Mesoscale magnetism at the grain boundaries in colossal magnetoresistive films

We report the discovery of mesoscale regions with distinctive magnetic properties in epitaxial La$_{1-x}$Sr$_{x}$MnO$_{3}$ films which exhibit tunneling-like magnetoresistance across grain boundaries. By using temperature-dependent magnetic force microscopy we observe that the mesoscale regions are formed near the grain boundaries and have a different Curie temperature (up to 20 K {\it higher}) than the grain interiors. Our images provide direct evidence for previous speculations that the grain boundaries in thin films are not magnetically and electronically sharp interfaces. The size of the mesoscale regions varies with temperature and nature of the underlying defect.Comment: 4 pages of text, 4 figure

Grain boundary effects on magnetotransport in bi-epitaxial films of La0.7_{0.7}Sr0.3_{0.3}MnO3_3

The low field magnetotransport of La$_{0.7}$Sr$_{0.3}$MnO$_3$ (LSMO) films grown on SrTiO$_3$ substrates has been investigated. A high qualtity LSMO film exhibits anisotropic magnetoresistance (AMR) and a peak in the magnetoresistance close to the Curie temperature of LSMO. Bi-epitaxial films prepared using a seed layer of MgO and a buffer layer of CeO$_2$ display a resistance dominated by grain boundaries. One film was prepared with seed and buffer layers intact, while a second sample was prepared as a 2D square array of grain boundaries. These films exhibit i) a low temperature tail in the low field magnetoresistance; ii) a magnetoconductance with a constant high field slope; and iii) a comparably large AMR effect. A model based on a two-step tunneling process, including spin-flip tunneling, is discussed and shown to be consistent with the experimental findings of the bi-epitaxial films.Comment: REVTeX style; 14 pages, 9 figures. Figure 1 included in jpeg format (zdf1.jpg); the eps was huge. Accepted to Phys. Rev.

A Multi-model Analysis of Post-2020 Mitigation Efforts of Five Major Economies

This paper looks into the regional mitigation strategies of five major economies (China, EU, India, Japan and USA) in the context of the 2 degrees C target, using a multi-model comparison. In order to stay in line with the 2 degrees C target, a tripling or quadrupling of mitigation ambitions is required in all regions by 2050, employing vigorous decarbonization of the energy supply system and achieving negative emissions during the second half of the century. In all regions looked at, decarbonization of energy supply (and in particular power generation) is more important than reducing energy demand. Some differences in abatement strategies across the regions are projected: In India and the USA the emphasis is on prolonging fossil fuel use by coupling conventional technologies with carbon storage, whereas the other main strategy depicts a shift to carbon-neutral technologies with mostly renewables (China, EU) or nuclear power (Japan). Regions with access to large amounts of biomass, such as the USA, China and the EU, can make a trade-off between energy related emissions and land related emissions, as the use of bioenergy can lead to a net increase in land use emissions. After supply-side changes, the most important abatement strategy focuses on enduse efficiency improvements, leading to considerable emission reductions in both the industry and transport sectors across all regions. Abatement strategies for non-CO2 emissions and land use emissions are found to have a smaller potential. Inherent model, as well as collective, biases have been observed affecting the regional response strategy or the available reduction potential in specific (end-use) sectors

Impingement During Dislocation-Prone Activities: Geometric Modeling Analysis of an Uncemented Standard Versus Modular Dual Mobility Acetabular Cups

Background/Objectives: The stability of dual mobility (DM) total hip arthroplasty (THA) is often attributed to reduced impingement incidence and a superior range of motion (ROM) compared to the corresponding values when standard implants are used. However, few studies have directly explored this. Thus, the purpose of the present study was to compare the incidence of impingement and the range of motion between standard and DM acetabular cups, whose diameters are suited to the same patient anatomy. Methods: One standard and two DM implants were virtually implanted into a pelvis using a previously developed geometric model. Joint motions, which were representative of seven dislocation-prone activities of daily living (ADLs), as well as walking, were applied to each device type at a range of cup orientations (inclination/anteversion). Conclusions: There were no placement positions that avoided impingement across all seven ADLs, regardless of cup construct type. A similar impingement incidence and ROM were observed for standard and DM constructs, although the consequences of impingement are potentially more serious for DM devices (metal–metal contact) than for standard constructs (metal–polyethylene contact). This finding contradicts the common notion that DM-THAs have a reduced impingement incidence and superior ROM, instead suggesting that their stability may be attributed to alternative mechanisms, such as increased jump distance

TRY plant trait database – enhanced coverage and open access

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

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge, it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost