Stem Photosynthesis—A Key Element of Grass Pea (Lathyrus sativus L.) Acclimatisation to Salinity

Grass pea (Lathyrus sativus) is a leguminous plant of outstanding tolerance to abiotic stress. The aim of the presented study was to describe the mechanism of grass pea (Lathyrus sativus L.) photosynthetic apparatus acclimatisation strategies to salinity stress. The seedlings were cultivated in a hydroponic system in media containing various concentrations of NaCl (0, 50, and 100 mM), imitating none, moderate, and severe salinity, respectively, for three weeks. In order to characterise the function and structure of the photosynthetic apparatus, Chl a fluorescence, gas exchange measurements, proteome analysis, and Fourier-transform infrared spectroscopy (FT-IR) analysis were done inter alia. Significant differences in the response of the leaf and stem photosynthetic apparatus to severe salt stress were observed. Leaves became the place of harmful ion (Na⁺) accumulation, and the efficiency of their carboxylation decreased sharply. In turn, in stems, the reconstruction of the photosynthetic apparatus (antenna and photosystem complexes) activated alternative electron transport pathways, leading to effective ATP synthesis, which is required for the efficient translocation of Na⁺ to leaves. These changes enabled efficient stem carboxylation and made them the main source of assimilates. The observed changes indicate the high plasticity of grass pea photosynthetic apparatus, providing an effective mechanism of tolerance to salinity stress.     

Characterization of the Ion Beam Current Density of the RF Ion Source with Flat and Convex Extraction Systems

Silicon - The characterization of ion beam current density distribution and beam uniformity is crucial for improving broad-beam ion source technologies. The design of the broad ion beam extraction...     

Computer simulation of the growth of heterostructure systems

We have investigated the growth of heterostructures with high lattice mismatch and the growth of quantum wires on the top of ridges and through shadowing masks. Simulations are performed within a Monte Carlo scheme using tetrahedral lattice structure of semiconductor materials. It is shown that results of different simulations present similarities that we attribute to the primary role of kinetic effects as the driving force during epitaxial growth. The formation of 3D islands showing (111) facets, or (111) side walls when depositing through a shadowing mask, has been observed. The facets are of better quality than the top (001) surface because of the higher mobility of atoms on these facets.     

Microstructure of hardened gypsum pastes

Specific surface areas and pore size distribution analysis were taken as essential parameters to explore the microstructure of hardened gypsum pastes. The hydration of gypsum plaster is essentially affected by the water/plaster ratio of the mix, and by the presence of additives which might act as retarders or accelerators to the hydration process. Affecting the microstructure would mutually lead to variations of the compressive strength of the hardened pastes, and these variations are also discussed. Results are mainly expressed in terms of the solid (measured by the extent of its specific area) to the space (pore) ratios. Dual distribution of pore sizes was observed and the two groups of pores are designed as S (small) and L (large) pores. Similarities to the microstructure of hardened Portland cement pastes are indicated. Accelerators appear to function differently from retarders, and the effects of water/plaster ratios were investigated in both cases. The results obtained may carry many significant practical implications to the future use of hardened gypsum pastes.     

Polynomial time approximation algorithms for proportionate open‐shop scheduling

This paper deals with the presentation of polynomial time (approximation) algorithms for a variant of open‐shop scheduling, where the processing times are only machine‐dependent. This variant of scheduling is called proportionate scheduling and its applications are used in many real‐world environments. This paper develops three polynomial time algorithms for the problem. First, we present a polynomial time algorithm that solves the problem optimally if , where n and m denote the numbers of jobs and machines, respectively. If, on the other hand, , we develop a polynomial time approximation algorithm with a worst‐case performance ratio of that improves the bound existing for general open‐shops. Next, in the case of , we take into account the problem under consideration as a master problem and convert it into a simpler secondary approximation problem. Furthermore, we formulate both the master and secondary problems, and compare their complexity sizes. We finally present another polynomial time algorithm that provides optimal solution for a special case of the problem where .