The number of human cases of salmonellosis in the EU was 94,625 in 2015. Considering the source of these infections, Salmonella spp. was most frequently detected in broiler chicken meat and Salmonella Enteritidis (SE) was the most commonly reported serovar. The efficacy of probiotics in limiting Salmonella spp. infection in poultry has been demonstrated in numerous papers. The administration of probiotics at the level of primary production reduces the risk of contamination of poultry food products with Salmonella spp. A study was carried out in order to determine the potential for reducing the Salmonella spp. population in broiler chickens with the use of the Lavipan (JHJ, Poland) probiotic that comprised selected stains of lactic acid bacteria and Saccharomyces cervisae. Salmonella spp.-free broiler chickens were divided into two groups and received the same feed with (group L) or without (group C) the probiotic throughout the experiment. All day-old chickens were infected per os with SE. Samples of cecum content were collected 2, 4, and 6 weeks after SE infection and pectoral muscles were collected 6 weeks following SE infection for the evaluation of the SE population number. Serum samples for serological examinations were collected 6 weeks after infection. Six weeks after infection, the number of SE-positive cecal samples was lower in the L group (12.5% positive) in comparison to the C group (87.5%). Similar results were demonstrated for the muscle samples (25% in contrast to 87.5%). At the same time, in both cases, the SE CFU/g was significantly lower in the L group. The results of our study indicate that Lavipan was capable of reducing the population of SE in the gastrointestinal tract, which eventually improved the hygienic parameters of the pectoral muscles. Four weeks after infection, SE was not detected in any of the experimental groups. In both groups, no specific anti-SE antibodies were detected.
The Carpathian Orava Basin is a tectonic structure filled with Neogene and Quaternary deposits superimposed on the collision zone between the ALCAPA and European plates. Tectonic features of the south-eastern margin of the Orava Basin and the adjoining part of the fore-arc Central Carpathian Palaeogene Basin were studied. Field observations of mesoscopic structures, analyses of digital elevation models and geological maps, supplemented with electrical resistivity tomography surveys were performed. Particular attention was paid to joint network analysis. The NE-SW-trending Krowiarki and Hruštinka-Biela Orava sinistral fault zones were recognized as key tectonic features that influenced the Orava Basin development. They constitute the north-eastern part of a larger Mur-Mürz-Žilina fault system that separates the Western Carpathians from the Eastern Alps. The interaction of these sinistral fault zones with the older tectonic structures of the collision zone caused the initiation and further development of the Orava Basin as a strike-slip-related basin. The Krowiarki Fault Zone subdivides areas with a different deformation pattern within the sediments of the Central Carpathian Palaeogene Basin and was active at least from the time of cessation of its sedimentation in the early Miocene. Comparison of structural data with the recent tectonic stress field, earthquake focal mechanisms and GPS measurements allows us to conclude that the Krowiarki Fault Zone shows a stable general pattern of tectonic activity for more than the last 20 myr and is presently still active.
The correlation of data contained in a series of signal sample values makes the estimation of the statistical characteristics describing such a random sample difficult. The positive correlation of data increases the arithmetic mean variance in relation to the series of uncorrelated results. If the normalized autocorrelation function of the positively correlated observations and their variance are known, then the effect of the correlation can be taken into consideration in the estimation process computationally. A significant hindrance to the assessment of the estimation process appears when the autocorrelation function is unknown. This study describes an application of the conditional averaging of the positively correlated data with the Gaussian distribution for the assessment of the correlation of an observation series, and the determination of the standard uncertainty of the arithmetic mean. The method presented here can be particularly useful for high values of correlation (when the value of the normalized autocorrelation function is higher than 0.5), and for the number of data higher than 50. In the paper the results of theoretical research are presented, as well as those of the selected experiments of the processing and analysis of physical signals.
This paper presents the results of the theoretical and practical analysis of selected features of the function of conditional average value of the absolute value of delayed signal (CAAV). The results obtained with the CAAV method have been compared with the results obtained by method of cross correlation (CCF), which is often used at the measurements of random signal time delay. The paper is divided into five sections. The first is devoted to a short introduction to the subject of the paper. The model of measured stochastic signals is described in Section 2. The fundamentals of time delay estimation using CCF and CAAV are presented in Section 3. The standard deviations of both functions in their extreme points are evaluated and compared. The results of experimental investigations are discussed in Section 4. Computer simulations were used to evaluate the performance of the CAAV and CCF methods. The signal and the noise were Gaussian random variables, produced by a pseudorandom noise generator. The experimental standard deviations of both functions for the chosen signal to noise ratio (SNR) were obtained and compared. All simulation results were averaged for 1000 independent runs. It should be noted that the experimental results were close to the theoretical values. The conclusions and final remarks were included in Section 5. The authors conclude that the CAAV method described in this paper has less standard deviation in the extreme point than CCF and can be applied to time delay measurement of random signals.
