Superconducting pairing symmetry in MoTe2_{2}

Topological superconductors have long been sought for their potential use in quantum computing. The type-II Weyl semimetal MoTe$_{2}$ is an obvious candidate, exhibiting a superconducting state below 500 mK at ambient pressure, but the question remains whether the pairing is conventional $s^{++}$ or topological $s^{+-}$. The application of external pressure favors the superconducting state in MoTe$_{2}$ and suppresses the structural transition from $1T'$ to $T_{d}$. The competition between the two structures leads to a mixed phase that strongly enhances the disorder present in the system, remarkably without affecting the superconducting transition temperature, in contrast to the expectation of $s^{+-}$ pairing superconductivity. Our thorough analysis of the electrical and Hall resistivities as a function of pressure yields the most accurate temperature-pressure phase diagram available to date for MoTe$_{2}$ and a detailed view of the relationship between disorder and superconductivity, supporting a conventional $s^{++}$ pairing symmetry

Magnetism and unconventional superconductivity in Cen_nMm_mIn3n+2m_{3n+2m} heavy-fermion crystals

We review magnetic, superconducting and non-Fermi-liquid properties of the structurally layered heavy-fermion compounds Ce$_n$M$_m$In$_{3n+2m}$ (M=Co, Rh, Ir). These properties suggest d-wave superconductivity and proximity to an antiferromagetic quantum-critical point.Comment: submitted 23rd International Conference on Low Temperature Physics (LT-23), Aug. 200

Optimal treatment allocations in space and time for on-line control of an emerging infectious disease

A key component in controlling the spread of an epidemic is deciding where, whenand to whom to apply an intervention.We develop a framework for using data to informthese decisionsin realtime.We formalize a treatment allocation strategy as a sequence of functions, oneper treatment period, that map up-to-date information on the spread of an infectious diseaseto a subset of locations where treatment should be allocated. An optimal allocation strategyoptimizes some cumulative outcome, e.g. the number of uninfected locations, the geographicfootprint of the disease or the cost of the epidemic. Estimation of an optimal allocation strategyfor an emerging infectious disease is challenging because spatial proximity induces interferencebetween locations, the number of possible allocations is exponential in the number oflocations, and because disease dynamics and intervention effectiveness are unknown at outbreak.We derive a Bayesian on-line estimator of the optimal allocation strategy that combinessimulation–optimization with Thompson sampling.The estimator proposed performs favourablyin simulation experiments. This work is motivated by and illustrated using data on the spread ofwhite nose syndrome, which is a highly fatal infectious disease devastating bat populations inNorth America

The Bivariate Normal Copula

We collect well known and less known facts about the bivariate normal distribution and translate them into copula language. In addition, we prove a very general formula for the bivariate normal copula, we compute Gini's gamma, and we provide improved bounds and approximations on the diagonal.Comment: 24 page

HopScotch - a low-power renewable energy base station network for rural broadband access

The provision of adequate broadband access to communities in sparsely populated rural areas has in the past been severely restricted. In this paper, we present a wireless broadband access test bed running in the Scottish Highlands and Islands which is based on a relay network of low-power base stations. Base stations are powered by a combination of renewable sources creating a low cost and scalable solution suitable for community ownership. The use of the 5~GHz bands allows the network to offer large data rates and the testing of ultra high frequency ``white space'' bands allow expansive coverage whilst reducing the number of base stations or required transmission power. We argue that the reliance on renewable power and the intelligent use of frequency bands makes this approach an economic green radio technology which can address the problem of rural broadband access

CeIr3_{3}Ge7_{7}: a local moment antiferromagnetic metal with extremely low ordering temperature

