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A Method for the Evaluation of Urban Freight Transport Models as a Tool for Improving the Delivery of Sustainable Urban Transport Policy
PublicationThe article presents a method which helps local authorities to evaluate urban freight transport models. Given the complex requirements for input data and the inability to supply them for most cities, a proper quantitative evaluation of model functionality may be quite difficult for local authorities. Freight transport models designed to support sustainable urban freight transport objectives are a particular example. To overcome...
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Mathematical Models of Control Systems of Angular Speed of Steam Turbines for Diagnostic Tests of Automatic and Mechatronic Devices
PublicationAccurate modeling of physical processes of many automatics and mechatronics systems is often necessity. In power system such a process is control of angular velocity of power objects during connection to operation in parallel. This process is extremely dynamic. For this reason response of control system depends from changes of many physical parameters (temperature, pressure and flow of the medium, etc.). Precision modeling influences...
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Interpretable deep learning approach for classification of breast cancer - a comparative analysis of multiple instance learning models
PublicationBreast cancer is the most frequent female cancer. Its early diagnosis increases the chances of a complete cure for the patient. Suitably designed deep learning algorithms can be an excellent tool for quick screening analysis and support radiologists and oncologists in diagnosing breast cancer.The design of a deep learning-based system for automated breast cancer diagnosis is not easy due to the lack of annotated data, especially...
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Genetic and pharmacologic proteasome augmentation ameliorates Alzheimer’s-like pathology in mouse and fly APP overexpression models
PublicationThe proteasome has key roles in neuronal proteostasis, including the removal of misfolded and oxidized proteins, presynaptic protein turnover, and synaptic efficacy and plasticity. Proteasome dysfunction is a prominent feature of Alzheimer’s disease (AD). We show that prevention of proteasome dysfunction by genetic manipulation delays mortality, cell death, and cognitive deficits in fly and cell culture AD models. We developed...
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Genetic and pharmacologic proteasome augmentation ameliorates Alzheimer’s-like pathology in mouse and fly APP overexpression models
PublicationThe proteasome has key roles in neuronal proteostasis, including the removal of misfolded and oxidized proteins, presynaptic protein turnover, and synaptic efficacy and plasticity. Proteasome dysfunction is a prominent feature of Alzheimer’s disease (AD). We show that prevention of proteasome dysfunction by genetic manipulation delays mortality, cell death, and cognitive deficits in fly and cell culture AD models. We developed...
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Limits of enhanced of macro- and meso-scale continuum models for studying size effect in concrete under tension
PublicationThe paper investigates a mechanical quasi-static size effect in concrete during splitting tension at the macro- and meso-level. In experiments, five different diameters of cylindrical concrete specimens were tested. Twodimensional plane strain finite element (FE) simulations were carried out to reproduce the experimental size effect. The size effect in experiments by Carmona et al. was also simulated. Two enhanced continuum concrete...
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Towards Designing an Innovative Industrial Fan: Developing Regression and Neural Models Based on Remote Mass Measurements
PublicationThis article presents the process of the construction and testing a remote, fully autonomous system for measuring the operational parameters of fans. The measurement results obtained made it possible to create and verify mathematical models using linear regression and neural networks. The process was implemented as part of the first stage of an innovative project. The article presents detailed steps of constructing a system to...
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Real-Time Facial Features Detection from Low Resolution Thermal Images with Deep Classification Models
PublicationDeep networks have already shown a spectacular success for object classification and detection for various applications from everyday use cases to advanced medical problems. The main advantage of the classification models over the detection models is less time and effort needed for dataset preparation, because classification networks do not require bounding box annotations, but labels at the image level only. Yet, after passing...
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Experimental validation of pressure drop models during flow boiling of R134a – effect of flow acceleration and entrainment
PublicationA crucial step to assure proficient work of power and process apparatus is their proper design. A wide array of those devices operates within boiling or condensation of the working fluid to benefit from high heat transfer rates. Two-phase flows are associated with high heat transfer coefficients because of the latent heat of evaporation and high turbulence level between the liquid and the solid surface. Predicting heat transfer...
