Publications Repository - Gdańsk University of Technology

Page settings

polski
Publications Repository
Gdańsk University of Technology

Show publications from the year

Recent items

  • Linear Time-Varying Dynamic-Algebraic Equations of Index One on Time Scales
    • Svetlin Georgiev
    • Sergey Kryzhevich
    2024

    In this paper, we introduce a class of linear time-varying dynamic-algebraic equations (LTVDAE) of tractability index one on ar- bitrary time scales. We propose a procedure for the decoupling of the considered class LTVDAE. Explicit formulae are written down both for transfer operator and the obtained decoupled system. A projector ap- proach is used to prove the main statement of the paper and sufficient conditions of decoupling are also written down explicitly.

  • Local basis function method for identification of nonstationary systems
    • Artur Gańcza
    2024 Full text

    This thesis is focused on the basis function method for the identification of nonstationary processes. The first chapter describes a group of models that can be identified using the basis function method. The next chapter describes the basic version of the basis function method, including its algebraic and statistical properties. The following section introduces the local basis function (LBF) method: its properties are described and similarities and differences between LBF and the basic basis function method are highlighted. The main difference lies in the approach to estimation. The primary version of the basis function method provides estimates for the entire analysis interval. The analysis window is then shifted so that estimates can be found for the next set of observations. In the case of the LBF method, the data from the analysis window are used to find parameter estimates for only one time instant within the analysis interval. The window is then moved to the subsequent observation and the estimation process is repeated. As a result, one obtains more accurate estimates at the expense of the increased computational burden.

  • Long-range, water-mediated interaction between a moderately active antifreeze protein molecule and the surface of ice
    • Joanna Grabowska
    • Anna Kuffel
    • Jan Zielkiewicz
    2024 JOURNAL OF CHEMICAL PHYSICS

    Using molecular dynamics simulations, we show that a molecule of moderately active antifreeze protein (type III AFP, QAE HPLC-12 isoform) is able to interact with ice in an indirect manner. This interaction occurs between the ice binding site (IBS) of the AFP III molecule and the surface of ice, and it is mediated by liquid water which separates these surfaces. As a result, the AFP III molecule positions itself at a specific orientation and distance relative to the surface of ice, which enables the effective binding (via hydrogen bonds) of the molecule with the nascent ice surface. Our results show that the final adsorption of the AFP III molecule on the surface of ice is not achieved by chaotic diffusion movements, but it is preceded by a remote, water-mediated interaction between the IBS and the surface of ice. The key factor that determines the existence of this interaction is the ability of water molecules to spontaneously form large, high-volume aggregates which can be anchored to both the IBS of the AFP molecule and the surface of ice. The results presented in this work for AFP III are in full agreement with the ones obtained by us previously for hyperactive CfAFP, which indicates that the mechanism of the remote interaction of these molecules with ice remains unchanged despite significant differences in the molecular structure of their ice binding sites. For that reason we can expect that also other types of AFPs interact with the ice surface according to an analogous mechanism.

  • Looking For Motivation. How to Keep Students’ Software Projects from Ending up on the Shelf?
    • Teresa Zawadzka
    • Michał Zawadzki
    • Agnieszka Landowska
    2024

    IT specialists in the business environment work in teams according to the established methodology and using the established toolkit. From the university’s point of view, preparing IT students to work in such an environment is a challenging task, as it requires either cooperation with business or the simulation of similar conditions in the university environment. Participation of students in real projects can provide them with the necessary practical skills. The aim of this paper is to present the experience gained in running real-life, long-term projects in academia, and to provide guidelines on how to involve students in running these projects to the benefit of students.

  • Looking through the past: better knowledge retention for generative replay in continual learning
    • Valeriya Khan
    • Sebastian Cygert
    • Kamil Deja
    • Tomasz Trzciński
    • Bartłomiej Twardowski
    2024 Full text IEEE Access

    In this work, we improve the generative replay in a continual learning setting to perform well on challenging scenarios. Because of the growing complexity of continual learning tasks, it is becoming more popular, to apply the generative replay technique in the feature space instead of image space. Nevertheless, such an approach does not come without limitations. In particular, we notice the degradation of the continually trained model’s performance could be attributed to the fact that the generated features are far from the original ones when mapped to the latent space. Therefore, we propose three modifications that mitigate these issues. More specifically, we incorporate the distillation in latent space between the current and previous models to reduce feature drift. Additionally, a latent matching for the reconstruction and original data is proposed to improve generated features alignment. Further, based on the observation that the reconstructions are better for preserving knowledge, we add the cycling of generations through the previously trained model to make them closer to the original data. Our method outperforms other generative replay methods in various scenarios. Code available at https://github.com/valeriya-khan/looking-through-the-past.

  • Low temperature rotary Stirling engine: conceptual design and theoretical analysis
    • Jacek Kropiwnicki
    2024 APPLIED THERMAL ENGINEERING

    The use of low-temperature energy sources for electricity generation demands a dual focus: a substantial enhancement in the efficiency of energy conversion devices and a reduction in system production costs. Particularly in scenarios where low-temperature energy sources are scarce, this factor can be pivotal in facilitating widespread adoption of such technologies. The Stirling engine emerges as a promising solution capable of meeting these articulated expectations, owing to its straightforward design and utilization of non-toxic, non-flammable, and cost-effective working mediums. This paper introduces a novel concept of a rotary Stirling engine, exhibiting significant potential for operation with low-temperature energy sources. Additionally, an analytical model of the engine is presented, enabling simulations of its operation under varying supply temperatures and geometric configurations. To analyse the impact of internal leaks on the net efficiency and net power of the engine, a modified adiabatic model was introduced. It was observed that utilizing identical heat exchangers for heat supply at 250°C and 100°C could lead to a decline in net efficiency from 8% to 3% for the worst case. Furthermore, an analysis was performed to assess the impact of the heater's overall heat transfer coefficient and engine rotational speed on both net efficiency and net mechanical power for a heat supply temperature of 200°C.

  • Low-Barrier Hydrogen Bond Determines Target-Binding Affinity and Specificity of the Antitubercular Drug Bedaquiline
    • Joanna Słabońska
    • Subrahmanyam Sappati
    • Antoni Marciniak
    • Jacek Czub
    2024 ACS Medicinal Chemistry Letters

    The role of short strong hydrogen bonds (SSHB) in ligand-target binding remains largely unexplored, thereby hin- dering a potentially important avenue in the rational drug de- sign. Here, we investigate the interaction between bedaquiline (Bq), a potent anti-tuberculosis drug, and the mycobacterial ATP synthase, to unravel the role of a specific hydrogen bond to a conserved acidic residue in the target affinity and specificity. Our ab initio molecular dynamics simulations reveal that this bond belongs to the SSHB category and accounts for a substan- tial fraction of the target binding energy. We also demonstrate that the presence of an extra acidic residue (D32), found exclu- sively in mycobacteria, cooperatively enhances the HB strength ensuring the specificity for the mycobacterial target. Consis- tently, we show that the removal of D32 markedly weakens the affinity, leading to Bq resistance associated with mutations of D32 to non-acidic residues. By designing simple Bq analogs, we then explore the possibility to overcome the resistance and po- tentially broaden the Bq antimicrobial spectrum by making the SSHB independent on the presence of the extra acidic residue.

  • Low-Cost and Precise Automated Re-Design of Antenna Structures Using Interleaved Geometry Scaling and Gradient-Based Optimization
    • Anna Pietrenko-Dąbrowska
    • Sławomir Kozieł
    2024 KNOWLEDGE-BASED SYSTEMS

    Design of contemporary antennas is an intricate endeavor involving multiple stages, among others, tuning of geometry parameters. In particular, re-designing antennas to different operating frequencies, makes parametric optimization imperative to ensure the best achievable system performance. If the center frequency at the current design is distant from the target one, local tuning methods generally fail, whereas global algorithms (e.g., nature-inspired procedures) incur prohibitive computational expenses, especially when antenna evaluation is performed using full-wave electromagnetic (EM) analysis. In this paper, a novel technique involving automated decision-making has been developed, whose main objective is low-cost and precise re-design of antenna structures over wide ranges of operating frequencies. The employed methodology involves knowledge-based simultaneous scaling of antenna dimensions and gradient-based performance improvements. The two stages are automatically interleaved, and embedded into an iterative optimization procedure. The problem-specific knowledge allows for carrying out the scaling phase, in which fast relocation of the center frequency of the antenna is performed, based on a single EM analysis of the structure. The gradient-based tuning phase enhances the design quality with regard to the assumed objectives. The process defaults to local optimization after the antenna center frequency becomes sufficiently close to the target. The main novelty of the proposed algorithm consists in development of an automated knowledge-based framework of quasi-global search capabilities linking brute-force scaling and design refinement. Our technique has been demonstrated with the use of three microstrip antennas, optimized for best matching and maximum in-band gain. The main findings are that for all structures, satisfactory designs have been identified despite poor starting points, with operating frequencies being away from the assumed targets. At the same time, the computational cost is comparable to conventional local search. The proposed approach is versatile, simple to implement and easy to handle, in particular, its control parameters do not require tailoring to a specific antenna structure at hand.

