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  • Corporate social responsibility and forward default risk under firm and industry heterogeneity
    • Muhammad Mushafiq
    • Błażej Prusak
    • Magdalena Markiewicz
    2024 Pełny tekst Entrepreneurial Business and Economics Review

    Objective: This study aims to evaluate the impact of corporate social responsibility on forward default risk (FDR) under the setting of firm and industry heterogeneity. Research Design & Methods: This study evaluated the impact of corporate social responsibility (CSR) on FDR using the data of 497 companies from 2007-2021 in the S&P 500 index, taking into account firm and industry heterogeneity aspects. This study utilized instrumental variable regression using the generalized method of moments (IV-GMM) estimation technique which is robust for controlling the pertinent issue of endogeneity. Findings: This study found a negative relationship between CSR and FDR in the full sample. From the firm size aspect, this study found that CSR is more effective in mitigating FDR in large-cap firms than in mid-cap firms. Firm age heterogeneity exhibited a distinct behaviour, as young and middle-aged firms had a stronger impact on FDR management in comparison to old firms. Industry heterogeneity showed that industries with higher customer interaction have a higher impact on corporate social responsibility to control FDR. Industries with lower customer interaction have a lower impact on corporate social responsibility and FDR. Implications & Recommendations: We proposed some policy recommendations based on the findings in the context of firm and industry heterogeneity. Especially the management of mid-cap and young corporations should improve the CSR policy to enhance CSR performance which would lead to stabilized protection against FDR. Similarly, consumer-intensive industries should also focus on enhancing CSR initiatives to decrease FDR. Non-consumer-intensive industries should focus on enhancing CSR policy and at the same time pay particular attention to communicating CSR results to end consumers to reduce FDR. Contribution & Value Added: This study is the first to explore CSR’s impact on financial parameters under heterogeneity.

  • Correlations of structural, thermal and electrical properties of sodium doped complex borophosphosilicate glass
    • Zuzanna Milewczyk
    • Sharafat Ali
    • Piotr Okoczuk
    • Jacek Ryl
    • Ryszard Barczyński
    • Natalia Wójcik
    2024 Pełny tekst CERAMICS INTERNATIONAL

    Borophosphosilicate glasses with varying sodium ion concentrations were investigated for their, structural, thermal, and electrical properties. All the obtained glasses were transparent except the glass with the highest sodium content, which exhibited translucency due to inhomogeneities. Increasing sodium content led to reduced boron and silicon content while maintaining a constant B/Si ratio, indicating progressive depolymerization of the glass network. Confocal microscopy, scanning electron microscopy, and atomic force microscopy showed homogeneous and granular structure for samples with lower sodium content, but higher sodium content resulted in visible agglomeration/nanocrystallization. X-ray diffractograms showed amorphous nature for most samples, with samples doped with the highest concentrations of Na2O showing several broad reflections suggesting nanoscale crystallinity. Fourier-transform infrared spectroscopy revealed shifts in dominant bands with increasing sodium content, indicating depolymerization of the borate network. An observed decrease in glass transition temperature and thermal stability with increasing sodium content was attributed to depolymerization and formation of non-bridging oxygens. Impedance spectroscopy revealed two relaxation processes associated with the transport of Na+ ions through two different regions. DC conductivity and activation energy predominantly increased with the sodium ion content at high temperatures.

  • Corrigendum to “An investigation on residual stress and fatigue life assessment of T-shape welded joints” [Eng. Fail. Anal. 141 (2022) 106685]
    • Jeetendra Mourya
    • Greg Wheatley
    • Mohammed Nizam Khan
    • Reza Masoudi Nejad
    • Ricardo Branco
    • Wojciech Macek
    2024 ENGINEERING FAILURE ANALYSIS

    This paper aims to quantitatively evaluate the residual stress and fatigue life of T-type welded joints with a multi-pass weld in different direction. The main research objectives of the experimental test were to test the residual stress by changing direction along with multiple wielding passes and determine the fatigue life of the welded joints. The result shows that compressive residual stress increases in the sample gradually from single-pass weld to double and triple-pass weld. Moreover, the fatigue life of the specimen also gradually improves with an increasing number of welding passes. Performing multi-pass welding in different directions affects the material’s residual stress and fatigue life, which is an essential factor to consider for assuring the strength of the welded joint.

  • Corrigendum to “Experimental analysis on the risk of vortex ventilation and the free surface ventilation of marine propellers”
    • Anna Kozłowska
    2024 APPLIED OCEAN RESEARCH

    The paper presents a discussion of the ventilation inception and air drawing prediction of ships propellers, aiming to predict under what conditions ventilation will happen, and the actual physical mechanism of the ventilation.

  • Corrigendum to “Fatigue life improvement using low transformation temperature weld material with measurement of residual stress” [Int. J. Fatigue 164 (2022) 107137]
    • Jordan Franks
    • Greg Wheatley
    • Pedram Zamani
    • Reza Masoudi Nejad
    • Wojciech Macek
    • Ricardo Branco
    2024 INTERNATIONAL JOURNAL OF FATIGUE

    Welding processes often produce high levels of tensile residual stress. Low transformation temperature (LTT) welding wires utilise phase transformation strains to overcome the thermal contraction of a cooling weld. In this paper, the residual stress within each weld was quantified using the milling/strain gauge method, being the strain change measured as the weldment was milled away. The fatigue tests were conducted under uniaxial loading considering two types of LTT materials. The results show that the crack propagation of all samples was similar in cycles although both LTT materials extended the crack initiation, and, therefore, the overall life of the part. It was found that both LTT materials reduced the residual tensile stresses, increased the residual compressive stresses, leading to increase in fatigue life about 30%.

  • Corrigendum to “The influence of α,ω-diols and SiO2 particles on CO2 absorption and NH3 escaping during carbon dioxide capture in ammonia solutions” [J. CO2 Util. 80 (2024) 102698]
    • Temesgen Amibo
    • Donata Konopacka-Łyskawa
    2024 Pełny tekst Journal of CO2 Utilization

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  • Corrosion damage identification based on the symmetry of propagating wavefield measured by a circular array of piezoelectric transducers: Theoretical, experimental and numerical studies
    • Beata Zima
    • Jochen Moll
    2024 Pełny tekst MECHANICAL SYSTEMS AND SIGNAL PROCESSING

    The article investigates the results obtained from numerical simulations and experimental tests concerning the propagation of guided waves in corroded steel plates. Developing innovative methodologies for assessing corrosion-induced degradation is crucial for accurately diagnosing offshore and ship structures exposed to harsh environmental conditions. The main aim of the research is to analyze how surface irregularities affect wave propagation characteristics. An investigation was conducted for antisymmetric fundamental mode A0. Specifically, the study examines the asymmetrical wavefronts generated by nonuniform thickness in damaged specimens. Initially, numerical analysis explores the impact of thickness variation on wave field symmetry. Corroded plates with varying levels of degradation are modeled using the random fields approach, with degradation levels ranging from 0 % to 60 %. Subsequently, the research investigates how the standard deviation of thickness distribution (from 5 % to 20 % of the initial thickness) and excitation frequency (from 50 to 150 kHz) influence recorded signals and the shape of reconstructed wavefronts. Each scenario compares wavefront symmetry levels estimated using rotational and bilateral symmetry degrees as indicative parameters. The numerical simulations are complemented by experimental tests conducted on plates with three different degradation levels. The results demonstrate the efficacy of the proposed wave field analysis approach for assessing structural integrity, as evidenced by the agreement between numerical predictions and experimental observations.

  • Corrosion Inhibition of AZ31-xLi (x = 4, 8, 12) magnesium alloys in sodium chloride solutions by aqueous molybdate
    • Maria Osipenko
    • Andrei Paspelau
    • Aliaksandr Kasach
    • Jacek Ryl
    • Konrad Skowron
    • Janusz Adamiec
    • Irina Kurilo
    • Dmitry Kharitonov
    2024 CORROSION SCIENCE

    Corrosion of lithium-containing AZ31 magnesium alloys AZ31-xLi (x = 4, 8, and 12 wt%) has been examined in 0.05 M NaCl solution with and without 10–150 mM of Na2MoO4 inhibitor. Potentiodynamic polarization, electrochemical impedance spectroscopy (EIS), and dynamic electrochemical impedance spectroscopy (DEIS) measurements were used to correlate the phase composition and microstructure of the alloys with their corrosion propensity and effectiveness of the molybdate inhibitor, giving high inhibition efficiency (>85%) at concentrations higher than ca. 35 mM. Post-corrosion microstructure, Raman, and X-ray photoelectron spectroscopy analyses allowed to provide the inhibition mechanism of AZ31-xLi alloys by molybdate ions.

