2,846 research outputs found
Upscaling the Use of Fallout Radionuclides in Soil Erosion and Sediment Budget Investigations: Addressing the Challenge
AbstractThe application of fallout radionuclides in soil erosion investigations and related sediment budget studies has provided a widely used tool for improving understanding of soil erosion and sediment transfer processes. However, most studies using fallout radionuclides undertaken to date have focussed on small areas. This focus on small areas reflects both the issues addressed and practical constraints associated with sample collection and analysis. Increasing acceptance of the important role of fine sediment in degrading aquatic habitats and in the transfer and fate of nutrients and contaminants within terrestrial and fluvial systems has emphasised the need to consider larger areas and the catchment or regional scale. The need to upscale existing approaches to the use of fallout radionuclides to larger areas represents an important challenge. This contribution provides a brief review of existing and potential approaches to upscaling the use of fallout radionuclides and presents two examples where such approaches have been successfully applied. These involve a national scale assessment of soil erosion rates in England and Wales based on 137Cs measurements and an investigation of the sediment budgets of three small/intermediate-size catchments in southern Italy
Objective pilling evaluation of wool fabrics
An objective pilling evaluation method based on the multi-scale two-dimensional dual-tree complex wavelet transform and linear discriminant function of Bayes\u27 Rule was developed. The surface fuzz and pills are identified from the high-frequency noise, fabric textures, fabric surface unevenness, and illuminative variation of a pilled fabric image by the two-dimensional dual-tree complex wavelet decomposition and reconstruction. The energies of the reconstructed subimages in six spatial orientations (±15º, ±45º, ±75º) are calculated as the elements of the pilling feature vector, whose dimension is reduced by principal component analysis. A linear discriminant function of Bayes\u27 Rule was used as a classifier to establish classification rules among the five pilling grades. A new pilled sample with the same physical construction can then be automatically assigned to one of the five pilling grades by the classification rules. A general evaluation of the proposed method was conducted using the SM50 woven, non-woven, and SM54 knitted standard pilling test image sets. The results suggest that the new method can successfully establish classification rules among the five pilling grade groups for each of the three standard pilling test image sets and should be applicable to practical objective pilling evaluation
The WISDOM Radar: Unveiling the Subsurface Beneath the ExoMars Rover and Identifying the Best Locations for Drilling
The search for evidence of past or present life on Mars is the principal objective of the 2020 ESA-Roscosmos ExoMars Rover mission. If such evidence is to be found anywhere, it will most likely be in the subsurface, where organic molecules are shielded from the destructive effects of ionizing radiation and atmospheric oxidants. For this reason, the ExoMars Rover mission has been optimized to investigate the subsurface to identify, understand, and sample those locations where conditions for the preservation of evidence of past life are most likely to be found. The Water Ice Subsurface Deposit Observation on Mars (WISDOM) ground-penetrating radar has been designed to provide information about the nature of the shallow subsurface over depth ranging from 3 to 10 m (with a vertical resolution of up to 3 cm), depending on the dielectric properties of the regolith. This depth range is critical to understanding the geologic evolution stratigraphy and distribution and state of subsurface H2O, which provide important clues in the search for life and the identification of optimal drilling sites for investigation and sampling by the Rover's 2-m drill. WISDOM will help ensure the safety and success of drilling operations by identification of potential hazards that might interfere with retrieval of subsurface samples
Recurrent Latent Variable Networks for Session-Based Recommendation
In this work, we attempt to ameliorate the impact of data sparsity in the
context of session-based recommendation. Specifically, we seek to devise a
machine learning mechanism capable of extracting subtle and complex underlying
temporal dynamics in the observed session data, so as to inform the
recommendation algorithm. To this end, we improve upon systems that utilize
deep learning techniques with recurrently connected units; we do so by adopting
concepts from the field of Bayesian statistics, namely variational inference.
Our proposed approach consists in treating the network recurrent units as
stochastic latent variables with a prior distribution imposed over them. On
this basis, we proceed to infer corresponding posteriors; these can be used for
prediction and recommendation generation, in a way that accounts for the
uncertainty in the available sparse training data. To allow for our approach to
easily scale to large real-world datasets, we perform inference under an
approximate amortized variational inference (AVI) setup, whereby the learned
posteriors are parameterized via (conventional) neural networks. We perform an
extensive experimental evaluation of our approach using challenging benchmark
datasets, and illustrate its superiority over existing state-of-the-art
techniques
Can multi-TeV (top and other) squarks be natural in gauge mediation?
