An internet of laboratory things

By creating “an Internet of Laboratory Things” we have built a blend of real and virtual laboratory spaces that enables students to gain practical skills necessary for their professional science and engineering careers. All our students are distance learners. This provides them by default with the proving ground needed to develop their skills in remotely operating equipment, and collaborating with peers despite not being co-located. Our laboratories accommodate state of the art research grade equipment, as well as large-class sets of off-the-shelf work stations and bespoke teaching apparatus. Distance to the student is no object and the facilities are open all hours. This approach is essential for STEM qualifications requiring development of practical skills, with higher efficiency and greater accessibility than achievable in a solely residential programme

Does poverty cause conflict? Isolating the causal origins of the conflict trap

Does poverty cause civil conflict? A considerable literature seeks to answer this question, yet concerns about reverse causality threaten the validity of extant conclusions. To estimate the impact of poverty on conflict and to determine whether the relationship between them is causal, it is necessary to identify a source of exogenous variation in poverty. We do this by introducing a robust instrument for poverty: a time-varying measure of international inequalities. We draw upon existing theories about the structural position of a country in the international economic network—specifically, the expectation that countries in the core tend to be wealthier and those on the periphery struggle to develop. This instrument is plausibly exogenous and satisfies the exclusion restriction, which suggests that it affects conflict only through its influence upon poverty. Instrumental variables probit regression is employed to demonstrate that the impact of poverty upon conflict appears to be causal

Should energy labels for washing machines be expanded to include a durability rating?

Washing machines are a key household appliance that can be found in the majority of UK homes. Over 2.5 million are sold in the UK every year and account for one of the highest material and production impacts of householder products in the UK (WRAP, 2011). Energy efficiency ratings are provided as a method for consumers to make an informed purchasing decision and were brought in by EU legislation to reduce energy use and enable users to reduce running costs, as it is known that the greater environmental impact of a washing machine is during use. From 2014, all washing machines sold must be at a minimum A rated, with ratings increasing to A+++. However, under this current labelling system the embodied impacts and durability of the machines are ignored. Through semi-structured interviews with consumers, manufacturers and distributors, this paper explores different perceptions of longevity and expectations of performance and durability. The paper explores whether energy labels should be expanded to include durability information, as this could enable consumers to make a decision based not only on cost and energy efficiency but also on expected lifespan. Existing manufacturer’s guarantees may give an indication of the expected durability of the product and this is investigated to explore if there is a positive correlation. The findings will further discuss the potential impacts of providing durability information and how this could enable manufacturers and consumers to shift towards a low material and energy future

An investigative study of a spectrum-matching imaging system Final report

Evaluation system for classification of remote objects and materials identified by solar and thermal radiation emissio

Hall drift of axisymmetric magnetic fields in solid neutron-star matter

Hall drift, i. e., transport of magnetic flux by the moving electrons giving rise to the electrical current, may be the dominant effect causing the evolution of the magnetic field in the solid crust of neutron stars. It is a nonlinear process that, despite a number of efforts, is still not fully understood. We use the Hall induction equation in axial symmetry to obtain some general properties of nonevolving fields, as well as analyzing the evolution of purely toroidal fields, their poloidal perturbations, and current-free, purely poloidal fields. We also analyze energy conservation in Hall instabilities and write down a variational principle for Hall equilibria. We show that the evolution of any toroidal magnetic field can be described by Burgers' equation, as previously found in plane-parallel geometry. It leads to sharp current sheets that dissipate on the Hall time scale, yielding a stationary field configuration that depends on a single, suitably defined coordinate. This field, however, is unstable to poloidal perturbations, which grow as their field lines are stretched by the background electron flow, as in instabilities earlier found numerically. On the other hand, current-free poloidal configurations are stable and could represent a long-lived crustal field supported by currents in the fluid stellar core.Comment: 8 pages, 5 figure panels; new version with very small correction; accepted by Astronomy & Astrophysic

