Landau-Ginzburg skeletons

We study the class of indecomposable two-dimensional Landau-Ginzburg theories with (2,2) supersymmetry and central charge c < 6 with the aim of classifying all such theories up to marginal deformations. Our results include cases overlooked in previous classifications. The results are rigorous for three or fewer fields and more generally are rigorous if we assume an extra bound. Numerics suggest that we have the complete set of indecomposable Landau-Ginzburg families with c<6. This set consists of 38 infinite families and a finite list of 418 sporadic cases. The basic tools are classic results of Kreuzer and Skarke on quasi-homogeneous isolated singularities and solutions to certain feasibility integer programming problems.Comment: 39 pages and tikz figures, three text files with LG charges included in submission; v2 fixes two sets of charge

The effects of variation in snow properties on passive microwave snow mass estimation

Estimating snow mass at continental scales is difficult, but important for understanding land-atmosphere interactions, biogeochemical cycles and the hydrology of the Northern latitudes. Remote sensing provides the only consistent global observations, butwith unknown errors. Wetest the theoretical performance of the Chang algorithm for estimating snow mass from passive microwave measurements using the Helsinki University of Technology (HUT) snow microwave emission model. The algorithm's dependence upon assumptions of fixed and uniform snow density and grainsize is determined, and measurements of these properties made at the Cold Land Processes Experiment (CLPX) Colorado field site in 2002–2003 used to quantify the retrieval errors caused by differences between the algorithm assumptions and measurements. Deviation from the Chang algorithm snow density and grainsize assumptions gives rise to an error of a factor of between two and three in calculating snow mass. The possibility that the algorithm performsmore accurately over large areas than at points is tested by simulating emission from a 25 km diameter area of snow with a distribution of properties derived from the snow pitmeasurements, using the Chang algorithm to calculate mean snow-mass from the simulated emission. The snowmass estimation froma site exhibiting the heterogeneity of the CLPX Colorado site proves onlymarginally different than that from a similarly-simulated homogeneous site. The estimation accuracy predictions are tested using the CLPX field measurements of snow mass, and simultaneous SSM/I and AMSR-E measurements

X-ray microcalorimetry for space

The X-ray microcalorimeter is an X-ray detector of potentially high energy resolution and quantum efficiency. The energy of incident X-rays is determined by measuring the resultant change in the resistance of a cooled semiconductor as an X-ray is incident on it. The history of X-ray microcalorimetry is reviewed, the current state of the art is placed in the context of contemporary X-ray detectors, and new X-ray detectors in the development stages. The performance of X-ray microcalorimeters is compared to other detectors. The principles of operation of microcalorimeters are discussed, and the relations between operating parameters established. The system devised and operated by the University of London microcalorimetry collaboration is described, and the future development of X-ray microcalorimetry considered. The design and implementation of a suite of computer programmes to analyse the data generated by the detector is described, and a space-based processing system defined. Results obtained with the detector operating at 100 mK in 1991 facing a Fe source are presented and analysed. A resolution of 316 eV is shown at 200mK, and 276 eV at 100mK. The absence of the expected improvement in resolution at the lower temperature is investigated. The microcalorimeter as an observational tool will require a space platform at a low temperature. Various low-temperature techniques are described, and the design and operation of the adiabatic demagnetisation refrigerator (ADR) used is described and modelled. The ADR is appraised as a means of cooling a space-based detector to 100mK, and a hypothetical system involving a 2-stage ADR is devised and modelled. One ADR operates between 100 mK and 1.0 K, and a second operates between 1.0 K and 4.0 K. The complete cooling system maintains a 100mK stage for 59 hours, with a recycle time of 17 hours. Replacing the high temperature ADR with a pumped helium tank cooling to 2.0 K increases the hold time to 80 hours, recycling in 3 minutes

A near real-time algorithm for flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management and flood forecasting. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, and in urban areas with reasonable accuracy

Near real-time flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, classifying 89% of flooded pixels correctly, with an associated false positive rate of 6%. Of the urban water pixels visible to TerraSAR-X, 75% were correctly detected, with a false positive rate of 24%. If all urban water pixels were considered, including those in shadow and layover regions, these figures fell to 57% and 18% respectively

Near real-time flood detection in urban and rural areas using high resolution Synthetic Aperture Radar images