We investigate whether multi-TeV (1-3 TeV) squarks can be natural in models
of gauge mediated SUSY breaking. The idea is that for some boundary condition
of the scalar (Higgs and stop) masses, the Higgs (mass), evaluated at the
renormalization scale GeV, is not very sensitive to (boundary
values of) the scalar masses (this has been called ``focussing'' in recent
literature). Then, the stop masses can be multi-TeV without leading to
fine-tuning in electroweak symmetry breaking. {\em Minimal} gauge mediation
does {\em not} lead to this focussing (for all values of and the
messenger scale): the (boundary value of) the Higgs mass is too small compared
to the stop masses. Also, in minimal gauge mediation, the gaugino masses are of
the same order as the scalar masses so that multi-TeV scalars implies multi-TeV
gauginos (especially gluino) leading to fine-tuning. We discuss ideas to {\em
increase} the Higgs mass relative to the stop masses (so that focussing can be
achieved) and also to {\em suppress} gaugino masses relative to scalar masses
(or to modify the gaugino mass relations) in {\em non-minimal} models of gauge
mediation -- then multi-TeV (top and other) squarks can be natural. Specific
models of gauge mediation which incorporate these ideas and thus have squarks
(and in some cases, the gluino) heavier than a TeV without resulting in
fine-tuning are also studied and their collider signals are contrasted with
those of other models which have multi-TeV squarks.Comment: LaTeX, 29 pages, 9 eps figures. Replacing an earlier version. In
version 3, some references and a minor comment have been added and typos have
been correcte
The effect of finite-range interactions in classical transport theory
The effect of scattering with non-zero impact parameters between consituents
in relativistic heavy ion collisions is investigated. In solving the
relativistic Boltzmann equation, the characteristic range of the collision
kernel is varied from approximately one fm to zero while leaving the mean-free
path unchanged. Modifying this range is shown to significantly affect spectra
and flow observables. The finite range is shown to provide effective
viscosities, shear, bulk viscosity and heat conductivity, with the viscous
coefficients being proportional to the square of the interaction range
Understanding Microbial Divisions of Labor
Microbial Biotechnolog
Some Relations between Twisted K-theory and E8 Gauge Theory
Recently, Diaconescu, Moore and Witten provided a nontrivial link between
K-theory and M-theory, by deriving the partition function of the Ramond-Ramond
fields of Type IIA string theory from an E8 gauge theory in eleven dimensions.
We give some relations between twisted K-theory and M-theory by adapting the
method of Diaconescu-Moore-Witten and Moore-Saulina. In particular, we
construct the twisted K-theory torus which defines the partition function, and
also discuss the problem from the E8 loop group picture, in which the
Dixmier-Douady class is the Neveu-Schwarz field. In the process of doing this,
we encounter some mathematics that is new to the physics literature. In
particular, the eta differential form, which is the generalization of the eta
invariant, arises naturally in this context. We conclude with several open
problems in mathematics and string theory.Comment: 23 pages, latex2e, corrected minor errors and typos in published
versio
Very static enforcement of dynamic policies
Security policies are naturally dynamic. Reflecting this, there has been a growing interest in studying information-flow properties which change during program execution, including concepts such as declassification, revocation, and role-change.
A static verification of a dynamic information flow policy, from a semantic perspective, should only need to concern itself with two things: 1) the dependencies between data in a program, and 2) whether those dependencies are consistent with the intended flow policies as they change over time. In this paper we provide a formal ground for this intuition. We present a straightforward extension to the principal flow-sensitive type system introduced by Hunt and Sands (POPL’06, ESOP’11) to infer both end-to-end dependencies and dependencies at intermediate points in a program. This allows typings to be applied to verification of both static and dynamic policies. Our extension preserves the principal type system’s distinguishing feature, that type inference is independent of the policy to be enforced: a single, generic dependency analysis (typing) can be used to verify many different dynamic policies of a given program, thus achieving a clean separation between (1) and (2).
We also make contributions to the foundations of dynamic information flow. Arguably, the most compelling semantic definitions for dynamic security conditions in the literature are phrased in the so-called knowledge-based style. We contribute a new definition of knowledge-based progress insensitive security for dynamic policies. We show that the new definition avoids anomalies of previous definitions and enjoys a simple and useful characterisation as a two-run style property
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