  • Corrosion Monitoring in Petroleum Installations—Practical Analysis of the Methods
    • Juliusz Orlikowski
    • Agata Jazdzewska
    • Iwona Łuksa
    • Michał Szociński
    • Kazimierz Darowicki
    2024 Pełny tekst Materials

    This paper presents the most typical corrosion mechanisms occurring in the petroleum industry. The methods of corrosion monitoring are described for particular corrosion mechanisms. The field and scope of the application of given corrosion-monitoring methods are provided in detail. The main advantages and disadvantages of particular methods are highlighted. Measurement difficulties and obstacles are identified and widely discussed based on actual results. Presented information will allow the corrosion personnel in refineries to extract more reliable data from corrosion-monitoring systems.

  • Corrosion of AISI1018 and AISI304 steel exposed to sulfates
    • Ginneth Millan Ramirez
    • Miguel Angel Baltazar-Zamora
    • Ce Tochtli Méndez Ramírez
    • Maciej Niedostatkiewicz
    • Hubert Byliński
    2024 Inżynieria Bezpieczeństwa Obiektów Antropogenicznych

    This research analyses the behavior of corrosion, durability, and quality of reinforced concrete samples coated with two different materials when exposed to contaminated soil with sulfates. The initial assessment involved evaluating the water absorption rate of the coating materials before and after exposure to a solution containing 3%푁푎2푆푂4+3%푀푔푆푂4+3%퐾2푆푂4+3%퐶푎푆푂4to determine their durability. the corrosion potential and linear polarization resistance technique were employed to measure the corrosion rate. Carbon steel and AISI 304 steel bars were tested alongside a stainless counter electrode. The findings indicate that the solvent-based coating exhibited superior performance, demonstrating reduced corrosion and water absorption rates. Additionally, the presence of sulfates led to the formation of a surface layer on the concrete, initially aiding in limiting waterpenetration. However, over time, this layer eventually causes damage to the concrete from the inside out.

  • Corrosion performance of super duplex stainless steel and pipeline steel dissimilar welded joints: a comprehensive investigation for marine structures
    • Anup Kumar Maurya
    • Shailesh M. Pandey
    • Rahul Chhibber
    • Dariusz Fydrych
    • Chandan Pandey
    2024 INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

    This study investigates the corrosion behavior of dissimilar gas tungsten arc (GTA) welded joints between super duplex stainless steel (sDSS 2507) and pipeline steel (X-70) using electrochemical and immersion corrosion tests. The GTA welds were fabricated using ER2594 and ER309L fller metals. The study examined the electrochemical characteristics and continuous corrosion behavior of samples extracted from various zones of the weldments in a 3.5 wt.% NaCl solution, employing electrochemical impedance spectroscopy, potentiodynamic polarization methods, and an immersion corrosion test. EIS and immersion investigations revealed pitting corrosion in the X-70 base metal/X-70 heat-afected zone, indicating inferior overall corrosion resistance due to galvanic coupling. The corrosion byproducts identifed in complete immersion comprised α-FeOOH, γ-FeOOH, Fe3O4, and Fe2O3, whereas γ-FeOOH and Fe3O4 were predominant in dry/wet cyclic conditions. Corrosion escalated with dry/wet cycle conditions while maintaining a lower level in complete immersion. The corrosion mechanism involves three wet surface stages in dry/wet cycles and typical oxygen absorption during complete immersion. Proposed corrosion models highlight the infuence of Cl−, O2, and rust layers.

  • Cost-effective methods of fabricating thin rare-earth element layers on SOC interconnects based on low-chromium ferritic stainless steel and exposed to air, humidified air or humidified hydrogen atmospheres
    • Łukasz Mazur
    • Paweł Winiarski
    • Bartosz Kamecki
    • Justyna Ignaczak
    • Sebastian Molin
    • Tomasz Brylewski
    2024 INTERNATIONAL JOURNAL OF HYDROGEN ENERGY

    Most oxidation studies involving interconnects are conducted in air under isothermal conditions, but during real-life solid oxide cell (SOC) operation, cells are also exposed a mixture of hydrogen and water vapor. For this study, an Fe–16Cr low-chromium ferritic stainless steel was coated with different reactive element oxides – Gd2O3, CeO2, Ce0.9Y0.1O2 – using an array of methods: dip coating, electrodeposition and spray pyrolysis. The samples underwent oxidation experiments carried out over 100 h in three different atmospheres at 800 °C: air, an air/H2O mixture, and an Ar/H2/H2O mixture. The influence of different atmospheres on the corrosion of the Fe–16Cr steel was determined via oxidation kinetics studies; the corrosion product was evaluated using X-ray diffraction, scanning electron microscopy and area-specific resistance (ASR) measurements. All coated samples exhibited lower parabolic oxidation rate constants than bare steel and most also had lower ASR. The applied modifications were found to be sufficiently effective to allow the investigated low-chromium steel to be considered for application as an interconnect material for SOCs.

  • Cost-Effective Piggyback Forward dc-dc Converter
    • Oleksandr Matiushkin
    • Oleksandr Husev
    • Hossein Afshari
    • Dmitri Vinnikov
    • Ryszard Strzelecki
    2024

    The novel piggyback dc-dc converter as a cost-effective solution is presented in this work. It provides a wide input voltage range of regulation with a low component count. The novel solution is an advanced forward dc-dc converter with an additional clamp output capacitor. The idea of such a type of converter is to transfer magnetizing energy of transformer to the output side, instead of using input clamp circuit. The design guidelines of the passive component of the proposed solution are discussed. A digital domain proportional integral controller is designed for the off-grid system validation, and it provides a stable output voltage in a wide range of the input voltage and power. Experimental prototype of the proposed piggyback converter along with experimental results of critical points are presented. The efficiency study of the proposed solution is done.

  • Cost-Efficient Globalized Parameter Optimization of Microwave Components through Response-Feature Surrogates and Nature-Inspired Metaheuristics
    • Anna Pietrenko-Dąbrowska
    • Sławomir Kozieł
    • Łukasz Gołuński
    2024 Pełny tekst IEEE Access

    Design of contemporary microwave devices predominantly utilizes computational models, including both circuit simulators, and full-wave electromagnetic (EM) evaluation. The latter constitutes the sole generic way of rendering accurate assessment of the system outputs that considers phenomena such as cross-coupling or radiation and dielectric losses. Consequently, for reliability reasons, the final tuning of microwave device parameters is commonly performed utilizing EM simulation software. As EM analysis is computationally heavy, parametric optimization entails significant costs, also for local algorithms. The expenses generated by global search procedures are incomparably higher, and often prohibitive. Still, global optimization is more and more often necessary, for example, when re-designing a structure over extended ranges of operating conditions (bandwidth, power split ratios, etc.), when more than a single local optimum exists (e.g., optimization of frequency selective surfaces), or simply due to the absence of quality initial design (e.g., compact circuits obtained using the slow-wave phenomenon). A possible workaround is surrogate-assisted optimization, yet a construction of accurate replacement models is a challenge by itself. This paper offers an innovative approach to a rapid globalized optimization of passive microwave components. It combines a machine learning procedure, specifically, an iterative construction and refinement of fast surrogates (with infill criterion being a minimization of the predictor-yielded objective improvement) with a response feature technology, where the metamodel targets suitably appointed characteristic points of the circuit outputs. These so-called response features are in a nearly linear relationship with the geometry parameters, which facilitates the search process and reduces the expenditures associated with surrogate model construction. Identification of the infill points is executed using a particle swarm optimization algorithm. Numerical experiments carried out using two microstrip circuits demonstrate the capability for a global search of the proposed algorithm, and its superior performance over direct nature-inspired-based optimization and surrogate-assisted search at the level of complete circuit characteristics.

