Electron-Induced Electron Yields of Uncharged Insulating Materials

This study presents electron-induced electron yield measurements from high-resistivity, high-yield materials to validate a model for the yield of uncharged insulators. These measurements are accomplished by using a low-fluence, pulsed incident electron beam and charge neutralization to minimize charge accumulation. Our measurements show large changes in total yield curves and yield decay curves, even for incident electron fluences of/mm2. We model the evolution of the yield as charge accumulates in the material in terms of electron re-capture based on the extended Chung-Everhart model of the electron emission spectrum. This model is used to explain anomalies measured in high yield ceramics, and to provide a method for determining the uncharged yield in highly insulating, high yield materials. Relevance of these results to spacecraft charging will also be discussed

A topological algorithm for identification of structural domains of proteins

<p>Abstract</p> <p>Background</p> <p>Identification of the structural domains of proteins is important for our understanding of the organizational principles and mechanisms of protein folding, and for insights into protein function and evolution. Algorithmic methods of dissecting protein of known structure into domains developed so far are based on an examination of multiple geometrical, physical and topological features. Successful as many of these approaches are, they employ a lot of heuristics, and it is not clear whether they illuminate any deep underlying principles of protein domain organization. Other well-performing domain dissection methods rely on comparative sequence analysis. These methods are applicable to sequences with known and unknown structure alike, and their success highlights a fundamental principle of protein modularity, but this does not directly improve our understanding of protein spatial structure.</p> <p>Results</p> <p>We present a novel graph-theoretical algorithm for the identification of domains in proteins with known three-dimensional structure. We represent the protein structure as an undirected, unweighted and unlabeled graph whose nodes correspond to the secondary structure elements and edges represent physical proximity of at least one pair of alpha carbon atoms from two elements. Domains are identified as constrained partitions of the graph, corresponding to sets of vertices obtained by the maximization of the cycle distributions found in the graph. When a partition is found, the algorithm is iteratively applied to each of the resulting subgraphs. The decision to accept or reject a tentative cut position is based on a specific classifier. The algorithm is applied iteratively to each of the resulting subgraphs and terminates automatically if partitions are no longer accepted. The distribution of cycles is the only type of information on which the decision about protein dissection is based. Despite the barebone simplicity of the approach, our algorithm approaches the best heuristic algorithms in accuracy.</p> <p>Conclusion</p> <p>Our graph-theoretical algorithm uses only topological information present in the protein structure itself to find the domains and does not rely on any geometrical or physical information about protein molecule. Perhaps unexpectedly, these drastic constraints on resources, which result in a seemingly approximate description of protein structures and leave only a handful of parameters available for analysis, do not lead to any significant deterioration of algorithm accuracy. It appears that protein structures can be rigorously treated as topological rather than geometrical objects and that the majority of information about protein domains can be inferred from the coarse-grained measure of pairwise proximity between elements of secondary structure elements.</p

Ericaceous vegetation of the Bale Mountains of Ethiopia will prevail in the face of climate change

Climate change impacts the structure, functioning, and distribution of species and ecosystems. It will shift ecosystem boundaries, potentially affecting vulnerable ecosystems, such as tropical Africa's high mountain ecosystems, i.e., afroalpine ecosystems, and their highly susceptible uniquely adapted species. However, ecosystems along these mountains are not expected to respond similarly to the change. The ericaceous woody vegetation, located between the low-elevation broadleaf forests and high-elevation afroalpine vegetation, are anticipated to be affected differently. We hypothesize that projected climate change will result in an upward expansion and increasing dominance of ericaceous vegetation, which will negatively impact the endemic rich afroalpine ecosystems of the extensive Sanetti plateau. Hence, we modeled the impact of future climate change on the distribution of ericaceous vegetation and discussed its effect on bordering ecosystems in the Bale Mountains. We applied four familiar correlative modeling approaches: bioclim, domain, generalized linear methods, and support vector machines. We used WorldClim’s bioclimatic variables as environmental predictors and two representative concentration pathways (RCPs) of the IPCC Fifth Assessment Report climate change scenarios, namely RCP4.5 and RCP8.5 for future climate projection. The results indicate increased ericaceous vegetation cover on the midaltitude of northwestern and northern parts of the massif, and the Sanetti plateau. We observed upward range expansion and increase of close ericaceous vegetation in midaltitudes, while receding from the lower range across the massif. Moreover, the current ericaceous vegetation range correlates to the temperature and precipitation trends, reaffirming the critical role of temperature and precipitation in determining species distributions along elevational gradients. The results indicate the high likelihood of considerable changes in this biodiversity hotspot in Eastern Africa