  • Low-Cost Method for Internal Surface Roughness Reduction of Additively Manufactured All-Metal Waveguide Components
    • Jakub Sorocki
    • Ilona Piekarz
    • Michał Baranowski
    • Adam Lamęcki
    • Alberto Cattenone
    • Stefania Marconi
    • Gianluca Alaimo
    • Nicolo Delmonte
    • Lorenzo Silvestri
    • Bozzi Maurizio
    2024 Full text IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES

    In this study, a novel low-cost polishing method for internal surface roughness reduction of additively manufactured components, developed for waveguide (WG) circuits operating in the millimeter frequency range is proposed. WG components fabricated using powder bed fusion (PBF) generally feature roughness of ten to fifty microns, which influences the increase of roughness-related conductor power losses having a major effect on the electrical performance of additively manufactured allmetal WGs. To improve and decrease the surface roughness of circuits fabricated using PBF, glass microbeads as an abrasive medium are proposed to be used in combination with a rotary tumbler. This technique allows the abrasive medium to efficiently penetrate internal long channels and cavities, having cross section dimensions in the range of sub- to a few millimeters. An experimental study was carried out on an example of WG sections and bandpass filters fabricated using PBF through selective laser melting (SLM), operating within the 8.2 to 40 GHz range. Polishing impact on both mechanical and electrical properties was studied showing surface roughness reduction by 18% and sixth order filter’s insertion loss reduction at 23 GHz by 40% after 24 h of tumbling with 300–400 µm large glass microbeads.

  • Low-cost multiband four-port phased array antenna for sub-6 GHz 5G applications with enhanced gain methodology in Radio-over-fiber systems using modulation instability
    • Hassan Zakeri
    • Rasul Azizpour
    • Parsa Khoddami
    • Gholamreza Moradi
    • Mohammad Alibakhshikenari
    • Chan Hwang See
    • Tayeb Dendini
    • Francisco Falcone
    • Sławomir Kozieł
    • Ernesto Limiti
    2024 Full text IEEE Access

    Phased array antenna (PAA) technology is essential for applications requiring high gain and wide bandwidth, such as sensors, medical, and 5G. Achieving such a design, however, is a challenging and intricate process that calls for precise calculations and a combination of findings to alter the phase and amplitude of each unit. Furthermore, coupling effects between these PAA structure elements can only be completed with the use of full-wave electromagnetic simulation tools. Due to recent advances, radio-over-fiber (RoF) technology has been positioned as a possible alternative for high-capacity wireless communications. This paper presents a low-cost, multiband Sub-6 GHz 5G PAA with enhanced gain achieved through integration with a new specialized RoF system design to improve PAA performance by using the phenomenon of modulation instability (MI). Optimizing the antenna’s Defected Ground Structure (DGS) leads to even more improvement. To enable operation across three distinct frequency bands (Sub6 GHz n78 band (3-3.8 GHz), n79 band (3.8-5 GHz), and n46 band (5-5.5 GHz)), the proposed antenna design features four elliptical patches strategically positioned at the four sides of the ground plane, providing comprehensive 360° coverage in the azimuth plane. Additionally, integrating elliptical slots and upper gaps contributes to improvement. The proposed PAA’s experimentally validated gain values are 5.2 dB, 7.4 dB, and 7.8 dB in the n78, n79, and n46 bands, respectively. For improving the performance of the proposed PAA in RoF systems, anomalous fibers (n2 ̸= 0 and β2 < 0) are employed to consider the modulation instability (MI) phenomenon, which can lead to the generation of the MI gain on the carrier sideband. The true time delay (TTD) technique controls the beam pattern by adjusting the time delay between adjacent radiation elements. Furthermore, the TTD technique utilizes frequency combs for the proposed 4-element array antenna to apply MI gain to all antenna elements.

  • Low-Loss 3D-Printed Waveguide Filters Based on Deformed Dual-Mode Cavity Resonators
    • Michał Baranowski
    • Łukasz Balewski
    • Adam Lamęcki
    • Michał Mrozowski
    2024 Full text IEEE Access

    This paper introduces a new type of waveguide filter with smooth profile, based on specially designed dual-mode (DM) cavity resonators. The DM cavity design is achieved by applying a shape deformation scheme. The coupling between the two orthogonal cavity modes is implemented by breaking the symmetry of the structure, thus eliminating the need for additional coupling elements. The modes operating in the cavity are carefully analyzed and a scheme for managing the spurious modes is discussed. Two filter prototypes employing the designed DM cavities are developed and described in detail. The first design is a fourth-order bandpass filter (BPF) with a 90◦ rotated output and a transmission zero (TZ), whereas the second design is an eighth-order filter with four TZs. Both designs are developed, taking into account the limitations of 3D printing technology to enable their single-piece fabrication without internal supports. The structures benefit from additive manufacturing (AM) by having a smooth surface profile and reduced weight, which is often highly desirable for high-power and low-loss applications. Filter prototypes were manufactured using selective laser melting (SLM) from aluminum alloy and tested to validate the designs. Measurement results are consistent with the simulation and prove the validity of the proposed solutions. Both measured BPF prototypes demonstrate low insertion loss, i.e., 0.11 dB and 0.25 dB for the fourth-order and eighthorder designs, respectively. The estimated Q-factors reach 3500 and 4500, which is a very good result for 3D-printed parts.

  • LSA Is not Dead: Improving Results of Domain-Specific Information Retrieval System Using Stack Overflow Questions Tags
    • Szymon Olewniczak
    • Julian Szymański
    • Piotr Malak
    • Robert Komar
    • Agnieszka Letowska
    2024 Full text

    The paper presents the approach to using tags from Stack Overflow questions as a data source in the process of building domain-specific unsupervised term embeddings. Using a huge dataset of Stack Overflow posts, our solution employs the LSA algorithm to learn latent representations of information technology terms. The paper also presents the Teamy.ai system, currently developed by Scalac company, which serves as a platform that helps match IT project inquiries with potential candidates. The heart of the system is the information retrieval module that searches for the best-matching candidates according to the project requirements. In the paper, we used our pre-trained embeddings to enhance the search queries using the query expansion algorithm from the neural information retrieval domain. The proposed solution improves the precision of the retrieval compared to the basic variant without query expansion.

  • Łukowy wiadukt Pomorskiej Kolei Metropolitalnej w Gdańsku. Założenia projektowe i stan techniczny po 10 latach eksploatacji
    • Krzysztof Żółtowski
    • Przemysław Kalitowski
    • Mikołaj Binczyk
    • Tomasz Romaszkiewicz
    2024 Mosty

    Artykuł przedstawia historię, projektowanie i ocenę techniczną po 10 latach eksploatacji wiaduktu WK11 w Gdańsku, będącego częścią Pomorskiej Kolei Metropolitalnej. Opisuje proces budowy i wyzwania związane z rekonstrukcją historycznego mostu z 1914 roku, który został zniszczony podczas II wojny światowej. Autorzy szczegółowo analizują koncepcje projektowe, w tym rozważania nad schematem statycznym i zastosowanym materiałem. W artykule zawarto wyniki zaawansowanych analiz numerycznych, które doprowadziły do ostatecznego kształtu wiaduktu. Po 10 latach użytkowania wiadukt WK11 nadal jest w dobrym stanie technicznym, a jedyne zauważalne ślady zużycia to drobne rysy skurczowe. Konstrukcja działa zgodnie z założeniami projektowymi.

  • Machine learning approach to packaging compatibility testing in the new product development process
    • Norbert Piotrowski
    2024 Full text JOURNAL OF INTELLIGENT MANUFACTURING

    The paper compares the effectiveness of selected machine learning methods as modelling tools supporting the selection of a packaging type in new product development process. The main goal of the developed model is to reduce the risk of failure in compatibility tests which are preformed to ensure safety, durability, and efficacy of the finished product for the entire period of its shelf life and consumer use. This kind of testing is mandatory inter alia for all aerosol packaging as any mechanical alterations of the packaging can cause the pressurized product to unseal and stop working properly. Moreover, aerosol products are classified as dangerous goods and any leaking of the product or propellent can be a serious hazard to the storage place, environment, and final consumer. Thus, basic compatibility observations of metal aerosol packaging (i.e. general corrosion, pitting corrosion, coating blistering or detinning) and different compatibility factors (e.g. formula ingredients, water contamination, pH, package material and coatings) were discussed. Artificial intelligence methods applied in the design process can reduce the lengthy testing time as well as developing costs and help benefit from the knowledge and experience of technologists stored in historical data in databases.

