High energy emission from microquasars

The microquasar phenomenon is associated with the production of jets by X-ray binaries and, as such, may be associated with the majority of such systems. In this chapter we briefly outline the associations, definite, probable, possible, and speculative, between such jets and X-ray, gamma-ray and particle emission.Comment: Contributing chapter to the book Cosmic Gamma-Ray Sources, K.S. Cheng and G.E. Romero (eds.), to be published by Kluwer Academic Publishers, Dordrecht, 2004. (19 pages

N=2 supergravity and supercurrents

We address the problem of classifying all N=2 supercurrent multiplets in four space-time dimensions. For this purpose we consider the minimal formulation of N=2 Poincare supergravity with a tensor compensator, and derive its linearized action in terms of three N=2 off-shell multiplets: an unconstrained scalar superfield, a vector multiplet, and a tensor multiplet. Such an action was ruled out to exist in the past. Using the action constructed, one can derive other models for linearized N=2 supergravity by applying N=2 superfield duality transformations. The action depends parametrically on a constant non-vanishing real isotriplet g^{ij}=g^{ji} which originates as an expectation value of the tensor compensator. Upon reduction to N=1 superfields, we show that the model describes two dually equivalent formulations for the massless multiplet (1,3/2)+(3/2,2) depending on a choice of g^{ij}. In the case g^{11}=g^{22}=0, the action describes (i) new minimal N=1 supergravity; and (ii) the Fradkin-Vasiliev-de Wit-van Holten gravitino multiplet. In the case g^{12}=0, on the other hand, the action describes (i) old minimal N=1 supergravity; and (ii) the Ogievetsky-Sokatchev gravitino multiplet.Comment: 40 pages; v2: added references, some comments, new appendi

Garden and landscape-scale correlates of moths of differing conservation status: significant effects of urbanization and habitat diversity

Moths are abundant and ubiquitous in vegetated terrestrial environments and are pollinators, important herbivores of wild plants, and food for birds, bats and rodents. In recent years, many once abundant and widespread species have shown sharp declines that have been cited by some as indicative of a widespread insect biodiversity crisis. Likely causes of these declines include agricultural intensification, light pollution, climate change, and urbanization; however, the real underlying cause(s) is still open to conjecture. We used data collected from the citizen science Garden Moth Scheme (GMS) to explore the spatial association between the abundance of 195 widespread British species of moth, and garden habitat and landscape features, to see if spatial habitat and landscape associations varied for species of differing conservation status. We found that associations with habitat and landscape composition were species-specific, but that there were consistent trends in species richness and total moth abundance. Gardens with more diverse and extensive microhabitats were associated with higher species richness and moth abundance; gardens near to the coast were associated with higher richness and moth abundance; and gardens in more urbanized locations were associated with lower species richness and moth abundance. The same trends were also found for species classified as increasing, declining and vulnerable under IUCN (World Conservation Union) criteria

Deep diversification of an AAV capsid protein by machine learning.

Modern experimental technologies can assay large numbers of biological sequences, but engineered protein libraries rarely exceed the sequence diversity of natural protein families. Machine learning (ML) models trained directly on experimental data without biophysical modeling provide one route to accessing the full potential diversity of engineered proteins. Here we apply deep learning to design highly diverse adeno-associated virus 2 (AAV2) capsid protein variants that remain viable for packaging of a DNA payload. Focusing on a 28-amino acid segment, we generated 201,426 variants of the AAV2 wild-type (WT) sequence yielding 110,689 viable engineered capsids, 57,348 of which surpass the average diversity of natural AAV serotype sequences, with 12-29 mutations across this region. Even when trained on limited data, deep neural network models accurately predict capsid viability across diverse variants. This approach unlocks vast areas of functional but previously unreachable sequence space, with many potential applications for the generation of improved viral vectors and protein therapeutics