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Automated Parameter Determination for Horizontal Curves for the Purposes of Road Safety Models with the Use of the Global Positioning System
PublicationThis paper presents the results of research conducted to develop an automated system capable of determining parameters for horizontal curves. The system presented in this article could calculate the actual course of a road by means of a two-stage positioning of recorded points along the road. In the first stage, measurements were taken with a Real-Time Network (RTN) receiver installed in a research vehicle. In the second stage,...
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A Cost-Effective Method for Reconstructing City-Building 3D Models from Sparse Lidar Point Clouds
PublicationThe recent popularization of airborne lidar scanners has provided a steady source of point cloud datasets containing the altitudes of bare earth surface and vegetation features as well as man-made structures. In contrast to terrestrial lidar, which produces dense point clouds of small areas, airborne laser sensors usually deliver sparse datasets that cover large municipalities. The latter are very useful in constructing digital...
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Rapid Design Centering of Multi-Band Antennas Using Knowledge-Based Inverse Models and Response Features
PublicationAccounting for manufacturing tolerances as well as uncertainties concerning operating conditions and material parameters is one of the important yet often neglected aspects of antenna development. Appropriate quantification of uncertainties allows for estimating the fabrication yield but also to carry out robust design (e.g., yield maximization). For reliability reasons, statistical analysis should be executed at the accuracy level...
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Low-Cost Quasi-Global Optimization of Expensive Electromagnetic Simulation Models by Inverse Surrogates and Response Features
PublicationConceptual design of contemporary high-frequency structures is typically followed by a careful tuning of their parameters, predominantly the geometry ones. The process aims at improving the relevant performance figures, and may be quite expensive. The reason is that conventional design methods, e.g., based on analytical or equivalent network models, often only yield rough initial designs. This is especially the case for miniaturized...
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Initializing the EM Algorithm for Univariate Gaussian, Multi-Component, Heteroscedastic Mixture Models by Dynamic Programming Partitions
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Constructing genuinely entangled multipartite states with applications to local hidden variables and local hidden states models
PublicationBuilding upon the results of R. Augusiak et al. [Phys. Rev. Lett. 115, 030404 (2015)] we develop a general approach to the generation of genuinely entangled multipartite states of any number of parties from genuinely entangled states of a fixed number of parties, in particular, the bipartite entangled ones. In our approach, certain isometries whose output subspaces are either symmetric or genuinely entangled in some multipartite...
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Improving Accuracy of Respiratory Rate Estimation by Restoring High Resolution Features With Transformers and Recursive Convolutional Models
PublicationNon-contact evaluation of vital signs has been becoming increasingly important, especially in light of the COVID- 19 pandemic, which is causing the whole world to examine people’s interactions in public places at a scale never seen before. However, evaluating one’s vital signs can be a relatively complex procedure, which requires both time and physical contact between examiner and examinee. These re- quirements limit the number...
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Cobalt(II) tri-tert-butoxysilanethiolates: in search of models for catalytic metal site of liver alcohol dehydrogenase
PublicationPrzeprowadzono syntezę trzech kompleksów: [Co{SSi(OBut)3}2(NH3)(L-pic)],[Co{SSi(OBut)3}2(NH3)2]xMeCN i [Co{SSi(OBut)3}3(H2O)][NHEt3]. Kompleksy są monomeryczne, dla nich wyznaczono strukturę krystalograficzną. Kompleks [Co{SSi(OBut)3(NH3)(L-pic)] o rdzeniu CoN2OS2 posiada dwa różne ligandy azotowe, zaś [Co{SSi(OBut)3(L-pic)] stanowi substrat do syntezy związku modelującego centrum katalityczne LADH.