  • Machine learning for the management of biochar yield and properties of biomass sources for sustainable energy
    • Giao Van Nguyen
    • Prabhakar Sharma
    • Ümit Ağbulut
    • Huu Son Le
    • Thanh Hai Truong
    • Marek Dzida
    • Minh Ho Tran
    • Huu Cuong Le
    • Viet Dung Tran
    2024 Biofuels Bioproducts & Biorefining-Biofpr

    Biochar is emerging as a potential solution for biomass conversion to meet the ever increasing demand for sustainable energy. Efficient management systems are needed in order to exploit fully the potential of biochar. Modern machine learning (ML) techniques, and in particular ensemble approaches and explainable AI methods, are valuable for forecasting the properties and efficiency of biochar properly. Machine-learning-based forecasts, optimization, and feature selection are critical for improving biomass management techniques. In this research, we explore the influences of these techniques on the accurate forecasting of biochar yield and properties for a range of biomass sources. We emphasize the importance of the interpretability of a model, as this improves human comprehension and trust in ML predictions. Sensitivity analysis is shown to be an effective technique for finding crucial biomass characteristics that influence the synthesis of biochar. Precision prognostics have far-reaching ramifications, influencing industries such as biomass logistics, conversion technologies, and the successful use of biomass as renewable energy. These advances can make a substantial contribution to a greener future and can encourage the development of a circular biobased economy. This work emphasizes the importance of using sophisticated data-driven methodologies such as ML in biochar synthesis, to usher in ecologically friendly energy solutions. These breakthroughs hold the key to a more sustainable and environmentally friendly future.

  • Machine Learning-Based Wetland Vulnerability Assessment in the Sindh Province Ramsar Site Using Remote Sensing Data
    • Rana Waqar Aslam
    • Hong Shu
    • Iram Naz
    • Abdul Quddoos
    • Andaleeb Yaseen
    • Khansa Gulshad
    • Saad Saud Alarifi
    2024 Full text Remote Sensing

    Wetlands provide vital ecological and socioeconomic services but face escalating pressures worldwide. This study undertakes an integrated spatiotemporal assessment of the multifaceted vulnerabilities shaping Khinjhir Lake, an ecologically significant wetland ecosystem in Pakistan, using advanced geospatial and machine learning techniques. Multi-temporal optical remote sensing data from 2000 to 2020 was analyzed through spectral water indices, land cover classification, change detection and risk mapping to examine moisture variability, land cover modifications, area changes and proximity-based threats over two decades. The random forest algorithm attained the highest accuracy (89.5%) for land cover classification based on rigorous k-fold cross-validation, with a training accuracy of 91.2% and a testing accuracy of 87.3%. This demonstrates the model’s effectiveness and robustness for wetland vulnerability modeling in the study area, showing 11% shrinkage in open water bodies since 2000. Inventory risk zoning revealed 30% of present-day wetland areas under moderate to high vulnerability. The cellular automata–Markov (CA–Markov) model predicted continued long-term declines driven by swelling anthropogenic pressures like the 29 million population growth surrounding Khinjhir Lake. The research demonstrates the effectiveness of integrating satellite data analytics, machine learning algorithms and spatial modeling to generate actionable insights into wetland vulnerability to guide conservation planning. The findings provide a robust baseline to inform policies aimed at ensuring the health and sustainable management and conservation of Khinjhir Lake wetlands in the face of escalating human and climatic pressures that threaten the ecological health and functioning of these vital ecosystems.

  • Machine-learning methods for estimating compressive strength of high-performance alkali-activated concrete
    • Torkan Shafighfard
    • Farzin Kazemi
    • Neda Asgarkhani
    • Doo-Yeol Yoo
    2024 ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE

    High-performance alkali-activated concrete (HP-AAC) is acknowledged as a cementless and environmentally friendly material. It has recently received a substantial amount of interest not only due to the potential it has for being used instead of ordinary concrete but also owing to the concerns associated with climate change, sustainability, reduction of CO2 emissions, and energy consumption. The characteristics and amounts of the ingredients used to produce HP-AAC influence its compressive strength. This study performs a comparative analysis based on machine learning (ML) algorithms to present an ensemble model capable of predicting the compressive strength of HP-AAC. This is in response to the development of sophisticated prediction approaches that seek to lower the cost of experimental tools and labor. An extensive framework including 538 experimental datasets with 18 input parameters are extracted. In addition, stacked ML (SM) models are developed to provide their best base estimator combination with the highest capability. The results show that stacked model (SM-5) with score of 14, and prediction accuracy of 98% following by the largest experiment-to-predicted ratio, provide the best estimations of compressive strength of HP-AAC, which has the lowest error values compare to other 18 ML models. Thereafter, a graphical user interface (GUI) is provided and validated by extra experimental tests for estimating the compressive strength, cost, and carbon emission of HP-AAC. Overall, the significance of the current study highlight the outstanding performance of developed stacked ML and GUI for predicting the compressive strength of HP-ACC, which contribute for the on-going research in this area.

  • Machine-Learning Methods for Estimating Performance of Structural Concrete Members Reinforced with Fiber-Reinforced Polymers
    • Farzin Kazemi
    • Neda Asgarkhani
    • Torkan Shafighfard
    • Robert Jankowski
    • Doo-Yeol Yoo
    2024 ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING

    In recent years, fiber-reinforced polymers (FRP) in reinforced concrete (RC) members have gained significant attention due to their exceptional properties, including lightweight construction, high specific strength, and stiffness. These attributes have found application in structures, infrastructures, wind power equipment, and various advanced civil products. However, the production process and the extensive testing required for assessing their suitability incur significant time and cost. The emergence of Industry 4.0 has presented opportunities to address these drawbacks by leveraging machine learning (ML) methods. ML techniques have recently been used to forecast the properties and assess the importance of process parameters for efficient structural design and their broad applications. Given their wide range of applications, this work aims to perform a comprehensive analysis of ML algorithms used for predicting the mechanical properties of FRPs. The performance evaluation of various models was discussed, and a detailed analysis of their pros and cons was provided. Finally, the limitations that currently exist in these techniques were pinpointed, and suggestions were given to improve their prediction precision suitable for evaluating the mechanical properties of FRP components.

  • Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
    • Sławomir Kozieł
    • Anna Pietrenko-Dąbrowska
    2024 Full text Scientific Reports

    Maximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit reliability, but the expense of conducting rudimentary EM-driven global optimization by means of popular bio-inspired algorithms is impractical. Similarly, nonlinear system characteristics pose challenges for surrogate-assisted methods. This paper introduces an innovative technique leveraging variable-fidelity EM simulations and response feature technology within a kriging-based machine-learning framework for cost-effective global parameter tuning of microwave passives. The efficiency of this approach stems from performing most operations at the low-fidelity simulation level and regularizing the objective function landscape through the response feature method. The primary prediction tool is a co-kriging surrogate, while a particle swarm optimizer, guided by predicted objective function improvements, handles the search process. Rigorous validation demonstrates the proposed framework's competitive efficacy in design quality and computational cost, typically requiring only sixty high-fidelity EM analyses, juxtaposed with various state-of-the-art benchmark methods. These benchmarks encompass nature-inspired algorithms, gradient search, and machine learning techniques directly interacting with the circuit's frequency characteristics.

  • Machine-learning-based precise cost-efficient NO2 sensor calibration by means of time series matching and global data pre-processing
    • Sławomir Kozieł
    • Anna Pietrenko-Dąbrowska
    • Marek Wójcikowski
    • Bogdan Pankiewicz
    2024 Full text Engineering Science and Technology-An International Journal-JESTECH

    Air pollution remains a considerable contemporary challenge affecting life quality, the environment, and economic well-being. It encompasses an array of pollutants—gases, particulate matter, biological molecules—emanating from sources such as vehicle emissions, industrial activities, agriculture, and natural occurrences. Nitrogen dioxide (NO2), a harmful gas, is particularly abundant in densely populated urban areas. Given its detrimental impact on health and the environment, precise monitoring of NO2 levels is crucial for devising effective strategies to mitigate risks. However, precise measurement of NO2 presents challenges as it traditionally relies on expensive and heavy (therefore, stationary) equipment. This has led to the pursuit of more affordable alternatives, though their dependability is frequently questionable. This study introduces an innovative technique for precise calibration of low-cost NO2 sensors. Our methodology involves statistical preprocessing of sensor measurements to align their distributions with reference data. The core of the calibration model is an artificial neural network (ANN), trained to synchronize sensor and reference time series measurements. It incorporates environmental variables such as temperature, humidity, and atmospheric pressure, along with readings from redundant NO2 sensors for cross-referencing, and short time series of primary sensor NO2 measurements. This enables efficient learning of typical sensor changes over time in relation to these factors. Additionally, an interpolative kriging model serves as an auxiliary surrogate to enhance the correction process's reliability. Validation using an autonomous monitoring platform from Gdansk University of Technology, Poland, and public reference station data gathered over five months shows remarkable calibration accuracy, with a correlation coefficient close to 0.95 and RMSE of 2.4 µg/m3. These results position the corrected sensor as an attractive and cost-effective alternative to conventional NO2 measurement methods.

