Morphological,Anatomical, and Phytochemical Studies of Carlina acaulis L. Cypsela

Carlina acaulis L. has a long tradition of use in folk medicine. The chemical composition of the roots and green parts of the plant is quite well known. There is the lowest amount of data on the cypsela (fruit) of this plant. In this study, the microscopic structures and the chemical composition of the cypsela were investigated. Preliminary cytochemical studies of the structure of the Carlina acaulis L. cypsela showed the presence of substantial amounts of protein and lipophilic substances. The chemical composition of the cypsela was investigated using spectrophotometry, gas chromatography with mass spectrometry, and high-performance liquid chromatography with spectrophotometric and fluorescence detection. The cypsela has been shown to be a rich source of macro- and microelements, vegetable oil (25%), α-tocopherol (approx. 2 g/kg of oil), protein (approx. 36% seed weight), and chlorogenic acids (approx. 22 g/kg seed weight). It also contains a complex set of volatile compounds. The C. acaulis cypsela is, therefore, a valuable source of nutrients and bioactive substances.     

Heteropolyanions doped polyimine—Preparation and spectroscopic properties

It is demonstrated that aromatic polyimine obtained by the condensation of p-phenylenediamine and terephtalaldehyde can be chemically doped with heteropolyanions of Keggin-type. The spectroscopic studies show that polyimine undergoes protonation. The structural identity of the Keggin units are preserved upon incorporation into the polymer matrix.     

Prototype selection algorithms for distributed learning

Distributed learning from data is one of the typical tasks solved by distributed data-mining techniques and is seen as a fundamental computational problem. One of the approaches suitable for distributed learning is to select, by data reduction, relevant local patterns, called also prototypes, from geographically distributed databases. Next, locally selected prototypes can be moved to other sites and merged into the global knowledge model. The paper presents three agent-based population learning algorithms for distributed learning. The proposed algorithms are based on agent collaborations in distributed prototype selection processes and on agent collaborations when the learning global model is created. The basic property of the presented algorithms is that the prototypes are selected by agent-based population learning algorithm from data clusters induced at distributed sites. The main goal of the paper is to empirically compare how the way of inducing such clusters can influence the distributed learning performance. The paper investigates the agent-based population learning algorithms used to solve distributed data reduction and gives a brief discussion of the procedures for clusters initialization. Finally, computational experiment results are shown.     

Preliminary study on the accuracy of respiratory input impedance measurement using the interrupter technique

Respiratory input impedance contains information about the state of pulmonary mechanics in the frequency domain. In this paper the possibility of respiratory impedance measurement by interrupter technique as well as the accuracy of this approach are assessed. Transient states of flow and pressure recorded during expiratory flow interruption are simulated with a complex, linear model for the respiratory system and then used to calculate the impedance, including three states of respiratory mechanics and the influence of the measurement noise. The results of computations are compared to the known, theoretical impedance of the model. At 1 kHz sampling rate, the optimal time window lays between 100 and 200 ms and is centred around the pressure jump caused by the flow interruption. The proposed algorithm yields satisfactory accuracy in the range from 10 to 400 Hz, particularly to 150 Hz. Depending on the simulated respiratory system state, the error of calculated impedance (relative Euclidean distance between the vectors of computed and theoretical values), for the window of 190 ms, varies between 5.0% and 7.1%.     

Voltage preamplifier for extensional quartz sensors used in scanning force microscopy

Extensional-mode quartz resonators are being increasingly used as force sensors in dynamic scanning force microscopy or atomic force microscopy (AFM). We propose a voltage preamplifier in order to amplify the charge induced on quartz electrodes. The proposed solution has some advantages over the typically used current-to-voltage converters. First, the gain does not depend on the inner parameters of the quartz resonator, which are usually unknown for the specific resonator and may even vary during the measurement. Second, with such an amplifier a better signal-to-noise ratio can be achieved. Finally, we present AFM images of the Si(111) and the SiO(2) surfaces obtained by the voltage preamplifier with simultaneously recorded tunneling current.     

