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Gdańsk University of Technology

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Publications from the year 2020

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  • Cząsteczki mikroRNA - nowy biologicznie aktywny składnik mleka kobiecego
    • Patrycja Jakubek
    • Joanna Cieślewicz
    • Agnieszka Bartoszek-Pączkowska
    2020 Full text Postępy Higieny i Medycyny Doświadczalnej

    Cząsteczki mikroRNA są krótkimi, niekodującymi oligonukleotydami odpowiadającymi za potranskrypcyjną regulację ekspresji genów. W wyniku ich aktywności kontrolowanych jest wiele procesów komórkowych oraz szlaków sygnalizacyjnych. Od 2010 roku wiadomo, że wchodzą one w skład mleka kobiecego, które obecnie uznaje się za jedno z najbogatszych pokarmowych źródeł mikroRNA. Funkcje tych cząsteczek w organizmie karmionego mlekiem matki dziecka są związane z kształtowaniem się układu odpornościowego, wzrostem i prawidłowym rozwojem. Wykazano, że cząsteczki mikroRNA pochodzące z mleka kobiecego są stabilne w warunkach in vitro symulujących trawienie w przewodzie pokarmowym niemowlęcia oraz mogą podlegać wchłanianiu przez enterocyty, przez co stanowią potencjalnie bioaktywny składnik mleka kobiecego sprzyjający rozwojowi niemowląt karmionych piersią. Ochronę przed degradacją w wyniku działania RNaz bądź niskiego pH zapewnia otoczka egzosomów, które stanowią nośnik mikroRNA we frakcji odtłuszczonej mleka, natomiast we frakcji lipidowej i komórkowej funkcję tę przypisuje się koloidalnym skupiskom pęcherzyków, zwanych kuleczkami tłuszczowymi, oraz laktocytom. W przeciwieństwie do mleka matki, sztuczne mieszanki mlekozastępcze zawierają tylko nieliczne cząsteczki mikroRNA – co więcej – wywodzące się od innych organizmów. Można przypuszczać, że dodatek krótkich RNA o sekwencjach identycznych z mikroRNA występującymi naturalnie w mleku kobiecym do preparatów do karmienia zastępczego niemowląt może stać się nowym, ważnym składnikiem mieszanek mlekozastępczych.

  • Czy komputer może zrobić błąd rachunkowy?
    • Joanna Raczek
    2020 Programista Junior

    W szkole błędy rachunkowe nie są mile widziane, w dodatku zazwyczaj nie wolno na lekcjach matematyki używać kalkulatorów. Jaka szkoda! Przecież kalkulator nigdy się nie myli! Ale czy na pewno?

  • Czy stan oznakowania dróg samorządowych ma wpływ na bezpieczeństwo ruchu drogowego?
    • Olga Białczak- Koprowska
    • Alicja Gardocka
    • Joanna Wachnicka
    2020 Drogownictwo

    Głównym celem artykułu była analiza stanu oznakowania dróg wojewódzkich oraz bezpieczeństwa ruchu drogowego na dwóch drogach wojewódzkich zlokalizowanych w województwie pomorskim, na których nastąpił wzrost wypadków w latach 2015-2017 w stosunku do lat 2012-2014. Badanie rozpoczęto od przeanalizowania stanu bezpieczeństwa ruchu drogowego bazując na danych o wypadkach. Następnie udano się na wizję lokalną, gdzie za pomocą oględzin sprawdzono stan oznakowania pionowego i poziomego. Podczas badania sprawdzono aktualny stan techniczny oznakowania, widoczność znaków, prawidłowość oznakowania oraz jego wpływ na bezpieczeństwo ruchu. Zwrócono także uwagę na stan techniczny jezdni oraz otoczenie wokół drogi. Zbadano odcinek biegnący od okolic miejscowości Babidół do okolic miejscowości Piekło Dolne na drodze wojewódzkiej 221 oraz odcinek biegnący od miejscowości Mierzeszyn do miejscowości Horniki Dolne na drodze 226. Głównym problemem na przeanalizowanych odcinkach drogi wojewódzkiej 221 i 226 była niedostateczna szerokość jezdni, która jest niedostosowana do natężenia ruchu panującego na analizowanym odcinku. Szerokość jezdni nie uwzględnia ruchu pieszych, całe pobocze przysłaniają korony drzew rosnące przy drodze, jednocześnie zasłaniają one także znaki pionowe. Oznakowanie pionowe i poziome przed zakrętami na drodze wojewódzkiej nr 226 w ogóle nie występuje, natomiast na drodze wojewódzkiej nr 221 i 227 oznakowanie poziome jest nieczytelne i wytarte, a oznakowanie pionowe jest zbyt późno. Na drodze wojewódzkiej nr 221 występują odcinki dróg na których mamy nagromadzenie znaków drogowych, natomiast na drodze wojewódzkiej nr 226 mamy sytuację skrajną pokazującą ewidentne braki w oznakowaniu szczególnie poziomym. Na zbadanych odcinkach dróg wojewódzkich przejścia są zaniedbane oraz niewidoczne z punktu widzenia kierowcy. Podczas badań odcinków wybranych dróg wojewódzkich zauważono, że oznakowanie pionowe jest nieczytelne, stare oraz zniszczone. 40% oznakowania pionowego nie posiada naklejek identyfikujących ze znakiem producenta, rokiem produkcji i typem folii odblaskowej. W złym stanie są również słupki hektometryczne, które w warunkach nocnych są niezbędne do wyznaczania geometrii drogi. Są one brudne, nieczytelne, porośnięte roślinnością oraz ścięte- prawdopodobnie po zdarzeniach drogowych. Znacznie gorzej jest z oznakowaniem poziomym, którego nie ma w ogóle lub jest ono niewidoczne.

