# Lodz University of Technology

• Łódź, Poland
Recent publications
Leishmaniasis is a group of contagious diseases having high surveillance among dogs. According to World Health Organization (WHO), ninety-two territories were infected around the world in 2018. One billion dogs live in areas endemic for Leishmaniasis and are at risk of infection. Almost one million cases are reported annually. The dog's population is categorized into five classes like susceptible (S), latent (L), infectious (I), uninfected (R), and infected (Q). The Leishmaniasis delayed model is developed to analyze and control its spread. Equilibria, positivity, boundedness, reproduction number, and parameter sensitivity are the model's essential features. The stability of the model is investigated in a local and global sense with the help of the Routh Hurwitz criterion and Lyapunov theory. In the end, simulations are presented to verify the theoretical analysis of the delayed model.
This work presents a novel cluster based optimization procedure for estimating parameter values that yield stable, periodic responses with desired amplitude in nonlinear vibrating systems. The parameter values obtained by conventional nonlinear optimization schemes, with minimization of amplitude as the objective, may not furnish periodic and stable responses. Moreover, global optimization strategies may converge to isolated optima that are sensitive to parametric perturbations. In practical engineering systems, unstable or isolated optimal orbits are not practically realizable. To overcome these limitations, the proposed method tries to converge to a cluster in the r-dimensional parameter space in which the design specifications including the specified optimality, periodicity, stability and robustness are satisfied. Thus, it eliminates the need for computationally expensive bifurcation studies to locate stable, periodic parameter regimes before optimization. The present method is based on a hybrid scheme which involves the algebraic form of the governing equations in screening phase and its differential form in the selection phase. In the screening phase, force and energy balance conditions are used to rephrase the nonlinear governing equations in terms of the design parameter vector. These rephrased equations are reduced to algebraic form using a harmonic balance procedure which also specifies the desired amplitude and frequency of the response. An error norm based on this algebraic form is defined and is used to contract the search bounds in the parameter space leading to convergence to a cluster. The selection phase of the algorithm uses shooting method coupled with evaluation of Floquet multipliers to retain only those vectors in the arrived cluster yielding stable periodic solutions. The method is validated with Den Hartog's vibration absorbers and is then applied to vibration absorbers with material nonlinearity and vibration isolators with geometric nonlinearity. In both the cases, the converged cluster is shown to yield stable, periodic responses satisfying the amplitude condition. Parametric perturbation studies are conducted on the cluster to illustrate its robustness. The use of algebraic form of governing equations in the screening phase drastically reduces the computational time needed to converge to the cluster. The fact that the present method converges to a cluster in the parameter space rather than to a single parameter value offers the designer more freedom to choose the design vector from inside the cluster. It also ensures that the design is robust to small changes in parameter values.
This paper presents a novel method for improving the invariance of convolutional neural networks (CNNs) to selected geometric transformations in order to obtain more efficient image classifiers. A common strategy employed to achieve this aim is to train the network using data augmentation. Such a method alone, however, increases the complexity of the neural network model, as any change in the rotation or size of the input image results in the activation of different CNN feature maps. This problem can be resolved by the proposed novel convolutional neural network models with geometric transformations embedded into the network architecture. The evaluation of the proposed CNN model is performed on the image classification task with the use of diverse representative data sets. The CNN models with embedded geometric transformations are compared to those without the transformations, using different data augmentation setups. As the compared approaches use the same amount of memory to store the parameters, the improved classification score means that the proposed architecture is more optimal.
In this article, we model and study the spread of COVID-19 in Germany, Japan, India and highly impacted states in India, i.e., in Delhi, Maharashtra, West Bengal, Kerala and Karnataka. We consider recorded data published in Worldometers and COVID-19 India websites from April 2020 to July 2021, including periods of interest where these countries and states were hit severely by the pandemic. Our methodology is based on the classic susceptible–infected–removed (SIR) model and can track the evolution of infections in communities, i.e., in countries, states or groups of individuals, where we (a) allow for the susceptible and infected populations to be reset at times where surges, outbreaks or secondary waves appear in the recorded data sets, (b) consider the parameters in the SIR model that represent the effective transmission and recovery rates to be functions of time and (c) estimate the number of deaths by combining the model solutions with the recorded data sets to approximate them between consecutive surges, outbreaks or secondary waves, providing a more accurate estimate. We report on the status of the current infections in these countries and states, and the infections and deaths in India and Japan. Our model can adapt to the recorded data and can be used to explain them and importantly, to forecast the number of infected, recovered, removed and dead individuals, as well as it can estimate the effective infection and recovery rates as functions of time, assuming an outbreak occurs at a given time. The latter information can be used to forecast the future basic reproduction number and together with the forecast on the number of infected and dead individuals, our approach can further be used to suggest the implementation of intervention strategies and mitigation policies to keep at bay the number of infected and dead individuals. This, in conjunction with the implementation of vaccination programs worldwide, can help reduce significantly the impact of the spread around the world and improve the wellbeing of people.