  • Macrocyclic derivatives of imidazole as chromoionophores for bismuth(III)/lead(II) pair
    • Błażej Galiński
    • Ewa Wagner-Wysiecka
    2024 Full text SENSORS AND ACTUATORS B-CHEMICAL

    18-membered diazomacrocycles with imidazole or 4-methylimidazole residue as a part of macrocycle were used as chromoionophores in bismuth(III) and lead(II) dual selective optodes for the first time. Cellulose triacetate membranes doped with macrocyclic chromoionophores are bismuth(III) and lead(II) selective with color change from orange/red to different shades of blue and violet, respectively. Results obtained for model and real samples of bismuth(III) and lead(II) showed that easily accessible and regenerable sensor materials can be used for spectrophotometric and colorimetric detection and determination of bismuth(III) and lead(II). The obtained LOD values for bismuth(III) are 1.63×10-7 M and 3.03×10-7 M with spectrophotometric and colorimetric detection, respectively, when using optode with imidazole residue. For sensing material with 4-methylimidazole in macroring the lowest detection limits were obtained for lead(II): 2.14×10-7 M and 3.99×10-7 M with spectrophotometric and digital color analysis detection mode, respectively.

  • Magnetic field mapping along a NV-rich nanodiamond-doped fiber
    • Adam Filipkowski
    • Mariusz Mrózek
    • Grzegorz Stępniewski
    • Mateusz Ficek
    • Dariusz Pysz
    • Wojciech Gawlik
    • Ryszard Buczyński
    • Adam M. Wojciechowski
    • Mariusz Klimczak
    2024 APPLIED PHYSICS LETTERS

    Integration of NV−-rich diamond with optical fibers enables guiding quantum information on the spin state of the NV− color center. Diamond-functionalized optical fiber sensors have been demonstrated with impressive sub-nanotesla magnetic field sensitivities over localized magnetic field sources, but their potential for distributed sensing remains unexplored. The volumetric incorporation of diamonds into the optical fiber core allows developing fibers sensitive to the magnetic field over their entire length. Theoretically, this makes distributed optical readout of small magnetic fields possible, but does not answer questions on the addressing of the spatial coordinate, i.e., the location of the field source, nor on the performance of a sensor where the NV− fluorescence is detected at one end, thereby integrating over color centers experiencing different field strength and microwave perturbation. Here, we demonstrate distributed magnetic field measurements using a step-index fiber with the optical core volumetrically functionalized with NV− diamonds. A microwave antenna on a translation stage is scanned along a 13 cm long section of a straight fiber. The NV− fluorescence is collected at the fiber's far end relative to the laser pump input end. Optically detected magnetic resonance spectra were recorded at the fiber output for every step of the antenna travel, revealing the magnetic field evolution along the fiber and indicating the magnetic field source location. The longitudinal distribution of the magnetic field along the fiber is detected with high accuracy. The simplicity of the demonstrated sensor would be useful for, e.g., magnetic-field mapping of photonics- and/or spintronics-based integrated circuits.

  • Magnetic hydrophobic deep eutectic solvents for orbital shaker-assisted dispersive liquid-liquid microextraction (MAGDES-OS-DLLME) - determination of nickel and copper in food and water samples by FAAS
    • Adil Elik
    • Hameed Haq
    • Grzegorz Boczkaj
    • Seçkin Fesliyan
    • Özlem Ablak
    • Nail Altunay
    2024 JOURNAL OF FOOD COMPOSITION AND ANALYSIS

    In this work, a cheap and widely applicable dispersive liquid-liquid microextraction (DLLME) method was developed for the extraction of Ni(II) and Cu(II) from water and food samples and analysis using flame atomic absorption spectrometry. DLLME was assisted by orbital shaker, while ferrofluid as an extractant was based on deep eutectic solvent (DES). This ferrofluid was made of hydrophobic DES (hDES), composed of lauric acid and menthol (molar ratio 1:2), and toner powder@aliquat 336 magnetic particles. The extraction procedure does not require any heating or centrifugation. The method limits of detection value were 0.15 µg L−1 and 0.03 µg L−1 for Ni(II) and Cu(II) respectively along with wide linearity range (0.4–250 µg L−1). The validation of the method was performed using certified reference materials (CRMs). The studies revealed excellent accuracy between results obtained by the developed method and expected values for all CRMs. The relative recoveries of Ni(II) and Cu(II) ions ranged from 92.8% to 98.6%. The developed method was further used for the determination of Ni(II) and Cu(II) in real water and food samples and provided quantitative recoveries.

  • Magnetic superhydrophobic melamine sponges for crude oil removal from water
    • Patrycja Makoś-Chełstowska
    • Edyta Słupek
    • Aleksandra Mielewczyk-Gryń
    • Tomasz Klimczuk
    2024 CHEMOSPHERE

    This paper proposes the preparation of a new sorbent material based on melamine sponges (MS) with superhydrophobic, superoleophilic, and magnetic properties. This study involved impregnating the surface of commercially available MS with eco-friendly deep eutectic solvents (DES) and Fe3O4 nanoparticles. The DES selection was based on the screening of 105 eutectic mixtures using COSMO-RS modeling. Other parameters affecting the efficiency and selectivity of oil removal from water were optimized using the Box-Bhenken model. Menthol:Thymol (1:1)@Fe3O4-MS exhibited the highest sorption capacity for real crude oils (101.7–127.3 g/g). This new sponge demonstrated paramagnetic behavior (31.06 emu/g), superhydrophobicity (151°), superoleophobicity (0°), low density (15.6 mg/cm3), high porosity (99 %), and excellent mechanical stability. Furthermore, it allows multiple regeneration processes without losing its sorption capacity. Based on these benefits, Menthol:Thymol (1:1)@Fe3O4-MS shows promise as an efficient, cost-effective, and eco-friendly substitute for the existing sorbents.

  • Management of ground tire rubber waste by incorporation into polyurethane-based composite foams
    • Aleksander Hejna
    • Paulina Kosmela
    • Adam Olszewski
    • Łukasz Zedler
    • Krzysztof Formela
    • Katarzyna Skórczewska
    • Adam Piasecki
    • Mariusz Marć
    • Roman Barczewski
    • Mateusz Barczewski
    2024 Full text ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH

    Rapid economic growth implicated the developing multiple industry sectors, including the automotive branch, increasing waste generation since recycling and utilization methods have not been established simultaneously. A very severe threat is the generation of enormous amounts of post-consumer tires considered burdensome waste, e.g., due to the substantial emissions of volatile organic compounds (VOCs). Therefore, it is essential to develop novel, environmentally friendly methods for their utilization, which would hinder their environmental impacts. One of the most promising approaches is shredding, resulting in the generation of ground tire rubber (GTR), which can be introduced into polymeric materials as filler. The presented work is related to the thermomechanical treatment of GTR in a twin-screw extruder with zinc borate, whose incorporation is aimed to enhance shear forces within the extruder barrel. Modified GTR was introduced into flexible polyurethane (PU) foams, and the impact of modification parameters on the cellular structure, static and dynamic mechanical performance, thermal stability, as well as thermal insulation, and acoustic properties were investigated. Emissions of VOCs from applied fillers and prepared composites were monitored and evaluated. Depending on the treatment parameters, beneficial changes in foams’ cellular structure were noted, which enhanced their thermal insulation performance, mechanical strength, and thermal stability. It was proven that the proposed method of GTR thermomechanical treatment assisted by zinc borate particles might benefit the performance of flexible PU foamed composites and hinder VOCs emissions, which could broaden the application range of GTR and provide novel ways for its efficient utilization

  • Managing and funding the innovative path: a close look at the SimLE scientific club at Gdańsk University of Technology, Poland
    • Wiktor Sieklicki
    • Maciej Zawadzki
    2024 Global Journal of Engineering Education

    This article presents a case study of the simply learn experience (SimLE) scientific club at Gdańsk University of Technology (Gdańsk Tech), Gdańsk, Poland, showcasing an effective model for blending theoretical knowledge with practical engineering applications. This student-led organisation aims to develop soft skills and handson experience through project work, participation in international contests and conferences. This study examines the funding mechanisms, educational impacts and management strategies of competitive achievements within SimLE. The results show that the level of financial support moderately affects the output of academic publications. However, this support is crucial for enhancing international visibility and facilitating participation in academic conferences. Also, it directly correlates with students’ engagement. Importantly, the research reveals that variations in scientific output are more closely associated with the composition of teams and management approaches rather than the extent of financial backing

  • Managing knowledge in a tourism crisis: case study from Poland
    • Ewa Stolarek-Muszyńska
    • Małgorzata Zięba
    • Ettore Bolisani
    • Enrico Scarso
    2024 Full text

    Purpose: This study deals with a tourism organisation from Poland, which experienced not only the COVID-19 pandemic, but also the close war situation in Ukraine which caused a significant decrease in tourist traffic and revenues. Since, based on the literature, knowledge management can be useful for crisis management, this study aims to explore the role and usefulness of KM during crisis situations in tourism. Methodology: Qualitative in-depth analysis was conducted by using data collected via semi-structured interview with the CEO of a local tourism organisation in Poland. The research output is presented in the form of a single case study with that organisation as the unit of analysis. Findings: The case highlighted that: a) a crisis may not be the most appropriate time for the implementation of KM from the scratch in an organisation; b) having some minimal KM experience can be essential for a more structured and complex KM approach; c) organisations may benefit from lessons learned during the crisis to get insights for developing KM. These findings suggest that practitioners and policymakers facilitate KM awareness among tourism organisations to enhance resilience in coping with future crises. Research limitations: This is a single case study and thus it cannot be easily generalised or provide a comprehensive overview of the whole sector. It is also a case study from a single country, affected by two serious crises which limits the applicability of the results to other countries. Practical implications: The study provides useful insights for practitioners in tourism organisations aspiring to improve internal processes of knowledge management and thus mitigating the future tourism crises. Originality/value: This paper contributes to the body of knowledge in terms of the role and relevance of KM during the tourism crisis. It provides food for thought for researchers investigating the knowledge and crisis management processes within the tourism industry.

  • Mangiferin: A comprehensive review on its extraction, purification and uses in food systems
    • Roberto Castro Munoz
    • René Cabezas
    • Maksymilian Plata Gryl
    2024 ADVANCES IN COLLOID AND INTERFACE SCIENCE

    With the target of fabricating healthier products, food manufacturing companies look for natural-based nutraceuticals that can potentially improve the physicochemical properties of food systems while being nutritive to the consumer and providing additional health benefits (biological activities). In this regard, Mangiferin joins all these requirements as a potential nutraceutical, which is typically contained in Mangifera indica products and its by-products. Unfortunately, knowing the complex chemical composition of Mango and its by-products, the extraction and purification of Mangiferin remains a challenge. Therefore, this comprehensive review revises the main strategies proposed by scientists for the extraction and purification of Mangiferin. Importantly, this review identifies that there is no report reviewing and criticizing the literature in this field so far. Our attention has been targeted on the timely findings on the primary extraction techniques and the relevant insights into isolation and purification. Our discussion has emphasized the advantages and limitations of the proposed strategies, including solvents, extracting conditions and key interactions with the target xanthone. Additionally, we report the current research gaps in the field after analyzing the literature, as well as some examples of functional food products containing Mangiferin.

  • Marine polymers in tissue bioprinting: Current achievements and challenges
    • Adrianna Banach-Kopeć
    • Szymon Mania
    • Robert Tylingo
    2024 Full text REVIEWS ON ADVANCED MATERIALS SCIENCE

    Bioprinting has a critical role in tissue engineering, allowing the creation of sophisticated cellular scaffolds with high resolution, shape fidelity, and cell viability. Achieving these parameters remains a challenge, necessitating bioinks that are biocompatible, printable, and biodegradable. This review highlights the potential of marine-derived polymers and crosslinking techniques including mammalian collagen and gelatin along with their marine equivalents. While denaturation temperatures vary based on origin, warm-water fish collagen and gelatin emerge as promising solutions. Building on the applications of mammalian collagen and gelatin, this study investigates their marine counterparts. Diverse research groups present different perspectives on printability and cell survival. Despite advances, current scaffolds are limited in size and layers, making applications such as extensive skin burn treatment or tissue regeneration difficult. The authors argue for the development of bioprinting, which includes spherical and adaptive printing. In adaptive printing, layers differentiate and propagate sequentially to overcome the challenges of multilayer printing and provide optimal conditions for the growth of deeply embedded cells. Moving the boundaries of bioprinting, future prospects include transformative applications in regenerative medicine.

  • Maritime traffic situation awareness analysis via high-fidelity ship imaging trajectory
    • Xinqiang Chen
    • Jinbiao Zheng
    • Chaofeng Li
    • Bing Wu
    • Huafeng Wu
    • Jakub Montewka
    2024 MULTIMEDIA TOOLS AND APPLICATIONS

    Situation awareness provides crucial yet instant information to maritime traffic participants, and significant attentions are paid to implement traffic situation awareness task via various maritime data source (e.g., automatic identification system, maritime surveillance video, radar, etc.). The study aims to analyze traffic situation with the support of ship imaging trajectory. First, we employ the dark channel prior model to remove fog in maritime videos to obtain high-resolution ship images (i.e., fog-free maritime images). Second, we track ships in each maritime image with the scale adaptive kernel correlation filter (SAMF), and thus obtain raw ship imaging trajectories. Third, we cleanse abnormal ship trajectory samples via curve-fitting and down sampling method, and thus further maritime traffic situation analysis is implemented. We analyze maritime traffic situation in three typical videos (i.e., three typical maritime traffic scenarios), and experimental results suggested that the proposed framework can extract high-resolution ship imaging trajectory for fulfilling the task of accurate maritime traffic situation awareness.

  • MARS - BAZA. warsztaty pozaziemskiej architektury ekstremalnej. Warsztaty w ramach Bałtyckiego Festiwalu Nauki
    • Aleksandra Karpińska
    • Agnieszka Kurkowska
    • Marta Koperska-Kośmicka
    • Marcin Kulesza
    2024

    Jak przetrwać w różnych warunkach? Czego potrzebujemy, by przeżyć, a czego, by żyć wygodnie? Poszukamy odpowiedzi na te pytania, by stanąć przed nie lada misją: wspólnie podejmiemy się największego wyzwania przyszłości - zbudujemy bazę na Marsie! Budowa schronienia, bazy, domu - troska o zaspokojenie podstawowych potrzeb towarzyszy nam od zawsze, a budowanie jest jednym z pierwszych trwałych działań ludzi, pomagającym spełnić nasze potrzeby bytowe. Z innymi wyzwaniami stykamy się jednak, kiedy planujemy budować dom, a innymi, kiedy spotykamy się z warunkami ekstremalnymi, kiedy standardowe rozwiązania nie mają zastosowania. Lekcja myślenia o projektowaniu w warunkach ekstremalnych to wstęp do zadania praktycznego w nurcie dizajnu spekulatywnego: uczestnicy będą projektować i budować w skali 1:1 model własnej bazy na Marsie.

  • Maximizing Bio-Hydrogen and Energy Yields Obtained in a Self-Fermented Anaerobic Bioreactor by Screening of Different Sewage Sludge Pretreatment Methods
    • Alaa A. El-kebeer
    • Usama F. Mahmoud
    • Sayed Ismail
    • Abu Abbas E. Jalal
    • Przemysław Kowal
    • Hussein Al-Hazmi
    • Gamal K. Hassan
    2024 Full text Processes

    Egypt faces significant challenges in managing its sewage sludge generated in large quantities from wastewater treatment plants. This study investigates the feasibility of utilizing sewage sludge as a renewable resource for hydrogen production through anaerobic digestion at the 100 L bioreactor level. Hydrogen is considered a promising alternative energy source due to its high energy content and environmental benefits. To optimize the microbial degradation process and maximize hydrogen production from sewage sludge, a specialized pretreatment is necessary. Various pretreatment methods have been applied to the sewage sludge, individually and in combination, to study the bio-hydrogen production from sewage sludge. The four methods of treatment were studied in batch assays as a pilot scale. Thermal pretreatment of sewage sludge significantly increases bio-hydrogen production yield compared to other sewage sludge pretreatment methods, producing the highest H2 yield (6.48 LH2/g VS). In general, the hydrogen yield of any type of pretreated inoculum was significantly higher than the untreated inoculum. At the same time, alkaline pretreatment improved the hydrogen yield (1.04 LH2/g VS) more than acid pretreatment (0.74 LH2/g VS), while the hydrogen yield for the combination of pretreatments (shock alkali pretreatment) was higher than both (1.73 LH2/g VS), On the other hand, untreated sewage sludge (control) had almost no hydrogen yield (0.03 LH2/g VS). The self-fermented anaerobic bioreactor improved sewage sludge utilization, increased bioenergy yields, and seems to be promising for treating complex wastes at this scale.