  • Cost-Efficient Measurement Platform and Machine-Learning-Based Sensor Calibration for Precise NO2 Pollution Monitoring
    • Anna Pietrenko-Dąbrowska
    • Sławomir Kozieł
    • Marek Wójcikowski
    • Bogdan Pankiewicz
    • Artur Rydosz
    • Tuan-Vu Cao
    • Krystian Wojtkiewicz
    2024 MEASUREMENT

    Air quality significantly impacts human health, the environment, and the economy. Precise real-time monitoring of air pollution is crucial for managing associated risks and developing appropriate short- and long-term measures. Nitrogen dioxide (NO2) stands as a common pollutant, with elevated levels posing risks to the human respiratory tract, exacerbating respiratory infections and asthma, and potentially leading to chronic lung diseases. Notwithstanding, precise NO2 detection typically demands complex and costly equipment. This paper explores NO2 monitoring using low-cost platforms, meticulously calibrated for reliability. An integrated measurement unit is first presented that contains primary and supplementary nitrogen dioxide sensors, as well as auxiliary detectors for evaluating outside and inside temperature and humidity. The calibration process utilizes data acquired over the period of five months from various reference stations. Employing machine learning with an artificial neural network (ANN)-based and kriging interpolation surrogate models, the correction strategy integrates additive and multiplicative enhancement, predicted by the ANN through auxiliary sensor data such as temperature, humidity, and the sensor-detected NO2 levels. Extensive verification studies showcase that this calibration approach notably enhances monitoring precision (r2 correlation coefficient surpassing 0.85 concerning reference data, and RMSE of less than four g/m3), rendering low-cost NO2 detection practical and dependable.

  • Cost-Efficient Multi-Objective Design of Miniaturized Microwave Circuits Using Machine Learning and Artificial Neural Network
    • Sławomir Kozieł
    • Anna Pietrenko-Dąbrowska
    • Leifur Leifsson
    2024

    Designing microwave components involves managing multiple objectives such as center frequencies, impedance matching, and size reduction for miniaturized structures. Traditional multi-objective optimization (MO) approaches heavily rely on computationally expensive population-based methods, especially when exe-cuted with full-wave electromagnetic (EM) analysis to guarantee reliability. This paper introduces a novel and cost-effective MO technique for microwave passive components utilizing a machine learning (ML) framework with artificial neural network (ANN) surrogates as the primary prediction tool. In this approach, mul-tiple candidate solutions are extracted from the Pareto set via optimization using a multi-objective evolutionary algorithm (MOEA) applied to the current ANN model. These solutions expand the dataset of available (EM-simulated) parameter vectors and refine the surrogate model iteratively. To enhance computational effi-ciency, we employ variable-resolution EM models. Tested on two microstrip cir-cuits, our methodology competes effectively against several surrogate-based ap-proaches. The average computational cost of the algorithm is below three hundred EM analyses of the circuit, with the quality of generated Pareto sets surpassing those produced by the benchmark methods.

  • Coupled DEM/CFD analysis of impact of free water on the static and dynamic response of concrete in tension regime
    • Marek Krzaczek
    • Andrzej Tejchman-Konarzewski
    • Michał Nitka
    2024 Pełny tekst COMPUTERS AND GEOTECHNICS

    W tym artykule zbadano numerycznie quasi-statyczne i dynamiczne zachowanie częściowo nasyconego płynem betonu w warunkach dwuwymiarowego (2D) jednoosiowego rozciągania w mezoskali. Obliczono, jaki wpływ ma zawartość wolnego płynu porowego (gazu i wody) na proces pękania i wytrzymałość betonu w rozciąganiu. Do symulacji zachowania betonu całkowicie i częściowo nasyconego płynem w warunkach quasi-statycznych i dynamicznych wykorzystano ulepszony model hydromechaniczny w skali porów, oparty na DEM/CFD. Podstawą koncepcji przepływu płynu była sieć kanałów na ciągłym obszarze pomiędzy dyskretnymi elementami. W bardzo porowatym, częściowo nasyconym betonie przyjęto dwufazowy laminarny przepływ płynu. Aby śledzić zawartość cieczy/gazu, wzięto pod uwagę położenie i objętość porów i rys. Symulacje numeryczne spójnych próbek ziarnistych o uproszczonej mezostrukturze sferycznej przypominającej beton przeprowadzono w warunkach suchych i mokrych dla dwóch różnych szybkości odkształcenia. Przeprowadzono badania wpływu ciśnienia porów płynu, nasycenia płynu i lepkości płynu na wytrzymałość i proces pękania betonu. Kwasi-statyczna wytrzymałość na rozciąganie spadała nieliniowo wraz ze wzrostem nasycenia płynu i lepkości płynu podczas migracji płynu przez pory i pęknięcia wskutek przyspieszenia procesu pękania. Jednakże podczas szybkiego dynamicznego odkształcenia przy rozciąganiu proces pękania został osłabiony z powodu ograniczenia migracji płynu wynikającego z niewystarczającego czasu płynu na opuszczenie porów. Spowodowało to nieliniowy wzrost dynamicznej wytrzymałości na rozciąganie wraz ze wzrostem nasycenia płynu i lepkości płynu.

  • Coupling between the photoactivity and CO2 adsorption on rapidly thermal hydrogenated vs. conventionally annealed copper oxides deposited on TiO2 nanotubes
    • Wiktoria Lipińska
    • Katarzyna Grochowska
    • Jacek Ryl
    • Jakub Karczewski
    • Mirosław Sawczak
    • Emerson Coy
    • Vincent Mauritz
    • Ryan Crisp
    • Katarzyna Siuzdak
    2024 JOURNAL OF MATERIALS SCIENCE

    Highly ordered spaced titanium dioxide nanotubes were fabricated via electrochemical anodization and modified with titania nanoparticles and copper oxides. Such materials were rapidly annealed in hydrogen atmosphere or conventionally in a tube furnace in air, in which the temperature slowly increases. Applied synthesis procedure can be considered as simple, cost-effective, and environmentally friendly as it allows for reduction in used materials and enhances sustainable engineering. Manipulating the chemical composition of materials by different thermal treatments resulted in various photoelectrochemical activities and density of CO2 adsorption sites. Rapidly annealed nanotubes decorated by copper oxides exhibit excellent electrochemical properties where one electrode combines both: solar to electricity conversion (photocurrent under visible light 30 µA/cm2) and CO2 adsorption systems (18 times higher current after CO2 saturation). Rapidly thermal hydrogenated TiO2 nanotubes with copper oxides had 17 times higher photocurrent and wider absorption band (380–780 nm) than conventionally annealed ones. Furthermore, the crystal planes such as Cu (111), Cu (220), Cu2O (110), CuO (002) and Cu0, Cu+, Cu2+ oxidation states, and oxygen vacancies were recognized for hydrogenated sample. It should be highlighted that thermal annealing conditions significantly affects ability of copper oxide to CO2 adsorption and CO2 reduction reaction for hydrogenated electrode.

  • Crack monitoring in concrete beams under bending using ultrasonic waves and coda wave interferometry: the effect of excitation frequency on coda
    • Magdalena Knak
    • Erwin Wojtczak
    • Magdalena Rucka
    2024 Pełny tekst

    Concrete is one of the most widely used construction materials in the world. In recent years, various non-destructive testing (NDT) and structural health monitoring (SHM) techniques have been investigated to improve the safety and control of the current condition of concrete structures. This study focuses on micro-crack monitoring in concrete beams. The experimental analysis was carried out on concrete elements subjected to three-point bending in a testing machine under monotonic quasi-static loading. During the tests, the fracture process was characterized using ultrasonic waves. The recorded signals were further processed by coda wave interferometry (CWI). This technique allowed the detection of cracks using the decorrelation between ultrasonic wave signals collected at different stages of degradation. Different values of excitation frequencies in the range from 100 kHz to 400 kHz were used to investigate the influence of frequency selection on the effectiveness of the damage indication based on the decorrelation of coda waves. The results obtained from the experiments were intended to highlight the effect of the applied frequencies on the coda wave interferometry.