CeIr$_3$Ge$_7$ is an antiferromagnetic metal with a remarkably low ordering temperature $T_{\rm N}$ = 0.63 K, while most Ce-based magnets order between 2 and 15 K. Thermodynamic and transport properties as a function of magnetic field or pressure do not show signatures of Kondo correlations, interaction competition, or frustration, as had been observed in a few antiferromagnets with comparably low or lower $T_{\rm N}$. The averaged Weiss temperature measured below 10 K is comparable to $T_{\rm N}$ suggesting that the RKKY exchange coupling is very weak in this material. The unusually low $T_{\rm N}$ in CeIr$_3$Ge$_7$ can therefore be attributed to the large Ce-Ce bond length of about 5.7 {\AA}, which is about 1.5 {\AA} larger than in the most Ce-based intermetallic systems.Comment: 4 figure

Response of the Heavy-Fermion Superconductor CeCoIn5_5 to Pressure: Roles of Dimensionality and Proximity to a Quantum-Critical Point

We report measurements of the pressure-dependent superconducting transition temperature $T_c$ and electrical resistivity of the heavy-fermion compound CeCoIn$_5$. Pressure moves CeCoIn$_5$ away from its proximity to a quantum-critical point at atmospheric pressure. Experimental results are qualitatively consistent with theoretical predictions for strong-coupled, d-wave superconductivity in an anisotropic 3D superconductor.Comment: 9 pages, 5 figure

Recon 2.2: from reconstruction to model of human metabolism.

IntroductionThe human genome-scale metabolic reconstruction details all known metabolic reactions occurring in humans, and thereby holds substantial promise for studying complex diseases and phenotypes. Capturing the whole human metabolic reconstruction is an on-going task and since the last community effort generated a consensus reconstruction, several updates have been developed.ObjectivesWe report a new consensus version, Recon 2.2, which integrates various alternative versions with significant additional updates. In addition to re-establishing a consensus reconstruction, further key objectives included providing more comprehensive annotation of metabolites and genes, ensuring full mass and charge balance in all reactions, and developing a model that correctly predicts ATP production on a range of carbon sources.MethodsRecon 2.2 has been developed through a combination of manual curation and automated error checking. Specific and significant manual updates include a respecification of fatty acid metabolism, oxidative phosphorylation and a coupling of the electron transport chain to ATP synthase activity. All metabolites have definitive chemical formulae and charges specified, and these are used to ensure full mass and charge reaction balancing through an automated linear programming approach. Additionally, improved integration with transcriptomics and proteomics data has been facilitated with the updated curation of relationships between genes, proteins and reactions.ResultsRecon 2.2 now represents the most predictive model of human metabolism to date as demonstrated here. Extensive manual curation has increased the reconstruction size to 5324 metabolites, 7785 reactions and 1675 associated genes, which now are mapped to a single standard. The focus upon mass and charge balancing of all reactions, along with better representation of energy generation, has produced a flux model that correctly predicts ATP yield on different carbon sources.ConclusionThrough these updates we have achieved the most complete and best annotated consensus human metabolic reconstruction available, thereby increasing the ability of this resource to provide novel insights into normal and disease states in human. The model is freely available from the Biomodels database (http://identifiers.org/biomodels.db/MODEL1603150001)

Does gamma-aminobutyric acid (GABA) influence the development of chronic inflammation in rheumatoid arthritis?

<p>Abstract</p> <p>Background</p> <p>Recent studies have demonstrated a role for spinal p38 MAP kinase (MAPK) in the development of chronic inflammation and peripheral arthritis and a role for GABA in the inhibition of p38 MAPK mediated effects. Integrating these data suggests that GABA may play a role in downregulating mechanisms that lead to the production of proinflammatory agents such as interleukin-1, interleukin-6, and matrix metalloproteinase 3 – agents implicated in the pathogenesis of rheumatoid arthritis (RA). Genetic studies have also associated RA with members of the p38 MAPK pathway.</p> <p>Hypothesis</p> <p>We propose a hypothesis for an inefficient GABA signaling system that results in unchecked proinflammatory cytokine production via the p38 MAPK pathway. This model also supports the need for increasing research in the integration of immunology and neuroscience.</p