1,710 research outputs found

    Woodshedding : a phase in recovery from psychosis

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    Acquisition Challenges of Autonomous Systems

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    The Department of Defense has stated publicly that future defense capabilities will depend strongly on autonomous systems;systems that make sophisticated judgments about the world and choose appropriate courses of action, and perhaps even adapt and learn over time. Developing and deploying such systems poses more than just a technical challenge in robotics and artificial intelligence;it also poses many challenges to the acquisition process and workforce. From cost estimation to sustainment planning, every aspect of acquisition will be affected. Test and evaluation, in particular, may require not only novel methodologies and resources, but organizational and process changes as well.Naval Postgraduate School Acquisition Research Progra

    Highly challenging balance program reduces fall rate in Parkinson disease

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    Published in final edited form as: J Neurol Phys Ther. 2016 January ; 40(1): 24–30. doi:10.1097/NPT.0000000000000111BACKGROUND AND PURPOSE: There is a paucity of effective treatment options to reduce falls in Parkinson disease (PD). Although a variety of rehabilitative approaches have been shown to improve balance, evidence of a reduction in falls has been mixed. Prior balance trials suggest that programs with highly challenging exercises had superior outcomes. We investigated the effects of a theory-driven, progressive, highly challenging group exercise program on fall rate, balance, and fear of falling. METHODS: Twenty-three subjects with PD participated in this randomized cross-over trial. Subjects were randomly allocated to 3 months of active balance exercises or usual care followed by the reverse. During the active condition, subjects participated in a progressive, highly challenging group exercise program twice weekly for 90 minutes. Outcomes included a change in fall rate over the 3-month active period and differences in balance (Mini-Balance Evaluation Systems Test [Mini-BESTest]), and fear of falling (Falls Efficacy Scale-International [FES-I]) between active and usual care conditions. RESULTS: The effect of time on falls was significant (regression coefficient = -0.015 per day, P < 0.001). The estimated rate ratio comparing incidence rates at time points 1 month apart was 0.632 (95% confidence interval, 0.524-0.763). Thus, there was an estimated 37% decline in fall rate per month (95% confidence interval, 24%-48%). Improvements were also observed on the Mini-BESTest (P = 0.037) and FES-I (P = 0.059). DISCUSSION AND CONCLUSIONS: The results of this study show that a theory-based, highly challenging, and progressive exercise program was effective in reducing falls, improving balance, and reducing fear of falling in PD.Video abstract available for more insights from the authors (see Supplemental Digital Content 1, http://links.lww.com/JNPT/A120). TRIAL REGISTRATION: ClinicalTrials.gov NCT02302144.This study was funded by the Boston Claude D. Pepper Older Americans Independence Center (NIH 5P30AG031679). Additional support was provided by the American Parkinson Disease Association (ADPA); ADPAMA Chapter. (NIH 5P30AG031679 - Boston Claude D. Pepper Older Americans Independence Center; American Parkinson Disease Association (ADPA); ADPAMA Chapter

    Generating samples of extreme winters to support climate adaptation

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    Recent extreme weather across the globe highlights the need to understand the potential for more extreme events in the present-day, and how such events may change with global warming. We present a methodology for more efficiently sampling extremes in future climate projections. As a proof-of-concept, we examine the UK’s most recent set of national Climate Projections (UKCP18). UKCP18 includes a 15-member perturbed parameter ensemble (PPE) of coupled global simulations, providing a range of climate projections incorporating uncertainty in both internal variability and forced response. However, this ensemble is too small to adequately sample extremes with very high return periods, which are of interest to policy-makers and adaptation planners. To better understand the statistics of these events, we use distributed computing to run three 1000-member initial-condition ensembles with the atmosphere-only HadAM4 model at 60km resolution on volunteers’ computers, taking boundary conditions from three distinct future extreme winters within the UKCP18 ensemble. We find that the magnitude of each winter extreme is captured within our ensembles, and that two of the three ensembles are conditioned towards producing extremes by the boundary conditions. Our ensembles contain several extremes that would only be expected to be sampled by a UKCP18 PPE of over 500 members, which would be prohibitively expensive with current supercomputing resource. The most extreme winters we simulate exceed those within UKCP18 by 0.85 K and 37% of the present-day average for UK winter means of daily maximum temperature and precipitation respectively. As such, our ensembles contain a rich set of multivariate, spatio-temporally and physically coherent samples of extreme winters with wide-ranging potential applications

    A generalised multi-factor deep learning electricity load forecasting model for wildfire-prone areas

