Gypsum labyrinthine caves are characterized by a complex spatial structure, which can be treated as fractals and can be studied using appro- priate mathematical tools. Capacitance and correlation fractal dimensions of largest gypsum caves of the Western Ukraine (as well as the World’s largest ones) were calculated. The results were used to predict findings of new, undiscovered cave mazes parts.
00728nas a2200157 4500000000100000000000100001000000100002008004100003260000700044100002700051700002300078700002100101245006300122520037100185022001400556 2013 d c11 1 aViacheslav Andreychouk 1 aTomasz Błachowicz 1 aKrzysztof Domino 00 aFractal dimensions of gypsum cave-mazes of Western Ukraine 3 aGypsum maze caves of Western Ukraine are characterized by a complex spatial structure, which can be treated as fractals and can be studied using appropriate mathematical tools. Capacitance and correlation fractal dimensions of largest gypsum caves of the region were calculated. The results were used to predict findings of new, yet undiscovered parts of cave mazes. a1997-7492 00899nas a2200133 4500000000100000000000100001008004100002100002100043245010900064300001400173490000800187520055000195022002000745 2012 d 1 aKrzysztof Domino 00 aThe use of the Hurst exponent to investigate the global maximum of the Warsaw Stock Exchange WIG20 index a156–169 0 v391 3 aThe WIG20 index – the index of the 20 biggest companies traded on the Warsaw Stock Exchange – reached the global maximum on 29th October 2007. I have used the local DFA (Detrended Functional Analysis) to obtain the Hurst exponent (diffusion exponent) and investigate the signature of anti-correlation of share price evolution around the maximum. The analysis was applied to the share price evolution for variable DFA parameters. For many values of parameters, the evidence of anti-correlation near the WIG20 maximum was pointed out.
aISSN: 0378-4371 01301nas a2200133 4500000000100000000000100001008004100002100002100043245009200064300001300156490000800169520097600177022001401153 2011 d 1 aKrzysztof Domino 00 aThe use of the Hurst exponent to predict changes in trends on the Warsaw Stock Exchange a98–109 0 v390 3 aThe local properties of the time series of the evolution of share prices of 126 significant companies traded on the Warsaw Stock Exchange during the period between 1991–2008 have been investigated. The analysis was applied to daily financial returns. I have used the local DFA to obtain the Hurst exponent (diffusion coefficient) while searching for negative correlations by which changes of long-term trends would be effected. A certain evidence, proving that after the signature of anti-correlation – the drop in the Hurst exponent – the change in the trend and in the return rate of an investment is probable, was pointed out. Hence after further investigation this method may be useful as a part of an investment strategy. As the Warsaw Stock Exchange is relatively smaller and younger than other significant world Stock Exchanges – and as the developing market is less efficient – the generalization for others markets needs further investigation.
a0378-4371 01174nas a2200157 4500000000100000000000100001008004100002260001200043100002100055700002300076245011000099300001400209490000800223520077100231022001401002 2015 d c01/2015 1 aKrzysztof Domino 1 aTomasz Błachowicz 00 aThe use of copula functions for modeling the risk of investment in shares traded on world stock exchanges a142–151 0 v424 3 aIn this paper the two dimensional model of the investment in shares is presented. The shares prices from five different world stock exchanges (New York, London, Frankfurt, Honk Kong, and Sydney) are examined. The copula functions are used to model the risk of investment. The Hurst threshold exponent derived from the local Detrended Fluctuation Analysis is used to determine the safe investment portfolios with no extreme drops in shares prices. The most important result states that the threshold value is not universal for different markets, however, it is influenced by the subsequent level of market freedom. It was shown, that the level, relatively larger in US, UK, and Australia than in Germany and China, affects the Hurst exponent threshold value.
a0378-4371 01349nas a2200145 4500000000100000000000100001008004100002100002100043700002300064245011400087300001200201490000800213520096800221022001401189 2014 d 1 aKrzysztof Domino 1 aTomasz Błachowicz 00 aThe use of copula functions for modeling the risk of investment in shares traded on the Warsaw Stock Exchange a77–85 0 v413 3 aIn our work copula functions and the Hurst exponent calculated using the local Detrended Fluctuation Analysis (DFA) were used to investigate the risk of investment made in shares traded on the Warsaw Stock Exchange. The combination of copula functions and the Hurst exponent calculated using local DFA is a new approach. For copula function analysis bi- variate variables composed of shares prices of the PEKAO bank (a big bank with high capitalization) and other banks (PKOBP, BZ WBK, MBANK and HANDLOWY in decreasing capitalization order) and companies from other branches (KGHM—mining industry, PKNORLEN—petrol industry as well as ASSECO—software industry) were used. Hurst ex- ponents were calculated for daily shares prices and used to predict high drops of those prices. It appeared to be a valuable indicator in the copula selection procedure, since Hurst exponent’s low values were pointing on heavily tailed copulas e.g. the Clayton one.
a0378-4371 01430nas a2200169 4500000000100000000000100001008004100002260001200043100002100055700002300076700001900099245010000118300001400218490000800232520100600240022001401246 2014 d c07/2014 1 aKrzysztof Domino 1 aTomasz Błachowicz 1 aMaurycy Ciupak 00 aThe use of copula functions for predictive analysis of correlations between extreme storm tides a489–497 0 v413 3 aIn this paper we present a method used in quantitative description of weakly predictable hydrological, extreme events at inland sea. Investigations for correlations between variations of individual measuring points, employing combined statistical methods, were carried out. As a main tool for this analysis we used a two-dimensional copula function sensitive for correlated extreme effects. Additionally, a new proposed methodology, based on Detrended Fluctuations Analysis (DFA) and Anomalous Diffusion (AD), was used for the prediction of negative and positive auto-correlations and associated optimum choice of copula functions. As a practical example we analysed maximum storm tides data recorded at five spatially separated places at the Baltic Sea. For the analysis we used Gumbel, Clayton, and Frank copula functions and introduced the reversed Clayton copula. The application of our research model is associated with modelling the risk of high storm tides and possible storm flooding.
a0378-4371 01375nas a2200181 4500000000100000000000100001008004100002100001900043700002300062700002100085700001900106700001700125700001700142245010000159490001200259520090800271022001401179 2015 d 1 aAndrea Ehrmann 1 aTomasz Błachowicz 1 aKrzysztof Domino 1 aSusanne Aumann 1 aMarcus Weber 1 aHafed Zghidi 00 aExamination of hairiness changes due to washing in knitted fabrics using a random walk approach 0 v85 (20) 3 aThe relaxation of knitted fabrics is usually described in terms of dimensional changes of knitted loop widths and heights or fabric widths and heights, respectively. Due to washing, however, additional changes in the optical appearance and the haptic properties of a knitted fabric can occur, such as a change in the regularity or the hairiness. This article uses the random walk statistical approach to estimate the structural complexity of knitted fabrics directly after production and up to 10 washing cycles and shows that the Hurst exponent, resulting from the random walk process, is partly related to the cover factor of the knitted fabrics under investigation; however, it depicts significant contributions of the hairiness. Thus, this novel approach offers a quantitative measure of structural changes in knitted fabrics that cannot be described by cover factor or dimensional changes.