Extreme events gain the attention of researchers due to their utmost importance in various contexts ranging from climate to brain. An observable that deviates significantly from its long-time average will have adverse consequences for the system. This brings such recurrent events to the limelight of attention in interdisciplinary research. There is a need for research efforts in many systems in the real world to find solutions that can predict and mitigate the unfavorable effects of these recurring events. A comprehensive review of recent progress is provided to capture recent improvements in analyzing such very high-amplitude events from the point of view of dynamical systems and random walkers. We emphasize, in detail, the mechanisms responsible for the emergence of such events in complex systems. Several mechanisms that contribute to the occurrence of extreme events have been elaborated that investigate the sources of instabilities leading to them. In addition, we discuss the prediction of extreme events from two different contexts, using dynamical instabilities and data-based machine learning algorithms. Tracking of instabilities in the phase space is not always feasible and a precise knowledge of the dynamics of extreme events does not necessarily help in forecasting extreme events. Moreover, in most of the studies on high-dimensional systems, only a few degrees of freedom participate in extreme events’ formation. Thus, a notable inclusion of prediction through machine learning is of enormous significance, particularly for those cases where the governing equations of the model are explicitly unavailable. Besides, random walks on complex networks can represent several transport processes, and exceedances of the flux of walkers above a prescribed threshold may describe extreme events. We unveil theoretical studies on random walkers with their enormous potential for applications in reducing extreme events. We cover the possible controlling strategies, which may be helpful to mitigate extreme events in physical situations like traffic jams, heavy load of web requests, competition for shared resources, floods in the network of rivers, and many more. This review presents an overview of the current trend of research on extreme events in dynamical systems and networks, including random walkers, and discusses future possibilities. We conclude this review with an extended outlook and compelling perspective, along with the non-trivial challenges for further investigation.
In relation to conventional vacuum-based processing techniques inkjet printing enables upscaling fabrication of basic electronic elements, such as transistors and diodes. We present the fully inkjet printed flexible electronic circuits, including organic voltage inverter which can work as a NOT logic gate. For this purpose the special ink compositions were formulated to preparation of gate dielectric layer containing poly (4-vinylphenol) and of the semiconductor layer poly[2,5-(2-octyldodecyl)-3,6-diketopyrrolopyrrole-alt-5,5-(2,5-di(thien-2-yl)thieno [3,2-b]thiophene)]. A printed photoxidized poly (3-hexyltiophene) semiconductor was used as the active layer of the resistors. The operation of the printed inverters and NOT logic gates was analyzed based on the DC current–voltage characteristics of the devices. The resistance of the devices to atmospheric air was also tested. Not encapsulated samples stored for three years under ambient conditions. Followed by annealing to remove moisture showed unchanged electrical parameters in comparison to freshly printed samples.
In this paper, planar forced oscillations of a particle connected to the support via two nonlinear springs linked in series and two viscous dampers are investigated. The constitutive relationships for elastic forces of both springs are postulated in the form of the third-order power law. The geometric nonlinearity caused by the transverse motion of the pendulum is approximated by three terms of the Taylor series, which limits the range of applicability of the obtained results to swings with maximum amplitudes of about 0.6 rad. The system has two degrees of freedom, but its motion is described by two differential equations and one algebraic equation which have been derived using the Lagrange equations of the second kind. The classical multiple scales method (MSM) in the time domain was employed. However, the MSM variant with three scales of the time variable has been modified by developing new and dedicated algorithms to adapt the technique to solving problems described by the differential and algebraic equations (DAEs). The paper investigates the cases of forced and damped oscillation in non-resonant conditions, three cases of external resonances, and the internal 1: 2 resonance in the system. Moreover, the analysis of the stationary periodic states with external resonances was carried out, and investigations into the system’s stability were concluded in each case. Two methods of assessing asymptotic solutions have been proposed. The first is based on the determination of the error satisfying the equations of the mathematical model. The second one is a relative measure in the sense of the L2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${L}^{2}$$\end{document}-norm, which compares the asymptotic solution with the numerical one determined using the NDSolve procedure of Mathematica software. These measures show that the applied MSM solves the system to a high degree of accuracy and exposes the key dynamical features of the system. It was observed that the system exhibits jump phenomena at some points in the resonance cases, with stable and unstable periodic orbits. This feature predicts chaotic vibration in the system and defines the regions for its applications.
