Comparison of Algorithms and Parameterisations for Infiltration into Organic-Covered Permafrost Soils

Infiltration into frozen and unfrozen soils is critical in hydrology, controlling active layer soil water dynamics and influencing runoff. Few Land Surface Models (LSMs) and Hydrological Models (HMs) have been developed, adapted or tested for frozen conditions and permafrost soils. Considering the vast geographical area influenced by freeze/thaw processes and permafrost, and the rapid environmental change observed worldwide in these regions, a need exists to improve models to better represent their hydrology. In this study, various infiltration algorithms and parameterisation methods, which are commonly employed in current LSMs and HMs were tested against detailed measurements at three sites in Canada’s discontinuous permafrost region with organic soil depths ranging from 0.02 to 3 m. Field data from two consecutive years were used to calibrate and evaluate the infiltration algorithms and parameterisations. Important conclusions include: (1) the single most important factor that controls the infiltration at permafrost sites is ground thaw depth, (2) differences among the simulated infiltration by different algorithms and parameterisations were only found when the ground was frozen or during the initial fast thawing stages, but not after ground thaw reaches a critical depth of 15 to 30 cm, (3) despite similarities in simulated total infiltration after ground thaw reaches the critical depth, the choice of algorithm influenced the distribution of water among the soil layers, and (4) the ice impedance factor for hydraulic conductivity, which is commonly used in LSMs and HMs, may not be necessary once the water potential driven frozen soil parameterisation is employed. Results from this work provide guidelines that can be directly implemented in LSMs and HMs to improve their application in organic covered permafrost soils

Multi Matrix Vector Coherent States

A class of vector coherent states is derived with multiple of matrices as vectors in a Hilbert space, where the Hilbert space is taken to be the tensor product of several other Hilbert spaces. As examples vector coherent states with multiple of quaternions and octonions are given. The resulting generalized oscillator algebra is briefly discussed. Further, vector coherent states for a tensored Hamiltonian system are obtained by the same method. As particular cases, coherent states are obtained for tensored Jaynes-Cummings type Hamiltonians and for a two-level two-mode generalization of the Jaynes-Cummings model.Comment: 24 page

A long-term hydrometeorological dataset (1993–2014) of a northern mountain basin: Wolf Creek Research Basin, Yukon Territory, Canada

A set of hydrometeorological data is presented in this paper, which can be used to characterize the hydrometeorology and climate of a subarctic mountain basin and has proven particularly useful for forcing hydrological models and assessing their performance in capturing hydrological processes in subarctic alpine environments. The forcing dataset includes daily precipitation, hourly air temperature, humidity, wind, solar and net radiation, soil temperature, and geographical information system data. The model performance assessment data include snow depth and snow water equivalent, streamflow, soil moisture, and water level in a groundwater well. This dataset was recorded at different elevation bands in Wolf Creek Research Basin, near Whitehorse, Yukon Territory, Canada, representing forest, shrub tundra, and alpine tundra biomes from 1993 through 2014. Measurements continue through 2018 and are planned for the future at this basin and will be updated to the data website. The database presented and described in this article is available for download at https://doi.org/10.20383/101.0113.</p

An evaluative baseline for geo-semantic relatedness and similarity

In geographic information science and semantics, the computation of semantic similarity is widely recognised as key to supporting a vast number of tasks in information integration and retrieval. By contrast, the role of geo-semantic relatedness has been largely ignored. In natural language processing, semantic relatedness is often confused with the more specific semantic similarity. In this article, we discuss a notion of geo-semantic relatedness based on Lehrer’s semantic fields, and we compare it with geo-semantic similarity. We then describe and validate the Geo Relatedness and Similarity Dataset (GeReSiD), a new open dataset designed to evaluate computational measures of geo-semantic relatedness and similarity. This dataset is larger than existing datasets of this kind, and includes 97 geographic terms combined into 50 term pairs rated by 203 human subjects. GeReSiD is available online and can be used as an evaluation baseline to determine empirically to what degree a given computational model approximates geo-semantic relatedness and similarity