a1746-7748 01556nas a2200157 4500000000100000000000100001000000100002008004100003100001800044700001300062700001600075700002100091245010800112490000700220520117100227 2013 d 1 aN. Kruszewska 1 aP. Weber 1 aA. Gadomski 1 aKrzysztof Domino 00 aA METHOD OF MECHANICAL CONTROL OF STRUCTURE-PROPERTY RELATIONSHIP IN GRAINS-CONTAINING MATERIAL SYSTEMS 0 v44 3 aMaterial systems can grow indefinitely large unless there appear some physical restrictions superimposed on them. At first approximation, they can be restricted in their evolution by means of an external mechanical factor such as pressure. If the material system’s evolution can be described by a Smoluchowski type equation in the phase space of grain sizes, the average grain size magnitude can be suitably controlled by such mechanical factor. Both magnitude and direction of the factor can render the grain sizes either bigger or smaller than the one expected without any influence of the factor. We propose to embody the mechanical factor in the drift term of the corresponding Smoluchowski equation, in general, derivable from the entropy production principle. Such an embodiment allows one to modify controllably (over certain distinguished time scales of the process) the grain sizes, thus, the mechanically affected material properties such as superplasticity or superconductivity. A simple econophysical example, addressing investment strategies upon random-market tensions, is added to support the overall rationale of the method thus developed.
00881nas a2200169 4500000000100000000000100001008004100002100001700043700001900060700002200079700002100101700001900122245007500141300001400216490000600230520047500236 2015 d 1 aHafed Zghidi 1 aMaksym Walczak 1 aTomasz Blachowicz 1 aKrzysztof Domino 1 aAndrea Ehrmann 00 aImage Processing and Analysis of Textile Fibers by Virtual Random Walk a717–720 0 v5 3 aAn algorithm for extracting material shape and spatial information from non-uniform background, and for generating object skeletons for statistical two-dimensional experiments using random walk approach, is presented. This finds applications in textile analysis and microscopic analysis of various materials like hairs and allows for further precise determination of textile yarn dimensions as well as other geometrical characteristics like a fractal dimension.
01428nas a2200181 4500000000100000000000100001008004100002260000900043100002100052700002300073700002700096245009000123856010300213300001200316490000700328520089500335022001601230 2015 d c2015 1 aKrzysztof Domino 1 aPrzemysław Głomb 1 aZbigniew Łaskarzewski 00 aClassification of LPG clients using the Hurst exponent and the correlation coeficient uhttp://yadda.icm.edu.pl/yadda/element/bwmeta1.element.baztech-1ba91297-f921-4524-927c-381996c36512 a13–24 0 v27 3 aIn this paper we present the analysis of the gas usage for different types of buildings. First, we introduce the classical theory of building heating. This allows the establishment of theoretical relations between gas consumption time series and the outside air temperature for different types of buildings, residential and industrial. These relations imply dierent auto-correlations of gas usage time series as well as different cross-correlations between gas consumption and temperature time series for different types of buildings. Therefore, the autocorrelation and the cross-correlation were used to classify the buildings into three classes: housing, housing with high thermal capacity, and industry. The Hurst exponent was calculated using the global DFA to investigate auto-correlation, while the Kendall's τ rank coeficient was calculated to investigate cross-correlation
a 1896-5334 01178nas a2200169 4500000000100000000000100001008004100002100002200043700001900065700002100084245012100105856007100226300001400297490000800311520067500319022001400994 2016 d 1 aTomasz Blachowicz 1 aAndrea Ehrmann 1 aKrzysztof Domino 00 aStatistical analysis of digital images of periodic fibrous structures using generalized Hurst exponent distributions uhttp://www.sciencedirect.com/science/article/pii/S0378437116001795 a167 - 177 0 v452 3 aAbstract Distinction of diverse two-dimensional periodic structures can be based on a large number of methods and parameters, while the quantitative description of differences between similar samples is usually difficult. This article aims, by the use of statistical random walk in a generalized q-order dimensional space, at introducing a methodology to qualify the networked structures on the basis of exemplary textile samples. The presented results were obtained at 1-bit monochromatic maps obtained from optical microscopic pictures. Significant features of samples were represented by the obtained distributions of Hurst exponents and Shannon entropy calculations. a0378-4371 01766nas a2200133 4500000000100000000000100001008004100002100002200043700001900065700001700084700002100101245007400122520143600196 2015 d 1 aTomasz Blachowicz 1 aAndrea Ehrmann 1 aHafed Zghidi 1 aKrzysztof Domino 00 aOptical determination of hemp fiber structures by statistical methods 3 aOne of the most challenging tasks in optical examination of natural fibers – besides measuring fiber lengths and diameters – is the determination of the possible existence of branches in a fiber. Since usual automatic fiber examination systems are known to be irritated by fiber bifurcations, possibly leading to unreliable length measurements, a mechanism to detect and evaluate side branches would be helpful for both the developers and users of automatic fiber examination systems. Additionally, fibers with higher and lower amounts of bifurcations can be expected to show different mechanical properties when spun to a yarn or used in a fiber -reinforced plastic composite. Thus, different statistical methods have been used for image processing of scanned or microscopic pictures of natural fibers, such as hemp, flax, or linen. One of them, the so-called random-walk method, has been used before for the examination of microscopic images of yarns [1] and knitted fabrics [2-4], resulting in a novel method to measure yarn hairiness and fiber fineness optically. The article gives an overview of different shapes of single hemp fibers and fiber bundles and shows which differentiations can be made using statistical methods on the scanned pictures, pre-treated with newly developed numerical filters. These approaches are used to distinguish between hemp fibers which have been pre-treated with different methods.
