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  • Sample Preparation in Foodomics: Miniaturized Solid-Phase Extraction
    • Dorota Garwolińska
    • Renata Marcinkowska
    • Jacek Namieśnik
    • Weronika Hewelt-Belka
    2021

    Analytical chemists face a challenge to bring comprehensive information on a given food and biological sample by using the best available analytical techniques and meet the requirements of sustainable development and green chemistry at the same time. A key objective of this chapter is to review selected literature data on the utilization of solid-phase extraction techniques with special attention to their miniaturized modes in order to assess the safety, quality and nutritional value of foods. The techniques will be discussed in the context of different samples and analytical information which is about to be obtained.

  • Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
    • Kowsalya Thiagarajan
    • Mukunthan Manapakkam Anandan
    • Andrzej Stateczny
    • Parameshachari Bidare Divakarachari
    • Hemalatha Kivudujogappa Lingappa
    2021 Pełny tekst Remote Sensing

    Satellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification of satellite images. The HFEL uses three different types of Convolutional Neural Networks (CNN), namely AlexNet, LeNet-5 and a residual network (ResNet), to extract the appropriate features from images of the hierarchical framework. Additionally, the optimal features from the feature set are extracted using the Correlation Coefficient-Based Gravitational Search Algorithm (CCGSA). Further, the Multi Support Vector Machine (MSVM) is used to classify the satellite images by extracted features from the fully connected layers of the CNN and selected features of the CCGSA. Hence, the combination of HFEL and CCGSA is used to obtain the precise classification over different datasets such as the SAT-4, SAT-6 and Eurosat datasets. The performance of the proposed HFEL–CCGSA is analyzed in terms of accuracy, precision and recall. The experimental results show that the HFEL–CCGSA method provides effective classification over the satellite images. The classification accuracy of the HFEL–CCGSA method is 99.99%, which is high when compared to AlexNet, LeNet-5 and ResNet.

  • Scaling Up the Process of Titanium Dioxide Nanotube Synthesis and Its Effect on Photoelectrochemical Properties
    • Mariusz Szkoda
    • Konrad Trzciński
    • Zuzanna Zarach
    • Daria Roda
    • Marcin Łapiński
    • Andrzej Nowak
    2021 Pełny tekst Materials

    In this work, for the first time, the influence of scaling up the process of titanium dioxide nanotube (TiO2NT) synthesis on the photoelectrochemical properties of TiO2 nanotubes is presented. Titanium dioxide nanotubes were obtained on substrates of various sizes: 2 × 2, 4 × 4, 5 × 5, 6 × 6, and 8 × 8 cm2. The electrode material was characterized using scanning electron microscopy as well as Raman and UV–vis spectroscopy in order to investigate their morphology, crystallinity, and absorbance ability, respectively. The obtained electrodes were used as photoanodes for the photoelectrochemical water splitting. The surface analysis was performed, and photocurrent values were determined depending on their place on the sample. Interestingly, the values of the obtained photocurrent densities in the center of each sample were similar and were about 80 µA·cm2. The results of our work show evidence of a significant contribution to wider applications of materials based on TiO2 nanotubes not only in photoelectrochemistry but also in medicine, supercapacitors, and sensors

  • Scheduling of compatible jobs on parallel machines
    • Tytus Pikies
    2021

    The dissertation discusses the problems of scheduling compatible jobs on parallel machines. Some jobs are incompatible, which is modeled as a binary relation on the set of jobs; the relation is often modeled by an incompatibility graph. We consider two models of machines. The first model, more emphasized in the thesis, is a classical model of scheduling, where each machine does one job at time. The second one is a model of p-batching machines, where a machine can do many jobs at once. Precisely, the jobs have to be grouped into batches and the batches assigned to machines. In the case of the first model, no two jobs that are incompatible can be scheduled on the same machine. In the case of the second one, no two jobs that are incompatible can be scheduled in the same batch. The work analyzes problems of the scheduling with respect to two criteria of optimality, maximum completion time among the jobs and total completion time of jobs. We analyze the problem with the following types of machines: identical, uniform and unrelated. We provide further results for makespan criterion, which is quite commonly considered in the setting of classical machines. More importantly, we provide results for many classes of graphs with respect to the total completion time criterion, which has not been considered in the literature before for the classical machines in the considered setting. In particular, we provide polynomial time algorithms for identical machines; and complete partite graphs or cluster graphs. Also, for complete partite graphs and uniform machines we apply the techniques of rounding, partial exhaustive search, and linear programming to obtain 4-approximate algorithm. The algorithm demonstrates that an application of the techniques to the problems with total completion time criteria is feasible. Finally, there is presented a study of the cost coloring problem, which has direct implications for uniform p-batching machines. Hence, we also briefly consider uniform p-batching machines and weighted total completion time criterion, which is a generalization of total completion time. The study starts with an overview of recent advances in the scheduling algorithms in the context of scheduling incompatible jobs. After the overview, the results presented are: polynomial time algorithms; approximate algorithms with constant approximation ratio; inapproximability results up to some constant, and up to arbitrary constant.

  • Scheduling with Complete Multipartite Incompatibility Graph on Parallel Machines
    • Tytus Pikies
    • Krzysztof Turowski
    • Marek Kubale
    2021

    In this paper we consider a problem of job scheduling on parallel machines with a presence of incompatibilities between jobs. The incompatibility relation can be modeled as a complete multipartite graph in which each edge denotes a pair of jobs that cannot be scheduled on the same machine. Our research stems from the works of Bodlaender, Jansen, and Woeginger (1994) and Bodlaender and Jansen (1993). In particular, we pursue the line investigated recently by Mallek, Bendraouche, and Boudhar (2019). We provide several results concerning schedules, optimal or approximate with respect to the two most popular criteria of optimality: Cmax (makespan) and ΣCj (total completion time). We consider a variety of machine types in our paper: identical, uniform, and unrelated. Our results consist of delimitation of the easy (polynomial) and NP-hard problems within these constraints. We also provide algorithms, either polynomial exact algorithms for the easier problems, or algorithms with a guaranteed constant worst-case approximation ratio. In particular, we fill the gap on research for the problem of finding a schedule with the smallest ΣCj on uniform machines. We address this problem by developing a linear programming relaxation technique with an appropriate rounding, which to our knowledge is a novelty for this criterion in the considered setting.

  • Scheelite-Type Wide-Bandgap ABO4 Compounds (A = Ca, Sr, and Ba; B = Mo and W) as Potential Photocatalysts for Water Treatment
    • Marta Kowalkińska
    • Paweł Głuchowski
    • Tomasz Swebocki
    • Tadeusz Ossowski
    • Adam Ostrowski
    • Waldemar Bednarski
    • Jakub Karczewski
    • Anna Zielińska-Jurek
    2021 Pełny tekst Journal of Physical Chemistry C

    In the present study, alkaline-earth metal scheelite-type compounds ABO4 (A = Ca, Sr, Ba, B = Mo, W) synthesized by a hydrothermal method were systematically studied. The as-obtained photocatalysts were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), Brunauer-Emmett-Teller surface area analysis (BET), UV–Vis diffuse reflectance spectroscopy (DR/UV-Vis), photoluminescence, and thermoluminescence (TL) spectroscopy together with charge carrier’s lifetime measurements, electron paramagnetic resonance spectroscopy (EPR) and electrochemical impedance spectroscopy (EIS). The photocatalytic activity was studied in the reaction of phenol degradation under simulated solar light. The obtained tungstates and molybdates revealed excellent photocatalytic activity despite the low surface area and wide-bandgap typical for insulators. The mechanism of phenol degradation proceeded through hydroquinone and catechol formation in the presence of hydroxyl and superoxide radicals. The presence of electron traps allowed to absorb light with lower energy than resulting from the absorption edge. BaWO4 and SrWO4, with the most extended average carrier lifetime, were the most efficient photocatalysts from obtained series. In general, molybdates exhibited lower photocatalytic activity towards phenol degradation due to deeper trap states and lower average charge carriers' lifetimes than tungstates. Additionally, electrochemical studies emerged that molybdates exhibit more insulating behavior than tungstates. Overall results showed that wide-bandgap semiconductors, mainly tungstates, can be applied as earth-abundant photocatalytic materials for the degradation of persistent organic pollutants.