  • Maximizing SDN resilience to node‐targeted attacks through joint optimization of the primary and backup controllers placements
    • Michał Pióro
    • Mariusz Mycek
    • Artur Tomaszewski
    • Amaro de Sousa
    2024 NETWORKS

    In Software Defined Networks (SDN) packet data switches are configured by a limited number of SDN controllers, which respond to queries for packet forwarding decisions from the switches. To enable optimal control of switches in real time the placement of controllers at network nodes must guarantee that the controller-to-controller and switch-to-controller communications delays are bounded. Apart from the primary controllers that control the switches in the nominal state, separate backup controllers can be introduced that take over when the primary controllers are unavailable, and whose delay bounds are relaxed. In this paper we present optimization models to jointly optimize the placement of primary and backup controllers in long-distance SDN networks, aimed at maximizing the network's resilience to node-targeted attacks. Applying the models to two well-known network topologies and running a broad numerical study we show that, when compared with the standard approach of using only primary controllers, the use of backup controllers provides significant resilience gains, in particular in case of strict delay bounds.

  • Measuring Tilt with an IMU Using the Taylor Algorithm
    • Jerzy Demkowicz
    2024 Remote Sensing

    This article addresses the important problem of tilt measurement and stabilization. This is particularly important in the case of drone stabilization and navigation in underwater environments, multibeam sonar mapping, aerial photogrammetry in densely urbanized areas, etc. The tilt measurement process involves the fusion of information from at least two different sensors. Inertial sensors (IMUs) are unique in this context because they are both autonomous and passive at the same time and are therefore very attractive. Their calibration and systematic errors or bias are known problems, briefly discussed in the article due to their importance, and are relatively simple to solve. However, problems related to the accumulation of these errors over time and their autonomous and dynamic correction remain. This article proposes a solution to the problem of IMU tilt calibration, i.e., the pitch and roll and the accelerometer bias correction in dynamic conditions, and presents the process of calculating these parameters based on combined accelerometer and gyroscope records using a new approach based on measuring increments or differences in tilt measurement. Verification was performed by simulation under typical conditions and for many different inertial units, i.e., IMU devices, which brings the proposed method closer to the real application context. The article also addresses, to some extent, the issue of navigation, especially in the context of dead reckoning.

  • Mechanical Properties of 3D Printed Parts and Their Injection Molded Alternatives Subjected to Environmental Aging
    • Angela Jadwiga Andrzejewska
    2024 3D Printing and Additive Manufacturing

    Additive manufacturing is the technology used in medical, industrial, or lifestyle applications. The scientific literature include works reporting various manufacturing parameters’ influence on changes in additive manufacturing components’ mechanical behavior, especially with fused filament fabrication (FFF). The changes in mechanical strength and toughness of FFF compared to injection molding parts were studied. In the study, the FFF and injection molded parts were aged in buffered saline solution in temperature of 37C. The results show that by differentiating the orientation of the fibers during fabricating, it is possible to reach strength values similar to injection molded parts. Therefore, it was reported that the mechanical strength and toughness changed significantly after aging, and the FFF components lost strength more quickly than their injected alternatives. The research results can be useful during the fabrication of mechanically stable and biodegradable components, which can be more easily recycled than their injected alternatives when used with warmer temperatures and humidity. This article completes the present state of the art on the problem of environmental aging of parts produced from biodegradable materials. Especially, the research was related to the multilayer laminate structure.

  • Mechanical Properties of Additively Manufactured Polymeric Materials—PLA and PETG—For Biomechanical Applications
    • Rui F. Martins
    • Ricardo Branco
    • Miguel Martins
    • Wojciech Macek
    • Zbigniew Marciniak
    • Rui Silva
    • Daniela Trindade
    • Carla Moura
    • Margarida Franco
    • Cândida Malça
    2024 Full text Polymers

    The study presented herein concerns the mechanical properties of two common polymers for potential biomedical applications, PLA and PETG, processed through fused filament fabrication (FFF)—Material Extrusion (ME). For the uniaxial tension tests carried out, two printing orientations—XY (Horizontal, H) and YZ (Vertical, V)—were considered according to the general principles for part positioning, coordinates, and orientation typically used in additive manufacturing (AM). In addition, six specimens were tested for each printing orientation and material, providing insights into mechanical properties such as Tensile Strength, Young’s Modulus, and Ultimate Strain, suggesting the materials’ potential for biomedical applications. The experimental results were then compared with correspondent mechanical properties obtained from the literature for other polymers like ASA, PC, PP, ULTEM 9085, Copolyester, and Nylon. Thereafter, fatigue resistance curves (S-N curves) for PLA and PETG, printed along 45°, were determined at room temperature for a load ratio, R, of 0.2. Scanning electron microscope observations revealed fibre arrangements, compression/adhesion between layers, and fracture zones, shedding light on the failure mechanisms involved in the fatigue crack propagation of such materials and giving design reference values for future applications. In addition, fractographic analyses of the fatigue fracture surfaces were carried out, as well as X-ray Computed Tomography (XCT) and Thermogravimetric (TGA)/Differential Scanning Calorimetric (DSC) tests.

  • Mechanical response of human thoracic spine ligaments under quasi-static loading: An experimental study
    • Radosław Wolny
    • Tomasz Wiczenbach
    • Angela Andrzejewska
    • Jan Henryk Spodnik
    2024 Journal of the Mechanical Behavior of Biomedical Materials

    Purpose This study aimed to investigate the geometrical and mechanical properties of human thoracic spine ligaments subjected to uniaxial quasi-static tensile test. Methods Four human thoracic spines, obtained through a body donation program, were utilized for the study. The anterior longitudinal ligament (ALL), posterior longitudinal ligament (PLL), capsular ligament (CL), ligamenta flava (LF), and the interspinous ligament and supraspinous ligament complex (ISL + SSL), were investigated. The samples underwent specimen preparation, including dissection, cleaning, and reinforcement, before being immersed in epoxy resin. Uniaxial tensile tests were performed using a custom-designed mechanical testing machine equipped with an environmental chamber (T = 36.6 °C; humidity 95%). Then, the obtained tensile curves were averaged preserving the characteristic regions of typical ligaments response. Results Geometrical and mechanical properties, such as initial length and width, failure load, and failure elongation, were measured. Analysis of variance (ANOVA) revealed significant differences among the ligaments for all investigated parameters. Pairwise comparisons using Tukey's post-hoc test indicated differences in initial length and width. ALL and PLL exhibited higher failure forces compared to CL and LF. ALL and ISL + SSL demonstrated biggest failure elongation. Comparisons with other studies showed variations in initial length, failure force, and failure elongation across different ligaments. The subsystem (Th1 – Th6 and Th7 – Th12) analysis revealed increases in initial length, width, failure force, and elongation for certain ligaments. Conclusions Variations of both the geometric and mechanical properties of the ligaments were noticed, highlighting their unique characteristics and response to tensile force. Presented results extend very limited experimental data base of thoracic spine ligaments existing in the literature. The obtained geometrical and mechanical properties can help in the development of more precise human body models (HBMs).

  • Melanoma skin cancer detection using mask-RCNN with modified GRU model
    • K. M. Monica
    • J. Shreeharsha
    • Przemysław Falkowski-Gilski
    • Bożena Falkowska-Gilska
    • Mohan Awasthy
    • Rekha Phadk
    2024 Full text Frontiers in Physiology

    Introduction: Melanoma Skin Cancer (MSC) is a type of cancer in the human body; therefore, early disease diagnosis is essential for reducing the mortality rate. However, dermoscopic image analysis poses challenges due to factors such as color illumination, light reflections, and the varying sizes and shapes of lesions. To overcome these challenges, an automated framework is proposed in this manuscript. Methods: Initially, dermoscopic images are acquired from two online benchmark datasets: International Skin Imaging Collaboration (ISIC) 2020 and Human against Machine (HAM) 10000. Subsequently, a normalization technique is employed on the dermoscopic images to decrease noise impact, outliers, and variations in the pixels. Furthermore, cancerous regions in the pre-processed images are segmented utilizing the mask-faster Region based Convolutional Neural Network (RCNN) model. The mask-RCNN model offers precise pixellevel segmentation by accurately delineating object boundaries. From the partitioned cancerous regions, discriminative feature vectors are extracted by applying three pre-trained CNN models, namely ResNeXt101, Xception, and InceptionV3. These feature vectors are passed into the modified Gated Recurrent Unit (GRU) model for MSC classification. In the modified GRU model, a swish-Rectified Linear Unit (ReLU) activation function is incorporated that efficiently stabilizes the learning process with better convergence rate during training. Results and discussion: The empirical investigation demonstrate that the modified GRU model attained an accuracy of 99.95% and 99.98% on the ISIC 2020 and HAM 10000 datasets, where the obtained results surpass the conventional detection models.