01085nas a2200217 4500000000100000000000100001008004100002100001900043700001400062700002200076700002100098700001200119700001400131700001300145700001300158700002000171245005400191300001100245490000800256520060300264 2016 d 1 aAndrea Ehrmann 1 aS Komraus 1 aTomasz Blachowicz 1 aKrzysztof Domino 1 aMK Nees 1 aPJ Jakobs 1 aH Leiste 1 aM Mathes 1 aM Schaarschmidt 00 aPseudo exchange bias due to rotational anisotropy a7–10 0 v412 3 aFerromagnetic nanostructure arrays with particle dimensions between 160 nm and 400 nm were created by electron-beam lithography. The permalloy structures consist of rectangular-shaped walls around a square open space. While measuring their magnetic properties using the Magneto-Optical Kerr Effect (MOKE), in some angular regions an exchange bias (EB) seemed to appear. This paper gives an overview of possible reasons for this “pseudo exchange bias” and shows experimentally and by means of micromagnetic simulations that this effect can be attributed to unintentionally measuring minor loops. 01689nas a2200133 4500000000100000000000100001008004100002260001200043100002100055245010800076856005000184490000800234520131300242 2017 d c10/2016 1 aKrzysztof Domino 00 aThe use of the multi-cumulant tensor analysis for the algorithmic optimisation of investment portfolios uhttp://dx.doi.org/10.1016/j.physa.2016.10.042 0 v467 3 aThe cumulant analysis plays an important role in non Gaussian distributed data analysis. The shares' prices returns are good example of such data. The purpose of this research is to develop the cumulant based algorithm and use it to determine eigenvectors that represent investment portfolios with low variability. Such algorithm is based on the Alternating Least Square method and involves the simultaneous minimisation 2'nd - 6'th cumulants of the multidimensional random variable (percentage shares' returns of many companies). Then the algorithm was tested during the recent crash on the Warsaw Stock Exchange. To determine incoming crash and provide enter and exit signal for the investment strategy the Hurst exponent was calculated using the local DFA. It was shown that introduced algorithm is on average better that benchmark and other portfolio determination methods, but only within examination window determined by low values of the Hurst exponent. Remark that the algorithm of is based on cumulant tensors up to the 6'th order calculated for a multidimensional random variable, what is the novel idea. It can be expected that the algorithm would be useful in the financial data analysis on the world wide scale as well as in the analysis of other types of non Gaussian distributed data.
00361nas a2200133 4500000000100000000000100001008004100002100002100043700001400064700002400078245008100102856003700183490000700220 2017 d 1 aKrzysztof Domino 1 aAdam Glos 1 aMateusz Ostaszewski 00 aSuperdiffusive quantum stochastic walk definable on arbitrary directed graph uhttps://arxiv.org/abs/1701.04624 0 v17 00430nas a2200157 4500000000100000000000100001008004100002100002100043700001400064700002400078700001900102700002500121245008000146856003900226490000700265 2018 d 1 aKrzysztof Domino 1 aAdam Glos 1 aMateusz Ostaszewski 1 aŁukasz Pawela 1 aPrzemysław Sadowski 00 aProperties of quantum stochastic walks from the asymptotic scaling exponent uhttps://doi.org/10.26421/QIC18.3-4 0 v18 01097nas a2200157 4500000000100000000000100001008004100002100002100043700001700064700001900081245005900100856005400159300001000213490000700223520070900230 2018 d 1 aKrzysztof Domino 1 aPiotr Gawron 1 aŁukasz Pawela 00 aEfficient computation of higher order cumulant tensors uhttps://epubs.siam.org/doi/abs/10.1137/17M1149365 aA1610 0 v40 3 aIn this paper, we introduce a novel algorithm for calculating arbitrary order
cumulants of multidimensional data. Since the d'th order
cumulant can be presented in the form of an d-dimensional tensor, the
algorithm is presented using tensor operations. The algorithm provided in the
paper takes advantage of super-symmetry of cumulant and moment tensors.
We show that the proposed algorithm considerably reduces the computational
complexity and the computational memory requirement of cumulant calculation as
compared with existing algorithms. For the sizes of interest, the
reduction is of the order of d! compared to the naive algorithm.
High order cumulant tensors carry information about statistics of non-normally distributed multivariate data. In this work we present a new efficient algorithm for calculation of cumulants of arbitrary order in a sliding window for data streams. To present an application of the algorithm, we propose a measure of non-normality of data stream based on tensor norms of high order cumulant tensors. We show how to detect the transition from Gaussian distributed data to non-Gaussian ones in a~data stream. In order to achieve high implementation efficiency of operations on super-symmetric tensors, such as cumulant tensors, we employ the block structure to store and calculate only one hyper-pyramid part of such tensors.
01587nas a2200121 4500000000100000000000100001008004100002100002100043700001400064245011600078856003700194520123400231 2018 d 1 aKrzysztof Domino 1 aAdam Glos 00 aIntroducing higher order correlations to marginals' subset of multivariate data by means of Archimedean copulas uhttps://arxiv.org/abs/1803.07813 3 aIn this paper, we present the algorithm that alters the subset of marginals of multivariate standard distributed data into such modelled by an Archimedean copula. Proposed algorithm leaves a correlation matrix almost unchanged, but introduces a higher order correlation into a subset of marginals. Our data transformation algorithm can be used to analyse whether particular machine learning algorithm, especially a dimensionality reduction one, utilises higher order correlations or not. We present an exemplary application on two features selection algorithms, mention that features selection is one of the approaches to dimensionality reduction. To measure higher order correlation, we use multivariate higher order cumulants, hence to utilises higher order correlations be to use the Joint Skewness Band Selection (JSBS) algorithm that uses third-order multivariate cumulant. We show the robust performance of the JSBS in contrary to the poor performance of the Maximum Ellipsoid Volume (MEV) algorithm that does not utilise such higher order correlations. With this result, we confirm the potential application of our data generation algorithm to analyse a performance of various dimensionality reduction algorithms.
01325nas a2200133 4500000000100000000000100001008004100002260001200043100002100055245007600076490000800152520101700160022001401177 2020 d c07/2020 1 aKrzysztof Domino 00 aMultivariate cumulants in outlier detection for financial data analysis 0 v558 3 aThere are many research papers yielding the financial data models, where returns are tied either to the fundamental analysis or to the individual, often irrational, behaviour of investors. In the second case the bubble followed by the crisis is possible on the market. Such bubble or crisis is reflected by the cross-correlated extreme positive or negative returns of many assets. Such returns are modelled by the copula with the meaningful tail dependencies. The typical model of such cross-correlation provides the t-Student copula. The author demonstrates that the mutual information tied to this copula can be measured by the 4th order multivariate cumulants. Tested on the artificial data, the 4th order multivariate cumulant approach was used successfully for the financial crisis detection. For this end the author introduces the outliers detection algorithm. In addition this algorithm displays the potential application for the crisis prediction, complementary to the auto-correlation analysis.
a0378-4371 00914nas a2200157 4500000000100000000000100001008004100002260001200043100002200055700002700077700002100104245009100125856010300216490000700319520043000326 2018 d c06/2018 1 aTomasz Blachowicz 1 aViacheslav Andreychouk 1 aKrzysztof Domino 00 aRandom walk analysis of cave maps for exemplary gypsum caves- mazes of Western Ukraine uhttp://yadda.icm.edu.pl/yadda/element/bwmeta1.element.baztech-4877dc6c-6a75-45ae-bf9c-dffa091a26a1 0 v36 3 aThe paper presents a new method of quantitative parameterization of net geomorphological struc-
tures with the use of random walk formalism and an analysis of Hurst exponent distribution derived from
random walk experiments. As examples, horizontally developed gypsum caves were elaborated. The provid-
ed methodology is able to uniquely characterize cave systems.