Au/Ce1−xZrxO2 as effective catalysts for low-temperature CO oxidation

The physico-chemical properties and activity of Ce-Zr mixed oxides, CeO₂ and ZrO₂ in CO oxidation have been studied considering both their usefulness as supports for Au nanoparticles and their contribution to the reaction. A series of Ce_1−xZr_xO₂ (x = 0, 0.25, 0.5, 0.75, 1) oxides has been prepared by sol–gel like method and tested in CO oxidation. Highly uniform, nanosized, Ce-Zr solid solutions were obtained. The activity of mixed oxides in CO oxidation was found to be dependent on Ce/Zr molar ratio and related to their reducibility and/or oxygen mobility. CeO₂ and Ce_0.75Zr_0.25O₂, characterized by the cubic crystalline phase show the highest activity in CO oxidation. It suggests that the presence of a cubic crystalline phase in Ce-Zr solid solution improves its catalytic activity in CO oxidation. The relation between the physico-chemical properties of the supports and the catalytic performance of Au/Ce_1−xZr_xO₂ catalysts in CO oxidation reaction has been investigated. Gold was deposited by the direct anionic exchange (DAE) method. The role of the support in the creation of catalytic performance of supported Au nanoparticles in CO oxidation was significant. A direct correlation between activity and catalysts reducibility was observed. Ceria, which is susceptible to the reduction at the lowest temperature, in the presence of highly dispersed Au nanoparticles, appears to be responsible for the activity of the studied catalysts. CeO₂-ZrO₂ mixed oxides are promising supports for Au nanoparticles in CO oxidation whose activity is found to be dependent on Ce/Zr molar ratio.     

High Temperature Alters Secondary Metabolites and Photosynthetic Efficiency in Heracleum sosnowskyi

Due to global warming, invasive species have spread across the world. We therefore studied the impact of short-term (1 day or 2 days) and longer (7 days) heat stress on photosynthesis and secondary metabolites in Heracleum sosnowskyi, one of the important invasive species in the European Union. H. sosnowskyi leaves exposed to short-term heat stress (35 °C/1 d) showed a decrease in chlorophyll and maximum potential quantum efficiency of photosystem II (Fv/Fm) compared to control, 35 °C/2 d, or 30 °C/7 d treatments. In turn, the high level of lipid peroxidation and increased H₂O₂ accumulation indicated that the 30 °C/7 d stress induced oxidative damage. The contents of xanthotoxin and bergapten were elevated in the 2 d and 7 d treatments, while isopimpinellin was detected only in the heat-stressed plants. Additionally, the levels of free proline and anthocyanins significantly increased in response to high temperature, with a substantially higher increase in the 7 d (30 °C) treatment. The results indicate that the accumulation of proline, anthocyanins, and furanocoumarins, but not of phenolic acids or flavonols, contributes to protection of H. sosnowskyi plants against heat stress. Further studies could focus on the suppression of these metabolites to suppress the spread of this invasive species.     

Approach to calculation time-dependent moisture diffusivity for thin layered biological materials

A method is presented to determine the effective diffusivity from experimental drying kinetics as a time-dependent parameter. The method combines an analytical solution of Fick's equation in which the Fourier number is approximated using the empirical coefficients a and b with a semi-theoretical equation derived for quasi-stationary conditions. The resulting equation has been applied to calculate the effective diffusivity from literature data on the drying of tobacco lamina and sliced celery. The applicability of the method was confirmed by good agreement of calculated and experimental data. It was found that the effective diffusivity for tobacco lamina rises sharply from practically zero at the beginning of drying to a maximum of 9·10^{− 10} m²/s at 89 s, and then gradually decays with time of drying. The same trend was found for sliced celery, but the maximum of the effective diffusivity (1.6·10^{− 7} m²/min) was attained at 56 s. The exact definition of the effective diffusivity vs. drying time identifies two phases of drying: the first phase was characterized by the rising intensity of drying with the maximum at the end of this phase, followed by the phase of slow decrease in the intensity of moisture removal. The rising intensity of drying observed during the initial phase of the process can be explained by warming up of the dried material during the initial phase of drying.