  • Meldrum’s acid assisted formation of tetrahydroquinolin‑2‑one derivatives a short synthetic pathway to the biologically useful scaffold
    • Małgorzata Ryczkowska
    • Alicja Trocka
    • Anna Hromova
    • Sławomir Makowiec
    2024 Full text Scientific Reports

    A new method for the preparation of tetrahydroquinolin-2-one derivatives is presented. This approach involves a two-step reaction between enaminones and acylating agents, immediately followed by electrophilic cyclization, all within a single synthesis procedure, eliminating the need to isolate intermediates. The entire process is facilitated by the use of acyl Meldrum’s acids which not only shortens the preparation time of the substrates but also easily extends the range of substituents That can be used. The method’s scope and limitations were evaluated with various reagent combinations thus demonstrating its general applicability to the synthesis of tetrahydroquinolin-2-one core. Interestingly, some exceptions to the regular reaction pathway were observed when a strong EDG (electron donating group) was introduced via acyl Meldrum’s acids. The underlying mechanism of this phenomenon was elucidated during the investigation.

  • Merton-type default risk and financial performance: the dynamic panel moderation of firm size
    • Muhammad Mushafiq
    • Syed Ahmad Sami
    • Muhammad Khalid Sohail
    • Muzammal Ilyas Sindhu
    2024 Journal of Economic and Administrative Sciences

    Purpose – The main purpose of this study is to evaluate the probability of default and examine the relationship between default risk and financial performance, with dynamic panel moderation of firm size. Design/methodology/approach – This study utilizes a total of 1,500 firm-year observations from 2013 to 2018 using dynamic panel data approach of generalized method of moments to test the relationship between default risk and financial performance with the moderation effect of the firm size. Findings – This study establishes the findings that default risk significantly impacts the financial performance. The relationship between distance-to-default (DD) and financial performance is positive, which means the relationship of the independent and dependent variable is inverse. Moreover, this study finds that the firm size is a significant positive moderator between DD and financial performance. Practical implications – This study provides new and useful insight into the literature on the relationship between default risk and financial performance. The results of this study provide investors and businesses related to nonfinancial firms in the Pakistan Stock Exchange (PSX) with significant default risk’s impact on performance. This study finds, on average, the default probability in KSE ALL indexed companies is 6.12%. Originality/value – The evidence of the default risk and financial performance on samples of nonfinancial firms has been minimal; mainly, it has been limited to the banking sector. Moreover, the existing studies have only catered the direct effect of only. This study fills that gap and evaluates this relationship in nonfinancial firms. This study also helps in the evaluation of Merton model’s performance in the nonfinancial firms.

  • Mesoscopic simulations of a fracture process in reinforced concrete beam in bending using a 2D coupled DEM/micro-CT approach
    • Michał Nitka
    • Andrzej Tejchman-Konarzewski
    2024 Full text ENGINEERING FRACTURE MECHANICS

    W tej pracy zbadano numerycznie w warunkach 2D złożony proces pękania w krótkiej prostokątnej belce betonowej wzmocnionej jednym prętem podłużnym (bez zbrojenia pionowego) i poddanej quasi-statycznemu zginaniu w trzech punktach. Krytyczne pęknięcie poprzeczne w belce spowodowało jej uszkodzenie podczas doświadczenia. Symulacje numeryczne przeprowadzono klasyczną metodą elementów dyskretnych (DEM). Przyjęto trójfazowy opis betonu: kruszywa, zaprawa i międzyfazowe strefy przejściowe (ITZ) wokół kruszyw. W mezoskopowych obliczeniach DEM opartych na skanach rentgenowskich CT 2D przyjęto rzeczywisty kształt i połączenie cząstek kruszywa w betonie. W obliczeniach odtworzono pręt stalowy z żebrami. Założono także ITZ pomiędzy prętem a zaprawą. Bez narzucania prawa poślizgu, uwzględniono warunek geometryczny na granicy pręt/beton. W pracy skupiono się na wykresie siła-ugięcia, procesie pękania, siłach kontaktowych i naprężeniach wzdłuż pręta. Uzyskano dobry poziom zgodności ewolucji siły pionowej w zależności od ugięcia i mechanizmu zniszczenia w analizach DEM w porównaniu z testami laboratoryjnymi pomimo przyjęcia uproszczonych warunków 2D. Wykazano silny wpływ mezostruktury betonu na wzór pęknięcia.

  • Method for prediction of the frost resistance ability of air‐entrained concrete based on the 3D air void characteristics by x‐ray micro‐CT
    • Łukasz Skarżyński
    • Mikołaj Miśkiewicz
    2024 Structural Concrete

    In modern construction, one of the most important factors in the execution of contracts is time. Standard procedures for assessing the frost resistance or concrete are usually very time-consuming and can take up to 40 days. The current paper is experimentally and practically oriented. It presents an alternative testing method, based on air void network, that allows to assess the frost resistance of concrete within just a few days of taking the samples. X-ray micro-CT scans were introduced to obtain the quantitative and qualitative 3D information about the air void microstructure taking into account total air content: A [%], pores of the size below 300 μm in diameter content: A300 [%], specific surface of air voids: α [mm-1] and spacing factor: L [mm] in order to predict the freeze / thaw durability. To verify the assumptions of the frost resistance method, based on the analysis of pore microstructure, tests of freeze / thaw resistance in accordance with Polish supplement to European Standard [46] were carried out. Presented research revealed that the appropriate microstructure of air pores, in particular, content of micropores with the diameter less than 0.3 mm: A300 combined with a spacing factor: L [mm] can constitute a reliable basis for determining concrete freeze / thaw durability. Thus, method proposed in current paper can be effectively used for fast and trustworthy determination of the air-entrained concrete durability in a short time and without any special preparation of the tested sample, that allows immediate preventive or repair actions to be taken if required.

  • Methodology of generation of CFD meshes and 4D shape reconstruction of coronary arteries from patient-specific dynamic CT
    • Krzysztof Psiuk-Maksymowicz
    • Damian Borys
    • Bartlomiej Melka
    • Maria Gracka
    • Wojciech Adamczyk
    • Marek Rojczyk
    • Jaroslaw Wasilewski
    • Jan Głowacki
    • Mariusz Kruk
    • Marcin Nowak
    • Ziemowit Ostrowski
    • Ryszard Bialecki
    2024 Full text Scientific Reports

    Due to the difficulties in retrieving both the time‑dependent shapes of the vessels and the generation of numerical meshes for such cases, most of the simulations of blood flow in the cardiac arteries use static geometry. The article describes a methodology for generating a sequence of time‑dependent 3D shapes based on images of different resolutions and qualities acquired from ECG‑gated coronary artery CT angiography. The precision of the shape restoration method has been validated using an independent technique. The original proposed approach also generates for each of the retrieved vessel shapes a numerical mesh of the same topology (connectivity matrix), greatly simplifying the CFD blood flow simulations. This feature is of significant importance in practical CFD simulations, as it gives the possibility of using the mesh‑morphing utility, minimizing the computation time and the need of interpolation between boundary meshes at subsequent time instants. The developed technique can be applied to generate numerical meshes in arteries and other organs whose shapes change over time. It is applicable to medical images produced by other than angio‑CT modalities.

  • Miasta Nieskończone. Warsztaty animacji poklatkowej doodle-art. Bałtycki Festiwal Nauki 2024
    • Marta Koperska-Kośmicka
    • Agnieszka Kurkowska
    • Aleksandra Karpińska
    2024

    Warsztaty animacji poklatkowej w technice doodle-art, podczas których uczestnicy stworzyli wspólnie animowany film o mieście marzeń. Warsztaty z animacji poklatkowej są zajęciami rozwijającymi wyobraźnię i kreatywność. Film powstawał zespołowo, poprzez dodawanie nowych elementów rysunku przez każdego z uczestników. Kolejne fazy powstawania wymarzonego miasta zostały uwiecznione na zdjęciach, które po cyfrowej obróbce pozwoliły na stworzenie krótkiego, jednominutowego animowanego filmu.