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Data-driven models for fault detection using kernel PCA: A water distribution system case study
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Transcriptome Changes in Three Brain Regions during Chronic Lithium Administration in the Rat Models of Mania and Depression
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Effects of scatter plot initial solutions on regular grid facility layout algorithms in typical production models
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Application of Msplit method for filtering airborne laser scanning data sets to estimate digital terrain models
PublicationALS point cloud filtering involves the separation of observations representing the physical terrain surface from those representing terrain details. A digital terrain model (DTM) is created from a subset of points representing the ground surface. The accuracy of the generated DTM is influenced by several factors, including the survey method used, the accuracy of the source data, the applied DTM generation algorithm, and the survey...
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Flavonoids as tyrosinase inhibitors in in silico and in vitro models: basic framework of SAR using a statistical modelling approach
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Quantitative Soil Characterization for Biochar–Cd Adsorption: Machine Learning Prediction Models for Cd Transformation and Immobilization
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On the usefulness of selected radio waves propagation models for designing mobile wireless systems in container terminal environment
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Three-Dimensional Models of Liver Vessels for Navigation during Laparotomic Attenuation of Intrahepatic Portosystemic Shunt in Dogs
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Application of computational intelligence models in IoMT big data for heart disease diagnosis in personalized health care
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Impact of Feature Selection Methods on the Predictive Performance of Software Defect Prediction Models: An Extensive Empirical Study
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Selected mice models based on APP, MAPT and presenilin gene mutations in research on the pathogenesis of Alzheimer’s disease
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3D Morphable Models Application for Expanding Face Database Limited to Single Frontal Face Per Person
Publication1. Zaprezentowany materiał dotyczył badań nad rozszerzeniem dysponowanej bazy wzorców wizerunków twarzy, o dodatkowe wzorce z wariacją w ustawieniu. Dodatkowe wzorce były usyskiwane poprzez przejście z wizerunku twarzy 2D na model 3D, zasymulowanie zadanego ustawienia i powrót do dziedziny 2D (poprzez rzutowanie 3D->2D). W fazie konstrukcji modelu 3D, z wizerunku 2D była ściągana zarówno tekstura twarzy jak i siatka punktów charakterystycznych....
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Results of the application of tropospheric corrections from different troposphere models for precise GPS rapid static positioning
PublicationIn many surveying applications, determination of accurate heights is of significant interest. The delay caused by the neutral atmosphere is one of the main factors limiting the accuracy of GPS positioning and affecting mainly the height coordinate component rather than horizontal ones. Estimation of the zenith total delay is a commonly used technique for accounting for the tropospheric delay in static positioning. However, in the...
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Minimizing Distribution and Data Loading Overheads in Parallel Training of DNN Acoustic Models with Frequent Parameter Averaging
PublicationIn the paper we investigate the performance of parallel deep neural network training with parameter averaging for acoustic modeling in Kaldi, a popular automatic speech recognition toolkit. We describe experiments based on training a recurrent neural network with 4 layers of 800 LSTM hidden states on a 100-hour corpora of annotated Polish speech data. We propose a MPI-based modification of the training program which minimizes the...
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Fast Multi-Objective Optimization of Narrow-Band Antennas Using RSA Models and Design Space Reduction
PublicationComputationally efficient technique for multi-objective design optimization of narrow-band antennas is presented. In our approach, the corrected low-fidelity antenna model (obtained through coarse-discretization EM simulations) is enhanced using frequency scaling and response correction, sampled, and utilized to obtain a fast response surface approximation (RSA) antenna surrogate. The RSA model is constructed in the reduced design space....
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Data-driven models for fault detection using kernel pca:a water distribution system case study
PublicationKernel Principal Component Analysis (KPCA), an example of machine learning, can be considered a non-linear extension of the PCA method. While various applications of KPCA are known, this paper explores the possibility to use it for building a data-driven model of a non-linear system-the water distribution system of the Chojnice town (Poland). This model is utilised for fault detection with the emphasis on water leakage detection....