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    This paper proposes a generalised and robust multi-factor Gated Recurrent Unit (GRU) based Deep Learning (DL) model to forecast electricity load in distribution networks during wildfire seasons. The flexible modelling methods consider data input structure, calendar effects and correlation-based leading temperature conditions. Compared to the regular use of instantaneous temperature, the Mean Absolute Percentage Error (MAPE) is decreased by 30.73% by using the proposed input feature selection and leading temperature relationships. Our model is generalised and applied to eight real distribution networks in Victoria, Australia, during the wildfire seasons of 2015-2020. We demonstrate that the GRU-based model consistently outperforms another DL model, Long Short-Term Memory (LSTM), at every step, giving average improvements in Mean Squared Error (MSE) and MAPE of 10.06% and 12.86%, respectively. The sensitivity to large-scale climate variability in training data sets, e.g. El Ni\~no or La Ni\~na years, is considered to understand the possible consequences for load forecasting performance stability, showing minimal impact. Other factors such as regional poverty rate and large-scale off-peak electricity use are potential factors to further improve forecast performance. The proposed method achieves an average forecast MAPE of around 3%, giving a potential annual energy saving of AU\$80.46 million for the state of Victoria

    Frontal Structure of the Antarctic Circumpolar Current in the South Indian Ocean

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    Using recently published atlas data [Olbers et al., 1992] and the Fine Resolution Antarctic Model (FRAM) [Webb et al., 1991], an investigation has been conducted into the structure of the frontal jets centered around the region of the islands of Crozet (46°27'S, 52°0'E) and Kerguelen (48°15'S, 69°10'E) in the south Indian Ocean. Geostrophic current velocities and transports were calculated from the temperature and salinity fields available from the atlas and compared with results from FRAM and previous studies. We have identified the Agulhas Return Front (ARF) and the Subtropical Front (STF), as well as the following fronts of the Antarctic Circumpolar Current (ACC): the Subantarctic Front (SAP), the Polar Front (PF), and the Southern ACC Front (SACCF), from temperature and salinity characteristics and from geostrophic currents. This analysis of model and atlas data indicates that the jets associated with the ARF, STF, and SAF are topograpliically steered into a unique frontal system north of the islands, having some of the largest temperature and salinity gradients anywhere in the world ocean. The frontal jet associated with the ARF is detectable up to 75°E and has associated with it several northward branching jets. The PF bifurcates in the region of the Ob'Lena (Conrad) seamount; subsurface and surface expressions are identified, separated by as much as 8° of latitude immediately west of the Kerguelen Plateau. The surface expression, carrying the bulk of the transport (~65 Sv), is steered through the col in the Kerguelen Plateau at 56°S, 6° south of the latitude normally associated with the PF at this meridian. On crossing the plateau it rejoins the subsurface expression. In the south, passing eastward along the margin of the Antarctic continent and through the Princess Elizabeth Trough, a frontal jet is identified transporting up to 35 Sv, believed to be the SACCF [Orsi et al., 1995], placing the southern extent of the ACC in the region at 67°S. Copyright 1996 by the American Geophysical Union

    Acetylsalicylic acid interferes with embryonic kidney growth and development by a prostaglandin-independent mechanism

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    AIM: To evaluate the effects of the non-selective, non-steroidal anti-inflammatory drug (NSAID) acetylsalicylic acid (ASA), on ex vivo embryonic kidney growth and development. METHODS: Pairs of fetal mouse kidneys at embryonic day 12.5 were cultured ex vivo in increasing concentrations of ASA (0.04-0.4 mg/mL) for up to 7 d. One organ from each pair was grown in control media and was used as the internal control for the experimental contralateral organ. In some experiments, organs were treated with ASA for 48 h and then transferred either to control media alone or control media containing 10 ÎĽmol/L prostaglandin E2 (PGE2) for a further 5 d. Fetal kidneys were additionally obtained from prostaglandin synthase 2 homozygous null or heterozygous (PTGS2-/- and PTGS2-/+) embryos and grown in culture. Kidney cross-sectional area was used to determine treatment effects on kidney growth. Whole-mount labelling to fluorescently detect laminin enabled crude determination of epithelial branching using confocal microscopy. RESULTS: Increasing ASA concentration (0.1, 0.2 and 0.4 mg/mL) significantly inhibited metanephric growth (P < 0.05). After 7 d of culture, exposure to 0.2 mg/mL and 0.4 mg/mL reduced organ size to 53% and 23% of control organ size respectively (P < 0.01). Addition of 10 ÎĽmol/L PGE2 to culture media after exposure to 0.2 mg/mL ASA for 48 h resulted in a return of growth area to control levels. Application of control media alone after cessation of ASA exposure showed no benefit on kidney growth. Despite the apparent recovery of growth area with 10 ÎĽmol/L PGE2, no obvious renal tubular structures were formed. The number of epithelial tips generated after 48 h exposure to ASA was reduced by 40% (0.2 mg/mL; P < 0.05) and 47% (0.4 mg/mL; P < 0.01). Finally, growth of PTGS2-/- and PTGS2+/- kidneys in organ culture showed no differences, indicating that PTGS2 derived PGE2 may at best have a minor role. CONCLUSION: ASA reduces early renal growth and development but the role of prostaglandins in this may be minor
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