  • Crafting an ultrashort workplace incivility scale and determining cutoffs for varied risk levels through item response theory
    • Anna Maria Daderman
    • Beata Basińska
    • Carina Ragnestål-Impola
    • Marie Hedman
    • Anna Wicksell
    • Mathilde Faure Lindh
    • Åsa Cider
    2024 CURRENT PSYCHOLOGY

    Workplace incivility (WI), characterized by disrespectful or rude behavior in the workplace, is linked to poor mental health and overall well-being. The Workplace Incivility Scale (WIS) is a popular 7-item measure for assessing WI. There is a current need for an ultrashort conceptually clear version of the WIS. In addition, the cutoffs for varied at-risks of WI, requiring intervention, remains unknown. Using data from 426 employees across diverse organizations, we employed item response theory (IRT) to create an ultrashort WIS and establish cutoffs for high, moderate, low, and at-not risk of WI. Confirmatory factor analyses were utilized to validate WIS construct validity. In supporting convergent validity, WIS was correlated with workplace bullying and poor health-related quality of life. All items demonstrated adequate severity threshold parameters with very high discrimination and good reliability parameters except for item WIS7. We successfully developed an ultrashort and valid 3-item WIS, specifically comprising items WIS2–4, and identified cutoffs for varying levels of WI risk. This streamlined measure aims to reduce response burden and foster a healthier organizational culture. In essence, cutoff points streamline the classification process, allowing for quicker and more standardized identification of at-risk employees. This concise, valid, and reliable ultrashort WIS holds potential for use in intervention studies conducted by organizational and occupational health psychologists, ultimately promoting employee well-being and cultivating a positive workplace environment. The current study further advances the existing theoretical framework rooted in the social interactionist perspective by delineating WI as a distinct and independent construct.

  • Crank–Nicolson FDTD Method in Media Described by Time-Fractional Constitutive Relations
    • Damian Trofimowicz
    • Tomasz Stefański
    • Jacek Gulgowski
    2024 Pełny tekst

    In this contribution, we present the Crank-Nicolson finite-difference time-domain (CN-FDTD) method, implemented for simulations of wave propagation in media described by time-fractional (TF) constitutive relations. That is, the considered constitutive relations involve fractional-order (FO) derivatives based on the Grünwald-Letnikov definition, allowing for description of hereditary properties and memory effects of media and processes. Therefore, the TF constitutive relations make it possible to include, in a dielectric response, diffusion processes which are modelled mathematically by the diffusion-wave equation. We formulate fundamental equations of the proposed CN-FDTD method, and then we execute simulations which confirm its accuracy and applicability. Additionally, we perform numerical tests of stability, which confirm unconditional stability of the method. The proposed method is useful for researchers investigating numerical techniques in media described by FO derivatives.

  • C-reactive protein (CRP) evaluation in human urine using optical sensor supported by machine learning
    • Kacper Cierpiak
    • Paweł Wityk
    • Monika Kosowska
    • Patryk Sokołowski
    • Tomasz Talaśka
    • Jakub Gierowski
    • Michal Markuszewski
    • Małgorzata Szczerska
    2024 Scientific Reports

    The rapid and sensitive indicator of inflammation in the human body is C-Reactive Protein (CRP). Determination of CRP level is important in medical diagnostics because, depending on that factor, it may indicate, e.g., the occurrence of inflammation of various origins, oncological, cardiovascular, bacterial or viral events. In this study, we describe an interferometric sensor able to detect the CRP level for distinguishing between no-inflammation and inflammation states. The measurement head was made of a single mode optical fiber with a microsphere structure created at the tip. Its surface has been biofunctionalized for specific CRP bonding. Standardized CRP solutions were measured in the range of 1.9 µg/L to 333 mg/L and classified in the initial phase of the study. The real samples obtained from hospitalized patients with diagnosed Urinary Tract Infection or Urosepsis were then investigated. 27 machine learning classifiers were tested for labeling the phantom samples as normal or high CRP levels. With the use of the ExtraTreesClassifier we obtained an accuracy of 95% for the validation dataset. The results of real samples classification showed up to 100% accuracy for the validation dataset using XGB classifier.

  • Creating private and public value in data-related management projects: a cross-border case study from Switzerland and Italy
    • Elide Garbani-Nerini
    • Elena Marchiori
    • Nadzeya Sabatini
    • Lorenzo Cantoni
    2024 Pełny tekst

    The literature in the field of smart cities shows a continuous emphasis and interest in the topic of big data due to the extensive use of Information and Communication Technologies by public and private institutions within each city. There is undoubtedly value in big data: in data lie insights on the city, its stakeholders, citizens, products, and services. Challenges, though, lie in data’s variety, volume, and velocity, but also in managing them, considering the complex interplay between stakeholders inside a city or a country. Another layer of complexity is added when we consider a smart city as a smart destination where the visitor - often an international tourist - becomes an additional stakeholder of a smart city bringing in additional data. Such challenges, though, are even stronger when tourists do not stop at geographical borders: smart destinations become cross-border destinations. While there is a physical border between them, but most importantly, a legal difference in how data should be collected, stored, managed, and re-used [56, 59], data flows do not stop at this border. This complexity has to be managed both by governmental and tourism agencies. However, the literature between eGovernment and tourism is often theoretical in nature, and while it highlights the potential benefits of smart destinations and data-management processes, it does not provide detailed guidelines on how to implement these concepts in practice [41], especially in the context of cross-border smart destinations. With regards to this, not only has the need for guidelines risen to help tourism destinations tackle smart data- and technology-related projects, but also to define how stakeholders can come together to determine data policies and governance in order to create private as well as public value [60]. This paper responds to such a need by presenting the results of a cross-border research project conducted in Switzerland and Italy, where the model of a smart destination’s structure proposed by Ivars-Baidal et al. [35] has been applied, and its dimensions have been operationalized in a data-related management project. This allowed the authors to understand how to create public and private value managing data flows in a cross-border context, while also elaborating on the model reflecting on data’s dual role as a starting point but also as a central component impacting other dimensions.

  • Creep rupture study of dissimilar welded joints of P92 and 304L steels
    • Gaurav Dak
    • Krishna Guguloth
    • R. S. Vidyarthy
    • Dariusz Fydrych
    • Chandan Pandey
    2024 Welding in the World

    The present work investigates the high-temperature tensile and creep properties of the dissimilar metal weld joints of 304L austenitic stainless steel (SS) and P92 creep strength-enhanced ferritic-martensitic (CSEF/M) steel under diferent testing condition. Thermanit MTS 616 fller rod (P92 fller) and the multi-pass tungsten inert gas (TIG) welding process were used to create the dissimilar weld connection. The ultimate tensile strength (UTS) was evaluated in the temperature range of 450–850 °C. Creep testing was conducted at a temperature of 650 °C while applying stress levels of 130 MPa, 150 MPa, 180 MPa, and 200 MPa. The shortest creep life (2.53 h) was recorded for the specimen tested at 650 °C and subjected to 200 MPa, whereas the longest creep life (~242 h) was observed for the specimen tested at 650 °C with a stress of 130 MPa. The linear regression model was developed using an applied stress (σ) v/s rupture time (tR) plot at 650 °C. The applied stress and rupture time followed the logarithmic equation: log(tR)=22.57566+(-9.55294) log (σ). The detailed microstructural characterization and micro-hardness distribution across the fractured specimens was carried out. The fndings demonstrated that the service life span of this weld joint at high temperature and stress conditions is infuenced by the undesired microstructural changes at elevated temperature, such as coarsening of the precipitates, development of the Laves phase, softening of the matrix, and strain-ageing phenomenon.

  • Critical graphs upon multiple edge subdivision
    • Magda Dettlaff
    • Magdalena Lemańska
    • Adriana Roux
    2024 Pełny tekst Australasian Journal of Combinatorics

    A subset D of V (G) is a dominating set of a graph G if every vertex of V (G) − D has at least one neighbour in D; let the domination number γ(G) be the minimum cardinality among all dominating sets in G. We say that a graph G is γ-q-critical if subdividing any q edges results in a graph with domination number greater than γ(G) and there exists a set of q − 1 edges such that subdividing these edges results in a graph with domination number γ(G). In this paper we consider mainly γ-qcritical trees and give some general properties of γ-q-critical graphs; in particular, we characterize those trees T that are γ-(n(T) − 1)-critical. We also characterize γ-2-critical trees T with sd(T) = 2 and γ-3-critical trees T with sd(T) = 3, where the domination subdivision number sd(G) of a graph G is the minimum number of edges which must be subdivided (where each edge can be subdivided at most once) to construct a graph with domination number greater than γ(G).