00522nas a2200169 4500000000100000000000100001008004100002260001200043100002300055700002400078700002000102700002100122245011600143856007100259490000800330022001400338 2018 d c07/2018 1 aPrzemysław Głomb 1 aMichał Romaszewski 1 aMichał Cholewa 1 aKrzysztof Domino 00 aApplication of hyperspectral imaging and Machine Learning methods for the detection of gunshot residue patterns uhttp://www.sciencedirect.com/science/article/pii/S0379073818303657 0 v290 a0379-0738 02151nas a2200157 4500000000100000000000100001008004100002260001200043100002300055700002100078700002300099245013800122856005300260490000800313520167200321 2019 d c11/2018 1 aMałgorzata Domino 1 aKrzysztof Domino 1 aZdzisław Gajewski 00 aAn application of higher order multivariate cumulants in modelling of myoelectrical activity of porcine uterus during early pregnancy uhttps://doi.org/10.1016/j.biosystems.2018.10.019 0 v175 3 a
The analysis of the uterine contraction have become a general practice in an effort to improve the clinical management of uterine contractions during pregnancy and labour in human beings. The fluctuations in uterine activity may occur without affecting progress of gestation, however the painful and fashion contractions may be the first threat of misscarage. While pigs were considered as an referential preclinical model, the computational modelling of spontaneous myoelectrical activity of complex systems of porcine myometrium in peri-fertilization period has been proposed. The higher order statistic, multivariate cumulants and Joint Skewness Band Selection method, have been applied to study the dependence structure of electromyographic (EMG) signal with an effective EMG feature. Than the model of recognition of multivariate, myoelectricaly changes according to crucial stages for successful fertilization and early pregnancy maintenance has been estimated. We found that considering together time and frequency features of EMG signal was extremely non-Gaussian distributed and the higher order multivariate statistics such as cumulants, have to be used to determine the pattern of myoelectrical activity in reproductive tract. We confirmed the expectance that the probabilistic model changes on a daily base. We demonstrated the changes in proposed model at the crucial time points of in peri-fertilization period. We speculate the activity of the middle of uterine horn and the power (minimum and maximum) and pauses between myoelectrical burst features are essential for the functional role of uterine contractility in peri-fertilization period.
02140nam a2200133 4500000000100000000000100001008004100002260002400043100002100067245005200088856003700140520180100177022002801978 2019 d b IITiS PAN aGliwice 1 aKrzysztof Domino 00 aSelected Methods for non-Gaussian Data Analysis uhttps://arxiv.org/abs/1811.10486 3 aThe basic goal of computer engineering is the analysis of data. Such data are often large data sets distributed according to various distribution models. In this manuscript we focus on the analysis of non-Gaussian distributed data. In the case of univariate data analysis we discuss stochastic processes with auto-correlated increments and univariate distributions derived from specific stochastic processes, i.e. Levy and Tsallis distributions. Deep investigation of multivariate non-Gaussian distributions requires the copula approach. A copula is an component of multivariate distribution that models the mutual interdependence between marginals. There are many copula families characterised by various measures of the dependence between marginals. Importantly, one of those are `tail' dependencies that model the simultaneous appearance of extreme values in many marginals. Those extreme events may reflect a crisis given financial data, outliers in machine learning, or a traffic congestion. Next we discuss higher order multivariate cumulants that are non-zero if multivariate distribution is non-Gaussian. However, the relation between cumulants and copulas is not straight forward and rather complicated. We discuss the application of those cumulants to extract information about non-Gaussian multivariate distributions, such that information about non-Gaussian copulas. The use of higher order multivariate cumulants in computer science is inspired by financial data analysis, especially by the safe investment portfolio evaluation. There are many other applications of higher order multivariate cumulants in data engineering, especially in: signal processing, non-linear system identification, blind sources separation, and direction finding algorithms of multi-source signals.
aISBN: 978-83-926054-3-0 02528nas a2200193 4500000000100000000000100001008004100002260001200043100002300055700002100078700002200099700001500121700002300136700002300159245013100182856006100313490000800374520195200382 2019 d c01/2019 1 aMałgorzata Domino 1 aKrzysztof Domino 1 aBartosz Pawlinski 1 aMaria Sady 1 aMagdalena Gajewska 1 aZdzisław Gajewski 00 aComputational multivariate modeling of electrical activity of the porcine uterus during spontaneous and hormone-induced estrus uhttp://onlinelibrary.wiley.com/doi/10.1113/EP087451/full 0 v104 3 aIn pig production units, control of the estrous cycle and synchronization of ovulation have become routine herd management procedures. During the estrous cycle, under both induced and spontaneous conditions, the ovaries and the uterus undergo hormone-dominated physiological changes, these are consistent with the hypothesis that there is a functional role of uterine contractions in promoting fertilization. We have used electromyography to determine if the use of exogenous hormones, such as eCG and hCG, that have the potential to control the time of ovulation in female pigs, changes the multivariate relations between parameters of electrical bursts and modulates the patterns of myoelectrical activity. In the study presented here, we employed the mathematical approach of higher order multivariate cumulants in complex modeling of the myometrial electrical activity. The experiment was conducted on 12 mature Polish Landrace sows and uterine activity was recorded during both spontaneous and induced estrous cycles. The burst parameters were determined using six features, in the time domain and after the Fast Fourier transformation in the frequency domain. The evaluation of myoelectrical activity patterns was conducted based on the classical univariate statistical methods and the multivariate probabilistic modelling. The classical statistical approach indicated a weaker myoelectrical activity after hormonal stimulation, whereas the higher order multivariate statistical model showed evidence of similar status of activity and larger order of signals during induced estrus. Routine estrous cycle synchronization affects the multivariate probabilistic model of myometrial electrical activity.