  • Searching by heterogeneous agents
    • Dariusz Dereniowski
    • Łukasz Kuszner
    • Robert Ostrowski
    2021 JOURNAL OF COMPUTER AND SYSTEM SCIENCES

    In this work we introduce and study a pursuit-evasion game in which the search is performed by heterogeneous entities. We incorporate heterogeneity into the classical edge search problem by considering edge-labeled graphs: once a search strategy initially assigns labels to the searchers, each searcher can be only present on an edge of its own label. We prove that this problem is not monotone even for trees and we give instances in which the number of recontamination events is asymptotically quadratic in the tree size. Other negative results regard the NP-completeness of the monotone, and NP-hardness of an arbitrary (i.e., non-monotone) heterogeneous search in trees. These properties show that this problem behaves very differently from the classical edge search. On the other hand, if all edges of a particular label form a (connected) subtree of the input tree, then we show that optimal heterogeneous search strategy can be computed efficiently.

  • Seasonal and spatial differences in metal and metalloid concentrations in the snow cover of Hansbreen, Svalbard
    • Krystyna Kozioł
    • Aleksander Uszczyk
    • Filip Pawlak
    • Marcin Frankowski
    • Żaneta Polkowska
    2021 Pełny tekst Frontiers in Earth Science

    Metals and metalloids in snow on glaciers, depending on the season of deposition, may come from various sources: local rock dust (erosion of the geological substratum), marine aerosol, local human activity (e.g. fuel combustion, waste incineration) and long-range atmospheric transport. Hansbreen glacier, located close to the Polish Polar Station in Svalbard, is a perfect site to study metals and metalloids: it has complex geological substratum, a year-round presence of a small group of people, and is near the coast. We analysed a snapshot of elemental concentrations in snow samples from shallow cores corresponding to autumn, winter and spring deposition on Hansbreen. Eighteen cores of snow were collected across the glacier, revealing the influence of potential local pollution sources. In these samples, we predominantly found Na, Mg and K, followed by Zn, Ca, Al and Fe. Heavy metals (Bi, Hg) were also detected. Cluster analysis of the determined elemental concentrations divided them into three distinct groups: 1) Ag, As, Bi, Cd, Hg, Mo, Sb, Se and Zn – representing mostly long-range transported volatile elements, with possible extra local geological sources; 2) Al, Fe, Cu and Mn – elements with crustal sources, and 3) Na, Ca, Mg, K and Sr – mainly from sea spray aerosol. Such interpretation was confirmed by the calculation of sea salt contribution based on mean seawater composition. In the study site, snow was up to six times more efficient in bringing metal and metalloid pollution into terrestrial environment, when comparared to rain.

  • Seaweed as a resource for Anaerobic Digestion
    • Iwona Cichowska-Kopczyńska
    • Robert Aranowski
    2021

    Extensive growth of algae contributes to disruptive changes to the water ecosystems. This is mainly caused by redundant nutrients that are washed off the land and end up in waters. Tackling eutrophication by recovery of nutrients can be a solution to the problem. Cast marine biomass can be a resource for renewable energy technologies like anaerobic digestion. Such approach can contribute to the transition to a circular bio-economy and to preserving recreational value of the area.

  • Seaweed utilization issues in biogas production
    • Robert Aranowski
    • Iwona Cichowska-Kopczyńska
    2021

    Macroalgae can be seen as a renewable feedstock for the production of biofuels in many coastal areas around the World and especially in Baltic Sea region where the eutrophication is particularly troublesome. The investigation of anaerobic digestion technologies for extracting inexhaustible bioenergy from seaweed was conducted in many research institutions mainly in laboratory scale. Although seaweeds seem to have a great potential as a feedstock in anaerobic digestion due to high biomass yields and lack of competition with terrestrial plants on limited agricultural land, their potentially high heavy metals content and other impurities (like sand and plastics) creates significant problems for the digestion process, but also for the further use of the digestate. Due to high levels of contaminants, it is not always possible to directly use the cast seaweed as a substrate for biogas production. The micro and macro elements uptake by algae strongly depends on factors as water salinity, characteristics of habitats (e.g. presence of an nearby industrial area or existence of an estuary whose waters might carry additional nutrient loads from urban and agriculture areas). The main limiting factor of a digestate utilisation as an organic fertiliser is the heavy metals concentration but the main process issues during anaerobic digestion are caused by the presence of sand in the feedstock. Collected seaweed biomass (especially from sandy beaches) very often contains sand, which can negatively effect the durability of bioreactors and other biogas plant equipment. Pre-treatment of the collected seaweed is essential for the anaerobic digestion process safety and efficient operation of the biogas plant. Furthermore, different stages of pre-treatment as well as the combination of pre-treatment methods can greatly increase the quality of the methane yield. Present study focuses on pre-treatment methods case reducing sand contents in seaweed feedstock.

  • Secure Italian domination in graphs
    • Magda Dettlaff
    • Magdalena Lemańska
    • Juan A. RODRíGUEZ-VELáZQUEZ
    2021 Pełny tekst JOURNAL OF COMBINATORIAL OPTIMIZATION

    An Italian dominating function (IDF) on a graph G is a function f:V(G)→{0,1,2} such that for every vertex v with f(v)=0, the total weight of f assigned to the neighbours of v is at least two, i.e., ∑u∈NG(v)f(u)≥2. For any function f:V(G)→{0,1,2} and any pair of adjacent vertices with f(v)=0 and u with f(u)>0, the function fu→v is defined by fu→v(v)=1, fu→v(u)=f(u)−1 and fu→v(x)=f(x) whenever x∈V(G)∖{u,v}. A secure Italian dominating function on a graph G is defined as an IDF f which satisfies that for every vertex v with f(v)=0, there exists a neighbour u with f(u)>0 such that fu→v is an IDF. The weight of f is ω(f)=∑v∈V(G)f(v). The minimum weight among all secure Italian dominating functions on G is the secure Italian domination number of G. This paper is devoted to initiating the study of the secure Italian domination number of a graph. In particular, we prove that the problem of finding this parameter is NP-hard and we obtain general bounds on it. Moreover, for certain classes of graphs, we obtain closed formulas for this novel parameter.

  • Segmentation Quality Refinement in Large-Scale Medical Image Dataset with Crowd-Sourced Annotations
    • Tomasz Dziubich
    • Jan Cychnerski
    2021

    Deployment of different techniques of deep learning including Convolutional Neural Networks (CNN) in image classification systems has accomplished outstanding results. However, the advantages and potential impact of such a system can be completely negated if it does not reach a target accuracy. To achieve high classification accuracy with low variance in medical image classification system, there is needed the large size of the training data set with suitable quality score. This paper presents a study on the use of various consistency checking methods to refine the quality of annotations. It is assumed that tagging was done by volunteers (crowd-sourcing model). The aim of this work was to evaluate the fitness of this approach in the medical field and the usefulness of our innovative web tool designed to facilitate large-scale annotation of magnetic resonance (MR) images, as well as the accuracy of crowd-source assessment using this tool, comparing to expert classification. We present the methodology followed to annotate the collection of kidney MR scans. All of the 156 images were acquired from the Medical University of Gdansk. Two groups of students (with and without medical educational background) and three nephrologists were engaged. This research supports the thesis that some types of MR image annotations provided by naive individuals are omparable to expert annotation, but this process could be shortened in time. Furthermore, it is more costeffective in the simultaneous preservation of image analysis accuracy. With pixel-wise majority voting, it was possible to create crowd-sourced organ segmentations that match the quality of those created by individual medical experts (mAP up to 94% +/-3.9%).