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Volatile Compound Emissions from Stereolithography Three-Dimensional Printed Cured Resin Models for Biomedical Applications
PublicationStereolithography three-dimensional printing is used increasingly in biomedical applications to create components for use in healthcare and therapy. The exposure of patients to volatile organic compounds (VOCs) emitted from cured resins represents an element of concern in such applications. Here, we investigate the biocompatibility in relation to inhalation exposure of volatile emissions of three different cured commercial resins...
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublicationMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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Comparison of 2D and 3D culture models in the studies of the biological response induced by unsymmetrical bisacridines in cancer cells
PublicationMulticellular tumor spheroids are a good tool for testing new anticancer drugs, including those that may target cancer stem cells (CSCs), responsible for cancer progression, metastasis, and recurrence. Therefore, following the initial evaluation of the impact of antitumor unsymmetrical bisacridines (UAs) on lung and colon cancer cells using traditional monolayer cultures, I extended my investigations and applied the spherical model....
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Discrete-time predictive control design based on overparameterized delay-plant models and identified cancellation order.
PublicationPraca dotyczy uogólnionego sterowania predykcyjnego (GPC) obiektami opisanymi dyskretnoczasowymi modelami CARIMA z uproszczeniami (nieminimalnych, przeparametryzowanych) oraz o niezerowym opóźnieniu transportowym. Optymalne sterowanie predykcyjne wyznacza się na podstawie minimalnowariancyjnego oszacowania przyszłej odpowiedzi sterowanego obiektu. Poprzez analizę warunków rozwiązywalności zadania syntezy sterownika GPC, sformułowano...
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FE-analysis of the beaviour of concrete elements with coupled elasto-plastic-damage models with non-local softening
PublicationArtykuł omawia wyniki symulacji zachowania sie elementów betonowych poddanych cyklicznemu obciążeniu. Do symulacji zastosowano połączone modele sprężysto-plastyczne z degradacją sztywności i z nielokalnym osłabieniem. Wyniki symulacji porównano z doswiadczeniami.
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FE-modelling of concrete behaviour under mixed mode conditions with non-local and cohesive constitutive models.
PublicationW artykule przedstawiono wyniki symulacji rys zaokrąglonych w elementach betonowych w warunkach mieszanego sposobu obciążenia. Symulacje wykonano przy zastosowaniu modelu rys kohezyjnych i modeli mechaniki ośrodka ciągłego z nielokalnym osłabieniem.. Wyniki symulacji porównano z doświadczeniami.
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Application of enhanced elasto-plastic damage models to concrete under quasi-static and dynamic cyclic loading
PublicationArtykuł omawia wyniki symulacji zachowania sie elementów betonowych poddanych zginaniu w czasie cyklicznego obciążenia. Do symulacji zastosowano 3 połączone modele sprężysto-plastyczne z degradacją sztywności i z nielokalnym osłabieniem. Wyniki symulacji porównano bezpośrednio z doświadczeniami.
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Comparison of continuous and discontinuous constitutive models to simulate concrete behaviour under mixed mode failure conditions
PublicationW artykule porównano modele MES ciągłe i nieciągłe do symulacji zachowania betonu w warunkach mieszanego zniszczenia. W ramach modeli ciągłych zastosowano modele sprężysto-plastyczne oraz modele z redukcją sztywności sprężystej i nielokalnym osłabieniem. W ramach modeli nieciągłych zastosowano XFEM. Przedmiotem obliczeń były strefy lokalizacji i rysy w warunkach mieszanego zniszczenia wg testu doświadczalnego Nooru-Mohameda.
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Parameters and statistics of models made for selected companies of the Warsaw Stock Exchange
Open Research DataFor the WIG, WIG20 and mWIG40 indices, no day, week or month statistically differs from the average level of the index, which indicates no anomalies. The situation is different only for the index of small companies. In the case of sWIG80, the mean values on Friday, week 5 and 6, and during January, February and June were statistically different at the...