  • Data Acquisition and Processing for GeoAI Models to Support Sustainable Agricultural Practices
    • Agustin Garcia Pereira
    • Adegboyega Ojo
    • Curry Edward
    • Lukasz Porwol
    2020 Full text

    There are growing opportunities to leverage new technologies and data sources to address global problems related to sustainability, climate change, and biodiversity loss. The emerging discipline of GeoAI resulting from the convergence of AI and Geospatial science (Geo-AI) is enabling the possibility to harness the increasingly available open Earth Observation data collected from different constellations of satellites and sensors with high spatial, spectral and temporal resolutions. However, transforming these raw data into high-quality datasets that could be used for training AI and specifically deep learning models are technically challenging. This paper describes the process and results of synthesizing labelled-datasets that could be used for training AI (specifically Convolutional Neural Networks) models for determining agricultural land use pattern to support decisions for sustainable farming. In our opinion, this work is a significant step forward in addressing the paucity of usable datasets for developing scalable GeoAI models for sustainable agriculture.

  • Data governance: Organizing data for trustworthy Artificial Intelligence
    • Marijn Janssen
    • Paul Brous
    • Elsa Estevez
    • Luis S. Barbosa
    • Tomasz Janowski
    2020 Full text GOVERNMENT INFORMATION QUARTERLY

    The rise of Big, Open and Linked Data (BOLD) enables Big Data Algorithmic Systems (BDAS) which are often based on machine learning, neural networks and other forms of Artificial Intelligence (AI). As such systems are increasingly requested to make decisions that are consequential to individuals, communities and society at large, their failures cannot be tolerated, and they are subject to stringent regulatory and ethical requirements. However, they all rely on data which is not only big, open and linked but varied, dynamic and streamed at high speeds in real-time. Managing such data is challenging. To overcome such challenges and utilize opportunities for BDAS, organizations are increasingly developing advanced data governance capabilities. This paper reviews challenges and approaches to data governance for such systems, and proposes a framework for data governance for trustworthy BDAS. The framework promotes the stewardship of data, processes and algorithms, the controlled opening of data and algorithms to enable external scrutiny, trusted information sharing within and between organizations, risk-based governance, system-level controls, and data control through shared ownership and self-sovereign identities. The framework is based on 13 design principles and is proposed incrementally, for a single organization and multiple networked organizations.

  • Data regarding a new, vector-enzymatic DNA fragment amplification-expression technology for the construction of artificial, concatemeric DNA, RNA and proteins, as well as biological effects of selected polypeptides obtained using this method
    • Piotr Skowron
    • Natalia Krawczun
    • Joanna Żebrowska
    • Daria Krefft
    • Olga Żołnierkiewicz
    • Marta Bielawa
    • Joanna Jeżewska-Frąckowiak
    • Łukasz Janus
    • Małgorzata Witkowska
    • Małgorzata Palczewska
    • Adriana Schumacher
    • Anna Wardowska
    • Milena Deptuła
    • Artur Czupryn
    • Piotr Mucha
    • Arkadiusz Piotrowski
    • Paweł Sachadyn
    • Sylwia Rodziewicz-Motowidło
    • Michal Pikuła
    • Agnieszka Zylicz-Stachula
    2020 Full text Data in Brief