  • Segmented bio-based polyurethane composites containing powdered cellulose obtained from novel bio-based diisocyanate mixtures
    • Ewa Głowińska
    • Paulina Kasprzyk
    • Janusz Datta
    2021 Pełny tekst WOOD SCIENCE AND TECHNOLOGY

    A considerable number of research works focus on the positive influence of cellulose on the properties of polymer-based composites and their wide range of application possibilities. The present work is focused on the synthesis of novel bio-based polyurethane (bio-PU) composites filled with powdered cellulose (microcellulose, MC) in an amount of 5 wt.%. Bio-PU composites were synthesized via a non-solvent prepolymer method. First, the prepolymer was synthesized from diisocyanate mixture based on hexamethylene diisocyanate and bio-based polyisocyanate Tolonate™ X Flo 100 and α,ω-oligo(ethylene-butylene adipate)diol which contained cellulose. Then, resulted prepolymer was extended by bio-based 1,4 butanediol (bio-BDO). Bio-PU composites were obtained with the different [NCO]/[OH] molar ratios: 0.95, 1.0, 105 and 1.1. Special attention was paid to the influence of MC on the phase separation between soft and hard segments of bio-PU by studying the chemical structure, morphology and thermal and mechanical properties of the prepared cellulose-based composites.

  • Seismic damage diagnosis in adjacent steel and RC MRFs considering pounding effects through improved wavelet-based damage-sensitive feature
    • Benyamin Mohebi
    • Omid Yazdanpanah
    • Farzin Kazemi
    • Antonio Formisano
    2021 Journal of Building Engineering

    This paper aims to propose complex Morlet (cmorfb-fc) wavelet-based refined damage-sensitive feature (rDSF) as a new and more precise damage indicator to diagnose seismic damages in adjacent steel and Reinforced Concrete (RC) Moment Resisting Frames (MRFs) assuming pounding conditions using acceleration responses. The considered structures include 6- and 9-story steel and 4- and 8-story RC benchmark MRFs that are assumed to have different values of separation distances, δMT, calculated according to the ASCE 7-10 seismic provision. For the sake of pounding modelling, linear viscoelastic contact elements among the pounding structures are assumed. Furthermore, an algorithm is developed to compute the seismic collapse capacities of each pounding MRF through Incremental Dynamic Analyses (IDA) using OpenSees software. In the next step, auto-regressive movingaverage with exogenous input (ARX) model together with a stabilization diagram is utilized to appraise the natural frequencies of each adjacent MRF. Shannon entropies and correlation coefficient (ρ) are used to select the best cmorfb-fc wavelet. Based on the results, damage resulting from pounding effects can be accurately detected in both cases of with and without δMT, especially for steel MRFs.

  • Seismic Pounding Between Bridge Segments: A State-of-the-Art Review
    • Mahmoud Miari
    • Kok Choong
    • Robert Jankowski
    2021 ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING

    Earthquake-induced structural pounding in bridge structures has been observed in several previous seismic events. Collisions occur at the expansion joints provided between adjacent decks or between the deck and abutment. Pounding between the structural elements may lead to severe damages and even to the unseating of the bridge in certain cases. Several investigations have been performed to study pounding in bridges under uniform and non-uniform seismic excitations. Moreover, different mitigation measures have been suggested to overcome the drawbacks of this phenomenon. This work reviews previous research studies concerning earthquake-induced structural pounding in bridge structures, the factors that influence it and the recommended mitigation measures.

  • Selected Aspects of Pavement Texture Influence on Tire Rolling Resistance
    • Jerzy Ejsmont
    • Sławomir Sommer
    2021 Pełny tekst Coatings

    Tire rolling resistance has a significant influence on fuel consumption in cars and trucks and on CO2 emissions. Rolling resistance depends on the tire construction, pavement texture and stiffness, as well as environmental and traffic conditions. This article presents a pilot study on the impact of pavement texture on the rolling resistance of passenger car tires. Reasons why Mean Profile Depth is not a good descriptor of pavement characteristics from the point of view of rolling resistance are presented, and an experimental method which takes into account tire deformation on texture and partial enveloping is described. A method based on testing the volume and depth of tire tread deformation is also proposed.

  • Selected information technology tools supporting for maintenance and operation management electrical grids
    • Waldemar Kamrat
    2021 Pełny tekst Bulletin of the Polish Academy of Sciences-Technical Sciences

    The paper presents the main issues of management of electrical grids. Selected information technology tools supporting for electrical grids maintenance are presented. In electrical infrastructure maintenance of power companies the geographic information systems are increasingly used to support the management of theirs resources. Their functionalities in terms creating comprehensive databases for electrical infrastructure of power sector are described. The important information technology tools regarding spatial systems for supporting maintenance and operation management electrical grids and the conditions of their implementation are presented. This paper also attempts to innovative multidimensional evaluate the technical and economic benefits resulting from the use of modern information technology tools for the management of energy infrastructure.

  • Selected manufacturing difficulties encountered during setup of machining on cnc multi-axis linear automatic lathe and on cnc multi-spindle turning centers
    • Piotr Sender
    2021 Pełny tekst

    The article presents the observed manufacturing technology implementation difficulties in workshop practice, resulting from the construction and principles of operation on the DMG’s SPRINT 32/5 CNC linear automatic lathe and on the Mazak’s HQR 150 MSY and QTN 200 MS CNC turn - mill centers, and discusses possible rules for solving the production problems encountered. The article also discusses the principles of dividing the machining process and working steps on multi-spindle CNC turn - mill centers. It is worth to build a system supporting the selection of the sequence of treatments [1], taking into account the frequency of natural vibrations and stiffness obtained after each single machining operations. The article shows the method of verification of the selection of the machining planning method on CNC multi-spindle lathes.

  • Selected problems of decision making modelling in power engineering
    • Waldemar Kamrat
    2021 Pełny tekst Sustainable Energy Technologies and Assessments

    The paper presents the selected problems of decision making modelling in power engineering specially investment risk evaluation methods. The proposed model can be used in the range programming the development and investing process in power engineering. Decision making problems in power engineering and the evaluation of investment effectiveness in particular are closely related to modelling which relatively accurately reflects the complexity of market economy mechanisms. In order to analyze the phenomena mentioned above, models of existing processes, which are later used to achieve a set goal during decision making in a real situation, are applied. Its mathematical representation is a formalization of a model of a decision making task. A significant task in the whole process is to design a mathematical model, optimized by means of a goal function, whose arguments are decision variables meeting defined boundary conditions. Descriptions of decision making processes show that variables usually have non-negative values. Also the economic environment influences the quality of modelling. The dynamics of events causes that models of decision making processes can be analyzed. An attempt to take into account the influence of the factors mentioned above on the modelling of decision making in power engineering is presented in this paper.

  • Selection of an artificial pre-training neural network for the classification of inland vessels based on their images
    • Katarzyna Bobkowska
    • Izabela Bodus-olkowska Izabela
    2021 Pełny tekst Zeszyty Naukowe Akademii Morskiej w Szczecinie

    Artificial neural networks (ANN) are the most commonly used algorithms for image classification problems. An image classifier takes an image or video as input and classifies it into one of the possible categories that it was trained to identify. They are applied in various areas such as security, defense, healthcare, biology, forensics, communication, etc. There is no need to create one’s own ANN because there are several pre-trained networks already available. The aim of the SHREC projects (automatic ship recognition and identification) is to classify and identify the vessels based on images obtained from closed-circuit television (CCTV) cameras. For this purpose, a dataset of vessel images was collected during 2018, 2019, and 2020 video measurement campaigns. The authors of this article used three pre-trained neural networks, GoogLeNet, AlexNet, and SqeezeNet, to examine the classification possibility and assess its quality. About 8000 vessel images were used, which were categorized into seven categories: barge, special-purpose service ships, motor yachts with a motorboat, passenger ships, sailing yachts, kayaks, and others. A comparison of the results using neural networks to classify floating inland units is presented.