LinB and DhaA are well-known haloalkane dehalogenases (HLDs) capable of converting a plethora of halogenated alkanes, also those considered persistent pollutants. One way of studying the nature and efficiency of these important enzymes is to measure the kinetic isotope effect (KIE) on the metabolized reaction, in particular leaving group (either chloride or bromide) KIE. Although the general mechanism via which these two dehalogenating enzymes operate has been already studied and described, the isotope effects data providing information on the mechanistic details, especially Br KIE are scarce. In this work we aimed at gaining insights into the enzymatic dehalogenation of dibromo- and bromo-chloro- ethanes by LinB and DhaA, by combining experimental and computational methods. A model developed this way has been subsequently extended to dihalopropanes. Using the predicted free energy surface of the reaction catalyzed by HLD and kinetic isotope effects based on QM/MM calculations it has been demonstrated that with respect to the magnitudes of Br KIE conversion of 1,2-dibromoethane, 1-bromo-2-chloroethane or 1,2-dibromopropane, and therefore also other propanes should not differ. In the case of C KIE the scenario might be different as depending on the carbon position adjacent to the eliminated bromine substituent one can observe either larger or smaller isotope effect (~1.06 or 1.04 for the primary and secondary position, respectively). By predicting halogen binding isotope effects (BIEs) as well as computing interaction energy for each HLD-ligand complex the binding event preceding a chemical change in the active site has been characterized. The magnitude and direction of BIEs are discussed thoroughly by invoking the dynamics and the architecture of each active site, the strength of interactions with the first shell residues, and pointing to the dominating forces determining the binding of each of the studied ligands.
Distilleries generate huge amounts of by-products that have a negative impact on the environment, so the management of wastes generated by this sector should be improved. Because distillery by-products are a source of bioactive compounds, the recovery of these compounds not only reduces issues with environmental protection but also provides the basis for a waste-to-profit solution. Following the latest trends in the search for so-called green extraction techniques for recovering valuable products, this study investigated the effect of subcritical water extraction (SWE) conditions (temperature (25-260 • C), time (5-90 min), and solid-to-solvent ratio (1:5-1:50, w:v)) on the efficiency of recovery of bioactive compounds, i.e., polyphenols from distillery stillage, and on the antioxidant activity of the extracts. The highest extraction yield was obtained with 30-min SWE with a solid-to-solvent ratio of 1:15 at either 140 • C (for total polyphenol content and phenolic acid content) or 200 • C (for total flavonoid content), as indicated by the Response Surface Methodology analysis. Phenolic acids in the extracts were present mainly in free forms (up to 88% of the total content). The antioxidant activity, which was measured using several assays, correlated positively with the content of phenolic acids, which confirmed their significant contribution to the bioactive properties of the extracts. The antioxidant effects of the extracts were mostly due to hydroxycinnamic acids (especially ferulic and p-coumaric acids). Principal component analysis showed that the temperature and time of SWE were the factors that can explain the greatest amount of variation in the extraction yield, composition, and bioactive properties of the polyphenols. These results will influence the design of further processes, such as purification and concentration, which are necessary before using the extracted compounds as substrates that are applicable in various industries. Based on the analysis of the elemental composition, the biomass remaining after SWE was evaluated to consider the possibilities of its further utilization.
Global interest in the use of hydrogen as an alternative fuel to classical petroleum-based fuels has already assumed the form of concepts and plans based on which, by 2030, cars powered by this most popular element in the universe are to appear on roads of almost the entire world. This is not the first attempt in the history of mankind to use hydrogen in transportation. The first approach was at the beginning of the 20th century and the “golden era” of airships. The beginning of its end was the disaster of the British airship R101. It was the largest British airship, constructed to handle connections with the colonies. It crashed in France on its way to India due to a hydrogen leak on the night of 1 to 2 October 1930. After this disaster, work on large-scale, long-range airships was halted. Almost 100 years later, hydrogen is again appearing in transport in the broad sense, but this time as a fuel. Taking into account the physicochemical characteristics of hydrogen (the widest explosive limits after acetylene and the lowest minimum ignition energy of all gases) and the high ease of its penetration through all kinds of joints, seals and valves, it is necessary at this stage to develop and implement safety procedures related to transport, storage and refuelling of hydrogen vehicles. Procedures and operating principles of hydrogen stations used for fuelling both trucks and cars developed and implemented on the territory of the United States should be a starting point before construction may be started of dozens of similar facilities in our country as declared by Polish decision makers.
