The JEM-EUSO Mission

JEM-EUSO is a science mission to explore extremes of the Universe. It observes the dark-side of the Earth and detects UV photons emitted from the extensive air shower caused by an extreme energy particle (about 10(exp 20) eV). Such a particle arrives almost straightly through our Milky Way Galaxy and is expected to allow us to trace the source location by its arrival direction. This will open the door to the new astronomy with charged particles. In its five years operation including the tilted mode, JEM-EUSO will detect at least 1,000 events with E>7 X 10(exp 19) eV and determine the energy spectrum of trans-GZK region with a statistical accuracy of several percent. JEM-EUSO is planned to be transported with HTV (H2 Transfer Vehicle) and attached to the Japanese Experiment Module/ Exposure Facility (JEM/EF) of International Space Station. JAXA has selected JEM-EUSO for one of the mission candidates of the second phase utilization of JEM/EF for the launch of early 2010s. One year-long phase-A study will be carried out under JAXA

Quantification of phytic acid in grains

This report describes the validation of a cost effective method for quantifying phytic acid in grains, namely, rice and wheat, using UV/Vis spectroscopy. Background information describing phytic acid and its impact on human biological systems and hence the importance of its analysis is included in this report. The validation method involved a range of tests to determine accuracy, precision and reproducibility of the method. Multiple sample matrices were used including standards and spiked samples as described in the validation plan and criteria in Appendix 2. The method employed a commercially available assay kit from Megazyme® and was found to give accurate reliable data according to the performance characteristics attained. This method also has the potential for transfer to laboratories with limited resources, in particular developing countries. It is applicable to survey scale and small batch analysis owing to its relatively low start up and running costs, fast analysis time and ease of instrument set up for each analytical batch compared to established methods using ion chromatography

A motif-based approach to network epidemics

Networks have become an indispensable tool in modelling infectious diseases, with the structure of epidemiologically relevant contacts known to affect both the dynamics of the infection process and the efficacy of intervention strategies. One of the key reasons for this is the presence of clustering in contact networks, which is typically analysed in terms of prevalence of triangles in the network. We present a more general approach, based on the prevalence of different four-motifs, in the context of ODE approximations to network dynamics. This is shown to outperform existing models for a range of small world networks

Mapping arctic tundra vegetation communities using field spectroscopy and multispectral satellite data in North Alaska, USA

The Arctic is currently undergoing intense changes in climate; vegetation composition and productivity are expected to respond to such changes. To understand the impacts of climate change on the function of Arctic tundra ecosystems within the global carbon cycle, it is crucial to improve the understanding of vegetation distribution and heterogeneity at multiple scales. Information detailing the fine-scale spatial distribution of tundra communities provided by high resolution vegetation mapping, is needed to understand the relative contributions of and relationships between single vegetation community measurements of greenhouse gas fluxes (e.g., ~1 m chamber flux) and those encompassing multiple vegetation communities (e.g., ~300 m eddy covariance measurements). The objectives of this study were: (1) to determine whether dominant Arctic tundra vegetation communities found in different locations are spectrally distinct and distinguishable using field spectroscopy methods; and (2) to test which combination of raw reflectance and vegetation indices retrieved from field and satellite data resulted in accurate vegetation maps and whether these were transferable across locations to develop a systematic method to map dominant vegetation communities within larger eddy covariance tower footprints distributed along a 300 km transect in northern Alaska. We showed vegetation community separability primarily in the 450-510 nm, 630-690 nm and 705-745 nm regions of the spectrum with the field spectroscopy data. This is line with the different traits of these arctic tundra communities, with the drier, often non-vascular plant dominated communities having much higher reflectance in the 450-510 nm and 630-690 nm regions due to the lack of photosynthetic material, whereas the low reflectance values of the vascular plant dominated communities highlight the strong light absorption found here. High classification accuracies of 92% to 96% were achieved using linear discriminant analysis with raw and rescaled spectroscopy reflectance data and derived vegetation indices. However, lower classification accuracies (~70%) resulted when using the coarser 2.0 m WorldView-2 data inputs. The results from this study suggest that tundra vegetation communities are separable using plot-level spectroscopy with hand-held sensors. These results also show that tundra vegetation mapping can be scaled from the plot level (<1 m) to patch level (<500 m) using spectroscopy data rescaled to match the wavebands of the multispectral satellite remote sensing. We find that developing a consistent method for classification of vegetation communities across the flux tower sites is a challenging process, given thespatial variability in vegetation communities and the need for detailed vegetation survey data for training and validating classification algorithms. This study highlights the benefits of using fine-scale field spectroscopy measurements to obtain tundra vegetation classifications for landscape analyses and use in carbon flux scaling studies. Improved understanding of tundra vegetation distributions will also provide necessary insight into the ecological processes driving plant community assemblages in Arctic environments

