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Air pollution is a serious problem in North Macedonia. In this project all the air quality stations in North Macedonia were mapped along with the closest factories to these stations. Later, the collected data was used to analyze how the number of factories and the population density around air quality stations correlates with the amount of pollution measured by given station. Comparison between air quality data collected during whole year and only in winter months was also made. This whole process was carried in ArcGIS, a software which has variety of spatial visualization and processing tools. Our work shows that, as expected, there is a positive correlation between the number of factories close to a given station and the pollution that it measures. The same pattern is true for the population density, too. We hope that this research paper will have a positive impact for solving the air pollution problem and perhaps changes towards improving the whole situation will be made, especially in the areas identified with the highest amount of pollution.

Our study explored the cardiorespiratory interactions during three different ambient temperatures. We established coupling functions of cardiorespiratory interactions by applying dynamic Bayesian inference to investigate if and how thermoregulation affects those oscillators. Our preliminary results indicate that both, the coherence and coupling between cardiorespiratory oscillations change with individual level of temperature stress.

In addition to the need for security, everyday information exchange must be able to cope with noise and interference. We discuss the noise robustness of a recently-introduced communications protocol inspired by the human cardiorespiratory interaction, based on analysis methods originally developed for reconstructing coupling functions between oscillatory processes underlying the biological signals. Security is assured by use of multiple, time-varying, coupling functions between two or more dynamical systems, and the protocol allows for multiplexing of the information transfer. We focus on the exceptional noise-robustness that arises from the application of dynamical Bayesian inference to the stochastic differential equations. A particular advantage of the protocol is that it facilitates an effective separation between the deterministic information signals and the dynamical (channel) noise perturbations. We define reliability in terms of the bit-error-rate (BER) as a function of noise strength, expressed as the signal-to-noise ratio (SNR). We present results confirming that the coupling function protocol is highly noise robust, and that it outperforms other known communications protocols. In the broader context, we point out that this use of coupling functions between dynamical systems is a modular construct that can be extended to implement a range of different encryption concepts. Similarly, the method of dynamical Bayesian inference carries wider implications for future applications to noise reduction in communications using other protocols.

Spectrum sensing is a fundamental technique of cognitive radio (CR) system to detect the presence of primary user (PU) transmissions in the licensed spectrum. This paper investigates secondary user (SU) selection based cooperative spectrum sensing under exponentially embedded family (EEF) criterion. With an aim to estimate the optimal number of cooperative users who are better fitting for participating in cooperative sensing, we propose AIC, MDL, and EEF criteria to select the potential users among all cooperative users in the CR network. Based on the estimated user number, the global test statistic (GTS) is generated, and finally the fusion center (FC) makes the global decision on the presence/absence of the PU signal. Analysis and simulations verify that the proposed user selection based cooperative sensing schemes can significantly improve the spectrum sensing performance.

The effect of the drugs atropine (a parasympathetic blocker) and propranolol (a sympathetic blocker) is investigated. In the experiment, the subjects were measured under an experimental protocol that used saline controls, with both spontaneous and paced breathing as well as apnea. The recorded data included an electrocardiogram, end tidal CO 2 , blood pressure and a direct measurement of the muscle sympathetic nerve activity. The signals were analysed using time-frequency methods and an information theory approach, revealing information about the change in coupling and coherence that has not previously been studied. The results show that atropine strongly reduces the power in the signals and also removes the coupling and coherence between cardiovascular oscillations. The effects occur across a wide range of frequencies and provide insight into the neurophysiological mechanisms involved in the regulation of the cardiovascular system.

We discuss the advent of coupling functions as a new dimension in the analysis of cardiorespiratory interactions. By decomposing the separate coupling components in a phase oscillator model, we infer the cardiorespiratory coupling functions with dynamical Bayesian inference for time-evolving and noisy coupled systems. The inferred coupling functions are themselves time-varying processes. On a longer timescale, application to ageing shows that the coupling functions and the direct influence of respiration decrease as age increases. We find that the coupling functions can give rise to synchronization transitions, and that there are no significant changes in synchronization with age.

The heart rate variability (HRV) is analysed under the framework of a new class of self-sustained oscillators known as chronotaxic systems. These oscillators have time-varying frequencies that can be perturbed by noise but remain stable, resulting in dynamics that can appear both complex and simple. Methods developed for the inverse approach to these systems are applied to an HRV signal recorded under quasi-periodically forced respiration. The analysis suggests that the respiratory-related oscillation in the signal has the properties of a chronotaxic oscillator and an addition to an existing HRV model is proposed.

Bispectral analysis, introduced recently as a technique for revealing time-phase relationships among interacting noisy oscillators, has been used to study the nature of the coupling between cardiac and respiratory activity. Univariate blood flow signals recorded simultaneously by laser-Doppler flowmetry (LDF) on both legs and arms were analysed. Coupling between cardiac and respiratory activity was also checked by use of bivariate data and computation of the cross-bispectrum between simultaneously recorded ECG, blood pressure and respiratory signals. Recordings were taken during spontaneous breathing and paced respiration. It is shown that cardiorespiratory coupling exists during spontaneous as well as during paced respiration and that coupling information among cardiac and respiratory processes in young, healthy subjects is spatially invariant, but can be expected to change with cardiovascular diseases.

The simplified qualitative model resuming regulation mechanisms of soft tissue regeneration or degradation is presented. Clinical data obtained in multicenter study and analysed by the Assistant inductive learning system impose a clear conclusion that wounds treated by externally applied electrical current will heal significantly faster than wounds approached only by conventional treatment. Guidelines toward quantitative model of wound healing are outlined from the synergistic point of view.

The authors present results of analysis of the cardiovascular system based on the nonlinear system theory. The Lyapunov exponents of the time series obtained by monitoring the flow of blood in a healthy subject are calculated over a wide range of parameter values. For sufficiently large embedding dimension two typical spectra are observed. Either the authors have 4 paired and 1 zero, or 5 paired exponents.

An attempt to obtain an optimal set of input signals-electrical stimuli with different parameters-and responses which give appropriate information for revealing complete muscle properties of measured muscle is presented. Properties of the tibialis anterior muscle were examined by muscle dynamics and muscle fatigue measurements. The results show that differences in muscle dynamics and muscle fatigue already exist among subjects with normal tibialis anterior muscle. >

Dynamic modeling of the ankle joint is performed by means of the non-parameteric Wiener-Volterra approach. The original version is extended so that colored noise inputs can be handled. This is imposed from reality, i.e., all movements of the angle joint must be limited in frequency as well as in amplitude. Experiences related to the method are briefly summarized and supported with results obtained on a normal subject. >

An analytic method for stabilization of the unstable orbits of a complex system is applied to the problem of ferroresonance in power systems. The method is based on the feedback control theory proposed by Pyragas (1992). Simulation results are presented illustrating transitions from unstable, chaotic, to stable, periodic, orbits. The stability was evaluated using the largest Lyapunov exponent. In this way, an efficient approach to the damping and control of the ferroresonant chaotic oscillations, which can arise in high-voltage terminal equipment, is presented.