Reactive direction control for a mobile robot: A locust-like control of escape direction emerges when a bilateral pair of model locust visual neurons are integrated

Locusts possess a bilateral pair of uniquely identifiable visual neurons that respond vigorously to the image of an approaching object. These neurons are called the lobula giant movement detectors (LGMDs). The locust LGMDs have been extensively studied and this has lead to the development of an LGMD model for use as an artificial collision detector in robotic applications. To date, robots have been equipped with only a single, central artificial LGMD sensor, and this triggers a non-directional stop or rotation when a potentially colliding object is detected. Clearly, for a robot to behave autonomously, it must react differently to stimuli approaching from different directions. In this study, we implement a bilateral pair of LGMD models in Khepera robots equipped with normal and panoramic cameras. We integrate the responses of these LGMD models using methodologies inspired by research on escape direction control in cockroaches. Using ‘randomised winner-take-all’ or ‘steering wheel’ algorithms for LGMD model integration, the khepera robots could escape an approaching threat in real time and with a similar distribution of escape directions as real locusts. We also found that by optimising these algorithms, we could use them to integrate the left and right DCMD responses of real jumping locusts offline and reproduce the actual escape directions that the locusts took in a particular trial. Our results significantly advance the development of an artificial collision detection and evasion system based on the locust LGMD by allowing it reactive control over robot behaviour. The success of this approach may also indicate some important areas to be pursued in future biological research

Collective versus single-particle effects in the optical spectra of finite electronic quantum systems

We study optical spectra of finite electronic quantum systems at frequencies smaller than the plasma frequency using a quasi-classical approach. This approach includes collective effects and enables us to analyze how the nature of the (single-particle) electron dynamics influences the optical spectra in finite electronic quantum systems. We derive an analytical expression for the low-frequency absorption coefficient of electro-magnetic radiation in a finite quantum system with ballistic electron dynamics and specular reflection at the boundaries: a two-dimensional electron gas confined to a strip of width a (the approach can be applied to systems of any shape and electron dynamics -- diffusive or ballistic, regular or irregular motion). By comparing with results of numerical computations using the random-phase approximation we show that our analytical approach provides a qualitative and quantitative understanding of the optical spectrum.Comment: 4 pages, 3 figure

C1q deficiency leads to the defective suppression of IFN-α in response to nucleoprotein containing immune complexes

Almost all humans with homozygous deficiency of C1q develop systemic lupus erythematosus (SLE). The precise cellular mechanism (s) by which C1q prevents the development of SLE remains unclear. In this study, we tested the role of C1q in the regulation of IFN-α induced by immune complexes (ICs) in vitro, as well as the consequences of lack of C1q in vivo. Our experiments revealed that C1q preferentially promotes the binding of SLE ICs to monocytes rather than plasmacytoid dendritic cells, but this inhibition was not due to the induction of inhibitory soluble factors. The presence of C1q also altered the trafficking of ICs within monocytes such that ICs persisted in early endosomes. In patients with C1q deficiency, serum and cerebrospinal fluid levels of IFN-α and IFN-γ–inducible protein-10 levels were elevated and strongly correlated with Ro autoantibodies, demonstrating the clinical significance of these observations. These studies therefore associate C1q deficiency with defective regulation of IFN-α and provide a better understanding of the cellular mechanisms by which C1q prevents the development of IC-stimulated autoimmunity

The impact of an observationally based surface emissivity dataset on the simulation of Microwave Sounding Unit Temperatures

Relatively few studies have attempted to simulate synthetic MSU temperatures with use of a radiation model. Most employ the simpler and computationally less-expensive method of applying a static, global-mean weighting function to three-dimensional profiles of atmospheric temperature. Both approaches require a number of key assumptions. One of the major assumptions relates to surface emissivity. To date, two different strategies have been used for prescribing surface emissivity values. The first assumes a fixed global surface emissivity, while the second specifies separate (time-invariant) emissivity values for land and ocean. In this research, we introduce space- and time-dependence to the specified emissivity fields, using recent observationally-based estimates of surface emissivity changes over 1988 to 2000. We use a radiative transfer code to explore the impact of this more complex treatment of surface emissivity. This sensitivity analysis is performed with monthly-mean fields of surface temperature, atmospheric temperature, and moisture taken from multiple reanalyses. Our goal is to quantify the possible impact of emissivity changes on global-scale estimates of tropospheric temperature trends (e.g., trends estimated from MSU channel 2 and MSU 2LT), and to document the sensitivity of synthetic MSU temperatures to a variety of input data and processing choices

Identification of external influences on temperatures in California

We use eight different observational datasets to estimate California-average temperature trends over 1950-1999. Observed results are compared to trends from a suite of control simulations of natural internal climate variability. Observed increases in annual-mean surface temperature are distinguishable from climate noise in some but not all observational datasets. The most robust results are large positive trends in mean and maximum daily temperatures in late winter/early spring, as well as increases in minimum daily temperatures from January to September. These trends are inconsistent with model-based estimates of natural internal climate variability, and thus require one or more external forcing agents to be explained. Our results suggest that the warming of Californian winters over the second half of the twentieth century is associated with human-induced changes in large-scale atmospheric circulation. We also hypothesize that the lack of a detectable increase in summertime maximum temperature arises from a cooling associated with large-scale irrigation. This cooling may have, until now, counteracted the warming induced by increasing greenhouse gases and urbanization effects

