The origin of defects induced in ultra-pure germanium by Electron Beam Deposition

The creation of point defects in the crystal lattices of various semiconductors by subthreshold events has been reported on by a number of groups. These observations have been made in great detail using sensitive electrical techniques but there is still much that needs to be clarified. Experiments using Ge and Si were performed that demonstrate that energetic particles, the products of collisions in the electron beam, were responsible for the majority of electron-beam deposition (EBD) induced defects in a two-step energy transfer process. Lowering the number of collisions of these energetic particles with the semiconductor during metal deposition was accomplished using a combination of static shields and superior vacuum resulting in devices with defect concentrations lower than $10^{11}\,$cm$^{-3}$, the measurement limit of our deep level transient spectroscopy (DLTS) system. High energy electrons and photons that samples are typically exposed to were not influenced by the shields as most of these particles originate at the metal target thus eliminating these particles as possible damage causing agents. It remains unclear how packets of energy that can sometimes be as small of 2eV travel up to a $\mu$m into the material while still retaining enough energy, that is, in the order of 1eV, to cause changes in the crystal. The manipulation of this defect causing phenomenon may hold the key to developing defect free material for future applications.Comment: 18 pages, 9 figure

Neural development features: Spatio-temporal development of the Caenorhabditis elegans neuronal network

The nematode Caenorhabditis elegans, with information on neural connectivity, three-dimensional position and cell linage provides a unique system for understanding the development of neural networks. Although C. elegans has been widely studied in the past, we present the first statistical study from a developmental perspective, with findings that raise interesting suggestions on the establishment of long-distance connections and network hubs. Here, we analyze the neuro-development for temporal and spatial features, using birth times of neurons and their three-dimensional positions. Comparisons of growth in C. elegans with random spatial network growth highlight two findings relevant to neural network development. First, most neurons which are linked by long-distance connections are born around the same time and early on, suggesting the possibility of early contact or interaction between connected neurons during development. Second, early-born neurons are more highly connected (tendency to form hubs) than later born neurons. This indicates that the longer time frame available to them might underlie high connectivity. Both outcomes are not observed for random connection formation. The study finds that around one-third of electrically coupled long-range connections are late forming, raising the question of what mechanisms are involved in ensuring their accuracy, particularly in light of the extremely invariant connectivity observed in C. elegans. In conclusion, the sequence of neural network development highlights the possibility of early contact or interaction in securing long-distance and high-degree connectivity

Emergence of non-centrosymmetric topological insulating phase in BiTeI under pressure

The spin-orbit interaction affects the electronic structure of solids in various ways. Topological insulators are one example where the spin-orbit interaction leads the bulk bands to have a non-trivial topology, observable as gapless surface or edge states. Another example is the Rashba effect, which lifts the electron-spin degeneracy as a consequence of spin-orbit interaction under broken inversion symmetry. It is of particular importance to know how these two effects, i.e. the non-trivial topology of electronic states and Rashba spin splitting, interplay with each other. Here we show, through sophisticated first-principles calculations, that BiTeI, a giant bulk Rashba semiconductor, turns into a topological insulator under a reasonable pressure. This material is shown to exhibit several unique features such as, a highly pressure-tunable giant Rashba spin splitting, an unusual pressure-induced quantum phase transition, and more importantly the formation of strikingly different Dirac surface states at opposite sides of the material.Comment: 5 figures are include

Trace-gas metabolic versatility of the facultative methanotroph Methylocella silvestris

The climate-active gas methane is generated both by biological processes and by thermogenic decomposition of fossil organic material, which forms methane and short-chain alkanes, principally ethane, propane and butane1, 2. In addition to natural sources, environments are exposed to anthropogenic inputs of all these gases from oil and gas extraction and distribution. The gases provide carbon and/or energy for a diverse range of microorganisms that can metabolize them in both anoxic3 and oxic zones. Aerobic methanotrophs, which can assimilate methane, have been considered to be entirely distinct from utilizers of short-chain alkanes, and studies of environments exposed to mixtures of methane and multi-carbon alkanes have assumed that disparate groups of microorganisms are responsible for the metabolism of these gases. Here we describe the mechanism by which a single bacterial strain, Methylocella silvestris, can use methane or propane as a carbon and energy source, documenting a methanotroph that can utilize a short-chain alkane as an alternative to methane. Furthermore, during growth on a mixture of these gases, efficient consumption of both gases occurred at the same time. Two soluble di-iron centre monooxygenase (SDIMO) gene clusters were identified and were found to be differentially expressed during bacterial growth on these gases, although both were required for efficient propane utilization. This report of a methanotroph expressing an additional SDIMO that seems to be uniquely involved in short-chain alkane metabolism suggests that such metabolic flexibility may be important in many environments where methane and short-chain alkanes co-occur

FAK acts as a suppressor of RTK-MAP kinase signalling in Drosophila melanogaster epithelia and human cancer cells