  • Selective monitoring of noise emitted by vehicles involved in road traffic
    • Andrzej Czyżewski
    • Tomasz Śmiałkowski
    2021 Pełny tekst Journal of the Acoustical Society of America

    An acoustic intensity probe was developed measures the sound intensity in three orthogonal directions, making possible to calculate the azimuth and elevation angles, describing the sound source position. The acoustic sensor is made in the form of a cube with a side of 10 mm, on the inner surfaces of which the digital MEMS microphones are mounted. The algorithm works in two stages. The first stage is based on the analysis of sound intensity signals, and it detects acoustic events. The second stage analyses a detection function based on the normalized source position; its task is to determine whether the acoustic event represents a vehicle passing the sensor and detecting its movement direction. The acoustic probes were mounted inside intelligent lamps that illuminate the roadways depending on the volume of traffic. The paper explains how accurately traffic can be monitored through directional noise analysis and shows the resulting application to smart cities.

  • Selenium enrichment in broccoli sprouts as an initial step in the preparation of Certified Reference Material
    • Chintankumar Padariya
    • Małgorzata Rutkowska
    • Piotr Konieczka
    2021 Pełny tekst

    Selenium is considered one of the essential elements in animals and humans. The main source of selenium intake for humans is the diet. Selenium deficiency has one of the most concerning issues worldwide. Broccoli sprouts are five-to-six-day old broccoli plants, and they may exhibit stronger chemoprotective effects. Thus, the enrichment of selenium in broccoli sprouts can enhance anticancer properties. As a result of conducted study, four batches of selenium enriched sprouts have been produced in order to verify the efficiency of selenium uptake by broccoli sprouts under commercial conditions. –1 Sodium selenite solution (10 mg L ) was used to prepare seleniumenriched broccoli sprouts. Sodium selenite is available for biological uptake by plants. The results might be different while the addition of sodium selenite in each step of the germination process could enhance the concentration of selenium in broccoli sprouts. Therefore, it could be potentially selected as a candidate for certified reference materials

  • Self Portrait with a Mask
    • Paweł Sasin
    2021 Pełny tekst Sztuka i Dokumentacja

    Paweł SASIN - Self Portrait with a Mask “Every work of art is the child of its time, and, in many cases, the mother of our emotions. “ Wassily Kandynsky, Concerning the Spiritual in Art The two years 2020 and 2021 were marked by the COVID-19 pandemic – a lengthy period of time in which everyone felt in danger of losing one’s health or life. As a result, many people were experiencing negative emotion, becoming subject to psychological stress: feeling anxious, fearful, frustrated, upset, depressed. In such situations, finding motivations to overcome these feelings is crucial and positive, as it helps people to overcome inactivity and achieve goals. During the phase of stress mobilization, one often experiences elevated efficiency of intellectual and cognitive processes: the ability to make associations and conceive unique ideas is enhanced, as well as one’s sensitivity to stimuli; which results in people accessing a greater range of their potential abilities (Frączek, Kofta, „Frustracja i stres psychologiczny”/ “Frustration and Psychological Stress”). What I am about to present is an attempt to address the question of the influence which the COVID-19 pandemic, as a socially challenging experience, may have had on the spontaneity and authenticity of creative imagination possessed by people studying architecture. Obligatory isolation, social distancing and other restraining regulations, dangers stemming from the infectious qualities of the disease, finally the huge number of gravely ill and deceased victims – those circumstance served as a trigger to ask architecture students at the Gdańsk University of Technology to create a piece on the topic Self Portrait with a Mask as part of their sculpture course.

  • Self-assembly of vertically oriented graphene nanostructures: multivariate characterisation by Minkowski functionals and fractal geometry
    • Mattia Pierpaoli
    • Mateusz Ficek
    • Paweł Jakóbczyk
    • Jakub Karczewski
    • Robert Bogdanowicz
    2021 Pełny tekst ACTA MATERIALIA

    The enormous self-assembly potential that graphene and its derived layered materials offer for responding to the contemporary environmental challenges has made it one of the most investigated materials. Hence, tuning its extraordinary properties and understanding the effect at all scales is crucial to tailoring highly customised electrodes. Vertically oriented graphene nanostructures, also known as carbon nanowalls (CNWs), due to the large surface area and unique maze-like morphology, have attracted attention as a platform for advanced sensing applications. In this work, a holistic investigation approach has been developed to disrupt the synthesis-composition-structure-property paradigm and to dig out the hidden materials relationships. To achieve that, autonomous advanced image-analysis methods (Minkowski Functionals, Fractal Analysis) have been applied to SEM micrographs and successfully classified them. Morphological, electrical, and electrochemical characterisation has been performed for all of the samples. Multivariate data analysis has been employed to mine the relationships between the material features, specifically as it relates to the understanding of the intrinsic properties. As a result, this study is intended to both shed light on CNWs as a promising transparent hybrid electrochemical substrate for perfectly assembled electrochemical devices and to provide a new flexible method for nanomaterial design, characterisation and exploitation.

  • Self-assembly, stability and conductance of amphotericin B channels: bridging the gap between structure and function
    • Joanna Zielińska
    • Miłosz Wieczór
    • Paweł Chodnicki
    • Ewa Grela
    • Rafał Luchowski
    • Łukasz Nierzwicki
    • Tomasz Bączek
    • Wiesław I. Gruszecki
    • Jacek Czub
    2021 NANOSCALE

    Amphotericin B (AmB), one of the most powerful but also toxic drugs used to treat systemic mycoses, is believed to selectively permeabilize fungal cell membranes to ions in a sterol-dependent manner. Unfortunately, the structure of the biologically active AmB channels has long eluded researchers, obstructing the design of safer alternatives. Here, we investigate the structural and thermodynamic aspects of channel formation, stability, and selective ion conduction. We combine fluorescence lifetime imaging and molecular simulations to trace the process of channel assembly until the formation of stable, roughly octameric double-length channels (DLCs). This stoichiometry is confirmed by matching the predicted channel conductances with the past results of patch-clamp measurements. We then use free energy calculations to explain the effect of sterols on DLC stability and discuss the observed cation selectivity in structural terms, addressing several long-standing controversies in the context of their physiological relevance. Simulations of ion permeation indicate that only solvated ions pass through DLCs, revealing surprising solvation patterns in the channel lumen. We conclude our investigation by inspecting the role of the tail hydroxyl in the assembly of functional channels, pointing at possible origins of the cholesterol–ergosterol selectivity.

  • Self-assessment of competencies of students and graduates participating in didactic projects – Case study
    • Małgorzata Gawrycka
    • Justyna Kujawska
    • Michał Tomczak
    2021 Pełny tekst International Review of Economics Education

    Aim/purpose: the aim of this article is to examine the opinions of students and graduates of the faculty of economics of a technical university as regards their selfassessment of their preparation for entering the modern labour market. All the respondents participated during their studies in didactic projects aimed at improving their competencies taking into account the expectations of potential employers. Design/methodology/approach: the study was quantitative in nature and was carried out using the CAWI method. In the analysis of the study results, elements of descriptive statistics were used, such as: mean measures, structure indicators, structure similarity indicators and tests for the significance of mean values. A comparative analysis was conducted between two groups of respondents – students and graduates. Findings: the conducted study shows that by organising additional training for students, the university contributes to supplementing their theoretical and practical knowledge in the area of competencies required by the labour market today, in particular within the scope of specialist and technical competencies which are becoming indispensable in the Economy 4.0. Research implications/limitations: due to the small size of the test sample, the results should be treated with caution, are not representative and constitute only a case study. Originality/value/contribution: the results of the research confirm the importance of lifelong learning as regards reducing the competence gap among university graduates. The tools used in the above-mentioned process include additional training activities, such as the presented didactic projects addressed to students, complementary to the curriculum of studies. They enabled the students to extend their competencies even before they left the walls of the university and, as a result, facilitated their entry into the labour market.