Volcanic Contribution to Decadal Changes in Tropospheric Temperature

Despite continued growth in atmospheric levels of greenhouse gases, global mean surface and tropospheric temperatures have shown slower warming since 1998 than previously. Possible explanations for the slow-down include internal climate variability, external cooling influences and observational errors. Several recent modelling studies have examined the contribution of early twenty-first-century volcanic eruptions to the muted surface warming. Here we present a detailed analysis of the impact of recent volcanic forcing on tropospheric temperature, based on observations as well as climate model simulations. We identify statistically significant correlations between observations of stratospheric aerosol optical depth and satellite-based estimates of both tropospheric temperature and short-wave fluxes at the top of the atmosphere. We show that climate model simulations without the effects of early twenty-first-century volcanic eruptions overestimate the tropospheric warming observed since 1998. In two simulations with more realistic volcanic influences following the 1991 Pinatubo eruption, differences between simulated and observed tropospheric temperature trends over the period 1998 to 2012 are up to 15% smaller, with large uncertainties in the magnitude of the effect. To reduce these uncertainties, better observations of eruption-specific properties of volcanic aerosols are needed, as well as improved representation of these eruption-specific properties in climate model simulations

Distinguishing emotional distress from mental disorder: A qualitative exploration of the Four-Dimensional Symptom Questionnaire (4DSQ).

BACKGROUND: Primary care clinicians see people experiencing the full range of mental health problems. Determining when symptoms reflect disorder is complex. The Four-Dimensional Symptom Questionnaire (4DSQ) uniquely distinguishes general distress from depressive and anxiety disorders. It may support diagnostic conversations and targeting of treatment. AIM: We aimed to explore peoples' experiences of completing the 4DSQ and their perceptions of their resulting score profile across distress, depression, anxiety and physical symptoms. DESIGN AND SETTING: A qualitative study conducted in the UK with people recruited from primary care and community settings. METHOD: Participants completed the 4DSQ then took part in semi-structured telephone interviews. They were interviewed about their experience of completing the 4DSQ, their perceptions of their scores across four dimensions, and the perceived utility if used with a clinician. Interviews were transcribed verbatim and data were analysed thematically. RESULTS: Twenty-four interviews were conducted. Most participants found the 4DSQ easy to complete and reported that scores across the four dimensions aligned well with their symptom experience. Distinct scores for distress, depression and anxiety appeared to support improved self-understanding. Some valued the opportunity to discuss their scores and provide relevant context. Many felt the use of the 4DSQ with clinicians would be helpful and likely to support treatment decisions, although some were concerned about time-limited consultations. CONCLUSION: Distinguishing general distress from depressive and anxiety disorders aligned well with people's experience of symptoms. Use of the 4DSQ as part of mental health consultations may support targeting of treatment and personalisation of care

The Community Climate System Model version 3 (CCSM3)

Author Posting. © American Meteorological Society 2006. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Climate 19 (2006): 2122–2143, doi:10.1175/JCLI3761.1.The Community Climate System Model version 3 (CCSM3) has recently been developed and released to the climate community. CCSM3 is a coupled climate model with components representing the atmosphere, ocean, sea ice, and land surface connected by a flux coupler. CCSM3 is designed to produce realistic simulations over a wide range of spatial resolutions, enabling inexpensive simulations lasting several millennia or detailed studies of continental-scale dynamics, variability, and climate change. This paper will show results from the configuration used for climate-change simulations with a T85 grid for the atmosphere and land and a grid with approximately 1° resolution for the ocean and sea ice. The new system incorporates several significant improvements in the physical parameterizations. The enhancements in the model physics are designed to reduce or eliminate several systematic biases in the mean climate produced by previous editions of CCSM. These include new treatments of cloud processes, aerosol radiative forcing, land–atmosphere fluxes, ocean mixed layer processes, and sea ice dynamics. There are significant improvements in the sea ice thickness, polar radiation budgets, tropical sea surface temperatures, and cloud radiative effects. CCSM3 can produce stable climate simulations of millennial duration without ad hoc adjustments to the fluxes exchanged among the component models. Nonetheless, there are still systematic biases in the ocean–atmosphere fluxes in coastal regions west of continents, the spectrum of ENSO variability, the spatial distribution of precipitation in the tropical oceans, and continental precipitation and surface air temperatures. Work is under way to extend CCSM to a more accurate and comprehensive model of the earth's climate system.We would like to acknowledge the substantial contributions to and support for the CCSM project from the National Science Foundation (NSF), the Department of Energy (DOE), the National Oceanic and Atmospheric Administration, and the National Aeronautics and Space Administration