Optical flow tracking velocimetry of near-field explosions

To better understand the complex dynamics and physics associated with the rapid expansion of the detonation product fireball following an explosion, it is imperative to have a full description of its associated velocity field. Typical experimental techniques rely on simple single-point measurements captured from pressure transducers or Hopkinson pressure bars. In this technical design note, we aim to improve the current state-of-the-art by introducing a means to determine full velocity fields from high-speed video using optical flow tracking velocimetry. We demonstrate the significance of this method from our results by comparing velocity fields derived from high-speed video and a validated numerical model of the same case. A wider use of this technique will allow researchers to elucidate spatial and temporal features of explosive detonations, which could not be obtained thus far using single-point measurements

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.

The Sudbury Neutrino Observatory

The Sudbury Neutrino Observatory is a second generation water Cherenkov detector designed to determine whether the currently observed solar neutrino deficit is a result of neutrino oscillations. The detector is unique in its use of D2O as a detection medium, permitting it to make a solar model-independent test of the neutrino oscillation hypothesis by comparison of the charged- and neutral-current interaction rates. In this paper the physical properties, construction, and preliminary operation of the Sudbury Neutrino Observatory are described. Data and predicted operating parameters are provided whenever possible.Comment: 58 pages, 12 figures, submitted to Nucl. Inst. Meth. Uses elsart and epsf style files. For additional information about SNO see http://www.sno.phy.queensu.ca . This version has some new reference

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