Spectral method as a tool to examine microtextures of quartz sand-sized grains.

Well-rounded grains extracted from aeolian and subaqueous environments were analysed to determine a quantitative parameter describing the microtopographic surface properties of sand-sized quartz grains, expressed as a degree of smoothness or as an inverse roughness. To this end, the spectral method was used to calculate their fractal dimension values. Fractal characteristics and spectral fractal dimension (DS) were determined for a scanning electron microscope (SEM) image (560 × 560 pixels) obtained for each study grain. This parameter, (DS), describes the complexity of objects, which means that the higher its value, the more complicated the analysed grains are in terms of exterior roughness and surface microirregularities. The obtained results indicate that values of the parameter (DS) were higher for all aeolian grains compared to grains from either low- or high-energy subaqueous environments. This difference in results is attributed to the presence of microirregularities on the surface of aeolian grains, microtextures forms such as mechanically upturned. This parameter value increases as the energy of the aeolian environment increases. Values of (DS) for subaqueous environments grains correlated with the frequency of microtextures that resulted from high-energy grain-to-grain collisions (e.g., V-shaped percussion cracks), or from the chemical etching of the grain surface (e.g., solution pits, solution crevasses)-the higher the frequency of either collision or chemical-etching microtextures, the higher the value of the fractal dimension (DS). Thus, it has been demonstrated that fractal analysis can serve as a useful tool to discriminate between the analysed sedimentary environments, to assess a depositional system's kinetic energy, and to compare the intensity of chemical weathering.

Identification of preterm birth based on RQA analysis of electrohysterograms.

BACKGROUND AND OBJECTIVE: Common methods for data analysis are mainly based on linear concepts, but in recent years nonlinear dynamics methods have been introduced. It is a well-known fact that In typical biological systems lack of stationarity and rather sudden changes of state are the properties distinguishing them from each other. There is an urgent need to better understand the mechanical activity of the myometrium (its contractility) to find a solution for preterm delivery problem, the largest cause of neonatal deaths and morbidity. The electrohysterographic signal (EHG) is a good non-linear, bioelectrical indicator for the detection and identification of term and preterm birth. METHODS: The material of the study consists of EHG signals, obtained from 20 patients between the 24th and the 28th week of pregnancy with threatened preterm labor. The women were divided into two groups: those delivering after more than 7 days - group A (n = 10) and women delivering within 7 days - group B (n = 10). In this paper, an analysis of bioelectrical signals was performed by recurrence quantification analysis (RQA) and principal component analysis (PCA) to distinguish particular patterns for term and preterm birth. To date, these methods have not been used for the evaluation of bioelectrical activity in the uterus. To train novel classifiers for the EHG signals Support Vectors Machine classifications (multiclass SVM) was used. Statistical analysis was performed by means of non-parametric Mann-Whitney test. RESULTS: From among eleven parameters obtained from recurrence quantification analysis, five most appropriate were chosen: Recurrence Rate, Determinism, Laminarity, Entropy and Recurrence Period Density Entropy. Significant increase (p < .001) of Recurrence Rate was found in patients from group B, while increase of parameters, besides Laminarity, was found in patients from group A. The accuracy of classification obtained as a result of the analysis increased to 83,32%. CONCLUSION: We showed that the respectively selected recurrence quantificators obtained for that time series could be used to classify all those signals to the appropriate group. The proposed analysis could help in detecting preterm labor based on the EHG signal dynamics.

Fractal texture analysis of the healing process after bone loss.

