wymierną. Badania przeprowadzono dla różnych warunków pracy. Przyjęto stałą różnicę częstotliwości napięć synchronizowanych obiektów, różnicę częstotliwości zmieniającą się...
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Validation of EORTC, CUETO, and EAU risk stratification in prediction of recurrence, progression, and death of patients with initially non–muscle‐invasive bladder cancer (NMIBC): A cohort analysis
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Review of Research into Enterprise Bankruptcy Prediction in Selected Central and Eastern European Countries (prezentacja na konferencji TWENTY-SIXTH ANNUAL CONFERENCE MULTINATIONAL FINANCE SOCIETY)
PublicationUlotka konferencyjna: http://www.mfsociety.org/modules/modMainContent/uploadFiles/miscFiles/1562848077-MFC2019-Booklet-for-Distribution_2019-06-25.pdf
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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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Algorytmy hybrydowe optymalizacji w zastosowaniu do problemu sterowania systemami dystrybucji wody
PublicationW pracy analizowany jest problem optymalizującego zintegrowanego sterowania ilością i jakością w systemach dystrybucji wody. Proponowane decyzje i sterowania powinny zapewniać optymalizację przyjętego wskaźnika jakości, przy spełnieniu ograniczeń właściwych tej klasie systemów. Ostatecznie do rozwiązania złożonych zadań optymalizacji dynamicznej zaproponowane zostało podejście hybrydowe, wspomagające predykcyjne algorytmy sterowania...
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Productivity Enhancement by Prediction of Liquid Steel Breakout during Continuous Casting Process in Manufacturing of Steel Slabs in Steel Plant Using Artificial Neural Network with Backpropagation Algorithms
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Cytokine TGFβ Gene Polymorphism in Asthma: TGF-Related SNP Analysis Enhances the Prediction of Disease Diagnosis (A Case-Control Study With Multivariable Data-Mining Model Development)
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AOP173 key event associated pathway predictor – online application for the prediction of benchmark dose lower bound (BMDLs) of a transcriptomic pathway involved in MWCNTs-induced lung fibrosis
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Rapid Microwave Design Optimization in Frequency Domain Using Adaptive Response Scaling
PublicationIn this paper, a novel methodology for cost-efficient microwave design optimization in the frequency domain is proposed. Our technique, referred to as adaptive response scaling (ARS), has been developed for constructing a fast replacement model (surrogate) of the high-fidelity electromagnetic-simulated model of the microwave structure under design using its equivalent circuit (low-fidelity model). The basic principle of ARS is...
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Validation of EORTC, CUETO and EAU risk stratification in prediction of recurrence, progression and death of patients with initially non-muscle invasive bladder cancer (NMIBC): a cohort analysis with systematic review.
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Novel molecules containing structural features of NSAIDs and 1,2,3-triazole ring: Design, synthesis and evaluation as potential cytotoxic agents
PublicationFor the first time the template containing structural features of more than one NSAIDs and the 1,2,3-triazole ring was explored for the identification of potential cytotoxic agents. These new and complex molecules were predicted to be effective inhibitors of PDE4B by molecular modelling studies in silico. The multi-step synthesis of these compounds were carried out starting from the well-known drug nimesulide and involved the use...
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Selection of effective cocrystals former for dissolution rate improvement of active pharmaceutical ingredients based on lipoaffinity index
PublicationNew theoretical screening procedure was proposed for appropriate selection of potential cocrystal formers possessing the ability of enhancing dissolution rates of drugs. The procedure relies on the training set comprising 102 positive and 17 negative cases of cocrystals found in the literature. Despite the fact that the only available data were of qualitative character, performed statistical analysis using binary classification...
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Experimental and predicted physicochemical properties of monopropanolamine-based deep eutectic solvents
PublicationIn this work, the novel deep eutectic solvents (DESs) based on 3-amino-1-propanol (AP) as hydrogen bond donor (HBD) and tetrabutylammonium bromide (TBAB) or tetrabutylammonium chloride (TBAC) or tetraethylammonium chloride (TEAC) as hydrogen bond acceptors (HBAs) were synthesized with different molar ratios of 1: 4, 1: 6 and 1: 8 salt to AP. Fourier Transform Infrared Spectroscopy measurements were performed to provide an evidence...
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Adsorption onto zeolites: molecular perspective
Publication2D minerals are among key elements of advanced systems, but the need for understanding their interactions/reactions with materials and systems in which they are involved necessitates tracking their molecular and atomic monitoring. Zeolitic structures are microporous materials formed in the nature through volcanic activities or synthesis. Because of their outstanding physicochemical properties like cation exchange capacity and excellent...