  • Cryptocurrencies as a Speculative Asset: How Much Uncertainty is Included in Cryptocurrency Price?
    • Tayyaba Ahsan
    • Krystian Zawadzki
    • Khan Mubashir
    2024 Pełny tekst SAGE Open

    The aim of this paper is to examine the relationship between uncertainty indices (Geopolitical Uncertainty Index and Global Economic Policy Uncertainty Index) and cryptocurrencies. This study evaluated the behavior of cryptocurrencies with the evolution of uncertainties (GPU, EPU) on returns and volatility in terms of safe heaven as in traditional specualtive assets it increases their volaitility and reduces risk. For this purpose, this study examines the relationship between uncertanities indices, gold returns and crptocurrency by using the OLS regression for the monthly data from April 2017 to April 2022. The findings of this study indicate that the return and volatility of cryptocurrency increases. In particular, we note that the cryptocurrency market could serve as a weak hedge and safe against GEPU during a bull market; It could be considered a strong hedge, but in most cases could not serve as a safety against GPR. However, in case of Gold it is found that it serves as weak hedge against uncertainity indices and is not considered as safe heaven against GEPU and GPR. This study expands the current research on uncertainity indices and provides unique insight about the speculative nature of cryptocurrencies and safe heaven.

  • CuGaS2@NH2-MIL-125(Ti) nanocomposite: Unveiling a promising catalyst for photocatalytic hydrogen generation
    • Anna Pancielejko
    • Hanna Głowienke
    • Magdalena Miodyńska
    • Anna Gołąbiewska
    • Tomasz Klimczuk
    • Mirosław Krawczyk
    • Krzysztof B. Matusiak
    • Adriana Zaleska-Medynska
    2024 Pełny tekst INTERNATIONAL JOURNAL OF HYDROGEN ENERGY

    The development of efficient nanocomposites represents a promising strategy for enhancing the transfer and separation of photogenerated carriers within metal-organic frameworks (MOFs) for photocatalytic H2 generation. In this study, we report, for the first time, the successful fabrication of a novel CuGaS2@NH2-MIL-125(Ti) nanocomposite in a two-step synthesis, consisting of octahedral NH2-MIL-125(Ti) metal-organic frameworks interspersed with flat hexagonal plates of CuGaS2. The CuGaS2@NH2-MIL-125(Ti) nanocomposite effectively mitigates the recombination rate of photogenerated electron-hole pairs. Notably, the most active CuGaS2@NH2-MIL-125(Ti) composite (containing 30 wt% CuGaS2) achieves a remarkable hydrogen generation rate of 965.07 μmol/gcat, surpassing the performance of NH2-MIL-125(Ti) and CuGaS2 by approximately 83 and 144 times, respectively. Additionally, the apparent quantum efficiency for the most active material at a wavelength of 380 nm is 9.07%. This study provides valuable insights into the design of efficient I-III-VI2 compound-MOF nanocomposites for H2 generation applications.

  • CuMn1.7Fe0.3O4 – RE2O3 (RE=Y, Gd) bilayers as protective interconnect coatings for Solid Oxide Cells
    • Bartłomiej Lemieszek
    • Justyna Ignaczak
    • Krystian Lankauf
    • Patryk Błaszczak
    • Maciej Bik
    • Marcin Zajac
    • Maciej Sitarz
    • Piotr Jasiński
    • Sebastian Molin
    2024 Pełny tekst JOURNAL OF THE EUROPEAN CERAMIC SOCIETY

    Efficient replacement of materials based on critical elements such as cobalt is one of the greatest challenges facing the field of solid oxide cells. New generation materials, free of cobalt show potential to replace conventional materials. However, these materials are characterized by poor ability to block chromium diffusion. This article described the study of CuMn1.7Fe0.3O4 (CMFO) spinel combined with single metal oxide (Y2O3 or Gd2O3) thin films as protective coatings for steel interconnects. CMFO was examined using XRD and TPR. Coated steel samples were oxidized in an air atmosphere at 700 °C for 4000 h. The coatings and oxide scale microstructures and cross-sections were examined by CRI, XRD, and SEM-EDX. The electrical properties of the steel-coating system were evaluated using Area Specific Resistance measurements. Based on the results obtained, it can be concluded that the use of thin layers of rare earth oxides allowed for better blocking of chromium diffusion.

  • CUPPING DEFORMATION DURING DRYING OF BEECH WOOD (FAGUS SYLVATICA L.)
    • Ivan Klement
    • Tatiana Vilkovská
    • Peter Vilkovský
    • Aleksandra Suchta
    • Jacek Barański
    2024 Trieskove a Beztrieskove Obrabanie Dreva

    Wood drying does not only consist in removing its moisture: the quality of the dried product is the main requirement for the industrial process. Because wood shrinks during drying, deformations and stresses develops than can lead to unusable product. When developing drying technologies and methods, the aim is to achieve the shortest possible drying times. The most common defects in wood after drying include cross warping (cup), which significantly affects the efficiency of processing the raw material into products. The research was focused on the effect of different drying conditions (temperature, drying gradient) on the size of the cross warping. Despite very intensive drying and large moisture gradients at the end of drying, the values of cross-peeling in beech samples after high temperature drying were small and the positive effect of high temperatures on the amount of drying of the wood was confirmed. A reduction in the size of the cross warping can also be achieved by effective loading of the samples in combination with a more precise control of the high temperature drying process so that smaller values of the moisture gradients of the samples at the end of the drying process are achieved.

  • Current advances in membrane processing of wines: A comprehensive review
    • Youssef El Rayess
    • Roberto Castro Munoz
    • Alfredo Cassano
    2024 Pełny tekst TRENDS IN FOOD SCIENCE & TECHNOLOGY

    Background Membrane-based operations, especially pressure-driven membrane operations, are today well-established procedures for various applications in the wine industry thanks to their intrinsic properties and undoubted advantages over traditional methods. Emerging membrane processes, such as pervaporation, electrodialysis and osmotic distillation, forward osmosis, membrane contactors, offer new and interesting perspectives to improve quality and develop new products without compromising organoleptic properties. Scope and approach This review provides a comprehensive overview on the use of membrane operations in wine processing. A bibliometric and scientometric analysis has been done to provide the current advances dealing with the application of these operations in different steps of wine manufacture, including clarification, stabilization, concentration, acidification, deacidification and dealcoholization. The current challenges and perspectives are highlighted to guide further advancements of membrane technology in this field. Key findings and conclusions The use of conventional and emerging membrane systems offers interesting opportunities to improve and optimize current practices of the wine processing industry. Considerable progress has been done concerning the development of low-fouling materials, identification of wine molecules responsible for membrane fouling and methods to mitigate such phenomenon in the clarification of wines by microfiltration membranes. Technological progress in electrodialysis makes this process a very attractive method for tartrate stabilization, acidification and deacidification of wines. Different conventional and emerging membrane processes offer valid post-fermentation strategies to remove ethanol in wines while preserving their original characteristics. The global results provide interesting perspectives for a wider implementation of membrane processes in the winemaking industry and to redesign the traditional vinification process under the process intensification strategy.

  • Cybersecurity Assessment Methods—Why Aren’t They Used?
    • Rafał Leszczyna
    2024 IT Professional

    A recent survey of cybersecurity assessment methods proposed in academic and research environments revealed that their adoption in operational settings was extremely scarce. At the same time, the frameworks developed by industrial communities have been met with broad reception. The question arises of what contributed to the success of the methods. To answer it, three-part research that employed evaluation criteria, qualitative metrics, and continuity of support assessment was conducted. Among other findings, it shows that the continuity of support plays an important role in the adoption of a method. This, in turn, is connected to a sound funding model and a well-developed and active community of supporters.

  • Cyclic behaviour modelling of additively manufactured Ti-6Al-4V lattice structures
    • Michał Doroszko
    • Andrzej Seweryn
    2024 INTERNATIONAL JOURNAL OF MECHANICAL SCIENCES

    The present work is concerned with the numerical modelling of the cyclic behaviour of Ti-6Al-4V lattice structures. In the study, diamond structures of titanium alloy produced by the additive laser powder bed fusion (LPBF) method with different degrees of relative density were used. Realistic geometric models of the studied mesostructures were generated using computed microtomography, taking into account the imperfections of the material resulting from the manufacturing process. The numerical calculations also took into account the actual material hardening curve in the elastic-plastic strain range. One of the achievements of this work is the numerical modelling of cyclic loading of realistic mesostructures with their imperfections. The areas of the mesostructures most susceptible to fatigue cracking have been identified and analysed. True hysteresis loops and values of local stress and strain amplitude were determined at the locations of highest stress concentration in cyclically loaded diamond structures. The main achievement of the present work was the modelling of the macroscopic fatigue life of the investigated mesostructures based on the true values of stress and strain at the locations most exposed to fatigue cracking. For this purpose, a stress criterion for fatigue cracking of Ti-6Al-4V lattice structures fabricated by the additive LPBF method was proposed.