    Applications of bioactive peptides and polypeptides are emerging in areas such as drug development and drug delivery systems. These compounds are bioactive, biocompatible and represent a wide range of chemical properties, enabling further adjustments of obtained biomaterials. However, delivering large quantities of peptide derivatives is still challenging. Several methods have been developed for the production of concatemers – multiple copies of the desired protein segments. We have presented an efficient method for the production of peptides of desired length, expressed from concatemeric Open Reading Frame. The method employs specific amplification-expression DNA vectors. The main methodological approaches are described by Skowron et al., 2020 [1]. As an illustration of the demonstrated method's utility, an epitope from the S protein of Hepatitis B virus (HBV) was amplified. Additionally, peptides, showing potentially pro-regenerative properties, derived from the angiopoietin-related growth factor (AGF) were designed and amplified. Here we present a dataset including: (i) detailed protocols for the purification of HBV and AGF – derived polyepitopic protein concatemers, (ii) sequences of the designed primers, vectors and recombinant constructs (iii) data on cytotoxicity, immunogenicity and stability of AGF-derived polypeptides.

  • Daylight Appraisal Classes For Achitecture Students A Survey Combined With A Practical Assessment For Educational Training Recommendations
    • Natalia Sokół
    • Marta Waczyńska
    • Justyna Martyniuk-Pęczek
    2020 Full text

    The main objectives of this article are: (i) to present the relations between architecture students' subjective assessment of daylight in classrooms and the objective evaluation of daylit conditions using daylight simulations tools, (ii) to formulate guidelines and recommendations on daylight appraisal methods and tools which may be useful in architectural training. The methodology used includes an evaluation of the results of the direct questionnaire and the computational simulations of the observed conditions. One hundred ninety-four architecture students form three different universities in Poland assessed daylight in 13 different classrooms. The questionnaire aimed to investigate relationships between daylight subjective assessment, students’ perception and daylight knowledge. This paper focuses only on the results of the subjective appraisal of daylit interior spaces and the objective evaluation of the investigated conditions. The simulations of Daylight Factor and Daylight Autonomy were carried out using various available software and the available climate and weather data (for DA). The key findings of the study are: Daylight appraisal part: (i) Daylight factor simulations results correspond with subjective students' assessments of daylight sufficiency within the rooms for eight out of 13 cases. (ii) The were no significant correlations found between the mean illuminances values and the subjective students' appraisals of daylight. The subjective description of daylight within the investigated classrooms was similar (medium) for all the sessions. (iii) The subjective perception of uniformity for task illumination was rated by observers as a medium, while the mean illuminance levels varied from 61 to 460 lx. Architectural training part: (iv) The use of advanced computer daylight simulations tools supports educational activities and aids architectural design, only if the students can comprehend the obtained results (v) Available informative packages should cover contemporary analysis daylight tools.

  • Debonding Size Estimation in Reinforced Concrete Beams Using Guided Wave-Based Method
    • Beata Zima
    • Rafał Kędra
    2020 Full text SENSORS

    The following paper presents the results of the theoretical and experimental analysis of the influence of debonding size on guided wave propagation in reinforced concrete beams. The main aim of the paper is a development of a novel, baseline-free method for determining the total area of debonding between steel rebar embedded in a concrete cover on the basis of the average wave velocity or the time of flight. The correctness of the developed relationships was verified during the experimental tests, which included propagation of guided waves in concrete beams with the varying debonding size, shape and location. The analysis of the collected results proved that guided waves can be efficiently used not only in the debonding detection, but also in an exact determining of its total area, which is extremely important in the context of the nondestructive assessment of the load capacity of the reinforced concrete structures. The undeniable advantage of the proposed method is that there are no requirements for any baseline signals collected for an undamaged structure. The paper comprises of the detailed step by step algorithm description and a discussion of both the advantages and disadvantages.