The purpose of this chapter is to discuss methods of acquisition, visualization and analysis of the dynamics of a complex biomedical system, illustrated by the human stomatognathic system. The stomatognathic system consists of the teeth and the skull bones with the maxilla and the mandible. Its dynamics can be described by the change of mutual position of the lower/mandibular part versus the upper/maxillary one due to the physiological motion of opening, chewing and swallowing. In order to analyse the dynamics of the stomatognathic system its morphology and motion has to be digitized, which is done using static and dynamic multimodal imagery like CBCT and 3D scans data and temporal measurements of motion. The integration of multimodal data incorporates different direct and indirect methods of registration - aligning of all the data in the same coordinate system. The integrated sets of data form 4D multimodal data which can be further visualized, modeled, and subjected to multivariate time series analysis. Example results are shown. Although there is no direct method of imaging the TMJ motion, the integration of multimodal data forms an adequate tool. As medical imaging becomes ever more diverse and ever more accessible, organizing the imagery and measurements into unified, comprehensive records can deliver to the doctor the most information in the most accessible form, creating a new quality in data simulation, analysis and interpretation.aISBN 978-83-65603-96-8 02158nas a2200169 4500000000100000000000100001008004100002260005500043100001800098700002100116700002100137700001900158245011200177856003700289520163500326022002701961 2019 d bUTP University of Science & Technology a Bydgoszcz 1 aN. Kruszewska 1 aPiotr Bełdowski 1 aKrzysztof Domino 1 aKanika Lambert 00 aInvestigating conformation changes and network formation of mucin in joints functioning in human locomotion uhttps://arxiv.org/abs/1911.09383 3 a
Many different processes take place to facilitate lubrication of the joints functioning in human locomotion system. The main purpose of this is to avoid destroying the articular cartilage. Viscoelastic properties of the joints system are very sensitive on both temperature and concentration changes because of the change in conformation presented in the system proteins and protein network formation. We are searching for an answer to the question on how changes in temperature and concentration influence the conformational entropy of mucin protein which is a part of one of the key components, lubricin, which is believed to be responsible for gel formation inside synovial fluid. We are using molecular dynamic technique to obtain the information about dihedral (phi, psi) angles of the mucin during protein self - assembly by means of the computer simulation with a time duration up to 50 ns, parameterized by six temperatures ranged between 300 - 315 K, and six concentrations 10.68 - 267.1 g/L. The results show that between c3 and c4 (160 g/L and 214 g/L) a transition exists where crowding begins affecting the dynamics of protein network formation. In such a concentration ranges mucin has a chance to change the frictional properties of the system. Simultaneously there were no significant changes in conformations of the mucins molecules even after they created networks. The temperature changes also did not affect much of mucins conformations but it introduced slightly modifications in dihedral angles and after some critical value T=306 K it changed conformational entropy trend from decreasing to raising.
aISBN 978-83-65603-96-8 01760nas a2200181 4500000000100000000000100001008004100002260002800043100002100071700002100092700002200113700001800135245010400153300001100257490000700268520127600275020002701551 2021 d c11/2019 bSpringer, Cham 1 aPiotr Bełdowski 1 aKrzysztof Domino 1 aDamian Bełdowski 1 aRobert Dobosz 00 aAnalysis of Protein Intramolecular and Solvent Bonding on Example of Major Synovial Fluid Component a93-105 0 v17 3 aMolecular interactions within proteins are fundamental to maintain their conformation and role in biological systems. Understanding the nature and dynamics of the interactions is crucial as it can help understand phenomena occurring during physiological processes, drug design, and delivery, etc. This chapter presents the analysis of the dynamics of molecular interactions inside proteins on an example of albumin. We have performed computer simulations of albumin protein at its native/equilibrium state to understand the dynamics of bonding/interactions inside the protein and with water: hydrogen bonds and hydrophobic interactions. Furthermore, we extracted the data to look into interactions between particular amino acids (AA). As expected, charged AA, such as the glutamic acid (GLU) and lysine (LYS) one, form most intermolecular hydrogen bonds and bind most water.
Further, in hydrophobic contacts, the significant role plays phenylalanine (PHE) and leucine (LEU) amino-acids. We have also found that although its hydrophobic nature, the LEU forms the most stable contacts. This can be attributed to its position in the core of the protein. The presented results may help better understand the dynamics of a complex structure such as protein.
aISBN 978-3-030-67227-0 00555nas a2200169 4500000000100000000000100001008004100002260007300043100002300116700002100139700002400160700002000184245011100204856003700315300001100352020002200363 2019 d c2019 bWroclaw University of Science and Technology aWrocław, Poland 1 aPrzemysław Głomb 1 aKrzysztof Domino 1 aMichał Romaszewski 1 aMichał Cholewa 00 aBand selection with Higher Order Multivariate Cumulants for small target detection in hyperspectral images uhttps://arxiv.org/abs/1808.03513 ap. 121 a978-83-943803-2-8 02409nas a2200181 4500000000100000000000100001008004100002260001200043100002300055700001700078700002100095700002100116700001900137245007000156856009200226490000700318520190200325 2020 d c06/2020 1 aTomasz Błachowicz 1 aTobias Böhm 1 aJacek Grzybowski 1 aKrzysztof Domino 1 aAndrea Ehrmann 00 aAnalysis of AFM images of Nanofibre Mats for Automated Processing uhttp://www.tekstilec.si/wp-content/uploads/2020/06/10.14502Tekstilec2020.63.104-112.pdf 0 v63 3 aThe image processing of pictures from fi bres and fi brous materials facilitates the investigation of diverse ge-ometrical properties, such as yarn hairiness, fi bre bifurcations or fi bre lengths and diameters. Such irregular sample sets are naturally suitable to the statistical examination of images, using a random-walk algorithm. This results in the calculation of the so-called Hurst exponent, which is the asymptotic scaling exponent of the mean squared displacement of the walker’s position. Previous investigations have proven the appropri-ateness of this method for examinations of diff erent fi bres, yarns and textile fabrics. In a recent study, we used AFM (atomic force microscopy) images, split into diff erent greyscales, to analyse and quantify diff er-ences between various nanofi bre mats created from polyacrylonitrile. In addition to the strong infl uence of the nanofi bre diameters, a certain impact of the AFM settings was also seen and must be taken into account in future research.
01724nas a2200169 4500000000100000000000100001008004100002260001900043100001800062700002100080700001600101245004300117300001200160490000700172520134800179020002701527 2021 d bSpringer, Cham 1 aN. Kruszewska 1 aKrzysztof Domino 1 aPiotr Weber 00 aWater Behvaior Near the Lipid Bilayer a107-130 0 v17 3 a
In this chapter, we focus on the dynamics of water molecules situated in the vicinity of a phospholipid bilayer. Using a molecular dynamics simulation method, we studied interactions between water and the bilayer and tracked trajectories of the water molecules. Based on the hypothesis that molecules trapped inside the bilayer make different motions than the ones which are either attached to the surface or move freely in the water bulk, we divided the water molecules into three groups – the ones that exhibited subdiffusion (confined) motion, the ones that move diffusionally in the bulk and the ones that move superdiffusively due to interactions with the moving bilayer. In detail, the water behavior near the bilayer has been analyzed by mean squared displacement and entropy computed separately for the above mentioned three groups of molecules. To explain the subdiffusion motion of the water molecules, the number and the duration of hydrogen bonds created between water molecules and the bilayer have been investigated. In addition, we examined the mechanism of water molecule self-diffusion, by means of statistical tests. Our studies aim to present insight into the understanding of the lipid’s role in water self-diffusion, which can be responsible for triggering different tribological responses of the system.