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Experimental and predicted physicochemical properties of monopropanolamine-based deep eutectic solvents
PublicationIn this work, the novel deep eutectic solvents (DESs) based on 3-amino-1-propanol (AP) as hydrogen bond donor (HBD) and tetrabutylammonium bromide (TBAB) or tetrabutylammonium chloride (TBAC) or tetraethylammonium chloride (TEAC) as hydrogen bond acceptors (HBAs) were synthesized with different molar ratios of 1:4, 1:6 and 1:8 salt to AP. Fourier Transform Infrared Spectroscopy measurements were performed to provide an evidence...
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USING ARTIFICIAL NEURAL NETWORKS FOR PREDICTING SHIP FUEL CONSUMPTION
PublicationIn marine vessel operations, fuel costs are major operating costs which affect the overall profitability of the maritime transport industry. The effective enhancement of using ship fuel will increase ship operation efficiency. Since ship fuel consumption depends on different factors, such as weather, cruising condition, cargo load, and engine condition, it is difficult to assess the fuel consumption pattern for various types...
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Optimization of Saccharification Conditions of Lignocellulosic Biomass under Alkaline Pre-Treatment and Enzymatic Hydrolysis
PublicationPre-treatment is a significant step in the production of second-generation biofuels from waste lignocellulosic materials. Obtaining biofuels as a result of fermentation processes requires appropriate pre-treatment conditions ensuring the highest possible degree of saccharification of the feed material. An influence of the following process parameters were investigated for alkaline pre-treatment of Salix viminalis L.: catalyst concentration...
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Consequences of New Approach of Chemical Stability Tests of Active Pharmaceutical Ingredients (APIs)
PublicationThere is a great need of broaden look on stability tests of active pharmaceuticalingredients (APIs) in comparison with current requirements contained in pharmacopeia.By usage of many modern analytical methods the conception of monitoring the changesof APIs during initial stage of their exposure to harmful factors has been developed. Newknowledge must be acquired in terms of identification of each degradation...
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Indole-Acrylonitrile Derivatives as Potential Antitumor and Antimicrobial Agents—Synthesis, In Vitro and In Silico Studies
PublicationA series of 2-(1H-indol-2-yl)-3-acrylonitrile derivatives, 2a–x, 3, 4a–b, 5a–d, 6a–b, and 7, were synthesized as potential antitumor and antimicrobial agents. The structures of the prepared compounds were evaluated based on elemental analysis, IR, 1H- and 13NMR, as well as MS spectra. X-ray crystal analysis of the representative 2-(1H-indol-2-yl)-3-acrylonitrile 2l showed that the acrylonitrile double bond was Z-configured. All...
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Correlation between the number of Pro-Ala repeats in the EmrA homologue of Acinetobacter baumannii and resistance to netilmicin, tobramycin, imipenem and ceftazidime
PublicationAcinetobacter baumannii coccobacilli are dangerous to patients in intensive care units because of their multidrug resistance to antibiotics, developed mainly in the past decade. This study aimed to examine whether there is a significant correlation between the number of Pro-Ala repeats in the CAP01997 protein, the EmrA homologue of A. baumannii, and resistance to antibiotics. A total of 79 multidrug-resistant A. baumannii strains...
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Employing flowgraphs for forward route reconstruction in video surveillance system
PublicationPawlak’s flowgraphs were utilized as a base idea and knowledge container for prediction and decision making algorithms applied to experimental video surveillance system. The system is used for tracking people inside buildings in order to obtain information about their appearance and movement. The fields of view of the cameras did not overlap. Therefore, when an object was moving through unsupervised areas, prediction was needed...
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A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection
PublicationComputational cost is an important consideration for memory encoding prediction models that use data from dozens of implanted electrodes. We propose a method to reduce computational expense by selecting a subset of all the electrodes to build the prediction model. The electrodes were selected based on their likelihood of measuring brain activity useful for predicting memory encoding better than chance (in terms of AUC). A logistic...
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On Nature-Inspired Design Optimization of Antenna Structures Using Variable-Resolution EM Models
PublicationNumerical optimization has been ubiquitous in antenna design for over a decade or so. It is indispensable in handling of multiple geometry/material parameters, performance goals, and constraints. It is also challenging as it incurs significant CPU expenses, especially when the underlying computational model involves full-wave electromagnetic (EM) analysis. In most practical cases, the latter is imperative to ensure evaluation reliability....
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Constrained aerodynamic shape optimization using neural networks and sequential sampling
PublicationAerodynamic shape optimization (ASO) involves computational fluid dynamics (CFD)-based search for an optimal aerodynamic shape such as airfoils and wings. Gradient-based optimization (GBO) with adjoints can be used efficiently to solve ASO problems with many design variables, but problems with many constraints can still be challenging. The recently created efficient global optimization algorithm with neural network (NN)-based prediction...