48 research outputs found

    Selenium Status in Heifers, Late Pregnancy Cows and Their Calves in the Ć umava Region, Czech Republic

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    The objective of this study was to ascertain selenium status in beef cattle in different stages of production in the Ć umava region. In the region, blood collections and analyses for selected metabolic variables were performed in 54 animals in different production stages (18 heifers, 18 cows in late pregnancy and 18 calves aged 3 weeks on the average). Three herds were studied. The selenium status was determined both directly by measuring serum selenium (Se) contents and indirectly by measuring glutathione peroxidase (GSH-Px) activity in whole blood. The mean serum selenium concentration in all the animals under study (n = 54) was 30.6 ÎŒg/l +/- 2.91, and mean GSH-Px activity was 167.01 ÎŒkat/l +/- 92.39. In heifers, mean serum selenium concentration was 34.81 ÎŒg/l +/- 13.84; mean GSHPx activity was 186.96 ÎŒkat/l +/- 112.15. In late pregnancy cows, mean serum selenium concentration was 26.58 ÎŒg/l +/- 8.01, mean GSH-Px activity was 94.55 +/- 35.72 ÎŒkat/l. In calves, mean serum selenium concentration and GSH-Px activity were 30.41 ÎŒg/l +/- 12 and 219.54 ÎŒkat/l +/- 64.41, respectively. There was a statistically significant difference between the heifers and late pregnancy cows in both variables under study. However, between the late pregnancy cows and the calves, only the difference in GSH-Px activity was significant. The results indicate severe Se deficiency in the animals under study. It means apart from other things that mineral licks used did not provide enough minerals to meet the basic requirements of the animals

    First-principles study of Co- and Cu-doped Ni2MnGa along the tetragonal deformation path

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    The influence of Co and Cu doping on Ni-Mn-Ga Heusler alloy is investigated using the first-principles exact muffin-tin orbital method in combination with the coherent-potential approximation. Single-element doping and simultaneous doping by both elements are investigated in Ni50−xCoxMn25−yGa25−zCuy+z alloys, with dopant concentrations x,y, and z up to 7.5 at. %. Doping with Co in the Ni sublattice decreases the (c/a)NM ratio of the nonmodulated (NM) martensite, but it simultaneously increases the cubic phase stability with respect to the NM phase. Doping with Cu in the Mn or in Ga sublattices does not change the (c/a)NM ratio significantly and it decreases the cubic phase stability. For simultaneous doping by Co in the Ni sublattice and Cu in the Mn or Ga sublattices, the effects of the individual dopants are independent and about the same as for the single-element doping. Thus, the (c/a)NM ratio can be adjusted by Co doping while the phase stability can be balanced by Cu doping, resulting in stable martensite with a reduced (c/a)NM. The local stability of the cubic phase with respect to the tetragonal deformation can be understood on the basis of a density-of-states analysis.Peer reviewe

    Zinc and Copper Status of Beef Cattle in the Ć umava Region, Czech Republic

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    The aim of the study was to ascertain copper (Cu) and zinc (Zn) status in beef cattle in different stages of production pastured in a mountainous area with known soil deficiency of Zn and Cu. Data from seven beef herds (n = 100) were evaluated, each time for two production stages (cows in late pregnancy and heifers). Serum levels of zinc and copper were measured. Mean concentrations of Zn and Cu were 16.34+/-3.52 ÎŒmol l-1 and 11.17 +/-3.27 ÎŒmol l-1, respectively. Mean values measured in the heifers (n = 50) were 16.3 +/-3.58 ÎŒmol l-1 for zinc and 11.65 +/-3.32 ÎŒmol l-1 for copper. In the cows in late pregnancy (n = 50), serum concentrations of Zn and Cu were 16.37 +/- 3.46 ÎŒmol l-1 and 10.68 +/-3.07 ÎŒmol l-1, respectively. Neither for copper (p p < 0.99) significant differences were demonstrated between cows in late pregnancy and heifers. Moreover, analysis of their feed revealed that the content of these minerals was half of the recommended levels. Therefore, to achieve an adequate zinc status, both cattle categories pastured in this area should have access to mineral licks

    Metrology For Advanced Manufacturing – The Networking Project AdvManuNet

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    Advanced Manufacturing is a branch of manufacturing that is considered an important driver for future economic and societal progress. The European Commission (EC) has identified Advanced Manufacturing as one of six Key Enabling Technologies (KETs) with applications across multiple industrial sectors. The networking project JNP19Net01 AdvManuNet funded by EURAMET for four years starting in June 2020 aims to accelerate the process of establishing a European Metrology Network (EMN) to strengthen Europe’s position in Advanced Manufacturing. The consortium to deliver this project comprises National Metrological Institutes (PTB, NPL, INRIM, RISE, CMI, METAS, TUBITAK, GUM), Designated Institutes (BAM), University partners (Politecnico di Torino) and the European Society for Precision Engineering and Nanotechnology (euspen) from across Europe

    A compact null set containing a differentiability point of every Lipschitz function

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    We prove that in a Euclidean space of dimension at least two, there exists a compact set of Lebesgue measure zero such that any real-valued Lipschitz function defined on the space is differentiable at some point in the set. Such a set is constructed explicitly.Comment: 28 pages; minor modifications throughout; Lemma 4.2 is proved for general Banach space rather than for Hilbert spac

    Ferromagnetic behavior of ultrathin manganese nanosheets

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    Ferromagnetic behaviour has been observed experimentally for the first time in nanostructured Manganese. Ultrathin (∌\sim 0.6 nm) Manganese nanosheets have been synthesized inside the two dimensional channels of sol-gel derived Na-4 mica. The magnetic properties of the confined system are measured within 2K-300K temperature range. The confined structure is found to show a ferromagnetic behaviour with a nonzero coercivity value. The coercivity value remains positive throughout the entire temperature range of measurement. The experimental variation of susceptibility as a function of temperature has been satisfactorily explained on the basis of a two dimensional system with a Heisenberg Hamiltonian involving direct exchange interaction.Comment: 13 pages, 9 figure

    TRY plant trait database – enhanced coverage and open access

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    Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

    TRY plant trait database – enhanced coverage and open access

    Get PDF
    Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives
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