aISBN 978-3-030-67227-0 00434nas a2200169 4500000000100000000000100001008004100002260001200043100002100055700002400076700002200100700002300122700002200145700002300167245006700190490000700257 2023 d c01/2023 1 aKrzysztof Domino 1 aMátyás Koniorczyk 1 aKrzysztof Krawiec 1 aKonrad Jałowiecki 1 aSebastian Deffner 1 aBartłomiej Gardas 00 aQuantum annealing in the NISQ era: railway conflict management 0 v25 02683nas a2200181 4500000000100000000000100001008004100002260001200043100001800055700002100073700002200094700002100116700001900137245010300156856004600259490001100305520218500316 2020 d c12/2020 1 aN. Kruszewska 1 aKrzysztof Domino 1 aRadosław Drelich 1 aWieslaw Urbaniak 1 aAneta Petelska 00 aInteractions between Beta-2-glycoprotein-1 and phospholipid bilayer – a molecular dynamic study uhttps://doi.org/10.3390/membranes10120396 0 v10(12) 3 aThe study aims to investigate the interactions appearing when the Beta-2-glycoprotein-1 binds to a lipid bilayer. The inter- and intramolecular forces acting between the two macromolecular systems have been investigated using a molecular dynamics simulation method. The importance of water bridges has also been addressed. Additionally, the viscoelastic response of the bilayer has been studied. In detail - the (saturated-chain) DPPC and (unsaturated-chain) POPE bilayers have been chosen to test their behavior near the protein. Both of the lipids have a polar head, but of different chemical structure, and are similar to the main phospholipids present in the synovial fluid. This study is meaningful for further explanation of the worsening friction properties in articular cartilage, as the inactivation of phospholipid bilayers by Beta-2-glycoprotein-1 is believed to be a cause of destruction of cartilage in most rheumatic diseases and osteoarthritis. It was found that the protein binds stronger to the DPPC bilayer than to the POPE, but in both cases, it has the potential to change the local bilayer stability. Nevertheless, the binding forces are placed within a small area (only few lipids contribute to the binding, creating many interactions) but they together are not stronger than the covalent bonds between C-O, thus potentially it is possible to pull the lipids from the bilayer but detaching the lipids’ heads from the tail is not possible. Additionally, the protein causes water displacement from the vicinity of the bilayer, and this may be a contributor to instability of the bilayer (disrupting the water bridges needed for the stabilization of the bilayer). Moreover, it was found that the diffusivity of lipids in the DPPC bilayer bound to the protein is significantly different from the diffusivity of the ones which are not in contact with the protein. The POPE bilayer is stiffer due to intramolecular interactions, which are stronger than in the DPPC, thus the ratio of the viscous to elastic effects in the case of the POPE is greater than in the case of the DPPC. It is therefore harder to destabilize the POPE bilayer than the DPPC one.
03125nas a2200181 4500000000100000000000100001008004100002100002300043700002100066700002200087700002100109700001700130700001900147245010600166856004900272490000700321520261500328 2021 d 1 aTomasz Błachowicz 1 aKrzysztof Domino 1 aMichal Koruszowic 1 aJacek Grzybowski 1 aTobias Böhm 1 aAndrea Ehrmann 00 aStatistical analysis of nanofiber mat AFM images by gray-scale-resolved Hurst exponent distributions uhttps://www.mdpi.com/2076-3417/11/5/2436/pdf 0 v11 3 aTwo-dimensional structures, either periodic or random, can be classified by diverse mathematical methods. Quantitative descriptions of such surfaces, however, are scarce since bijec-tive definitions must be found to measure unique dependency between described structures and the chosen quantitative parameters. To solve this problem, we use statistical analysis of periodic fibrous structures by Hurst exponent distributions. Although such a Hurst exponent approach was suggested some years ago, the quantitative analysis of atomic force microscopy (AFM) images of nanofiber mats in such a way was described only recently. In this paper, we discuss the influence of typical AFM image post-processing steps on the gray-scale-resolved Hurst exponent distribution. Examples of these steps are polynomial background subtraction, aligning rows, deleting horizontal errors and sharpening. Our results show that while characteristic features of these false-color images may be shifted in terms of gray-channel and Hurst exponent, they can still be used to identify AFM images and, in the next step, to quantitatively describe AFM images of nanofibrous surfaces. Such a gray-channel approach can be regarded as a simple way to include some infor-mation about the 3D structure of the image.
01612nas a2200157 4500000000100000000000100001008004100002260001200043100002100055700001600076700001800092700002200110245011100132490000700243520120400250 2022 d c09/2022 1 aKrzysztof Domino 1 aAkash Kundu 1 aÖzlem Salehi 1 aKrzysztof Krawiec 00 aQuadratic and Higher-Order Unconstrained Binary Optimization of Railway Rescheduling for Quantum Computing 0 v21 3 aAs consequences of disruptions in railway traffic affect passenger experience/satisfaction, appropriate dispatching decisions are necessary. The problem of optimal scheduling the order of trains is known to be NP-hard, given the numerous restrictions of traffic nature. With the recent advances in quantum technologies, quantum annealing has become an alternative method to solve optimization problems. To use quantum annealing, the problem needs to be encoded in QUBO (quadratic unconstrained binary optimization) or HOBO (higher-order binary optimization) formulation. This paper introduces QUBO and HOBO representations for dispatching problems of railway traffic management, the latter is a new approach up to our knowledge. This new approach takes into account not only the single-track lines, but also the double- and multi-track lines. We consider the conditions of minimal span between trains, minimal stay on stations, track occupation, and rolling stock circulation. Furthermore, a hybrid algorithm is presented that allows obtaining better solutions compared to the ordinary approach. We demonstrate the implementation on the D-Wave Quantum Processing Unit and its hybrid solver.
00389nas a2200145 4500000000100000000000100001008004100002260001200043100002100055700002400076700002200100245006700122856004700189490000700236 2022 d c08/2022 1 aKrzysztof Domino 1 aMátyás Koniorczyk 1 aZbigniew Puchała 00 aStatistical quality assessment of Ising-based annealer outputs uhttps://doi.org/10.1007/s11128-022-03623-5 0 v21 02583nas a2200193 4500000000100000000000100001008004100002260011900043100001600162700002100178700001800199700002100217700002100238700002200259245012600281856006700407520189300474020002202367 2024 d c03/2024 bSpringer, Cham, Perspectives in Dynamical Systems II — Numerical and Analytical Approaches (DSTA 2021) 1 aPiotr Weber 1 aPiotr Bełdowski 1 aAdam Gadomski 1 aKrzysztof Domino 1 aPiotr Sionkowski 1 aDamian Ledziński 00 aStatistical method for analysis of interactions between chosen protein and chondroitin sulfate in an aqueous environment uhttps://link.springer.com/chapter/10.1007/978-3-031-56496-3_45 3 aWe present the statistical method to study the interaction between a chosen protein and another molecule (e.g., both being components of lubricin found in synovial fluid) in a water environment. The research is performed on the example of univariate time series of chosen features of the dynamics of mucin, which interact with chondroitin sulfate (4 and 6) in four different saline solutions.
