By determining the calcium retention capacity (CRC) of rat liver
mitochondria, we confirmed and extended previous observations
describing the activation of mitochondrial swelling by phosphate
and tert-butyl hydroperoxide (t-BHP). Using CRC measurements,
we showed that both phosphate and t-BHP decrease the extent
of calcium accumulation required for the full mitochondrial
permeability transition pore (MPTP) opening to 35 % of control
values and to only 15 % when both phosphate and t-BHP are
present in the medium. When changes in fluorescence were
evaluated at higher resolution, we observed that in the presence
of cyclosporine A fluorescence values return after each
Ca2+ addition to basal values obtained before the Ca2+ addition.
This indicates that the MPTP remains closed. However, in the
absence of cyclosporine A, the basal fluorescence after each
Ca2+ addition continuously increased. This increase was
potentiated both by phosphate and t-BHP until the moment when
the concentration of intramitochondrial calcium required for the
full opening of the MPTP was reached. We conclude that in the
absence of cyclosporine A, the MPTP is slowly opened after each
Ca2+ addition and that this rate of opening can be modified by
various factors such as the composition of the media and the
experimental protocol used.
Two-scale convergence is a powerful mathematical tool in periodic homogenization developed for modelling media with periodic structure. The contribution deals with the classical definition, its problems, the ''dua''' definition based on the so-called periodic unfolding. Since in the case of domains with boundary the unfolding operator introduced by D. Cioranescu, A. Damlamian, G. Griso does not satisfy the crucial integral preserving property, the contribution proposes a modified unfolding operator which satisfies the property and thus simplifies the theory. The properties of two-scale convergence are surveyed.
Changes in pigment composition and chlorophyll (Chl) fluorescence parameters were studied in 20 year-old Scots pine (Pinus sylvestris L.) trees grown in environment-controlled chambers and subjected to ambient conditions (CON), doubled ambient CO2 concentration (EC), elevated temperature (ambient +2-6 °C, ET), or a combination of EC and ET (ECT) for four years. EC did not significantly alter the optimal photochemical efficiency of photosystem 2 (PS2; Fv/Fm), or Chl a+b content during the main growth season (days 150-240) but it reduced Fv/Fm and the Chl a+b content and increased the ratio of total carotenoids to Chl a+b during the 'off season'. By contrast, ET significantly enhanced the efficiency of PS2 in terms of increases in Fv/Fm and Chl a+b content throughout the year, but with more pronounced enhancement in the 'off season'. The reduction in Fv/Fm during autumn could be associated with the CO2-induced earlier yellowing of the leaves, whereas the temperature-stimulated increase in the photochemical efficiency of PS2 during the 'off season' could be attributed to the maintenance of a high sink capacity. The pigment and fluorescence responses in the case of ECT showed a similar pattern to that for ET, implying the importance of the temperature factor in future climate changes in the boreal zone. and K. Y. Wang, S. Kellomäki, T. Zha.
P300 brain-computer interfaces (BCIs) have been gaining attention in recent years. To achieve good performance and accuracy, it is necessary to optimize both feature extraction and classification algorithms. This article aims at verifying whether supervised learning models based on self-organizing maps (SOM) or adaptive resonance theory (ART) can be useful for this task. For feature extraction, the state-of-the-art Windowed means paradigm was used. For classification, proposed classifiers were compared with state-of-the-art classifiers used in BCI research, such as Bayesian Linear Discriminant Analysis, or shrinkage LDA. Publicly available datasets from fifteen healthy subjects were used for the experiments. The results indicated that SOM-based models yield better results than ART-based models. The best performance was achieved by the LASSO model that was comparable to state-of-the-art BCI classifiers. Further possibilities for improvements are discussed.