The conversion of a waste heat energy to electricity is now becoming one of the key points to improve the energy efficiency in a process engineering. However, large losses of a low-temperature thermal energy are also present in power engineering. One of such sources of waste heat in power plants are exhaust gases at the outlet of boilers. Through usage of a waste heat regeneration system it is possible to attain a heat rate of approximately 200 MWth, under about 90°C, for a supercritical power block of 900 MWelfuelled by a lignite. In the article, we propose to use the waste heat to improve thermal efficiency of the Szewalski binary vapour cycle. The Szewalski binary vapour cycle provides steam as the working fluid in a high temperature part of the cycle, while another fluid – organic working fluid – as the working substance substituting conventional steam over the temperature range represented by the low pressure steam expansion. In order to define in detail the efficiency of energy conversion at various stages of the proposed cycle the exergy analysis was performed. The steam cycle for reference conditions, the Szewalski binary vapour cycle as well as the Szewalski hierarchic vapour cycle cooperating with a system of waste heat recovery have been comprised.
The paper presents a thermodynamic optimization of supercritical coal fired power plant. The aim of the study was to optimize part of the thermal cycle consisted of high-pressure turbine and two chosen highpressure feed water heaters. Calculations were carried out using IPSEpro software combined with MATLAB, where thermal efficiency and gross power generation efficiency were chosen as objective functions. It was shown that the optimization with newly developed framework is sufficiently precise and its main advantage is the reduction of computation time on comparison to the classical method. The calculations have shown the tendency of the increase in efficiency, with the rise of a number of function variables.
The use of shredded tyre in civil engineering applications is a significant potential end use market. The reuse of tyre chips may not only address growing environmental and economic concerns, but also help to solve geotechnical problems associated with low shear strength. The purpose of this paper is to investigate the properties of tyre chips and tyre chips – sand mixture, and to find the mixture with the highest shear strength. In this study, an experimental testing program was undertaken using a large – scale triaxial apparatus with the goal of evaluating the optimum percentage of tyre chips in sand. The effects on shear strength of varying percentage of tyre chips and varying confining pressure were studied. Tyre chips content was suspected to have influence on stress – strain and volumetric strain behaviour of the mixture. Some tests were conducted to check the influence of number of used membranes, of saturation and compaction, on sample properties.
Autocorrelation of signals and measurement data makes it difficult to estimate their statistical characteristics. However, the scope of usefulness of autocorrelation functions for statistical description of signal relation is narrowed down to linear processing models. The use of the conditional expected value opens new possibilities in the description of interdependence of stochastic signals for linear and non-linear models. It is described with relatively simple mathematical models with corresponding simple algorithms of their practical implementation. The paper presents a practical model of exponential autocorrelation of measurement data and a theoretical analysis of its impact on the process of conditional averaging of data. Optimization conditions of the process were determined to decrease the variance of a characteristic of the conditional expected value. The obtained theoretical relations were compared with some examples of the experimental results.
The article presents a zero-dimensional mathematical model of a tubular fuel cell and its verification on four experiments. Despite the fact that fuel cells are still rarely used in commercial applications, their use has become increasingly more common. Computational Flow Mechanics codes allow to predict basic parameters of a cell such as current, voltage, combustion composition, exhaust temperature, etc. Precise models are particularly important for a complex energy system, where fuel cells cooperate with gas, gas-steam cycles or ORCs and their thermodynamic parameters affect those systems. The proposed model employs extended Nernst equation to determine the fuel cell voltage and steadystate shifting reaction equilibrium to calculate the exhaust composition. Additionally, the reaction of methane reforming and the electrochemical reaction of hydrogen and oxygen have been implemented into the model. The numerical simulation results were compared with available experiment results and the differences, with the exception of the Tomlin experiment, are below 5%. It has been proven that the increase in current density lowers the electrical efficiency of SOFCs, hence fuel cells typically work at low current density, with a corresponding efficiency of 45–50% and with a low emission level (zero emissions in case of hydrogen combustion).
Powdery mildew, caused by Blumeria graminis f. sp. tritici, is one of the most important foliar diseases of cereals. Infection by this pathogen on triticale has intensified in Poland in the last few years. In this study we examined resistance to powdery mildew in triticale hybrids possessing resistance genes Pm4b and Pm6 introduced from common wheat. The materials tested were hybrids derived from triticale crosses with common wheat cultivars carrying the desired resistance genes. The presence of the transferred genes was reflected in increased field resistance and shown by the use of molecular markers. The paper discusses the potential introduction of the genes to improve powdery mildew resistance.
This research paper shows the influence of a repeated SPD (Severe Plastic Deformation) plastic forming with the DRECE technique (Dual Rolls Equal Channel Extrusion) on hardening of low carbon IF steel. The influence of number of passes through the device on change of mechanical properties, such as tensile strength TS and yield stress YS, of tested steel was tested. The developed method is based on equal channel extrusion with dual rolls and uses a repeated plastic forming to refinement of structure and improve mechanical properties of metal bands [1-2]. For the tested steel the increase of strength properties after the DRECE process was confirmed after the first pass in relation to the initial material. The biggest strain hardening is observed after the fourth pass.