A near real-time flood detection algorithm giving a synoptic overview of the extent of flooding in both urban and rural areas, and capable of working during night-time and day-time even if cloud was present, could be a useful tool for operational flood relief management. The paper describes an automatic algorithm using high resolution Synthetic Aperture Radar (SAR) satellite data that builds on existing approaches, including the use of image segmentation techniques prior to object classification to cope with the very large number of pixels in these scenes. Flood detection in urban areas is guided by the flood extent derived in adjacent rural areas. The algorithm assumes that high resolution topographic height data are available for at least the urban areas of the scene, in order that a SAR simulator may be used to estimate areas of radar shadow and layover. The algorithm proved capable of detecting flooding in rural areas using TerraSAR-X with good accuracy, and in urban areas with reasonable accuracy. The accuracy was reduced in urban areas partly because of TerraSAR-X’s restricted visibility of the ground surface due to radar shadow and layover

Optimal strategies for kiiking: active pumping to invert a swing

Kiiking is an extreme sport in which athletes alternate between standing and squatting to pump a standing swing till it is inverted and completes a rotation. A minimal model of the sport may be cast in terms of the control of an actively driven pendulum of varying length to determine optimal strategies. We show that an optimal control perspective, subject to known biological constraints, yields time-optimal control strategy similar to a greedy algorithm that aims to maximize the potential energy gain at the end of every cycle. A reinforcement learning algorithms with a simple reward is consistent with the optimal control strategy. When accounting for air drag, our theoretical framework is quantitatively consistent with experimental observations while pointing to the ultimate limits of kiiking performance

Using new and innovative technologies to assess clinical stage in early intervention youth mental health services: Evaluation study

Background: Globally there is increasing recognition that new strategies are required to reduce disability due to common mental health problems. As 75% of mental health and substance use disorders emerge during the teenage or early adulthood years, these strategies need to be readily accessible to young people. When considering how to provide such services at scale, new and innovative technologies show promise in augmenting traditional clinic-based services. Objective: The aim of this study was to test new and innovative technologies to assess clinical stage in early intervention youth mental health services using a prototypic online system known as the Mental Health eClinic (MHeC). Methods: The online assessment within the MHeC was compared directly against traditional clinician assessment within 2 Sydney-based youth-specific mental health services (headspace Camperdown and headspace Campbelltown). A total of 204 young people were recruited to the study. Eligible participants completed both face-to-face and online assessments, which were randomly allocated and counterbalanced at a 1-to-3 ratio. These assessments were (1) a traditional 45- to 60-minute headspace face-to-face assessment performed by a Youth Access Clinician and (2) an approximate 60-minute online assessment (including a self-report Web-based survey, immediate dashboard of results, and a video visit with a clinician). All assessments were completed within a 2-week timeframe from initial presentation. Results: Of the 72 participants who completed the study, 71% (51/72) were female and the mean age was 20.4 years (aged 16 to 25 years); 68% (49/72) of participants were recruited from headspace Camperdown and the remaining 32% (23/72) from headspace Campbelltown. Interrater agreement of participants’ stage, as determined after face-to-face assessment or online assessment, demonstrated fair agreement (kappa=.39, P\u3c.001) with concordance in 68% of cases (49/72). Among the discordant cases, those who were allocated to a higher stage by online raters were more likely to report a past history of mental health disorders (P=.001), previous suicide planning (P=.002), and current cannabis misuse (P=.03) compared to those allocated to a lower stage. Conclusions: The MHeC presents a new and innovative method for determining key clinical service parameters. It has the potential to be adapted to varied settings in which young people are connected with traditional clinical services and assist in providing the right care at the right tim

The effects of scene heterogeneity on soil moisture retrieval from passive microwave data

The s–x model of microwave emission from soil and vegetation layers is widely used to estimate soil moisture content from passive microwave observations. Its application to prospective satellite-based observations aggregating several thousand square kilometres requires understanding of the effects of scene heterogeneity. The effects of heterogeneity in soil surface roughness, soil moisture, water area and vegetation density on the retrieval of soil moisture from simulated single- and multi-angle observing systems were tested. Uncertainty in water area proved the most serious problem for both systems, causing errors of a few percent in soil moisture retrieval. Single-angle retrieval was largely unaffected by the other factors studied here. Multiple-angle retrievals errors around one percent arose from heterogeneity in either soil roughness or soil moisture. Errors of a few percent were caused by vegetation heterogeneity. A simple extension of the model vegetation representation was shown to reduce this error substantially for scenes containing a range of vegetation types