In this paper the explosive and fire properties of energy willow dust were experimentally determined before and after drying with superheated steam at temperatures of 120°C, 140°C, 160°C and 180°C. The conducted research has shown that the parameters of the operation of the installation of drying with superheated steam of the energy willow biomass have a decisive impact on the fire-explosive characteristics of the dust produced. The results indicate that the higher the drying temperature, the stronger the probability of ignition of the willow dust cloud, the faster the flame propagation and the higher the explosion intensity. Although the superheated steam drying installation for energy willow biomass is considered to be safe, the probability of occurrence of a fire or explosion events of the biomass dust-air mixture is likely.
Melatonin, the major secretory product of the pineal gland, not only regulates circadian rhythms, mood, and sleep but also has actions in neoplastic processes which are being intensively investigated. Melatonin is a promising molecule which considered a differentiating agent in some cancer cells at both physiological and pharmacological concentrations. It can also reduce invasive and metastatic status through receptors MT1 and MT2 cytosolic binding sites, including calmodulin and quinone reductase II enzyme, and nuclear receptors related to orphan members of the superfamily RZR/ROR. Melatonin exerts oncostatic functions in numerous human malignancies. An increasing number of studies report that melatonin reduces the invasiveness of several human cancers such as prostate cancer, breast cancer, liver cancer, oral cancer, lung cancer, ovarian cancer, etc. Moreover, melatonin's oncostatic activities are exerted through different biological processes including antiproliferative actions, stimulation of anti-cancer immunity, modulation of the cell cycle, apoptosis, autophagy, the modulation of oncogene expression, and via antiangiogenic effects. This review focuses on the oncostatic activities of melatonin that targeted cell cycle control, with special attention to its modulatory effects on the key regulators of the cell cycle, apoptosis, and telomerase activity.
PURPOSE: This paper aims to provide a comprehensive review of scholarly research focusing on using quantitative methods and particularly structural equation modeling (SEM) in management and economics studies, as well as provide a bibliometric agenda including the time horizon of individual publications, the highest citation rate, geographic and industry areas, methodological context, and keywords. METHODOLOGY: A systematic literature review (SLR) was undertaken using the Web of Science and Scopus databases. We limited our search to the last five years to identify the newest research publications, and we used keywords related to quantitative research while excluding qualitative research. Then we analyzed papers related to SEM and those published in English. FINDINGS: Our results confirmed that quantitative methods are used both in management and economics research, and showed a growing trend in the number of publications in the last five years. However, there are many more publications on management than on economics as well as there are more papers published in the Scopus database than Web of Science. Taking into account structural equation modeling, this method is used primarily in 1 Agnieszka Zakrzewska-Bielawska, Full Professor, Dean / Use of structural equation modeling in quantitative research in the field of management and economics: A bibliometric analysis in the systematic literature review management research. In terms of industry, publications using SEM considered both single-and multi-industry including, first, all Asian countries and then African ones. Publications, especially in the management field, are descriptive in nature and based on primary data collected using a survey questionnaire. Papers are published in various journals and the most cited are those published in journals with wider subject areas. IMPLICATIONS: The systematic literature review is a fundamental necessity in any field of knowledge, benefiting both academia and learners. Our results may be useful for future researchers planning research using quantitative methods, especially SEM, in the business or economic field, by indicating the most cited papers and journals as well as industry and country areas. ORIGINALITY AND VALUE: This paper represents a systematic attempt to link quantitative methods, with a particular emphasis on SEM, with research interests on managerial and economic subjects and papers published in the Web of Science and Scopus databases. Employing the bibliometric analysis within the systematic literature review, the paper shows interest and the current state of research using quantitative methods which proves its value and originality.