  • Self-employment of women: an opportunity or the last resort?
    • Dagmara Nikulin
    2021

    It is believed that automatization and technological changes will be the main drivers of work in the future. At the same time, there is a growing discussion about new forms of employment, such as self-employment. It may be either perceived as a chance for empowerment, through creating new job opportunities, that were not reachable previously, or as precarious work, with less stability, higher risk, and uncertain income. The main goal of this work is to analyze what makes women choose self-employment. Our cross-country study, conducted for 31 European countries based on 2014 European Labour Force Survey (LFS), brings a new perspective on the phenomenon. Our results suggest that self-employment may constitute an opportunity for women as higher level of skills and older age increase the probability of becoming self-employed. Moreover, as skilled people predominantly show greater skills related to the use of technology, one may conclude that the use of ICT may reinforce this form of work. On the other hand, self-employed women’s work is to a greater extent based on part-time arrangements and is frequently performed in the evenings. For this reason, it may be concluded that self-employment is an option for women who have to combine family life with work and have no chance to find typical paid employment.

  • Self-Organising map neural network in the analysis of electromyography data of muscles acting at temporomandibular joint.
    • Mateusz Troka
    • Wiktoria Wojnicz
    • Katarzyna Szepietowska
    • Izabela Lubowiecka
    2021

    The temporomandibular joint (TMJ) is the joint that via muscle action and jaw motion allows for necessary physiological performances such as mastication. Whereas mandible translates and rotates [1]. Estimation of activity of muscles acting at the TMJ provides a knowledge of activation pattern solely of a specific patient that an electromyography (EMG) examination was carried out [2]. In this work, a Self-Organising Maps (SOMs) based method was used to identify a hidden similarities in EMG data between different patients. Artificial Neural Network algorithm used for this work – Supervised Kohonen Network (SKN) was proposed and described in [3] and extended into a MATLAB toolbox by [4]. SKN algorithm was used to simulate the model, resulting in a chart called class profiles describing the calculated averages of the Kohonen weights of each variable. It shows how data similarity coming from different subjects is distributed. The obtained results let one to draw a conclusion about muscle significance during specific motion. This SOM based modelling method was intended to estimate TMJ instability and its muscle performance during jaw motions. The study was an attempt to identify and categorise patients with similarly possible disorders in TMJ area which can be evaluated from their muscles activation data.

  • Semantic segmentation training using imperfect annotations and loss masking
    • Adam Brzeski
    • Jan Cychnerski
    • Tomasz Dziubich
    • Tomasz Gilewicz
    • Jan Woś
    2021

    One of the most significant factors affecting supervised neural network training is the precision of the annotations. Also, in a case of expert group, the problem of inconsistent data annotations is an integral part of real-world supervised learning processes, well-known to researchers. One practical example is a weak ground truth delineation for medical image segmentation. In this paper, we have developed a new method of accurate segmentation of blood vessels based on a convolutional neural network. We focused on imperfect annotations for the semantic segmentation of blood vessels and introduced a concept of uncertainty masks and loss masking. These uncertainty masks can be created roughly by non-experts, which makes annotation process cheaper and faster. Quantitative results of our method on a real-world problem with missing annotations and on a perfectly labeled data set with artificially introduced noise are presented. Models trained with loss masking seem to be more robust regardless of the number of removed vessels. Noise robustness of four different model architectures has been tested and compared to the loss masking method, which turned out to have better performance during training on noisy data

  • SENSITIVITY ANALYSIS IN THE REHABILITATION OF HISTORIC TIMBER STRUCTURES ON THE EXAMPLES OF GREEK CATHOLIC CHURCHES IN POLISH SUBCARPATHIA
    • Katarzyna Szepietowska
    • Izabela Lubowiecka
    2021

    This work concerns structural and sensitivity analysis of carpentry joints used in historic wooden buildings in south-eastern Poland and western Ukraine. These are primarily sacred buildings and the types of joints characteristic for this region are saddle notch and dovetail joints. Thus, in the study the authors focus on these types of corner log joints. Numerical models of the joints are defined and finite element simulations of their statics are carried out. Moreover, a sensitivity analysis is performed in order to describe how the uncertainty of material properties including humidity of some structural members, caused during potential repairs, affect the structural behaviour of the whole connection. This represents the situation when some degraded logs are exchanged into new wood combining old, and often damp, wood with new and dry logs. A non-intrusive probabilistic approach to the sensitivity analysis is applied and regression-based Polynomial Chaos (PC) expansion method is used to propagate uncertainties.

  • Sensors and Sensor’s Fusion in Autonomous Vehicles
    • Andrzej Stateczny
    • Marta Wlodarczyk-Sielicka
    • Paweł Burdziakowski
    2021 Pełny tekst SENSORS

    Autonomous vehicle navigation has been at the center of several major developments, both in civilian and defense applications. New technologies such as multisensory data fusion, big data processing, and deep learning are changing the quality of areas of applications, improving the sensors and systems used. New ideas such as 3D radar, 3D sonar, LiDAR, and others are based on autonomous vehicle revolutionary development. The Special Issue entitled “Sensors and Sensor’s Fusion in Autonomous Vehicles” was focused on many aspects of autonomous vehicle sensors and their fusion, such as autonomous navigation, multi-sensor fusion, big data processing for autonomous vehicle navigation, sensors related to science/research, algorithms/technical development, analysis tools, synergy with sensors in navigation, and artificial intelligence methods for autonomous vehicle navigation.

  • Sequence-dependent structural properties of B-DNA: what have we learned in 40 years?
    • Gabriela da Rosa
    • Leandro Grille
    • Victoria Calzada
    • Katya Ahmad
    • Juan Pablo Arcon
    • Federica Battistini
    • Genís Bayarri
    • Thomas Bishop
    • Paolo Carloni
    • Thomas Cheatham III
    • Rosana Collepardo-Guevara
    • Jacek Czub
    • Jorge R. Espinosa
    • Rodrigo Galindo-Murillo
    • Sarah A. Harris
    • Adam Hospital
    • Charles Laughton
    • John H. Maddocks
    • Agnes Noy
    • Modesto Orozco
    • Marco Pasi
    • Alberto Pérez
    • Daiva Petkevičiūtė-Gerlach
    • Rahul Sharma
    • Ran Sun
    • Pablo D. Dans
    2021 Pełny tekst Biophysical Reviews

    The structure of B-DNA, the physiological form of the DNA molecule, has been a central topic in biology, chemistry and physics. Far from uniform and rigid, the double helix was revealed as a flexible and structurally polymorphic molecule. Conformational changes that lead to local and global changes in the helix geometry are mediated by a complex choreography of base and backbone rearrangements affecting the ability of the B-DNA to recognize ligands and consequently on its functionality. In this sense, the knowledge obtained from the sequence-dependent structural properties of B-DNA has always been thought crucial to rationalize how ligands and, most notably, proteins recognize B-DNA and modulate its activity, i.e. the structural basis of gene regulation. Honouring the anniversary of the first high-resolution X-ray structure of a B-DNA molecule, in this contribution, we present the most important discoveries of the last 40 years on the sequence-dependent structural and dynamical properties of B-DNA, from the early beginnings to the current frontiers in the field.