  • Micro- and nano-Illite to improve strength of untreated-soil as a nano soil-improvement (NSI) technique
    • M Cheraghalikhani,
    • Hamed Niroumand
    • Lech Bałachowski
    2024 Full text Scientific Reports

    Soil stabilization is a technique of improving the geotechnical properties of soils for various engineering applications. However, conventional stabilizers such as cement and lime have some limitations, such as high cost, environmental impact, and durability issues. Therefore, there is a need for alternative and innovative stabilizers that can overcome these challenges. This study introduces nano-Illite, a type of clay mineral, as a novel and efective soil stabilizer. Nano-Illite can form nano-cementation (NC) in soil, which is a process of enhancing the durability of various building materials. NC is also known as nano soil-improvement (NSI), a technique that has been developed in recent years. Four formulations of micro- and nano-Illite with concentrations of 0, 1, 2, and 3% were separately added to soil samples. The unconfned compressive strength (UCS) and the secant modulus at 50% of peak stress (E50) of the treated samples were measured and compared with the untreated samples. The results showed that 3% nano-Illite increased the UCS of soil by more than 2.2 times and the E50 by more than 1.5 times after 7 days of curing. Micro-Illite also improved the UCS and E50 of soil, but to a lesser extent. X-ray fuorescence (XRF), scanning electron microscopy (SEM), and X-ray difraction (XRD) analyses revealed the micro- and nano-structures of the soil specimens and the performance of Illite as a nano-additive. This research demonstrates the efectiveness of nano-Illite in soil improvement as a NSI technique, and its potential to replace or reduce the use of conventional stabilizers. This study also contributes to the understanding of the mechanisms and factors that infuence the NC process in soil.

  • Microbe Cultivation Guidelines to Optimize Rhamnolipid Applications
    • Ilona Kłosowska-Chomiczewska
    • Adam Macierzanka
    • Karol Parchem
    • Pamela Miłosz
    • Sonia Sarach
    • Iga Płaczkowska
    • Weronika Hewelt-Belka
    • Christian Jungnickel
    2024 Full text Scientific Reports

    In the growing landscape of interest in natural surfactants, selecting the appropriate one for specific applications remains challenging. The extensive, yet often unsystematized, knowledge of microbial surfactants, predominantly represented by rhamnolipids (RLs), typically does not translate beyond the conditions presented in scientific publications. This limitation stems from the numerous variables and their interdependencies that characterize microbial surfactant production. We hypothesized that a computational recipe for biosynthesizing RLs with targeted applicational properties could be developed from existing literature and experimental data. We amassed literature data on RL biosynthesis and micellar solubilization and augmented it with our experimental results on the solubilization of triglycerides (TGs), a topic underrepresented in current literature. Utilizing this data, we constructed mathematical models that can predict RL characteristics and solubilization efficiency, represented as logPRL = f(carbon and nitrogen source, parameters of biosynthesis) and logMSR = f(solubilizate, rhamnolipid (e.g. logPRL), parameters of solubilization), respectively. The models, characterized by robust R2 values of respectively 0.581-0.997 and 0.804, enabled the ranking of descriptors based on their significance and impact — positive or negative — on the predicted values. These models have been translated into ready-to-use calculators, tools designed to streamline the selection process for identifying a biosurfactant optimally suited for intended applications.

  • Microextraction by packed sorbent: Uncommon detection techniques, sorbents, samples and analytes
    • Vasil Andruch
    • Alina Kalyniukova
    • Tanya Yordanova
    • Justyna Płotka-Wasylka
    • Viera Vojteková
    • Gokhan Zengin
    2024 TRAC-TRENDS IN ANALYTICAL CHEMISTRY

    Among sample preparation approaches, the most desirable are procedures that ensure high efficiency and reproducibility, that are cheap, fast and simple, that minimize the number of operational steps and that require a small amount of sample and solvent and are thus environmentally friendly. Microextraction by packed sorbent (MEPS) is a miniaturized form of solid-phase extraction, the use of which has been continuously expanding since its introduction in 2004. This technique can be considered green, and due to its many advantages, it has been widely accepted and used for sample pretreatment prior to instrumental analysis. This mini-review deals with the presentation and discussion of atypical, less described approaches and solutions with the MEPS technique, especially in regard to the detection techniques and sorbents used, the samples analyzed and the analytes determined. We hope this review will interest, inspire and motivate readers to explore new MEPS applications.

  • Microfluidically Frequency-Reconfigurable Compact Self-Quadruplexing Tunable Antenna with High Isolation Based on Substrate Integrated Waveguide
    • Rusan Kumar Barik
    • Sławomir Kozieł
    2024 Full text Scientific Reports

    This communication presents a novel concept of microfluidically frequency-reconfigurable self-quadruplexing tunable antenna for quad-band applications. At the initial design stage, a substrate-integrated square cavity is divided into four unequal quarter-mode cavity resonators by inserting an X-shaped slot on the top surface of the cavity. Applying four 50-ohm microstrip feed-lines to these four quarter-mode cavity resonators enables quad-band operation with self-quadruplexing capabilities. The feed lines are organized orthogonally and off-center, which leads to port isolation greater than 32.3 dB. An equivalent network model is developed to validate the proposed antenna. To realize frequency reconfigurability, two microfluidic channels corresponding to each port are created by engraving the bottom surface of the cavity. To create a reconfigurable self-quadruplexing antenna, the channels are either filled with air or dielectric liquids of higher permittivity, so that the design offers independent tunability of the operating frequencies. As a proof of concept, the prototype of a self-quadruplexing tunable antenna is fabricated and validated through measurements. The antenna prototype occupies a footprint area of 0.37λg2. The design exhibits frequency tuning ranges of 350 MHz (8.3%), 500 MHz (10.3%), 610 MHz (11.2%), and 845 MHz (14.1%) for the first, second, third, and fourth operating bands, respectively. In all bands and across the entire tuning range, the realized gains of the designed antenna exceed 4.05 dBi. The electromagnetic modeling responses agree extremely well with the measured characteristics.

  • Microfluidically Frequency-Reconfigurable Self-Quadruplexing Antenna Based on Substrate Integrated Square-Cavity
    • Rusan Kumar Barik
    • Sławomir Kozieł
    2024 AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS

    In this article, a novel concept of self-quadruplexing tunable antenna (SQTA) enabled by microfluidic channels is investigated. The operating channels are either filled with air or dielectric liquids to enable frequency tunability. The proposed SQTA is implemented on the substrate-integrated square-cavity (SISC). A swastika-shaped slot is milled on the top-surface of the SISC to create four quarter-mode resonators. The resonators are excited by four 50-Ω microstrip lines to enable independent operating bands with self-quadruplexing properties. The working principle is validated by a custom-developed lumped-circuit model. The port isolations are better than 27dB due to the orthogonal and off-centered port allocation. Subsequently, two microfluidic channels corresponding to each quarter-mode resonator are milled from bottom-surface of the cavity. These two channels are filled with liquids of various permittivity to achieve frequency tunability. As a proof-of-concept, a prototype of the proposed SQTA is fabricated and demonstrated experimentally. The fabricated SQTA operates at 4.05-4.56 GHz, 4.645-5.295 GHz, 5.45-6.325 GHz, and 6.19-7.265 GHz. The measured realized gains of the SQTA are 4.4-4.5 dBi, 4.5-4.6 dBi, 4.8-4.9 dBi, and 4.9-4.95 dBi.

  • Microplastics in water resources: Global pollution circle, possible technological solutions, legislations, and future horizon
    • Saeed S. Albaseer
    • Hussein Al-Hazmi
    • Tonni Agustiono Kurniawan
    • Xianbao Xu
    • Sameer A.M. Abdulrahman
    • Peyman Ezzati
    • Sajjad Habibzadeh
    • Henner Hollert
    • Navid Rabiee
    • Eder C. Lima
    • Michael Badawi
    • Mohammad Saeb
    2024 SCIENCE OF THE TOTAL ENVIRONMENT

    Beneath the surface of our ecosystems, microplastics (MPs) silently loom as a significant threat. These minuscule pollutants, invisible to the naked eye, wreak havoc on living organisms and disrupt the delicate balance of our environment. As we delve into a trove of data and reports, a troubling narrative unfolds: MPs pose a grave risk to both health and food chains with their diverse compositions and chemical characteristics. Nevertheless, the peril extends further. MPs infiltrate the environment and intertwine with other pollutants. Worldwide, microplastic levels fluctuate dramatically, ranging from 0.001 to 140 particles.m-3 in water and 0.2 to 8766 particles.g-1 in sediment, painting a stark picture of pervasive pollution. Coastal and marine ecosystems bear the brunt, with each organism laden with thousands of microplastic particles. MPs possess a remarkable ability to absorb a plethora of contaminants, and their environmental behavior is influenced by factors such as molecular weight and pH. Reported adsorption capacities of MPs vary greatly, spanning from 0.001 to 12,700 μg·g−1. These distressing figures serve as a clarion call, demanding immediate action and heightened environmental consciousness. Legislation, innovation, and sustainable practices stand as indispensable defenses against this encroaching menace. Grasping the intricate interplay between microplastics and pollutants is paramount, guiding us toward effective mitigation strategies and preserving our health ecosystems.