This paper presents a method for the synthesis of ammonium alginate by interphase gas-solid reaction. It was confirmed by FTIR ATR spectroscopy analysis that a full substitution of acid groups by ammonium groups on the surface of powdered alginic acid was performed. Comparative studies on the properties of ammonium alginate solutions obtained by interphase reaction with those prepared by the classical method of dissolving alginic acid in an ammonia solution showed that the rheological properties of the solutions from these two derivatives do not differ significantly. Moreover, it was shown that aqueous solutions of ammonium alginate are more stable over time than solutions of sodium alginate. It was confirmed that ammonium alginate and sodium alginate are typical polyelectrolytes, as the addition of a low molecular weight electrolyte to their solutions resulted in a decrease in viscosity.
Stinging nettle (Urtica dioica L.) is a common perennial herb well known for its therapeutic, cosmetic and food use. Despite the popularity of nettle hydrolate, there is currently no literature describing its composition; likewise, there is still a lack of research describing in detail the parameters of hydrolates in general. U. dioica hydrolate fractions were obtained by industrial steam distillation of fresh herb. Total stinging nettle hydrolate was prepared by mixing an equal volume of each fraction. The volatiles were isolated from hydrolate samples by liquid–liquid extraction with diethyl ether, and analysed using GC-FID-MS. Over eighty volatile compounds were identified in U. dioica hydrolate. The main group of constituents were oxygenated compounds, mainly alcohols (e.g., (E)- and (Z)-hex-3-en-1-ol, carvacrol) and oxides (e.g., caryophyllene oxide). The content of volatiles in the representative sample of total hydrolate amounted to 58.2 mg/L. Some qualitative and quantitative changes in the composition of U. dioica hydrolate were observed during the progress of distillation. The content of low chain aliphatic alcohols ((E)- and (Z)-hex-3-en-1-ol) decreased, whereas the percentage of some monoterpene alcohols (carvacrol and α-terpineol) increased. The total content of volatiles in hydrolate also changed and decreased (128.0–6.2 mg/L) during distillation progress. According to our results, to produce stinging nettle hydrolate of good quality, the proper relationship between the amount of hydrolate and raw plant material should result in obtaining 0.74 L hydrolate from 1 kg of fresh stinging nettle herb. Therefore, it may be assumed that the high alcohol content may increase the microbiological stability of the product.
The aim of the research was to use bioactive heteropolysaccharides isolated from rye bran to obtain innovative systems for the controlled release of bioactive compounds. The core of the obtained encapsulates was honey and royal jelly. It was shown for the first time that preparations effectively ameliorated inflammatory response in lipopolysaccharide (LPS)-treated RAW 264.7 macrophages, decreasing the secretion of interleukin 6 (IL-6), tumor necrosis factor α (TNF-α) and nitric oxide (NO). The in vitro digestion process revealed that bee products’ encapsulates were stronger oxidative stress reducers and had sustained ability to reduction in inflammation state mediators. The lack of inhibitory effect on migration rate of human microvascular endothelial cells (HMEC-1) endothelial cells and mouse embryonic fibroblasts (NIH-3T3), both cell models involved in wound healing process, additionally identified these preparations as agents potentially used in the management of inflammatory response. In the process of a simulated digestion in vitro, the innovative microcapsules showed 85% higher biostability and two to ten times better bioavailability, compared to natural bee products.
A porous TiO2 layer was prepared with the plasma electrolytic oxidation (PEO) of Ti. In a further step, Pd was deposited on the TiO2 surface layer using the adsorption method. The activity of the Pd/TiO2/Ti catalyst was investigated during the oxidation of CO to CO2 in a mixture of air with 5% CO. The structure of the catalytic active layer was studied using a scanning electron microscope equipped with an energy dispersive spectrometer (SEM-EDS), time-of-flight secondary ion mass spectrometry (TOF-SIMS), inductively coupled plasma mass spectrometry (ICP-MS), and X-ray diffraction (XRD). The PEO process provided a porous TiO2 layer with a uniform thickness in the range of 5–10 µm, which is desirable for the production of Pd-supported catalysts. A TOF-SIMS analysis showed the formation of Pd nanoparticles after the adsorption treatment. The conversion of CO to CO2 in all samples was achieved at 150–280 °C, depending on the concentration of Pd. The composition of Pd/ TiO2/Ti was determined using ICP-MS. The optimum concentration of Pd on the surface of the catalyst was approximately 0.14% wt. This concentration was obtained when a 0.4% PdCl2 solution was used in the adsorption process. Increasing the concentration of PdCl2 did not lead to a further improvement in the activity of Pd/ TiO2/Ti.
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