Arsenic, antimony and selenium belong to toxic contaminants with high environmental risk. In contrast to metal cationic contaminants (Be, Zn, Cd, Hg Pb, etc.) the metalloids and nonmetals of groups 5 and 6 of periodic system generally form the oxyanions in two oxidizing states (i.e. arsenates and arsenites, antimonates and antimonites, as well as selenates and selenites) in dependence on redox potential and pH value. It is well known that above mentioned oxyanions have a strong adsorption affinity to hydrated oxides and/or oxides hydroxides of Fe, Al and Mn, preferably Fe forming stable surface complexes. In fact, commercially produced Fe oxides-based sorbents are too expensive for strongly contaminated aqueous systems. Aluminosilicates have opened new possibilities in sorption technology due to favourable surface properties, availability, environmental and economical reasons, but they are not selective sorbents of anionic contaminants thanks to a low pHZPC. A simple Fe/Al/Mn pre-treatment of raw aluminosilicates can significantly improve their sorption affinity to oxyanionic contaminants, including arsenites and arsenates, selenites and selenates and antimonites and antimonates, respectively. Different types of natural and/or second-rate clays (metakaolines with the large content of Fe, raw bentonites and natural clinoptilolite-rich tuff, ) from Central European localities were used for FeII, FeIII, AlIII and MnII pre-treatment., Barbora Doušová, Lucie Fuitová, Lenka Herzogová, Tomáš Grygar, David Koloušek and Vladimír Machovič., and Obsahuje bibliografii
Air transportation between Europe and the U.S. is becoming more and more significant. It can only hardly be replaced by other means of transportation, since its biggest advantages include speed and reliability. Air transportation forecasting is important for planning the development of airports and related infrastructure, and of course also for air carriers. Therefore, it is important to forecast the number of flights between selected airports in Europe and the U.S. and the number of transported persons. A gravity model is usually used for this forecasting. Determination of coefficients which significantly affect results of the formulas used in the gravity model is crucial. Coefficients are, as a rule, computed by an iterative algorithm implementing the gradient method. This technique has some limitations if the state space is inappropriate. Moreover, the exponent parameter in the formula is obviously fixed. We have chosen the new method of differential evolution to determine the gravity model coefficient. Differential evolution works with populations similarly to other evolution algorithms. It is suitable for solving complex numerical problems. The suggested methodology can be helpful for various airlines to forecast demand and plan new long-haul routes.
Point estimators based on minimization of information-theoretic divergences between empirical and hypothetical distribution induce a problem when working with continuous families which are measure-theoretically orthogonal with the family of empirical distributions. In this case, the ϕ-divergence is always equal to its upper bound, and the minimum ϕ-divergence estimates are trivial. Broniatowski and Vajda \cite{IV09} proposed several modifications of the minimum divergence rule to provide a solution to the above mentioned problem. We examine these new estimation methods with respect to consistency, robustness and efficiency through an extended simulation study. We focus on the well-known family of power divergences parametrized by α∈R in the Gaussian model, and we perform a comparative computer simulation for several randomly selected contaminated and uncontaminated data sets, different sample sizes and different ϕ-divergence parameters.
We show that dynamical systems in inverse problems are sometimes foliated if the embedding dimension is greater than the dimension of the manifold on which the system resides. Under this condition, we end up reaching different leaves of the foliation if we start from different initial conditions. For some of these cases we have found a method by which we can asymptotically guide the system to a specific leaf even if we start from an initial condition which corresponds to some other leaf. We demonstrate the method by two examples. In the chosen cases of the harmonic oscillator and Duffing's oscillator we find an alternative set of equations which represent a collapsed foliation, such that no matter what initial conditions we choose, the system would asymptotically reach the same desired sub-manifold of the original system. This process can lead to cases for which a system begins in a chaotic region, but is guided to a periodic region and vice versa. It may also happen that we could move from an orbit of one period to an orbit of another period.
Extendecl Classifier Systems, or XCS, are a soft-computing approach to machine learning in rule-based Systems. While XCS has been shown effective in learnirig accurate, compact and complete mappnigs of an environmenťs payoff landscape, it can require significant resources to do so. This paper presents four modifications that allow XCS to achieve high performance even in highly size-constrained populations. By modifying (1) the genetic algorithm trigger function, (2) the classifier deletion-selection mechanism, (3) the genetic algorithm selection function, and (4) the frequency of classifier parameter updates, the modified system uses the available population resources more efficiently. Ex{)erimental results demonstrate the irnprovement in performance achievcd with the proposed modifications in both the single-step 6-Multiplexer problem and the niulti-step Woods-2 problem.