Our statistical approach is based on recurrence methods to analyze chosen features of molecular dynamics. Such recurrence methods are usually applied to reconstruct the evolution of a molecular system in its reduced phase space, where the most important variables in the process are taken into account. In detail, the analyzed time-series are spitted onto sub-series of records that are expected to carry meaningful information about the system of molecules. Elements of sub-series are splinted by the constant delay-time lag (that is the parameter determined by statistical testing in our case), and the length of sub-series is the embedded dimension parameter (using the Cao method). We use the recurrent plots approach combined with the Shannon entropy approach to analyze the robustness of the sub-series determination. We hypothesize that the robustness of the sub-series determines some specifics of the dynamics of the system of molecules. We analyze rather highly noised features to demonstrate that such features lead to recurrence plots that graphically look similar. From the recurrence plots, the Shannon entropy has been computed. We have, however, demonstrated that the Shannon entropy value is highly dependent on the delay time value for analyzed features. Hence, elaboration of a more precise method of the recurrence plot analysis is required. For this reason, we suggest the random walk method that can be applied to analyze the recurrence plots automatically.
Motivated by recent efforts to develop quantum computing for practical, industrial-scale challenges, we demonstrate the effectiveness of state-of-the-art hybrid (not necessarily quantum) solvers in addressing the business-centric optimization problem of scheduling Automatic Guided Vehicles (AGVs). Some solvers can already leverage noisy intermediate-scale quantum (NISQ) devices. In our study, we utilize D-Wave hybrid solvers that implement classical heuristics with potential assistance from a quantum processing unit. This hybrid methodology performs comparably to existing classical solvers. However, due to the proprietary nature of the software, the precise contribution of quantum computation remains unclear. Our analysis focuses on a practical, business-oriented scenario: scheduling AGVs within a factory constrained by limited space, simulating a realistic production setting. Our approach maps a realistic AGVs problem onto one reminiscent of railway scheduling and demonstrates that the AGVs problem is better suited to quantum computing than its railway counterpart, the latter being denser in terms of the average number of constraints per variable. The main idea here is to highlight the potential usefulness of a hybrid approach for handling AGVs scheduling problems of practical sizes. We show that a scenario involving up to 21 AGVs, significant due to possible deadlocks, can be efficiently addressed by a hybrid solver in seconds.
01469nas a2200181 4500000000100000000000100001008004100002260001200043100002400055700002200079700002000101700002300121700002100144245011400165856003700279490000700316520096400323 2025 d c05/2025 1 aMátyás Koniorczyk 1 aKrzysztof Krawiec 1 aLudmila Botelho 1 aNikola Bešinović 1 aKrzysztof Domino 00 aSolving rescheduling problems in heterogeneous urban railway networks using hybrid quantum-classical approach uhttps://arxiv.org/abs/2309.06763 0 v34 3 aWe address the applicability of hybrid quantum-classical solvers for practical railway rescheduling management problems. We build an integer linear model for the given problem and solve it with D-Wave's quantum-classical hybrid solver as well as with CPLEX for comparison. The proposed approach is demonstrated on a real-life heterogeneous urban network in Poland, including both single- and double segments and covers all the requirements posed by the operator of the network. The computational results demonstrate the readiness for application and benefits of quantum-classical hybrid solvers in the a realistic railway scenario: they yield acceptable solutions on time, which is a critical requirement in a rescheduling situation. At the same time, the obtained solutions are feasible and in sometimes suboptimal. Moreover, though they are heuristics they offer a valid alternative and most importantly, outperform classical solvers in some cases.
00532nas a2200169 4500000000100000000000100001008004100002260001200043100002100055700002300076700002600099700001900125700002100144245014600165856004400311490000700355 2024 d c04/2024 1 aPiotr Sionkowski 1 aNatalia Kruszewska 1 aAgnieszka Kreitschitz 1 aStanislav Gorb 1 aKrzysztof Domino 00 aApplication of Recurrence Plot Analysis to Examine Dynamics of Biological Molecules on the Example of Aggregation of Seed Mucilage Components uhttps://www.mdpi.com/1099-4300/26/5/380 0 v26 01393nas a2200169 4500000000100000000000100001008004100002260001200043100002100055700002400076700002100100700002200121245007800143856003700221490000700258520095800265 2025 d c03/2025 1 aKatarzyna Gawlak 1 aJarosław Konieczny 1 aKrzysztof Domino 1 aJaroslaw Miszczak 00 aStatistical analysis of geoinformation data for increasing railway safety uhttps://arxiv.org/abs/2406.01083 0 v34 3 aThe impact of rail transport on the environment is one of the crucial factors for the sustainable development of this form of mass transport. We present a data-driven analysis of wild animal railway accidents in the region of southern Poland, a step to create the train driver warning system. We built our method by harnessing the Bayesian approach to the statistical analysis of information about the geolocation of the accidents. The implementation of the proposed a model does not require advanced knowledge of data mining and can be applied even in less developed railway systems with small IT support. Furthermore, we have discovered unusual patterns of accidents while considering the number of trains and their speed and time at particular geographical location of the railway network. We test the developed approach using data from southern Poland, compromising wildlife habitats and one of the most urbanised regions in Central Europe.
01395nas a2200169 4500000000100000000000100001008004100002260001200043100002100055700001700076700002000093700002300113700002200136245006000158490000700218520100000225 2025 d c08/2025 1 aKrzysztof Domino 1 aEmery Doucet 1 aReece Robertson 1 aBartłomiej Gardas 1 aSebastian Deffner 00 aOn the Baltimore Light RailLink into the quantum future 0 v15 3 aIn the current era of noisy intermediate-scale quantum (NISQ) technology, quantum devices present new avenues for addressing complex, real-world challenges including potentially NP-hard optimization problems. This work aims to showcase how the inherent noise in NISQ devices can be leveraged to solve such real-world problems effectively. Utilizing a D-Wave quantum annealer and IonQ's gate-based NISQ computers, we generate and analyze solutions for managing train traffic under stochastic disturbances. Our case study focuses on the Baltimore Light RailLink, which embodies the characteristics of both tramway and railway networks. We explore the feasibility of using NISQ technology to model the stochastic nature of disruptions in these transportation systems. Our research marks the inaugural application of both quantum computing paradigms to tramway and railway rescheduling, highlighting the potential of quantum noise as a beneficial resource in complex optimization scenarios.