  • Series-Slot-Fed Circularly Polarized Multiple-Input-Multiple-Output Antenna Array Enabling Circular Polarization Diversity for 5G 28-GHz Indoor Applications
    • Ubaid Ullah
    • Muath Al-hasan
    • Ismail Mabrouk
    • Sławomir Kozieł
    2021 Pełny tekst IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION

    In this paper, a four-element circularly polarized series-slot-fed multiple-input-multiple-output (MIMO) antenna array with circular polarization diversity is presented. The proposed design utilizes a combination of 45-degree inclined slots and a straight microstrip line feeding technique. The two antennas are designed to operate with the opposite sense of circular polarization (CP). CP is achieved by placing a patch of just about square dimensions on the top of the V-slot with orthogonal but unequal arms. The unequal arm of the slot degenerates the fundamental mode at a slightly different frequency with 90-degree phase difference occurring at the center frequency of each arm. Proper positioning of the patch on the top of the slot ensures excitation of CP. For realizing a MIMO antenna with different sense of polarization, both the slots and the patches are flipped with respect to the feedline. Following optimization at the full-wave level of description, the antenna is prototyped and validated experimentally. The realizable antenna footprint is 20 mm × 27.7 mm. The simulated and measured results indicate that the proposed antenna features a wide impedance bandwidth (|S11|<-10 dB) from 26.9 GHz to 30.7 GHz, 3 dB axial ratio bandwidth from 27.31 GHz to 29.65 GHz and the peak realized gain of 11.86 dBic. Moreover, it exhibits a low level of in-band isolation |S21|>-37 dB and almost negligible envelope correlation coefficient (ECC), less than 0.00025. The highly directional beams, high gain and compact size of the proposed antenna permit implementation of multiple antennas for indoor applications in the 28-GHz band.

  • Serotonergic–Muscarinic Interaction within the Prefrontal Cortex as a Novel Target to Reverse Schizophrenia-Related Cognitive Symptoms
    • Paulina Cieślik
    • Adrianna Radulska
    • Grzegorz Burnat
    • Leszek Kalinowski
    • Joanna M. Wierońska
    2021 Pełny tekst INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

    Recent studies revealed that the activation of serotonergic 5-HT1A and muscarinic M1, M4, or M5 receptors prevent MK-801-induced cognitive impairments in animal models. In the present study, the effectiveness of the simultaneous activation of 5-HT1A and muscarinic receptors at preventing MK-801-induced cognitive deficits in novel object recognition (NOR) or Y-maze tests was investigated. Activators of 5-HT1A (F15599), M1 (VU0357017), M4 (VU0152100), or M5 (VU0238429) receptors administered at top doses for seven days reversed MK-801-induced deficits in the NOR test, similar to the simultaneous administration of subeffective doses of F15599 (0.05 mg/kg) with VU0357017 (0.15 mg/kg), VU0152100 (0.05 mg/kg), or VU0238429 (1 mg/kg). The compounds did not prevent the MK-801-induced impairment when administered acutely. Their activity was less evident in the Y-maze. Pharmacokinetic studies revealed high brain penetration of F15599 (brain/plasma ratio 620%), which was detected in the frontal cortex (FC) up to 2 h after administration. Decreases in the brain penetration properties of the compounds were observed after acute administration of the combinations, which might have influenced behavioral responses. This negative effect on brain penetration was not observed when the compounds were administered repeatedly. Based on our results, prolonged administration of a 5-HT1A activator with muscarinic receptor ligands may be effective at reversing cognitive decline related to schizophrenia, and the FC may play a critical role in this interaction.

  • Service-based Resilience via Shared Protection in Mission-critical Embedded Networks
    • Doganalp Ergenc
    • Jacek Rak
    • Mathias Fischer
    2021 Pełny tekst IEEE Transactions on Network and Service Management

    Mission-critical networks, which for example can be found in autonomous cars and avionics, are complex systems with a multitude of interconnected embedded nodes and various service demands. Their resilience against failures and attacks is a crucial property and has to be already considered in their design phase. In this paper, we introduce a novel approach for optimal joint service allocation and routing, leveraging virtualized embedded devices and shared backup capacity for the fault-tolerant design of mission-critical networks. This approach operates in phases utilizing multiple optimization models. Furthermore, we propose a new heuristic that ensures resource efficiency and fault-tolerance against single node and link failures as pre-requisite for resilience. Our experiments for different application scenarios indicate that our heuristic achieves results close to the optimum and provides 50% of capacity gain compared to a dedicated capacity protection scheme. Moreover, our heuristic ensures fault-tolerance against at least 90% of all potential single node failures.

  • Seven Different Lighting Conditions in Photogrammetric Studies of a 3D Urban Mock-Up
    • Katarzyna Bobkowska
    • Paweł Burdziakowski
    • Jakub Szulwic
    • Karolina Zielińska-Dąbkowska
    2021 Pełny tekst ENERGIES

    One of the most important elements during photogrammetric studies is the appropriate lighting of the object or area under investigation. Nevertheless, the concept of “adequate lighting” is relative. Therefore, we have attempted, based on experimental proof of concept (technology readiness level—TRL3), to verify the impact of various types of lighting emitted by LED light sources for scene illumination and their direct influence on the quality of the photogrammetric study of a 3D urban mock-up. An important issue in this study was the measurement and evaluation of the artificial light sources used, based on illuminance (E), correlated colour temperature (CCT), colour rendering index (CRI) and Spectral power distribution (SPD) and the evaluation of the obtained point clouds (seven photogrammetric products of the same object, developed for seven different lighting conditions). The general values of the quality of the photogrammetric studies were compared. Additionally, we determined seventeen features concerning the group of tie-points in the vicinity of each F-point and the type of study. The acquired traits were related to the number of tie-points in the vicinity, their luminosities and spectral characteristics for each of the colours (red, green, blue). The dependencies between the identified features and the obtained XYZ total error were verified, and the possibility of detecting F-points depending on their luminosity was also analysed. The obtained results can be important in the process of developing a photogrammetric method of urban lighting monitoring or in selecting additional lighting for objects that are the subject of a short-range photogrammetric study.

  • Shadow Economy in Poland Recent Evidence Based on Survey Data
    • Dagmara Nikulin
    • Ewa Lechman
    2021

    The book provides an estimate of the size of the shadow economy in Poland. Using analogous data, it traces core determinants of the existence of the shadow economy in Poland. It compares results with neighbouring countries, and if possible, the remaining Central-Eastern economies. The book tells why the problem of the unreported economic activity matters; it presents the problem from different angles―economic, social and institutional. Next, it extensively reviews past research on the size and determinants of the shadow economy in Poland. It discusses available resources and empirical results showing the problem from micro-, and macroeconomic perspective. The authors present the methods used and the results of the survey, which are interpreted and discussed Finally it concludes on major drivers of shadow economy in Poland, providing recommendations and future research directions. The book is intended for practitioners and those seeking understanding of undeclared economic activities.

  • Shaft friction from the DMT and direct shear interface tests
    • Kamila Mikina
    • Jakub Konkol
    • Lech Bałachowski
    2021

    The article presents preliminary attempt to create tri-linear transfer curves for describing pile behaviour under axial loading. Transfer curves would use the parameter measured in dilatometer test, particularly a constrained modulus MDMT. The proposed method is based on concrete rough and smooth interface tests performed in a direct shear apparatus. Based on the obtained mobilization curves, relationships were created between the parameters describing the slope of individual transfer curves and the MDMT modulus. The obtained correlations were used to estimate the capacity of the concrete screw pile subjected to the static load test in tension.

  • Shape and force control of cable structures with minimal actuators and actuation
    • Najmadeen Saeed
    • Ahmed Manguri
    • Abubakr Adabar
    2021 International Journal of Space Structures

    Shape adjustment and stress control can be considered as one of the effective parameters in prestressed cable structures since such structures are widely constructed nowadays due to their characteristics. The assembly errors and applied loads hugely affect the cables’ nodal positions and stress due to their delicacy. The former could disturb the shape, which affects the appearance and the function of the structure. In contrast, the latter may increase the stress in some cables above the upper limit or induce slack in some others. Accordingly, a technique has been proposed that combined fmincon optimization that relies on four different algorithms with a controlling approach based on the force method. The presented method aims to minimize the total amount of actuation and miniaturize the number of actuators. The targets of previously confirmed techniques can be obtained with less actuation and fewer actuators by using the current technique. Based on the verified examples, the advantage of the current approach over the quoted methods is up to 55% and 37% in terms of the number of actuators and the total amount of actuation, respectively.