  • Cyclic deformation and fracture behaviour of additive manufactured maraging steel under variable-amplitude loading
    • Zbigniew Marciniak
    • Ricardo Branco
    • Wojciech Macek
    • Michał Dobrzyński
    • C. Malça
    2024 THEORETICAL AND APPLIED FRACTURE MECHANICS

    The cyclic deformation and fracture behaviour of 18Ni300 maraging steel produced by laser beam powder bed fusion is studied under variable-amplitude loading. The tests were conducted under fully-reversed strain-controlled conditions with a loading sequence comprising three ascending cycles and three descending cycles repeated sequentially until failure. After the tests, fracture surfaces were examined using height and volume surface topography parameters to characterise the fractographic features. Fracture surfaces were also analysed through scanning electron microscopy to identify the main failure modes. Fatigue life was predicted by using the Smith-Watson-Topper and the Basquin-Coffin-Manson models with the Palmgren-Miner damage rule. The former approach was more accurate leading to mean errors close to zero. The values of the kurtosis parameter obtained from both sides of the fracture surfaces correlated well with the fatigue life. SEM analysis showed a mixed ductile-brittle mode of fracture with a predominance of brittle fracture. Crack initiation occurred from manufacturing defects located at the surface or near-surface.

  • Cytocompatibility, antibacterial, and corrosion properties of chitosan/polymethacrylates and chitosan/poly(4‐vinylpyridine) smart coatings, electrophoretically deposited on nanosilver‐decorated titania nanotubes
    • Łukasz Pawłowski
    • Michał Bartmański
    • Anna Ronowska
    • Adrianna Banach-Kopeć
    • Szymon Mania
    • Bartłomiej Cieślik
    • Aleksandra Mielewczyk-Gryń
    • Jakub Karczewski
    • Andrzej Zieliński
    2024 JOURNAL OF BIOMEDICAL MATERIALS RESEARCH PART B-APPLIED BIOMATERIALS

    The development of novel implants subjected to surface modification to achieve high osteointegration properties at simultaneous antimicrobial activity is a highly current problem. This study involved different surface treatments of titanium surface, mainly by electrochemical oxidation to produce a nanotubular oxide layer (TNTs), a subsequent electrochemical reduction of silver nitrate and decoration of a nanotubular surface with silver nanoparticles (AgNPs), and finally electrophoretic deposition (EPD) of a composite of chitosan (CS) and either polymethacrylate-based copolymer Eudragit E 100 (EE100) or poly(4-vinylpyridine) (P4VP) coating. The effects of each stage of this multi-step modification were examined in terms of morphology, roughness, wettability, corrosion resistance, coating-substrate adhesion, antibacterial properties, and osteoblast cell adhesion and proliferation. The results showed that the titanium surface formed nanotubes (inner diameter of 97 ± 12 nm, length of 342 ± 36 nm) subsequently covered with silver nanoparticles (with a diameter of 88 ± 8 nm). Further, the silver-decorated nanotubes were tightly coated with biopolymer films. Most of the applied modifications increased both the roughness and the surface contact angle of the samples. The deposition of biopolymer coatings resulted in reduced burst release of silver. The coated samples revealed potent antimicrobial activity against both Gram-positive and Gram-negative bacteria. Total elimination (99.9%) of E. coli was recorded for a sample with CS/P4VP coating. Cytotoxicity results using hFOB 1.19, a human osteoblast cell line, showed that after 3 days the tested modifications did not affect the cellular growth according to the titanium control. The proposed innovative multilayer antibacterial coatings can be successful for titanium implants as effective postoperative anti-inflammation protection.

  • Czynniki wpływające na rozwój polskich winnic na przykładzie województwa wielkopolskiego
    • Elwira Brodnicka
    2024 Pełny tekst Problemy Jakości

    Cel: Celem głównym artykułu jest określenie ważności czynników wewnętrznych i zewnętrznych wpływających na rozwój polskich winnic na przykładzie województwa wielkopolskiego. Celem pomocniczym jest dokonanie charakterystyki właścicieli tych winnic i ustalenie czynników determinujących decyzję o założeniu winnicy przez inwestora. Projekt badania/metodyka badawcza/koncepcja: Do realizacji celu wykorzystano autorski kwestionariusz ankietowy oraz dane udostępnione przez KOWR. Badanie przeprowadzono metodą CAWI z wykorzystaniem formularza Google Forms. Uzyskane wyniki opracowano za pomocą analizy PCA oraz analizy CA. Przeprowadzono także analizę branży winiarskiej w latach gospodarczych 2011/2012 – 2021/2022. Wyniki/wnioski: W badaniu wzięło udział 11 (52%) właścicieli wielkopolskich winnic. W wyniku przeprowadzonych badań stwierdzono, że najczęściej osobą zakładającą winnicę jest mężczyzna po 50. roku życia. Najbardziej kluczowe predyspozycje mające wpływ na podjęcie decyzji o założeniu winnicy przez inwestora to hobby – czynniki o charakterze biznesowym, zaś o charakterze personalnym – kompetencje menadżerskie. Czynnikami wewnętrznymi ułatwiającymi zakładanie i funkcjonowanie winnic w województwie wielkopolskim są aspekty finansowe i społeczne, zaś czynnikami utrudniającymi – aspekty organizacyjno-zarządcze. Natomiast czynnikami zewnętrznymi ułatwiającymi zakładanie i funkcjonowanie winnic na badanym obszarze są czynniki inicjujące i środowiskowe, zaś czynnikami utrudniającymi są głównie aspekty koniunkturalne. Ograniczenia: Do ograniczeń prowadzonych badań można zaliczyć problem z identyfikacją winnic w województwie wielkopolskim wynikającą z braku ich jednolitego spisu. Zastosowanie praktyczne: Uzyskane wnioski z przeprowadzonych badań mogą stanowić drogowskaz dla potencjalnych inwestorów, wskazując na czynniki ograniczające i sprzyjając powstawaniu i funkcjonowaniu winnic. Oryginalność/wartość poznawcza: Dotychczas w literaturze przedmiotu nie prowadzono badań dotyczących wpływu czynników wewnętrznych i zewnętrznych na rozwój polskich winnic oraz czynników wpływających na podjęcie decyzji przez inwestora o założeniu winnicy

  • Damage detection in 3D printed plates using ultrasonic wave propagation supported with weighted root mean square calculation and wavefield curvature imaging
    • Erwin Wojtczak
    • Magdalena Rucka
    • Angela Andrzejewska
    2024 Pełny tekst

    3D printing (additive manufacturing, AM) is a promising approach to producing light and strong structures with many successful applications, e.g., in dentistry and orthopaedics. Many types of filaments differing in mechanical properties can be used to produce 3D printed structures, including polymers, metals or ceramics. Due to the simplicity of the manufacturing process, biodegradable polymers are widely used, e.g., polylactide (polylactide – PLA) with a practical application for manufacturing complex-shaped elements. The current work dealt with the application of ultrasonic guided waves for non-destructive damage detection and imaging in AM plates. Two specimens with defects were manufactured from PLA filament. Different sizes of damage areas were considered. The specimens were tested using the guided wave propagation technique. The waves were excited using a PZT actuator and recorded contactless with the scanning laser Doppler vibrometry (SLDV) in a set of points located at one surface of the sample. The collected signals were processed with two methods. The first was the weighted root mean square (WRMS) algorithm. Different values of the calculation parameters, namely, averaging time and weighting factor were considered. The WRMS damage maps for both samples were prepared to differentiate between intact and damaged areas. The second approach was wavefield curvature imaging (WCI) which allowed the determination of damage maps based on the curvature of the wavefront. The compensation of wave signals was performed to enhance the quality of results. It was observed that the size of the defect strongly influenced the efficiency of imaging with both methods. The limitations of the proposed approaches were characterized. The presented results confirmed that guided waves are promising for non-destructive damage imaging in AM elements.