Compartments revealed in food-web structure

Compartments(1) in food webs are subgroups of taxa in which many strong interactions occur within the subgroups and few weak interactions occur between the subgroups(2). Theoretically, compartments increase the stability in networks(1-5), such as food webs. Compartments have been difficult to detect in empirical food webs because of incompatible approaches(6-9) or insufficient methodological rigour(8,10,11). Here we show that a method for detecting compartments from the social networking science(12-14) identified significant compartments in three of five complex, empirical food webs. Detection of compartments was influenced by food web resolution, such as interactions with weights. Because the method identifies compartmental boundaries in which interactions are concentrated, it is compatible with the definition of compartments. The method is rigorous because it maximizes an explicit function, identifies the number of non-overlapping compartments, assigns membership to compartments, and tests the statistical significance of the results(12-14). A graphical presentation(14) reveals systemic relationships and taxa-specific positions as structured by compartments. From this graphic, we explore two scenarios of disturbance to develop a hypothesis for testing how compartmentalized interactions increase stability in food webs(15-17).Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62960/1/nature02115.pd

A millisecond quantum memory for scalable quantum networks

Scalable quantum information processing critically depends on the capability of storage of a quantum state. In particular, a long-lived storable and retrievable quantum memory for single excitations is of crucial importance to the atomic-ensemble-based long-distance quantum communication. Although atomic memories for classical lights and continuous variables have been demonstrated with milliseconds storage time, there is no equal advance in the development of quantum memory for single excitations, where only around 10 $\mu$s storage time was achieved. Here we report our experimental investigations on extending the storage time of quantum memory for single excitations. We isolate and identify distinct mechanisms for the decoherence of spin wave (SW) in atomic ensemble quantum memories. By exploiting the magnetic field insensitive state, ``clock state", and generating a long-wavelength SW to suppress the dephasing, we succeed in extending the storage time of the quantum memory to 1 ms. Our result represents a substantial progress towards long-distance quantum communication and enables a realistic avenue for large-scale quantum information processing.Comment: 11pages, 4 figures, submitted for publicatio

Measurement of χ c1 and χ c2 production with s√ = 7 TeV pp collisions at ATLAS

The prompt and non-prompt production cross-sections for the χ c1 and χ c2 charmonium states are measured in pp collisions at s√ = 7 TeV with the ATLAS detector at the LHC using 4.5 fb−1 of integrated luminosity. The χ c states are reconstructed through the radiative decay χ c → J/ψγ (with J/ψ → μ + μ −) where photons are reconstructed from γ → e + e − conversions. The production rate of the χ c2 state relative to the χ c1 state is measured for prompt and non-prompt χ c as a function of J/ψ transverse momentum. The prompt χ c cross-sections are combined with existing measurements of prompt J/ψ production to derive the fraction of prompt J/ψ produced in feed-down from χ c decays. The fractions of χ c1 and χ c2 produced in b-hadron decays are also measured

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Breaking Functional Connectivity into Components: A Novel Approach Using an Individual-Based Model, and First Outcomes

Landscape connectivity is a key factor determining the viability of populations in fragmented landscapes. Predicting ‘functional connectivity’, namely whether a patch or a landscape functions as connected from the perspective of a focal species, poses various challenges. First, empirical data on the movement behaviour of species is often scarce. Second, animal-landscape interactions are bound to yield complex patterns. Lastly, functional connectivity involves various components that are rarely assessed separately. We introduce the spatially explicit, individual-based model FunCon as means to distinguish between components of functional connectivity and to assess how each of them affects the sensitivity of species and communities to landscape structures. We then present the results of exploratory simulations over six landscapes of different fragmentation levels and across a range of hypothetical bird species that differ in their response to habitat edges. i) Our results demonstrate that estimations of functional connectivity depend not only on the response of species to edges (avoidance versus penetration into the matrix), the movement mode investigated (home range movements versus dispersal), and the way in which the matrix is being crossed (random walk versus gap crossing), but also on the choice of connectivity measure (in this case, the model output examined). ii) We further show a strong effect of the mortality scenario applied, indicating that movement decisions that do not fully match the mortality risks are likely to reduce connectivity and enhance sensitivity to fragmentation. iii) Despite these complexities, some consistent patterns emerged. For instance, the ranking order of landscapes in terms of functional connectivity was mostly consistent across the entire range of hypothetical species, indicating that simple landscape indices can potentially serve as valuable surrogates for functional connectivity. Yet such simplifications must be carefully evaluated in terms of the components of functional connectivity they actually predict