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Influence of service ageing on polyester-reinforced polyvinyl chloride-coated fabrics reported through mathematical material models
PublicationIn this paper the coupled service (constructional tension) and environmental (sunlight, rainfalls, temperature variations) ageing influence on the polyester-reinforced polyvinyl chloride (PVC)-coated fabric VALMEX is studied. Two cases of the same fabric have been analyzed: one USED for 20 years on the real construction of the Forest Opera in Sopot (Poland), and one kept as a spare material (NOT USED). The following tests have...
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COMPARATIVE ANALYSIS OF RESULTS OF APPLICATION OF MARKOV AND SEMI-MARKOV PROCESSES TO RELIABILITY MODELS OF MULTI-STATE TECHNICAL OBJECTS
PublicationDuring rational operation of technical objects and systems various operational decisions are made and decision-making process itself should be consisted in selecting that considered most favourable out of all possible to be taken. Choice of such decision is possible after taking into account many different information items but it never be completely correct without accounting for data and indices dealing with reliability. In...
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User-assisted methodology targeted for building structure interpretable QSPR models for boosting CO2 capture with ionic liquids
PublicationTask-specific ionic liquid (IL) is an emerging class of compounds that may be environmentally friendly. Properly selected, these compounds may be green alternative to amine solutions and can replace them in post-combustion carbon dioxide (CO2) capture processes on an industrial scale. However, owing to the vast diversity of ions and their possible combinations, laboratory research is time consuming and expensive. Therefore, computational...
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DESIGN LOGICAL LINGUISTIC MODELS TO CALCULATE NECESSITY IN TRUCKS DURING AGRICULTURAL CARGOES LOGISTICS USING FUZZY LOGIC
Publication: The study is aimed to develop the logic-linguistic models to design a number of rules for the correct calculation of the vehicles needed, taking into account the technical, technological, and weather and climate conditions of the harvesting and transport complex. The article has shown that the construction of the design of logic-linguistic models was not performed earlier to solve the problem of the agro-industrial production...
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Multi-DBD plasma actuator for flow separation control around NACA 0012 and NACA 0015 airfoil models
PublicationIn this paper application of innovative multi-DBD plasma actuator for flow separation control is presented. The influence of the airflowgenerated by this actuator on the flow around NACA 0012 and NACA 0015 airfoil models was investigated. The results obtained from 2D PIVmeasurements showed that the multi-DBD actuator with floating interelectrode can be attractive for leading and trailing edge separation control.
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Recent advances in rapid multiobjective optimization of expensive simulation models in microwave and antenna engineering by Pareto front exploration
PublicationPractical engineering design problems are inherently multiobjective, that is, require simultaneous control of several (and often conflicting) criteria. In many situations, genuine multiobjective optimization is required to acquire comprehensive information about the system of interest. The most popular solution techniques are populationbased metaheuristics, however, they are not practical for handling expensive electromagnetic...
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Surrogate-assisted EM-driven miniaturization of wideband microwave couplers by means of co-simulation low-fidelity models
PublicationThis article proposes a methodology for rapid design optimization of miniaturized wideband couplers. More specifically, a class of circuits is considered, in which conventional transmission lines are replaced by their abbreviated counterparts referred to as slow-wave compact cells. Our focus is on explicit reduction of the structure size as well as on reducing the CPU cost of the design process. For the sake of computational feasibility,...
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Improving platelet‐RNA‐based diagnostics: a comparative analysis of machine learning models for cancer detection and multiclass classification
PublicationLiquid biopsy demonstrates excellent potential in patient management by providing a minimally invasive and cost-effective approach to detecting and monitoring cancer, even at its early stages. Due to the complexity of liquid biopsy data, machine-learning techniques are increasingly gaining attention in sample analysis, especially for multidimensional data such as RNA expression profiles. Yet, there is no agreement in the community...