Radiological assessment of treatment effectiveness of guided bone regeneration (GBR) method in postresectal and postcystal bone loss cases, observed for one year. Group of 25 patients (17 females and 8 males) who underwent root resection with cystectomy were evaluated. The following combination therapy of intraosseous deficits was used, consisting of bone augmentation with xenogenic material together with covering regenerative membranes and tight wound closure. The bone regeneration process was estimated, comparing the images taken on the day of the surgery and 12 months later, by means of Kodak RVG 6100 digital radiography set. The interpretation of the radiovisiographic image depends on the evaluation ability of the eye looking at it, which leaves a large margin of uncertainty. So, several texture analysis techniques were developed and used sequentially on the radiographic image. For each method, the results were the mean from the 25 images. These methods compute the fractal dimension (D), each one having its own theoretic basis. We used five techniques for calculating fractal dimension: power spectral density method, triangular prism surface area method, blanket method, intensity difference scaling method and variogram analysis. Our study showed a decrease of fractal dimension during the healing process after bone loss. We also found evidence that various methods of calculating fractal dimension give different results. During the healing process after bone loss, the surfaces of radiographic images became smooth. The result obtained show that our findings may be of great importance for diagnostic purpose.

Synchronization in the bivariate intrauterine pressure signals' nonlinear dynamics methods.

It was shown earlier that nonlinear processes probably generate uterine contractions. In this study, the nonlinear synchronization measures (the mutual correlation dimension, the cross-approximate entropy, the mutual information and the nonlinear interdependencies) were employed to analyze the association between two time series representing the uterine contraction activity. Here the notion of synchronization is used in a loose sense as the synonym of correlation, the similarity of the signals or the similarity of their dynamics. The signals were recorded from the different topographic regions of the uterus: the cervix and the fundus. The results obtained by means of different algorithms are different but qualitatively similar for the checked methods.

Uterine contraction signals--application of the linear synchronization measures.

OBJECTIVE: In physiological research, there are not too many studies on multivariate data sets, containing two or more simultaneously recorded time series. It is important to examine synchronization in these kinds of signals. The aim of this study is to present the linear measures: the cross-correlation function, the coherence function, the wavelet cross-correlation and the wavelet coherence to assess synchronization between contractions in different topographic regions of the uterus. STUDY DESIGN: Spontaneous uterine activity was recorded directly by a dual micro-tip catheter (Millar Instruments, Inc., USA). The device consisted of two ultra-miniature pressure sensors. One sensor was placed in the fundus, the other one in the cervix. For this analysis, a healthy patient with normal contractions, a patient with dysmenorrhea, a patient with fibromyomas in the follicular phase, and the patient with endometriosis were selected. RESULTS: For each method the values of synchronization parameters for normal contractions were higher than the values of these parameters for other pairs of signals. The differences between these four groups of the uterine contraction signals were clear. The lowest values of the synchronization measures were in the case of dysmenorrheic patient. CONCLUSION: The analysis of synchronization of the uterine contractions signals may have a diagnostic value. For intrauterine pressure signals results obtained by means of different synchronization methods are different, but consistent.

New research models and novel signal analysis in studies on preterm labor: a key to progress?

Preterm labor affects up to 20% of pregnancies, is considered a main cause of associated neonatal morbidity and mortality and is responsible for neonatal care costs of multimillion euros. In spite of that, the commercial market for this clinical indication is rather limited, which may be also related to high liability. Consequently, with only a few exceptions, preterm labor is not in the orbit of great interest of the pharmaceutical industry. Coordinated effort of research community may bring the change and help required to reduce the influence of this multifactorial syndrome on society. Between the novel techniques that are being explored in a SAFE (The Special Non-Invasive Advances in Fetal and Neonatal Evaluation Network) group, there are new research models of preterm labor as well as novel methodology of analysis of biological signals. In this article, we briefly describe new clinical and nonclinical human models of preterm labor as well as summarize some novel methods of data processing and analysis that may be used in the context of preterm labor.

Uterine contractility: visualization of synchronization measures in two simultaneously recorded signals.