  • Decomposition of halogenated nucleobases by surface plasmon resonance excitation of gold nanoparticles
    • Telma S. Marques
    • Małgorzata Śmiałek-Telega
    • Robin Schürmann
    • Ilko Bald
    • Maria Raposo
    • Samuel Eden
    • Nigel J. Mason
    2020 Full text EUROPEAN PHYSICAL JOURNAL D

    Halogenated uracil derivatives are of great interest in modern cancer therapy, either as chemotherapeutics or radiosensitisers depending on their halogen atom. This work applies UV-Vis spectroscopy to study the radiation damage of uracil, 5-bromouracil and 5- uorouracil dissolved in water in the presence of gold nanoparticles upon irradiation with an Nd:YAG ns-pulsed laser operating at 532nm at dierent uences. Gold nanoparticles absorb light eciently by their surface plasmon resonance and can signicantly damage DNA in their vicinity by an increase of temperature and the generation of reactive secondary species, notably radical fragments and low energy electrons. A recent study using the same experimental approach characterized the ecient laser-induced decomposition of the pyrimidine ring structure of 5-bromouracil mediated by the surface plasmon resonance of gold nanoparticles. The present results show that the presence of irradiated gold nanoparticles decomposes the ring structure of uracil and its halogenated derivatives with similar eciency. In addition to the fragmentation of the pyrimidine ring, for 5-bromouracil the cleavage of the carbon-halogen bond could be observed, whereas for 5- uorouracil this reaction channel was inhibited. Locally-released halogen atoms can react with molecular groups within DNA, hence this result indicates a specic mechanism by which doping with 5-bromouracil can enhance DNA damage in the proximity of laser irradiated gold nanoparticles.

  • Decrease in Photovoltaic Module Efficiency Due to Deposition of Pollutants
    • Ewa Klugmann-Radziemska
    • Małgorzata Rudnicka
    2020 Full text IEEE Journal of Photovoltaics

    The deposition of pollutants on the surface of photovoltaic (PV) modules reduce the efficiency that can be achieved in given climatic conditions. This results in the loss of energy yield obtained from the solar installation. A number of factors determine the scale of this problem. The first of these is the amount of impurities deposited, the associated amount of precipitation, and the speed and direction of the wind. A second aspect is the type of pollution and the composition and structure of the sludge, which depends on the location of the installation. The type of installation, either stationary or sun tracking, is essential because the angle of inclination of modules, depending on the latitude, will determine the amount of dust deposited, especially for stationary installations. The observed decrease in efficiency of PV modules covered with dust equals 6–10% of the efficiency of a module free of impurities. This means that the user should maintain the module surface and schedule routine cleaning.

  • Decyzje optymalne z Solverem
    • Anna Baj-Rogowska
    2020

    Na rynku można odnaleźć wiele podręczników pomocnych w rozwijaniu kompetencji związanych z posługiwaniem się arkuszem kalkulacyjnym w praktyce menedżerskiej. Niewiele jest natomiast pozycji literaturowych pokazujących możliwości wykorzystania MS Solver do wspomagania decyzji. Niniejsza książka ma za zadanie wypełnić tę lukę. Jej celem jest przedstawienie możliwości dodatku Solver w procesie podejmowania decyzji optymalnych. Intencją Autorki było stworzenie podręcznika dla osób zainteresowanych samodzielną nauką pracy z MS Excel Solver. Niniejsze opracowanie składa się z trzech rozdziałów. Rozdział pierwszy zawiera teoretyczne podstawy wprowadzające do zagadnień podejmowania decyzji optymalnych. Przedstawiono w nim podstawowe pojęcia z tego zakresu, omówiono czym jest proces rozwiązywania problemów decyzyjnych ze szczególnym rozróżnieniem pomiędzy rozwiązywaniem problemów decyzyjnych a ich podejmowaniem. Drugi rozdział został dedykowany przedstawieniu funkcjonalności dodatku Solver wraz z omówieniem opcji ustawień i metod rozwiązań dostępnych w programie oraz raportów wyników, wrażliwości i granic. Na tak przygotowanej podbudowie teoretycznej w dalszej części rozdziału zaprezentowano praktyczne rozwiązanie krok po kroku prostego zadania decyzyjnego. Takie podejście przygotowuje Czytelnika do treści zawartych w rozdziale trzecim. Przedstawiono tutaj różnorodne i znacznie bardziej złożone problemy decyzyjne. Dobór przykładów ma na celu pokazanie potencjału Solvera.