A Survey of Volunteered Open Geo-Knowledge Bases in the Semantic Web

Over the past decade, rapid advances in web technologies, coupled with innovative models of spatial data collection and consumption, have generated a robust growth in geo-referenced information, resulting in spatial information overload. Increasing 'geographic intelligence' in traditional text-based information retrieval has become a prominent approach to respond to this issue and to fulfill users' spatial information needs. Numerous efforts in the Semantic Geospatial Web, Volunteered Geographic Information (VGI), and the Linking Open Data initiative have converged in a constellation of open knowledge bases, freely available online. In this article, we survey these open knowledge bases, focusing on their geospatial dimension. Particular attention is devoted to the crucial issue of the quality of geo-knowledge bases, as well as of crowdsourced data. A new knowledge base, the OpenStreetMap Semantic Network, is outlined as our contribution to this area. Research directions in information integration and Geographic Information Retrieval (GIR) are then reviewed, with a critical discussion of their current limitations and future prospects

Schmallenberg virus pathogenesis, tropism and interaction with the innate immune system of the host

Schmallenberg virus (SBV) is an emerging orthobunyavirus of ruminants associated with outbreaks of congenital malformations in aborted and stillborn animals. Since its discovery in November 2011, SBV has spread very rapidly to many European countries. Here, we developed molecular and serological tools, and an experimental in vivo model as a platform to study SBV pathogenesis, tropism and virus-host cell interactions. Using a synthetic biology approach, we developed a reverse genetics system for the rapid rescue and genetic manipulation of SBV. We showed that SBV has a wide tropism in cell culture and “synthetic” SBV replicates in vitro as efficiently as wild type virus. We developed an experimental mouse model to study SBV infection and showed that this virus replicates abundantly in neurons where it causes cerebral malacia and vacuolation of the cerebral cortex. These virus-induced acute lesions are useful in understanding the progression from vacuolation to porencephaly and extensive tissue destruction, often observed in aborted lambs and calves in naturally occurring Schmallenberg cases. Indeed, we detected high levels of SBV antigens in the neurons of the gray matter of brain and spinal cord of naturally affected lambs and calves, suggesting that muscular hypoplasia observed in SBV-infected lambs is mostly secondary to central nervous system damage. Finally, we investigated the molecular determinants of SBV virulence. Interestingly, we found a biological SBV clone that after passage in cell culture displays increased virulence in mice. We also found that a SBV deletion mutant of the non-structural NSs protein (SBVΔNSs) is less virulent in mice than wild type SBV. Attenuation of SBV virulence depends on the inability of SBVΔNSs to block IFN synthesis in virus infected cells. In conclusion, this work provides a useful experimental framework to study the biology and pathogenesis of SBV

Linking geographic vocabularies through WordNet

The linked open data (LOD) paradigm has emerged as a promising approach to structuring and sharing geospatial information. One of the major obstacles to this vision lies in the difficulties found in the automatic integration between heterogeneous vocabularies and ontologies that provides the semantic backbone of the growing constellation of open geo-knowledge bases. In this article, we show how to utilize WordNet as a semantic hub to increase the integration of LOD. With this purpose in mind, we devise Voc2WordNet, an unsupervised mapping technique between a given vocabulary and WordNet, combining intensional and extensional aspects of the geographic terms. Voc2WordNet is evaluated against a sample of human-generated alignments with the OpenStreetMap (OSM) Semantic Network, a crowdsourced geospatial resource, and the GeoNames ontology, the vocabulary of a large digital gazetteer. These empirical results indicate that the approach can obtain high precision and recall

The SSN ontology of the W3C semantic sensor network incubator group

The W3C Semantic Sensor Network Incubator group (the SSN-XG) produced an OWL 2 ontology to describe sensors and observations ? the SSN ontology, available at http://purl.oclc.org/NET/ssnx/ssn. The SSN ontology can describe sensors in terms of capabilities, measurement processes, observations and deployments. This article describes the SSN ontology. It further gives an example and describes the use of the ontology in recent research projects

Methods of asymptotic analysis in cavity quantum electrodynamics

The energy-level shift of a ground-state atom in front of a nondispersive dielectric half-space is calculated by quantizing the electric field by means of a normal-mode expansion and applying second-order perturbation theory to the electric-dipole Hamiltonian muE. It is shown that the contributions to this shift coming from traveling and from evanescent waves can be combined into a single expression which lends itself readily to asymptotic analysis for large atom-surface separations, while in the opposite asymptotic regime when the atom is close to the surface the combined expression is less convenient. Employing a Greens-function formalism instead of the normal-mode expansion leads directly to the combined formula, and in that case it is advantageous to be able to apply the same transformation backwards and split the energy shift into a sum of distinct contributions corresponding to different physical processes. The analysis serves to shed light on common sources of error in the literature and paves the way for the study of more complicated models in cavity quantum electrodynamics