  • Shape Memory Materials from Rubbers
    • Arunima Reghunadhan
    • Paduvilan Jibin
    • Vayyaprontavida Kaliyathan
    • Prajitha Velayudhan
    • Michał Strankowski
    • Sabu Thomas
    2021 Pełny tekst Materials

    Smart materials are much discussed in the current research scenario. The shape memory effect is one of the most fascinating occurrences in smart materials, both in terms of the phenomenon and its applications. Many metal alloys and polymers exhibit the shape memory effect (SME). Shape memory properties of elastomers, such as rubbers, polyurethanes, and other elastomers, are discussed in depth in this paper. The theory, factors impacting, and key uses of SME elastomers are all covered in this article. SME has been observed in a variety of elastomers and composites. Shape fixity and recovery rate are normally analysed through thermomechanical cycle studies to understand the effectiveness of SMEs. Polymer properties such as chain length, and the inclusion of fillers, such as clays, nanoparticles, and second phase polymers, will have a direct influence on the shape memory effect. The article discusses these aspects in a simple and concise manner.

  • Shape-Memory Polyurethane Polymers
    • Michał Strankowski
    • Paul Anju
    • Arunima Reghunadhan
    2021 Pełny tekst ACS SYMPOSIUM SERIES

    Polyurethanes (PUs) are one of the most widely used polymers in research and industry. They can be synthesized from chemical sources and natural sources. PUs are a very useful class of polymers and exhibit many desirable properties that can be exploited in various applications. PUs are formed by the reaction between polyols and isocyanates. A wide variety of polyols and isocyanates are available for synthesis, and hence we can produce a large number of PUs. PUs show high mechanical strength, chemical resistance, flexibility, and resilience. One of the major advantages of some specially designed PUs is their ability to recover their primary shape, which is known as shape memory. The shape-memory effect (SME) of PUs makes them popular in biomedical, electronic, and thermal applications. The SME can be monitored using different measures such as shape fixity, recovery time, and recovery rate. Various stimuli are applied to shape-memory materials to induce shape memory. PU polymers can be modified with different nanofillers, and these fillers influence the shape-recovery parameters. PU composites are popular because of a good property–price relationship. This chapter discusses the various factors affecting the SME of PU composites and the effect of different types of fillers on the PU matrix.

  • Shaping the City Responding to Climate Change – Concept of Development of the Right Bank of the Vistula River in Toruń, Poland,
    • Sylwia Sitniewska
    • Justyna Borucka
    2021

    The problems of cities of the 21st century are caused by anthropogenic oppression of the environment, through the growth of economic activity and continuous urbanisation, and taking away ecologically important open areas and biologically active areas. Increasingly frequent and sudden rains, strong winds, turbulence and rising world water levels are some of the consequences of climate change that have a direct impact on the functioning of cities. The article presents a study of a land-use plan for the right bank of the Vistula river in Toruń, Poland, in reference to ongoing climate change. The authors focus on the main assumption of this concept, which is to protect the area from increasing river floods expected due to strong climate change impact on Earth’s water cycle and temporary river water rise. The project strategy focussed on reshaping the Vistula river bank, as well as designing a solution that would allow floodwater to enter the area in a controlled manner. The newly designed area presented in the article is an attempt at conscious urban planning as well as planning activities in harmony with nature, and shows how such an approach to city planning can face the problems of climate change and could be a possible solution for future development of the city of Toruń.

  • Shear band evolution phenomena in direct shear test modelled with DEM.
    • Michał Nitka
    • Aleksander Grabowski
    2021 Pełny tekst POWDER TECHNOLOGY

    A direct shear test is widely used in the geotechnical engineering field. It is an easy and quick test to measure the shear properties of soil. This test often replaces more expensive and difficult tri-axial shear test. Despite that the direct shear test is known and used for a long time, it is still not well investigated at the grain scale. This paper deals with the micro behaviour of the cohesionless sand inside the direct shear box during a geotechnical test. Numerical calculations were performed with open-source discrete code YADE. The full 3D model was used, in order to eliminate some non-physical phenomena. The numerical stress-strain curve was directly compared with the laboratory results and good agreement was obtained. The focus was on the shape of the localized zone, the properties of this zone and its behaviour. The movement of the individual grains was studied. In our analysis, the stresses were also taken into consideration. The conclusions were validated on tests with different initial void ratio (dense or loose material) and with different vertical pressure.

  • Shear fracture of longitudinally reinforced concrete beams under bending using Digital Image Correlation and FE simulations with concrete micro-structure based on X-ray micro-computed tomography images
    • Łukasz Skarżyński
    • Ireneusz Marzec
    2021 Pełny tekst CONSTRUCTION AND BUILDING MATERIALS

    The paper presents experimental and numerical investigations of the shear fracture in rectangular concrete beams longitudinally reinforced with steel or basalt bar under quasi-static three point bending. Shear fracture process zone formation and development on the surface of beams was investigated by Digital Image Correlation (DIC) whereas thorough analyses of 3D material micro-structure, air voids, width and curvature of shear cracking were carried out by X-ray micro-computed tomography (micro-CT). Moreover, the 2D shear fracture patterns in beams were numerically simulated with the finite element method (FEM) using isotropic coupled elasto-plastic-damage constitutive model for concrete enhanced by a characteristic length of micro-structure. Concrete meso-structure was modelled as a random heterogeneous four-phase material composed of aggregate particles, cement matrix, ITZ zones and air voids on the basis of X-ray micro-CT images. Experimental and numerical results revealed a satisfactory agreement regarding to the mechanism of failure, load-bearing capacity as well as cracking pattern.

  • Short-Term Price Reaction to Filing for Bankruptcy and Restructuring Proceedings—The Case of Poland
    • Błażej Prusak
    • Marcin Potrykus
    2021 Pełny tekst Risks

    This study aims to check market reaction to filing for bankruptcy and restructuring proceedings and to verify the short-term effect of a price reversal in the Polish market in the years 2004–2019. The research was conducted by dividing the analysed companies according to the procedure (bankruptcy and restructuring) and market (the main market and the NewConnect market). The research methodology used in the study is the event analysis method (AR, CAR, AAR and CAAR rates were used in the research), with a few statistical tests (T-test, Generalized rank Z Test, Gen-eralized rank T-Test, Patell or Standardized Residual Test, Kolari and Pynnönen adjusted Patell or Standardized Residual Test). It was found that share prices in the Polish share market react quickly to public information about filing an application for bankruptcy or restructuring. For all analysed companies, the mean rate of return on the event day was equal to −14%, and on the next day, it was −3%. Regardless of the type of share market and the form of proceedings, the reversal effect was not confirmed in the short term. It was found that cumulative above-average rates of return fall more strongly for companies listed on the less liquid Newconnect market (−23.6%), and when information on the filing for bankruptcy proceedings is provided (−28.5%), as opposed to the main market (−19.1%) and restructuring proceedings (−17%). The cumulative average rate of return for all analysed companies in the research period (−2, +10 days) was equal to −20.6%.