  • Deep eutectic solvents vs ionic liquids: Similarities and differences
    • Justyna Płotka-Wasylka
    • Miguel De la Guardia
    • Vasil Andruch
    • Mária Vilková
    2020 Full text MICROCHEMICAL JOURNAL

    Deep eutectic solvents (DES) were introduced as an alternative to ionic liquids (IL) to overcome the drawbacks of IL solvents. However, some authors consider them to be a subclass of ILs. In contrast, other authors emphasize that these are by their nature independent, different groups of substances. Thus, the question arises: Which solvent group should DESs belong to? Maybe a new class should be added to the existing ones. The aim of this work is to attract the attention of researchers using DES in their studies to the need for a proper use of terms.

  • Deep Instance Segmentation of Laboratory Animals in Thermal Images
    • Magdalena Mazur-Milecka
    • Tomasz Kocejko
    • Jacek Rumiński
    2020 Full text Applied Sciences-Basel

    In this paper we focus on the role of deep instance segmentation of laboratory rodents in thermal images. Thermal imaging is very suitable to observe the behaviour of laboratory animals, especially in low light conditions. It is an non-intrusive method allowing to monitor the activity of animals and potentially observe some physiological changes expressed in dynamic thermal patterns. The analysis of the recorded sequence of thermal images requires smart algorithms for automatic processing of millions of thermal frames. Instance image segmentation allows to extract each animal from a frame and track its activity and thermal patterns. In this work, we adopted two instance segmentation algorithms, i.e., Mask R-CNN and TensorMask. Both methods in different configurations were applied to a set of thermal sequences, and both achieved high results. The best results were obtained for the TensorMask model, initially pre-trained on visible light images and finally trained on thermal images of rodents. The achieved mean average precision was above 90 percent, which proves that model pre-training on visible images can improve results of thermal image segmentation.

  • Deep learning based thermal image segmentation for laboratory animals tracking
    • Magdalena Mazur-Milecka
    • Jacek Rumiński
    2020 QIRT Journal

    Automated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are using thermal imaging – a technology that requires neither light nor human presence. The aim of the study was: (1) an efficiency analysis of deep learning based image segmentation algorithms for the need of laboratory rats images, (2) analysis of different methods of original thermal data conversion to grey scale images for the purpose of the segmentation, (3) evaluation of the image data range impact on segmentation results using deep learning networks. We have trained U-Net and V-Net architectures with images obtained from different temperature ranges. The results indicate, that networks trained on images containing a narrow range of temperature data equal to animals’ body temperature or even its part, are able to better perform the object segmentation than networks trained on the original data.

  • Deep learning for recommending subscription-limited documents
    • Grzegorz Chłodziński
    • Karol Woźniak
    2020 Full text

    Documents recommendation for a commercial, subscription-based online platform is important due to the difficulty in navigation through a large volume and diversity of content available to clients. However, this is also a challenging task due to the number of new documents added every day and decreasing relevance of older contents. To solve this problem, we propose deep neural network architecture that combines autoencoder with multilayer perceptron in a hybrid recommender system. We train our model using real-world historical data from commercial platform using interactions to capture user similarity and categorical document features to predict the probability of a user-document interaction. Our experimental results demonstrate the effectiveness of the proposed architecture. We plan to release our model in a commercial online platform to support a personalized user experience.

  • Deep Learning-Based Intrusion System for Vehicular Ad Hoc Networks
    • Li Fei
    • Zhang Jiayan
    • Song Jiaqi
    • Edward Szczerbicki
    2020 Full text CMC-Computers Materials & Continua

    The increasing use of the Internet with vehicles has made travel more convenient. However, hackers can attack intelligent vehicles through various technical loopholes, resulting in a range of security issues. Due to these security issues, the safety protection technology of the in-vehicle system has become a focus of research. Using the advanced autoencoder network and recurrent neural network in deep learning, we investigated the intrusion detection system based on the in-vehicle system. We combined two algorithms to realize the efficient learning of the vehicle’s boundary behavior and the detection of intrusive behavior. In order to verify the accuracy and efficiency of the proposed model, it was evaluated using real vehicle data. The experimental results show that the combination of the two technologies can effectively and accurately identify abnormal boundary behavior. The parameters of the model are self-iteratively updated using the time-based back propagation algorithm. We verified that the model proposed in this study can reach a nearly 96% accurate detection rate.