Receptor Tyrosine Kinases (RTKs) and Focal Adhesion Kinase (FAK) regulate multiple signalling pathways, including mitogen-activated protein (MAP) kinase pathway. FAK interacts with several RTKs but little is known about how FAK regulates their downstream signalling. Here we investigated how FAK regulates signalling resulting from the overexpression of the RTKs RET and EGFR. FAK suppressed RTKs signalling in Drosophila melanogaster epithelia by impairing MAPK pathway. This regulation was also observed in MDA-MB-231 human breast cancer cells, suggesting it is a conserved phenomenon in humans. Mechanistically, FAK reduced receptor recycling into the plasma membrane, which resulted in lower MAPK activation. Conversely, increasing the membrane pool of the receptor increased MAPK pathway signalling. FAK is widely considered as a therapeutic target in cancer biology; however, it also has tumour suppressor properties in some contexts. Therefore, the FAK-mediated negative regulation of RTK/MAPK signalling described here may have potential implications in the designing of therapy strategies for RTK-driven tumours

Constraints on Non-Newtonian Gravity from Recent Casimir Force Measurements

Corrections to Newton's gravitational law inspired by extra dimensional physics and by the exchange of light and massless elementary particles between the atoms of two macrobodies are considered. These corrections can be described by the potentials of Yukawa-type and by the power-type potentials with different powers. The strongest up to date constraints on the corrections to Newton's gravitational law are reviewed following from the E\"{o}tvos- and Cavendish-type experiments and from the measurements of the Casimir and van der Waals force. We show that the recent measurements of the Casimir force gave the possibility to strengthen the previously known constraints on the constants of hypothetical interactions up to several thousand times in a wide interaction range. Further strengthening is expected in near future that makes Casimir force measurements a prospective test for the predictions of fundamental physical theories.Comment: 20 pages, crckbked.cls is used, to be published in: Proceedings of the 18th Course of the School on Cosmology and Gravitation: The Gravitational Constant. Generalized Gravitational Theories and Experiments (30 April- 10 May 2003, Erice). Ed. by G. T. Gillies, V. N. Melnikov and V. de Sabbata, 20pp. (Kluwer, in print, 2003

MMS observations of electron-scale filamentary currents in the reconnection exhaust and near the X line

© 2016. American Geophysical Union. All Rights Reserved.We report Magnetospheric Multiscale observations of macroscopic and electron-scale current layers in asymmetric reconnection. By intercomparing plasma, magnetic, and electric field data at multiple crossings of a reconnecting magnetopause on 22 October 2015, when the average interspacecraft separation was ~10km, we demonstrate that the ion and electron moments are sufficiently accurate to provide reliable current density measurements at 30ms cadence. These measurements, which resolve current layers narrower than the interspacecraft separation, reveal electron-scale filamentary Hall currents and electron vorticity within the reconnection exhaust far downstream of the X line and even in the magnetosheath. Slightly downstream of the X line, intense (up to 3μA/m2) electron currents, a super-Alfvénic outflowing electron jet, and nongyrotropic crescent shape electron distributions were observed deep inside the ion-scale magnetopause current sheet and embedded in the ion diffusion region. These characteristics are similar to those attributed to the electron dissipation/diffusion region around the X line

Distinguishing Asthma Phenotypes Using Machine Learning Approaches.

Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as asthma endotypes. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies

Influence of wiring cost on the large-scale architecture of human cortical connectivity

In the past two decades some fundamental properties of cortical connectivity have been discovered: small-world structure, pronounced hierarchical and modular organisation, and strong core and rich-club structures. A common assumption when interpreting results of this kind is that the observed structural properties are present to enable the brain's function. However, the brain is also embedded into the limited space of the skull and its wiring has associated developmental and metabolic costs. These basic physical and economic aspects place separate, often conflicting, constraints on the brain's connectivity, which must be characterized in order to understand the true relationship between brain structure and function. To address this challenge, here we ask which, and to what extent, aspects of the structural organisation of the brain are conserved if we preserve specific spatial and topological properties of the brain but otherwise randomise its connectivity. We perform a comparative analysis of a connectivity map of the cortical connectome both on high- and low-resolutions utilising three different types of surrogate networks: spatially unconstrained (‘random’), connection length preserving (‘spatial’), and connection length optimised (‘reduced’) surrogates. We find that unconstrained randomisation markedly diminishes all investigated architectural properties of cortical connectivity. By contrast, spatial and reduced surrogates largely preserve most properties and, interestingly, often more so in the reduced surrogates. Specifically, our results suggest that the cortical network is less tightly integrated than its spatial constraints would allow, but more strongly segregated than its spatial constraints would necessitate. We additionally find that hierarchical organisation and rich-club structure of the cortical connectivity are largely preserved in spatial and reduced surrogates and hence may be partially attributable to cortical wiring constraints. In contrast, the high modularity and strong s-core of the high-resolution cortical network are significantly stronger than in the surrogates, underlining their potential functional relevance in the brain