Survival under dry conditions was examined in males and females of Alphitobius diaperinus Panzer (Coleoptera: Tenebrionidae), a beetle of tropical origin. The range of individual responses and the effect of gender on water loss were also evaluated. Females exhibit significantly longer survival (Lt50 and Lt90) than males under desiccating conditions. Larger females beetles have a greater initial water mass and hence can tolerate greater water losses. Such beetles have longer survival under dry conditions. Males and females loose an average of 54.8 and 58.9% of their body water prior to death. The insects were inactive most of the time, when kept under dry conditions; the rate of decrease in body water was thus reduced. Beetles of both gender display a negative correlation between the rates of water loss under desiccating conditions and the duration of survival. We conclude that the difference in survival period between males and females is due to a combination of greater female tolerance to desiccation and larger body size.
This paper is concerned with Francis water turbine power control issue. There are introduced six conceptions of power controllers and corresponding control loop features are discussed. The control features are illustrated with step responses and the major attention is paid to the undesirable under-control effect. On an example of control system with an elementary description and with relatively short turbine pipeline feeder are the control features compared. and Obsahuje seznam literatury
The uniqueness theorem is proved for the linearized problem describing radiation and scattering of time-harmonic water waves by a vertical shell having an arbitrary horizontal cross-section. The uniqueness holds for all frequencies, and various locations of the shell are possible: surface-piercing, totally immersed and bottom-standing. A version of integral equation technique is outlined for finding a solution.
A multi-head 1-way pushdown automaton with k heads is a pushdown automaton with k 1-way read heads on the input tape and a stack. It was previously shown that the deterministic variant of the model cannot accept all the context free languages. In this paper, we introduce a 2-tape, 2-head model namely Watson-Crick pushdown automata where the content of the second tape is determined using a complementarity relation, similar to Watson-Crick automata. We show computational powers of nondeterministic two-head pushdown automata and nondeterministic Watson-Crick pushdown automata are same. Moreover, deterministic Watson-Crick pushdown automata can accept all the context free languages.
Paper summarizes the results in the area of information physics that is a new progressively developing field of study trying to introduce basics of information variables into physics. New parameters, like wave information flow, wave information/knowledge content or wave information impedance, are first defined and then represented by wave probabilistic functions. Next, relations between newly defined parameters are used to compute information power or to build wave information circuits covering feedbacks, etc.
The paper presents the basic theory of wave probabilistic models together with their features. By introduction of the complementarity's principle between x-representation and k-representation the probability theory is completed for "structural" parameter which carries information about the changes of time series or random processes. The next feature of wave probabilistic models is the quantization principle or definition of probabilistic inclusion-exclusion rules.
The paper continues with the theory of wave probabilistic models and uses the inclusion-exclusion rule to describe quantum entanglement as a wave probabilities resonance principle. The achieved results are mathematically described and an illustrative example is shown to demonstrate the possible applications of the presented theory.
This paper presents the results of the application of wavelet decomposition to processing data from the GGP sites (The Global Geodynamics Project). The GGP is an international project within which the Earth's gravity field changes are recorded with high accuracy at a number of stations worldwide using superconducting gravimeters. Data with a 5-second sampling interval from Wettzell and Bad Homburg were used for the research. The wavelet transform enables the investigation of the temporal changes of the oscillation amplitudes or the decomposition of the time series for the analysis of the required frequencies. The wavelet decomposition was performed using the regular orthogonal symmetric Meyer wavelet. The research concerned data from an earthquake period recorded at various locations and a quiet period when the gravimeters worked without any disturbances. The decomposition was followed by the Fast Fourier Transform for signal frequency components and then by correlation analyses of corresponding frequency components (for periods from 10 to 60 000 seconds) for all sensor combinations, for the quiet and the earthquake periods separately. Frequency components defining long term changes for all sensor combinations, as well as combinations between two sensors at the same site for the quiet days are characterised by high correlation coefficients. For the time of the earthquake, the Wettzell site data proved strong correlation for all frequency components, while the Bad Homburg site data showed an unexpected decrease of correlation for the majority of frequency components. The authors also showed that wavelet decomposition can be a good method of data interpolation, especially from the time of earthquakes. Moreover, it is a very useful tool for filtering the data and removing the noises., Janusz Bogusz, Anna Klos and Wieslaw Kosek., and Obsahuje bibliografii
The paper presents a multi-output wavelet neural network (WNN) which, taking benefit of wavelets and neural networks, is able to accomplish data feature extraction and modeling. In this work, WNN is implemented with a feedforward one-hidden layer architecture, whose activation functions in its hidden layer neurons are wavelet functions, in our case, the first derivative of a Gaussian function. The network training is performed using a backpropagation algorithm, adjusting the connection weights along with the network parameters. This principle is applied to the simultaneous quantification of heavy metals present in liquid media, taking the cyclic voltammogram obtained with a modified epoxy-graphite composite sensor as departure information. The combination between processing tools and electrochemical sensors is already known as an electronic tongue.