The analysis of the uterine contraction signals in nonpregnant states gives information about physiological changes during the menstrual cycle. Spontaneous uterine activity was recorded directly by a dual microtip catheter. The device consisted of two ultra-miniature pressure sensors. One sensor was placed in the fundus, the other in the cervix. It was important to identify time delays between contractions in two topographic locations, which may be of potential diagnostic significance in various pathologies: dysmenorrhea, endometriosis, and fecundity disorders. In this study the following synchronization measures-the cross-correlation, the semblance, the mutual information-were used to visualize the time delay changes over time. These measures were computed in a moving window with a width corresponding to approximately two or three contractions. As a result, the running synchronization functions were obtained. The running synchronization functions visualize changes in the propagation of the two simultaneously recorded signals. The propagation% parameter assessed from these functions allows for quantitative description of synchronization. Finally, we illustrate the use of running synchronization functions to investigate the effect of treatment with tamoxifen on primary dysmenorrhea.

Effect of short-term, low-dose treatment with tamoxifen in patients with primary dysmenorrhea.

Current treatment of painful periods and other symptoms related to primary dysmenorrhea (PD) is usually commenced with non-steroidal anti-inflammatory drugs or oral contraceptives, which fails in about 10% of affected patients. Tamoxifen, a selective estrogen-receptor modulator (SERM), has been demonstrated to directly inhibit uterine contractions, causing improvement in uterine blood flow. It could be considered for application in selected groups of dysmenorrheic patients, for instance carriers of breast cancer-associated antigen (BRCA) genes, breast cancer survivors or women with advanced endometriosis. Thus the aim of the present study was to investigate the effect of short-term treatment with tamoxifen on PD and PD-related symptoms, as well as its direct effect on parameters of intrauterine pressure during the painful menstruation, in a group of dysmenorrheic patients. After two cycles of administration of tamoxifen we noted a significant decrease in bleeding together with reductions in the severity of menstrual cramps, diarrhea, headache, fatigue and anxiety. In intrauterine pressure assessments, tamoxifen significantly decreased propagation of uterine contractions. In conclusion, SERMs such as tamoxifen may constitute a therapeutic option in selected groups of patients, improving dysmenorrheic symptoms. Additionally to its receptor-mediated effects, tamoxifen was shown to exert a direct influence on uterine contractile activity that may explain the decrease of menstrual pain and cramps noted in the studied group.

Visualization of synchronization of the uterine contraction signals: running cross-correlation and wavelet running cross-correlation methods.

In physiological research, we often study multivariate data sets, containing two or more simultaneously recorded time series. The aim of this paper is to present the cross-correlation and the wavelet cross-correlation methods to assess synchronization between contractions in different topographic regions of the uterus. From a medical point of view, it is important to identify time delays between contractions, which may be of potential diagnostic significance in various pathologies. The cross-correlation was computed in a moving window with a width corresponding to approximately two or three contractions. As a result, the running cross-correlation function was obtained. The propagation% parameter assessed from this function allows quantitative description of synchronization in bivariate time series. In general, the uterine contraction signals are very complicated. Wavelet transforms provide insight into the structure of the time series at various frequencies (scales). To show the changes of the propagation% parameter along scales, a wavelet running cross-correlation was used. At first, the continuous wavelet transforms as the uterine contraction signals were received and afterwards, a running cross-correlation analysis was conducted for each pair of transformed time series. The findings show that running functions are very useful in the analysis of uterine contractions.

Fractal analysis of the uterine contractions.

The fractal dimension D may be calculated in many ways, since its strict definition, the Hausdorff definition is too complicated for practical estimation. In this paper we perform a comparative study often methods of fractal analysis of time series. In Benoit, a commercial program for fractal analysis, five methods of computing fractal dimension of time series (rescaled range analysis, power spectral analysis, roughness-length, variogram methods and wavelet method) are available. We have implemented some other algorithms for calculating D: Higuchi's fractal dimension, relative dispersion analysis, running fractal dimension, method based on mathematical morphology and method based on intensity differences. For biomedical signals results obtained by means of different algorithms are different, but consistent.