  • Siderofory bakteryjne – rola w patogenezie i potencjał wykorzystania w diagnostyce
    • Beata Krawczyk
    • Aleksandra Rosińska
    2021 Pełny tekst

    Do prawidłowego funkcjonowania i wzrostu organizmów żywych zarówno ludzi, jak i bakterii niezbędne jest żelazo. Mikroelement ten występuje na dwóch różnych stopniach utlenienia: jako jon żelazawy (Fe2+) rozpuszczalny w roztworach fizjolo-gicznych oraz jako jon żelazowy (Fe3+), który nie tworzy roztworów wodnych [1]. Dzięki swoim właściwościom oksydo-redukcyjnym, żelazo wpływa na poprawne funkcjonowanie bardzo licznej grupy enzymów, m.in. cytochromów, oksydoreduktaz NADH-CoQ10, oksydoreduktazy bursztynianu-CoQ10. Enzymy te biorą udział w ważnych dla życia procesach metabolicznych, w czasie których produkowane są cząsteczki ATP. Bez udziału żelaza niemożliwe jest oddychanie. Żelazo wchodzi w skład hemoglobiny – białka transportującego tlen z płuc do wszystkich komórek w ludzkim organizmie. Ponadto bierze udział w neurogenezie, różnicowaniu komórek mózgu oraz jest kofaktorem licznych enzymów uczestniczących w syntezie neuro-przekaźników. W sytuacji niedoboru żelaza odpowiedź układu odpornościowego jest bardzo osłabiona [1, 2]. W komórkach bakteryjnych rola tego pierwiastka jest równie istotna i opiera się na zdolności jonów żelaza do utleniania i redukcji. Enzymy redoks znajdują się w cytozolu lub związane są z błoną komórkową, a jednym z ważniejszych jest reduktaza rybo-nukleotydowa – kluczowy enzym w procesie syntezy DNA. Ponadto jon żelazowy często jest końcowym akceptorem elektronów w łańcuchu oddechowym bakterii beztlenowych [3]. Do prawidłowego funkcjonowania i wzrostu komórka bakteryjna wymaga 10-7 M wolnych jonów żelazowych. W organizmie żywiciela bakteria musi zmierzyć się z bardzo ograniczonym dostępem do tego kluczowego pierwiastka. Większość komórko-wego żelaza gospodarza jest związana z jego białkami, a stężenie wolnych jonów żelaza we krwi jest o wiele za niskie do swobodnej dyfuzji. Aby zaspokoić zapotrzebowanie na ten mikroelement, mikroorganizmy produkują siderofory, czyli różnorodne che-micznie cząsteczki chelatujące jony i rozpoczynają konkurencję z gospodarzem o do-stępną pulę żelaza [3].

  • Sieci neuronowe oparte na prawach fizyki
    • Marek Moszyński
    • Bartłomiej Borzyszkowski
    • Karol Damaszke
    • Jakub Romankiewicz
    • Marcin Świniarski
    2021

    Wiele fizycznie nieuzasadnionych sieci neuronowych, mimo zadowalają- cej wydajności, generuje sprzeczności z logiką i prowadzi do rozbieżno- ści wyników z rzeczywistością. Jedną z metod poprawy funkcjonowania typowego modelu typu “black-box” na etapie uczenia, jest rozszerzenie jego funkcji kosztu o zależność bezpośrednio inspirowaną wzorem fizycz- nym. Niniejszy rozdział wyjaśnia koncepcję budowy sieci neuronowych opartych na prawach fizyki, zawiera przegląd zaproponowanych rozwią- zań w tej dziedzinie oraz opisuje możliwości implementacji funkcji strat wykorzystujących wzory fizyczne. Ponadto przedstawione badania poka- zują, że przewidywania algorytmów inspirowanych przez fizykę mogą być nie tylko optymalne, ale również naukowo spójne z równaniami dziedzi- nowymi. Ostatecznie wykorzystanie wiedzy naukowej zawartej w dosto- sowanych funkcjach kosztów pokazuje, że metodyka ta gwarantuje wy- niki spójne z prawami fizyki, a także lepszą generalizację w porównaniu z klasycznymi sieciami neuronowymi.

  • Signal Propagation in Electromagnetic Media Modelled by the Two-Sided Fractional Derivative
    • Jacek Gulgowski
    • Dariusz Kwiatkowski
    • Tomasz Stefański
    2021 Pełny tekst Fractal and Fractional

    In this paper, wave propagation is considered in a medium described by a fractional-order model, which is formulated with the use of the two-sided fractional derivative of Ortigueira and Machado. Although the relation of the derivative to causality is clearly specified in its definition, there is no obvious relation between causality of the derivative and causality of the transfer function induced by this derivative. Hence, causality of the system is investigated; its output is an electromagnetic signal propagating in media described by the time-domain two-sided fractional derivative. It is demonstrated that, for the derivative order in the range [1,+∞), the transfer function describing attenuated signal propagation is not causal for any value of the asymmetry parameter of the derivative. On the other hand, it is shown that, for derivative orders in the range (0,1), the transfer function is causal if and only if the asymmetry parameter is equal to certain specific values corresponding to the left-sided Grünwald–Letnikov derivative. The results are illustrated by numerical simulations and analyses. Some comments on the Kramers–Krönig relations for logarithm of the transfer function are presented as well.

  • Significant Production of Thermal Energy in Partially Ionized Hyperbolic Tangent Material Based on Ternary Hybrid Nanomaterials
    • Umar Nazir
    • Muhammas Sohail
    • Muhammad Bilal Hafeez
    • Marek Krawczuk
    2021 Pełny tekst ENERGIES

    Nanoparticles are frequently used to enhance the thermal performance of numerous materials. This study has many practical applications for activities that have to minimize losses of energy due to several impacts. This study investigates the inclusion of ternary hybrid nanoparticles in a partially ionized hyperbolic tangent liquid passed over a stretched melting surface. The fluid motion equation is presented by considering the rotation effect. The thermal energy expression is derived by the contribution of Joule heat and viscous dissipation. Flow equations were modeled by using the concept of boundary layer theory, which occurs in the form of a coupled system of partial differential equations (PDEs). To reduce the complexity, the derived PDEs (partial differential equations) were transformed into a set of ordinary differential equations (ODEs) by engaging in similarity transformations. Afterwards, the converted ODEs were handled via a finite element procedure. The utilization and effectiveness of the methodology are demonstrated by listing the mesh-free survey and comparative analysis. Several important graphs were prepared to show the contribution of emerging parameters on fluid velocity and temperature profile. The findings show that the finite element method is a powerful tool for handling the complex coupled ordinary differential equation system, arising in fluid mechanics and other related dissipation applications in applied science. Furthermore, enhancements in the Forchheimer parameter and the Weissenberg number are necessary to control the fluid velocity

  • Similarities and differences in the production of renewable energy in Central and Eastern Europe countries
    • Agnieszka Wałachowska
    2021

    Research background: In the era of climate change, environmental degradation, but also growing pub-lic awareness, there is a need to look for new ecological energy sources. This condition can be met by renewable energy sources (RES). The EU seeks to have a 32% share of its gross final energy consumption from renewable sources by 2030. While the EU as a whole is on course to meet its tar-gets, the question is if production of renewable energy at a given level is not a chal-lenge for selected Central and Eastern Europe countries (CEECs) trsdi-tionslly dependent on fossil fuels. In order to take steps to develop RES in the studied countries, there is a need to analyze their diversity in terms of the potential. The results of such analyses should support the implementation of adopted strate-gies. Purpose of the article: The article divides the CEECs into similar groups by the structure and volume of energy production from RES. This production was com-pared with the value of Gross Domestic Product (GDP) of each studied country, the number of in-habitants and its area. Methods: Cluster analysis. The research based on the data provided by Euro-stat. Findings & Value added: The division of the studied region into subgroups de-pends on how the RES energy production is related to the GDP value, the number of inhabitants and the area of individual country. This reference allows to reflect the specificity of individual countries in more appropriate way than just an analysis of the absolute values of this production. The applied approach allows for a broad-er look at RES production for selected countries in the region. The obtained results can be used for the development of a common energy and climate policy to create and develop their own renewable energy markets.