02089nas a2200193 4500000000100000000000100001008004100002260011800043100002100161700001600182700001800198700002100216700002300237700002100260245010200281856006600383520142400449020002201873 2024 d c03/2024 bSpringer, Cham, Perspectives in Dynamical Systems II — Numerical and Analytical Approaches (DSTA 2021) 1 aPiotr Bełdowski 1 aPiotr Weber 1 aAdam Gadomski 1 aPiotr Sionkowski 1 aNatalia Kruszewska 1 aKrzysztof Domino 00 aStudies of the Interaction Dynamics in Albumin–Chondroitin Sulfate Systems by Recurrence Method uhttps://link.springer.com/chapter/10.1007/978-3-031-56496-3_5 3 aThe physicochemical basis of lubrication of articular cartilage is still not fully understood. However, the synergy between components of the synovial fluid can be a crucial factor that could explain this phenomenon. This work presents a nonlinear data analysis technique named the recurrence method, applied to the system involved two of such synovial fluid’s components: albumin and chondroitin sulfate (CS) immersed in a water environment. This analysis s performed in order to obtain the “statistical fingerprint” of the dynamics of the interaction between the molecules, and to answer whether the variables are more deterministic or more random. The system simulation has been prepared by molecular docking method followed by molecular dynamics simulations. The already mentioned recurrence method has been applied to time series of the energy of binding, and time series of number of intermolecular hydrogen bonds, as these features describe well binding between the two molecules. In detail, the time delay approach and embedded dimension approach have been applied to extract meaningful records from time series. Then, by means of recurrence plots and entropy approach, we discuss the similarities and differences between the molecular systems consisting of CS-4 and CS-6 molecules. Our main finding is higher affinity of chondroitin sulfate IV to albumin as compared with chondroitin sulfate VI.
a978-3-031-56495-6 00442nas a2200145 4500000000100000000000100001008004100002260001200043100002100055700002100076700002200097245012300119856004700242490000700289 2025 d c12/2024 1 aKrzysztof Domino 1 aArkadiusz Sochan 1 aJaroslaw Miszczak 00 aAnalytical assessment of workers' safety concerning direct and indirect ways of getting infected by dangerous pathogen uhttps://doi.org/10.1016/j.jocs.2024.102509 0 v85 00542nas a2200169 4500000000100000000000100001008004100002260010600043100002000149700001700169700002100186700002100207700002300228700002200251245004900273856005000322 2025 d c12/2025 bIEEE International Conference on Quantum Computing and Engineering (QCE25) aAlbuquerque, USA 1 aReece Robertson 1 aEmery Doucet 1 aZakaria Mzaouali 1 aKrzysztof Domino 1 aBartłomiej Gardas 1 aSebastian Deffner 00 aSimon's Period Finding on a Quantum Annealer uhttps://ieeexplore.ieee.org/document/11250344 00535nas a2200169 4500000000100000000000100001008004100002260001200043100002200055700002100077700002300098700002700121700002100148245013900169856005000308490000700358 2025 d c08/2025 1 aMonika Okoniewska 1 aPiotr Sionkowski 1 aNatalia Kruszewska 1 aKrzysztof Błażejczyk 1 aKrzysztof Domino 00 aA Scalable and Automated Recurrence Plot Method for Detecting Climate Change: The Case of the UTCI Bioclimatic Index in Central Europe uhttps://ieeexplore.ieee.org/document/11121937 0 v63 00402nas a2200145 4500000000100000000000100001008004100002100001800043700001900061700002400080700002100104700002400125700002100149245008600170 d 1 aEwa Kędziera 1 aWojciech Gamon 1 aMátyás Koniorczyk 1 aZakaria Mzaouali 1 aAndrea Galadíková 1 aKrzysztof Domino 00 aEMU circulation planning for Silesian Railways: case study and a quantum approach 00429nas a2200169 4500000000100000000000100001008004100002260001200043100001700055700002100072700002000093700002300113700002200136700002100158245006900179300001100248 2026 d c05/2026 1 aEmery Doucet 1 aZakaria Mzaouali 1 aReece Robertson 1 aBartłomiej Gardas 1 aSebastian Deffner 1 aKrzysztof Domino 00 aThermodynamic significance of QUBO encoding on quantum annealers a054512 00463nas a2200145 4500000000100000008004100001653002200042653002400064653001800088100002100106700001900127245011700146856004200263490001200305 2025 d 10 atransport szynowy 10 aobliczenia kwantowe 10 aoptymalizacja 1 aKrzysztof Domino 1 aWojciech Gamon 00 aOd Baltimore do Śląska: komputery kwantowe i hybrydowe metody optymalizacji w planowaniu transportu szynowego uhttps://tmir.sitk.org.pl/nr-8-2025-r/ 0 v08 2025 02325nas a2200133 4500000000100000008004100001100001800042700002100060700002200081700002600103245010300129856003600232520192300268 2026 d 1 aDariusz Pojda 1 aKrzysztof Domino 1 aMichał Tarnawski 1 aAgnieszka Anna Tomaka 00 aTransformation-driven generation of comparable projection images from multimodal anatomical scenes uhttp://arxiv.org/abs/2606.16573 3 aThis work addresses the computational problem of generating reproducible projection-space observations from heterogeneous anatomical scenes whose components may undergo independent spatial transformations. We propose a transformation-driven framework for synthetic projection imaging from multimodal anatomical data and demonstrate it on mandibular-motion scenarios. In contrast to conventional Digitally Reconstructed Radiograph (DRR) approaches primarily designed for registration, projection realism, or rendering efficiency, the proposed formulation treats projection imaging as an observation process operating on an explicitly represented anatomical scene. Independently transformable volumetric and surface-based anatomical objects are embedded within a shared scene representation and propagated directly into projection space through explicit transformations. Projection geometry, acquisition modelling, material interpretation, and image presentation remain explicitly separated, enabling controlled exploration of methodological assumptions while preserving reproducibility and direct comparability between generated projections. Particular emphasis is placed on transformation-driven anatomical scenarios relevant to craniofacial analysis, including mandibular motion and therapeutic repositioning. Using a shared anatomical reference scene composed of CT/CBCT volumes, segmented structures, surface models, and auxiliary anatomical or therapeutic objects, the framework enables generation of directly comparable VirtualRTG projections from multiple anatomical configurations while preserving identical imaging assumptions. Rather than aiming at fully physically faithful radiographic simulation, the proposed approach provides a controllable and reproducible methodological environment for studying anatomy--projection relationships, motion observability, and transformation-aware imaging workflows.