  • Damage of a post-tensioned concrete bridge – Unwanted cracks of the girders
    • Bartosz Sobczyk
    • Łukasz Pyrzowski
    • Mikołaj Miśkiewicz
    2024 ENGINEERING FAILURE ANALYSIS

    The cracking of a post-tensioned T-beam superstructure, which was built using the incremental launching method, is analyzed in the paper. The problem is studied in detail, as specific damage was observed in the form of longitudinal cracks, especially in the mid-height zone of the girder at the interface of two assembly sections. The paper is a case study. A detailed inspection is done and non-destructive testing results of the girders are briefly discussed. The attention is especially focused on advanced and comprehensive numerical simulations of the bridge mechanical behavior. Linear and nonlinear static calculations are performed employing the Finite Element Method at global and local levels of precision, enabling deep insight into the bridge response during all the stages of bridge construction and after it is opened to traffic. The crack propagation process in local analyses is described by the application of the Concrete Damage Plasticity law, the parameters of which were carefully chosen. The predicted damage patterns closely resemble those observed at the site. The results reveal, that the girder damage process was initiated when centric prestressing was applied, because vertical reinforcement of the assembly section front-end surface was not designed. However, the damage did not compromise the safety of the bridge. Finally, the repair methods employed are described and also a discussion is presented on how to prevent the occurrence of such cracking.

  • Data Domain Adaptation in Federated Learning in the Breast Mammography Image Classification Problem
    • Łukasz Erimus
    • Aleksandra Borowska
    • Adrian Jaromin
    • Agnieszka Lewko
    • Jacek Rumiński
    2024

    We are increasingly striving to introduce modern artificial intelligence techniques in medicine and elevate medical care, catering to both patients and specialists. An essential aspect that warrants concurrent development is the protection of personal data, especially with technology's advancement, along with addressing data disparities to ensure model efficacy. This study assesses various domain adaptation techniques and federated learning to determine optimal integration strategies for enhanced security and the challenges posed by diverse datasets. Experiments utilized deep learning models, three domain adaptation methods, and a federated learning framework, focusing on mammography imaging for breast cancer detection. Results indicate a notable improvement of up to 20% with domain adaptation and an additional 10% with federated learning integration.

  • Data fusion of sparse, heterogeneous, and mobile sensor devices using adaptive distance attention
    • Jean-Marie Lepioufle
    • Philipp Schneider
    • Paul David Hamer
    • Rune Odegard
    • Islen Vallejo
    • Tuan-Vu Cao
    • Amir Taherkordi
    • Marek Wójcikowski
    2024 Environmental Data Science

    In environmental science, where information from sensor devices are sparse, data fusion for mapping purposes is often based on geostatistical approaches. We propose a methodology called adaptive distance attention that enables us to fuse sparse, heterogeneous, and mobile sensor devices and predict values at locations with no previous measurement. The approach allows for automatically weighting the measurements according to a priori quality information about the sensor device without using complex and resource-demanding data assimilation techniques. Both ordinary kriging and the general regression neural network (GRNN) are integrated into this attention with their learnable parameters based on deep learning architectures. We evaluate this method using three static phenomena with different complexities: a case related to a simplistic phenomenon, topography over an area of 196 km2 and to the annual hourly NO2 concentration in 2019 over the Oslo metropolitan region (1026 km2 ). We simulate networks of 100 synthetic sensor devices with six characteristics related to measurement quality and measurement spatial resolution. Generally, outcomes are promising: we significantly improve the metrics from baseline geostatistical models. Besides, distance attention using the Nadaraya–Watson kernel provides as good metrics as the attention based on the kriging system enabling the possibility to alleviate the processing cost for fusion of sparse data. The encouraging results motivate us in keeping adapting distance attention to space-time phenomena evolving in complex and isolated areas.

  • Data on LEGO sets release dates and worldwide retail prices combined with aftermarket transaction prices in Poland between June 2018 and June 2023
    • Wiktor Oczkoś
    • Bartosz Podgórski
    • Wiktoria Szczepańska
    • Tomasz Maria Boiński
    2024 Pełny tekst Data in Brief

    The dataset contains LEGO bricks sets item count and pricing history for AI-based set pricing prediction. The data spans the timeframe from June 2018 to June 2023. The data was obtained from three sources: Brickset.com (LEGO sets retail prices, release dates, and IDs), Lego.com official web page (ID number of each set that was released by Lego, its retail prices, the current status of the set) and promoklocki.pl web page (the retail prices for Poland, prices from aftermarket transactions). The data was merged based on the official LEGO set ID. With high granularity of the data (averaged monthly prices per LEGO set) the dataset permits the computation of variables at the set level and could support both aggregate and time-series analyses whereas the sparseness of the data permits the analysis of collector behavior allowing pinpointing of expected qualities from the purchased products and their resale potential. This may be useful to a broad range of researchers and data scientists using statistical methods and machine-learning techniques for price prediction.

  • Data science: Not one size fits all. When building models, you need to get your claim categories right from the beginning
    • Piotr Lebiedź
    2024 The Actuary

    When it comes to insurance modelling, there is plenty of material and training on how to build statistical models. We can use these resources to learn about generalised linear models and gradient boosting machines (see feature, overleaf), understanding their advantages and weak points. The same applies to different transformations and techniques, such as splines, variables mapping, geographical classification, finding significant interactions and mitigating adverse selection. The statistics background and modelling best practices are similar across various industries, so a general data science approach is usually good enough for entry-level actuaries – especially given that, in insurance pricing, we usually use commonly known distributions such as Tweedie, Poisson or gamma. But there is one insurance-specific area in predictive modelling: how to structure our actuarial analyses in the first place. Pricing actuaries tend to put a lot of effort into building the most accurate statistical models and optimising their Gini scores, root mean squared error and/or Akaike information criterion, but it’s equally (if not more) important to understand the product and structure risk modelling in the first place. So, how should we split our risk models?

  • Data-Driven Modeling of Mechanical Properties of Fiber-Reinforced Concrete: A Critical Review
    • Farzin Kazemi
    • Torkan Shafighfard
    • Doo-Yeol Yoo
    2024 ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING

    Fiber-reinforced concrete (FRC) is extensively used in diverse structural engineering applications, and its mechanical properties are crucial for designing and evaluating its performance. The compressive, flexural, splitting tensile, and shear strengths of FRCs are among the most important attributes, which have been discussed more extensively than other properties. The accurate prediction of these properties, which are required for design criteria, has been a challenge because of their high uncertainties. Statistical and empirical models have been extensively utilized. However, such models require extensive experimental work and can produce incorrect outcomes when there are complicated interactions among the qualities of concrete, the makeup of the blend, and the curing environment. To address this issue, machine learning (ML) methods have been increasingly applied in recent years to solve complex structural engineering problems. Predictive models can provide a strong solution for time-consuming numerical simulations and expensive experiments. This study explores the ML techniques applied in this context and provides a comprehensive analysis of artificial intelligence methods used for predicting the mechanical properties of FRCs. It also highlights the key observations, challenges, and future trends in this field. This study serves as a valuable resource for researchers in selecting accurate models that match their applications. It also encourages material engineers to become familiar with and employ ML methods to design FRC mixtures appropriately.

  • Data-driven Models for Predicting Compressive Strength of 3D-printed Fiber-Reinforced Concrete using Interpretable Machine Learning Algorithms
    • Muhammad Arif
    • Faizullah Jan
    • Aïssa Rezzoug
    • Muhammad Ali Afridi
    • Muhammad Luqman
    • Waseem Akhtar Khan
    • Marcin Kujawa
    • Hisham Alabduljabbar
    • Majid Khan
    2024 Case Studies in Construction Materials

    3D printing technology is growing swiftly in the construction sector due to its numerous benefits, such as intricate designs, quicker construction, waste reduction, environmental friendliness, cost savings, and enhanced safety. Nevertheless, optimizing the concrete mix for 3D printing is a challenging task due to the numerous factors involved, requiring extensive experimentation. Therefore, this study used three machine learning techniques, including Gene Expression Programming (GEP), Multi-Expression Programming (MEP), and Decision Tree (DT), to forecast the compressive strength of 3D printed fiber-reinforced concrete (3DP-FRC). The dataset comprises 299 data points with sixteen variables gathered from experimental research studies. For training the model, 70% of the dataset was used, while the remaining 30% was reserved for model testing. Several statistical metrics were utilized to evaluate the accuracy and applicability of the models. In addition, SHapley Additive exPlanations (SHAP), partial dependence plots, and individual conditional expectations approach were employed for the interpretability of the models. The proposed GEP, MEP, and DT models indicated enhanced efficacy, exhibiting correlation coefficient (R) scores of 0.996, 0.987, and 0.990, with mean absolute errors (MAE) of 1.029, 4.832, and 2.513, respectively. Overall, the established GEP model demonstrated exceptional performance compared to MEP and DT, showcasing high prediction precision in assessing the strength of 3DP-FRC. Moreover, a simple empirical formulation has been devised using GEP to predict the compressive strength, offering a simplified and efficient approach for predicting 3DP-FRC strength. The SHAP approach identified water, silica fume, fiber diameter, curing age, and loading directions as leading controlling parameters in predicting strength of 3DP-FRC. In summary, the proposed models can potentially minimize both the computational workload and the need for experimental trials in formulating the mixed design of 3D-printed concrete.