  • Defective TiO2 Core-Shell Magnetic Photocatalyst Modified with Plasmonic Nanoparticles for Visible Light-Induced Photocatalytic Activity
    • Zuzanna Bielan
    • Agnieszka Sulowska
    • Szymon Dudziak
    • Siuzdak Katarzyna
    • Jacek Ryl
    • Anna Zielińska-Jurek
    2020 Full text Catalysts

    In the presented work, for the first time, the metal-modified defective titanium(IV) oxide nanoparticles with well-defined titanium vacancies, was successfully obtained. Introducing platinum and copper nanoparticles (NPs) as surface modifiers of defective d-TiO2 significantly increased the photocatalytic activity in both UV-Vis and Vis light ranges. Moreover, metal NPs deposition on the magnetic core allowed for the effective separation and reuse of the nanometer-sized photocatalyst from the suspension after the treatment process. The obtained Fe3O4@SiO2/d-TiO2-Pt/Cu photocatalysts were characterized by X-ray diffractometry (XRD) and specific surface area (BET) measurements, UV-Vis diffuse reflectance spectroscopy (DR-UV/Vis), X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM). Further, the mechanism of phenol degradation and the role of four oxidative species (h+, e−, •OH, and •O2−) in the studied photocatalytic process were investigated

  • Deflated Preconditioned Solvers for Parametrized Local Model Order Reduction
    • Martyna Mul
    • Michał Mrozowski
    2020

    One of steps in the design of microwave filters is numerical tuning using full-wave simulators. Typically, it is a time-consuming process as it uses advanced computational methods, e.g. the finite-element method (FEM) and it usually requires multiple optimization steps before the specification goals are met. FEM involves solving a large sparse system of equations at many frequency points and therefore its computational cost is high. One of the ideas to speed up the numerical optimization is parametrized model-order reduction (PMOR). The key point in model order reduction, is that the original large sparse system of FE equations is replaced with a small and dense one, that can be solved at many frequency points with substantially smaller computational effort. PMOR yields in the parameter dependent reduced-order model which might be reused in subsequent optimization steps.

  • Deformation and Surface Color Changes of Beech and Oak Wood Lamellas Resulting from the Drying Process
    • Jacek Barański
    • Aleksandra Konopka
    • Tatiana Vilkovská
    • Ivan Klement
    • Peter Vilkovský
    2020 Full text BIORESOURCES

    The drying process was examined relative to parameters’ influence on the deformation and surface layer color changes of beech wood (Fagus sylvatica L.) and oak wood (Quercus robur L.). The goal was to analyze the impact of drying process conditions, wood and growth rings types, and load on the deformation and surface color changes of drying thin wooden elements. A further aim was to reduce the time of the lamella drying and minimize wood products defects. During each drying, 40 pieces of wood were dried, divided into two groups. For the first group, 30 pieces were dried under a uniformly distributed load of approximately 50 kg, while for the second group, 10 samples were dried without weight. The lamellas dried under load exhibited fewer cup, bow, and twist deformations than the lamellas dried without load. Cracks in the dried lamellas occurred comparably in those dried under and without load. Color changes in the specimens before and after drying were observed and measured. The differences in colorimetric parameters (a, b, and L) between wood without defects and with defects were less marked after drying than before drying. The color changes were only noticed in the surface layers of the specimens.

  • Degradation of ferritic X10CrAlSi18 stainless steel caused by slurry
    • Alicja Krella
    • Marta Buszko
    • Grzegorz Gajowiec
    2020 ENGINEERING FAILURE ANALYSIS

    The slurry erosion tests of ferritic X10CrAlSi18 steel were carried out using a slurry pot device. In order to investigate the erosion process, two series of tests were performed: first one with a constant impact velocity of 5 m/s, 7 m/s and 9 m/s and the second one, during which the impact velocity was changed after every exposure. During each test, an influence of test conditions on volume loss, surface hardness and roughness with exposure time was studied. The normalized erosion rate and erosion efficiency parameter increased linearly with velocity in the range between 5 and 9 m/s. Surface hardness increased exponentially with an exponent n = 0.27. The erosive efficiency parameter determined for tests carried out with variable impact velocity was higher than for tests with constant velocity. The erosion performance increased as the difference in consecutive impact velocity increased. At the beginning of slurry tests, surface hardness and roughness increased rapidly. A fluctuation in erosion rate and surface roughness was noted in the tests performed with variable impact velocity. The amplitudes of these fluctuations decreased with the test duration. Surface hardness influenced damage formed on the specimen’s surface. With increasing surface hardness, surface roughness (Ra parameter) decreased. For surface hardness over 280 HV flakes were formed on the specimen surface.