Shift of percolation thresholds for epidemic spread between static and dynamic small-world networks

The aim of the study was to compare the epidemic spread on static and dynamic small-world networks. The network was constructed as a 2-dimensional Watts-Strogatz model (500x500 square lattice with additional shortcuts), and the dynamics involved rewiring shortcuts in every time step of the epidemic spread. The model of the epidemic is SIR with latency time of 3 time steps. The behaviour of the epidemic was checked over the range of shortcut probability per underlying bond 0-0.5. The quantity of interest was percolation threshold for the epidemic spread, for which numerical results were checked against an approximate analytical model. We find a significant lowering of percolation thresholds for the dynamic network in the parameter range given. The result shows that the behaviour of the epidemic on dynamic network is that of a static small world with the number of shortcuts increased by 20.7 +/- 1.4%, while the overall qualitative behaviour stays the same. We derive corrections to the analytical model which account for the effect. For both dynamic and static small-world we observe suppression of the average epidemic size dependence on network size in comparison with finite-size scaling known for regular lattice. We also study the effect of dynamics for several rewiring rates relative to latency time of the disease.Comment: 13 pages, 6 figure

Geochemistry and health Kenyan stakeholder workshops 2022

This report summarises an exchange visit carried out by the British Geological Survey (BGS) to disseminate soil geochemical and public health data collated over the previous five years with partners from the University of Eldoret and Moi University to relevant stakeholders. A series of workshops provided a platform for the co-design of digital tool applications to ensure accessible data and to identify end-users with appropriate heads of agricultural and public health offices from 20 County governments. Workshop hubs were held in Kisii, Kisumu, and Eldoret between 23rd June and 3rd July 2022. This report describes a knowledge exchange visit to Kenya by BGS with partners at the University of Eldoret and Moi University leading on the dissemination of consortia data outputs and outcomes via coordinated workshops for leaders in agricultural and public health invited from each of 20 County governments (50+ attendees across three hubs), with additional practitioners familiar with the research-to-government-to-industry interaction in attendance. The geochemistry and public health data resulted from a comprehensive programme of data collection between 2016 and 2019 to inform the geochemical spatial influence on agricultural practices and for future use of a geochemical predictive model in determining the geospatial influence on non-communicable diseases (e.g. cancer, micronutrient deficiency). Additional focussed meetings with key stakeholders were undertaken to improve data uptake and outcomes, including the Kenyan Marine and Fisheries Research Institute, Kenyan Agricultural and Livestock Research Organisation and Kenya Forestry Research Institute. Background for the project collation of the data can be found at: https://www.bgs.ac.uk/geology-projects/geochemistry-and-health

The role of lithospheric flexure in the landscape evolution of the Wilkes Subglacial Basin and Transantarctic Mountains, East Antarctica

Reconstructions of the bedrock topography of Antarctica since the Eocene–Oligocene Boundary (ca. 34 Ma) provide important constraints for modelling Antarctic ice sheet evolution. This is particularly important in regions where the bedrock lies below sea level, since in these sectors the overlying ice sheet is thought to be most susceptible to past and future change. Here we use 3D flexural modelling to reconstruct the evolution of the topography of the Wilkes Subglacial Basin (WSB) and Transantarctic Mountains (TAM) in East Antarctica. We estimate the spatial distribution of glacial erosion beneath the East Antarctic Ice Sheet, and restore this material to the topography, which is also adjusted for associated flexural isostatic responses. We independently constrain our post‐34 Ma erosion estimates using offshore sediment stratigraphy interpretations. Our reconstructions provide a better‐defined topographic boundary condition for modelling early East Antarctic Ice Sheet history. We show that the majority of glacial erosion and landscape evolution occurred prior to 14 Ma, which we interpret to reflect more dynamic and erosive early ice sheet behaviour. In addition, we use closely‐spaced 2D flexural models to test previously proposed hypotheses for a flexural origin of the TAM and WSB. The pre‐34 Ma topography shows lateral variations along the length of the TAM and WSB that cannot be explained by uniform flexure along the front of the TAM. We show that some of these variations may be explained by additional flexural uplift along the south‐western flank of the WSB and the Rennick Graben in northern Victoria Land

Bias reduction in traceroute sampling: towards a more accurate map of the Internet

Traceroute sampling is an important technique in exploring the internet router graph and the autonomous system graph. Although it is one of the primary techniques used in calculating statistics about the internet, it can introduce bias that corrupts these estimates. This paper reports on a theoretical and experimental investigation of a new technique to reduce the bias of traceroute sampling when estimating the degree distribution. We develop a new estimator for the degree of a node in a traceroute-sampled graph; validate the estimator theoretically in Erdos-Renyi graphs and, through computer experiments, for a wider range of graphs; and apply it to produce a new picture of the degree distribution of the autonomous system graph.Comment: 12 pages, 3 figure