  • Dataset Characteristics and Their Impact on Offline Policy Learning of Contextual Multi-Armed Bandits
    • Piotr Januszewski
    • Dominik Grzegorzek
    • Paweł Czarnul
    2024 Pełny tekst

    The Contextual Multi-Armed Bandits (CMAB) framework is pivotal for learning to make decisions. However, due to challenges in deploying online algorithms, there is a shift towards offline policy learning, which relies on pre-existing datasets. This study examines the relationship between the quality of these datasets and the performance of offline policy learning algorithms, specifically, Neural Greedy and NeuraLCB. Our results demonstrate that NeuraLCB can learn from various datasets, while Neural Greedy necessitates extensive coverage of the action-space for effective learning. Moreover, the way data is collected significantly affects offline methods’ efficiency. This underscores the critical role of dataset quality in offline policy learning.

  • Daylight metrics and requirements: A review of reference documents for architectural practice
    • Amanda Pinheiro, Moura
    • Claudia David Naves
    • Natalia Sokół
    • Justyna Martyniuk-Pęczek
    2024 Pełny tekst

    Daylight has always been part of architectural practice since architects have used it to define spaces and create complex structures. Daylighting is, nowadays, seen as key strategy for sustainability, energy efficiency and resilience in buildings. This article aims to investigate daylight requirements in reference documents for architectural practice through the collection and qualitative analysis of documents. 117 reference documents were analysed and divided into standards, rating systems, building and urban codes, regulations and guidelines. Results show that static and dynamic metrics are common within standards and rating systems while building and urban codes and regulations often use metrics based on building and urban geometry. Among standards and rating systems, Daylight Factor (DF) is still one of the most used metrics, even if dynamic metrics offer advanced analyses; building and urban codes and regulations are very specific for each location, with a predominant use of geometric metrics; and guidelines can use both types of metrics.

  • Dc Leakage Current in Isolated Grid-Connected dc Nanogrid - Origins and Elimination Methods
    • Mohammadreza Azizi
    • Oleksandr Husev
    • Oleksandr Veligorskyi
    • Marek Turzyński
    • Ryszard Strzelecki
    2024

    The LV dc system is a relatively new trend in the distribution sector, which seems to grow widely in the near future due to its promising advantages. In this context, LV dc protection and grounding are challenging issues. Although the galvanically isolated connection mode of dc nanogrid to the ac grid has high reliability, the leakage current can still be injected into the ac grid through the interwinding capacitors and the insulation resistance between the primary and secondary windings of the transformer. The way of grounding the dc nanogrid can also be a determining factor in the leakage current and its dc components. This study deals with the leakage current in the galvanically isolated dc nanogrid. Then, it examines the dc leakage current and its relationship with the dc nanogrid grounding and finally provides solutions to remove the dc components in the leakage current.

  • Dead time effects compensation strategy by third harmonic injection for a five-phase inverter
    • Krzysztof Łuksza
    • Dmytro Kondratenko
    • Arkadiusz Lewicki
    2024 Pełny tekst Archives of Electrical Engineering

    This paper proposes a method for compensation of dead-time effects for a fivephase inverter. In the proposed method an additional control subsystem was added to the field-oriented control (FOC) scheme in the coordinate system mapped to the third harmonic. The additional control loop operates in the fixed, orthogonal reference frame ( α - β coordinates) without the need for additional Park transformations. The purpose of this method is to minimize the dead-time effects by third harmonic injection in two modes of operation of the FOC control system: with sinusoidal supply and with trapezoidal supply. The effectiveness of the proposed control method was verified experimentally on a laboratory setup with a prototype five-phase interior permanent magnet synchronous machine (IPMSM). All experimental results were presented and discussed in the following paper.

  • Decisional-DNA-Based Digital Twin Implementation Architecture for Virtual Engineering Objects
    • Syed Imran Shafiq
    • Cesar Sanin
    • Edward Szczerbicki
    2024 Pełny tekst CYBERNETICS AND SYSTEMS

    Digital twin (DT) is an enabling technology that integrates cyber and physical spaces. It is well-fitted for manufacturing setup since it can support digitalized assets and data analytics for product and process control. Conventional manufacturing setups are still widely used all around the world for the fabrication of large-scale production. This article proposes a general DT implementation architecture for engineering objects/artifacts used in conventional manufacturing. It will empower manufacturers to leverage DT for real-time decision-making, control, and prediction for efficient production. An application scenario of Decisional-DNA based anomaly detection for conventional manufacturing tools is demonstrated as a case study to explain the architecture.

  • Decision-making under stress: A psychological and neurobiological integrative model
    • Luis Sarmiento Rivera
    • Pamela Lopes da Cunha
    • Sonia Tabares
    • Gustavo Tafet
    • Amauri Gouveia Jr
    2024 Brain, Behavior, and Immunity - Health

    Understanding the impact of stress on cognitive processes, particularly decision-making, is crucial as it underpins behaviors essential for survival. However, research in this domain has yielded disparate results, with inconsistencies evident across stress-induction paradigms and drug administration protocols designed to investigate specific stress pathways or neuromodulators. Building upon empirical studies, this research identifies a multifaceted matrix of variables contributing to the divergent findings. This matrix encompasses factors such as the temporal proximity between stressors and decision tasks, the nature of stressors and decision contexts, individual characteristics including psychobiological profiles and affective states at the time of decision-making and even cultural influences. In response to these complexities, we propose a comprehensive model that integrates these relevant factors and their intricate interplay to elucidate the mechanisms governing decision-making during stressful events. By synthesizing these insights, our model not only refines existing paradigms but also provides a framework for future study designs, offering avenues for theoretical advancements and translational developments in the field of stress's impact on cognitive functions. This research contributes to a deeper understanding of the nuanced relationship between stress and decision-making, ultimately advancing our knowledge of cognitive processes under challenging conditions.

  • Decoding imagined speech for EEG-based BCI
    • Carlos A. Reyes-García
    • Alejandro A. Torres-García
    • Tonatiuh Hernández-del-Toro
    • Jesus Garcia Salinas
    • Luis Villaseñor-Pineda
    2024

    Brain–computer interfaces (BCIs) are systems that transform the brain's electrical activity into commands to control a device. To create a BCI, it is necessary to establish the relationship between a certain stimulus, internal or external, and the brain activity it provokes. A common approach in BCIs is motor imagery, which involves imagining limb movement. Unfortunately, this approach allows few commands. As an alternative, this chapter presents another approach, an internal language-related stimulus known as imagined speech, which is the action of imagining the diction of a word without emitting any sound or articulating any movement. This neuroparadigm is more intuitive, less subjective, and ambiguous, which are very relevant advantages; however, the cost to properly process the brain signal is not trivial. This chapter describes the main components of an EEG-based imagined speech BCI, along with key works, emerging trends, and challenges in this research area. Regarding the challenges, we present four of them in the pursuit of decoding imagined speech. The first challenge involves accurately recognizing isolated words. The second one is the automatic selection of a subset of EEG channels aiming to reduce computational cost and provide evidence of promising locations for studying imagined speech. The third challenge introduces an innovative approach to addressing scenarios where a new word needs to be added to the vocabulary after the computational model has been trained. Lastly, the fourth challenge concerns the online recognition of words from continuous EEG signals. Despite advances in the area, there is still much work to be done. Important initial steps have been taken in terms of the application of novel techniques for preprocessing, artifact removal, feature extraction, and classification which are the stages to be taken to process the collected signal. Additionally, the community has shared datasets and organized evaluation forums to accelerate the search for solutions.