Bias adjustment of satellite-based precipitation estimation using gauge observations: A case study in Chile

Satellite-based precipitation estimates (SPEs) are promising alternative precipitation data for climatic and hydrological applications, especially for regions where ground-based observations are limited. However, existing satellite-based rainfall estimations are subject to systematic biases. This study aims to adjust the biases in the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Cloud Classification System (PERSIANN-CCS) rainfall data over Chile, using gauge observations as reference. A novel bias adjustment framework, termed QM-GW, is proposed based on the nonparametric quantile mapping approach and a Gaussian weighting interpolation scheme. The PERSIANN-CCS precipitation estimates (daily, 0.04°×0.04°) over Chile are adjusted for the period of 2009–2014. The historical data (satellite and gauge) for 2009–2013 are used to calibrate the methodology; nonparametric cumulative distribution functions of satellite and gauge observations are estimated at every 1°×1° box region. One year (2014) of gauge data was used for validation. The results show that the biases of the PERSIANN-CCS precipitation data are effectively reduced. The spatial patterns of adjusted satellite rainfall show high consistency to the gauge observations, with reduced root-mean-square errors and mean biases. The systematic biases of the PERSIANN-CCS precipitation time series, at both monthly and daily scales, are removed. The extended validation also verifies that the proposed approach can be applied to adjust SPEs into the future, without further need for ground-based measurements. This study serves as a valuable reference for the bias adjustment of existing SPEs using gauge observations worldwide

Fermi surface instabilities in CeRh2Si2 at high magnetic field and pressure

We present thermoelectric power (TEP) studies under pressure and high magnetic field in the antiferromagnet CeRh2Si2 at low temperature. Under magnetic field, large quantum oscillations are observed in the TEP, S(H), in the antiferromagnetic phase. They suddenly disappear when entering in the polarized paramagnetic (PPM) state at Hc pointing out an important reconstruction of the Fermi surface (FS). Under pressure, S/T increases strongly of at low temperature near the critical pressure Pc, where the AF order is suppressed, implying the interplay of a FS change and low energy excitations driven by spin and valence fluctuations. The difference between the TEP signal in the PPM state above Hc and in the paramagnetic state (PM) above Pc can be explained by different FS. Band structure calculations at P = 0 stress that in the AF phase the 4f contribution at the Fermi level (EF) is weak while it is the main contribution in the PM domain. By analogy to previous work on CeRu2Si2, in the PPM phase of CeRh2Si2 the 4f contribution at EF will drop.Comment: 10 pages, 13 figure

Merging high-resolution satellite-based precipitation fields and point-scale rain gauge measurements-A case study in Chile

With high spatial-temporal resolution, Satellite-based Precipitation Estimates (SPE) are becoming valuable alternative rainfall data for hydrologic and climatic studies but are subject to considerable uncertainty. Effective merging of SPE and ground-based gauge measurements may help to improve precipitation estimation in both better resolution and accuracy. In this study, a framework for merging satellite and gauge precipitation data is developed based on three steps, including SPE bias adjustment, gauge observation gridding, and data merging, with the objective to produce high-quality precipitation estimates. An inverse-root-mean-square-error weighting approach is proposed to combine the satellite and gauge estimates that are in advance adjusted and gridded, respectively. The model is applied and tested with the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) estimates (daily, 0.04° × 0.04°) over Chile, for the 6 year period of 2009-2014. Daily observations from about 90% of collected gauges over the study area are used for model calibration; the rest of the gauged data are regarded as ground “truth” for validation. Evaluation results indicate high effectiveness of the model in producing high-resolution-precision precipitation data. Compared to reference data, the merged data (daily) show correlation coefficients, probabilities of detection, root-mean-square errors, and absolute mean biases that were consistently improved from the original PERSIANN-CCS estimates. The cross-validation evidences that the framework is effective in providing high-quality estimates even over nongauged satellite pixels. The same method can be applied globally and is expected to produce precipitation products in near real time by integrating gauge observations with satellite estimates