7,533 research outputs found
Green roofs in Melbourne - potential and practice
In Melbourne, green roofs are increasingly being included in the new and retrofitted buildings that claim to be ‘sustainable’ or ‘green’. This enthusiasm follows overseas experience where a variety of benefits have been recorded; these include a reduction in heating and cooling loads. This benefit is of particular importance because of the urgent need to reduce the greenhouse gas emissions associated with air conditioning. What is the potential for such savings and to what extent are some of the existing green roofs likely to achieve these benefits? This paper begins with a review of the overseas experience to reduce conditioning loads, particularly cooling, in temperate climates. Some observations on the potential and practice of green roofs in Melbourne is then presented. The results of measurements of plant canopy, soil and hard surface temperatures on two green roofs in the Melbourne Central Business District are discussed and future on-going work is outlined.<br /
A linear mixed effects model for seasonal forecasts of Arctic sea ice retreat
With sea ice cover declining in recent years, access to open Arctic waters has become a growing interest to numerous stakeholders. Access requires time for planning and preparation, which creates the need for accurate seasonal forecasts of summer sea ice characteristics. One important attribute is the timing of sea ice retreat, of which current statistical and dynamic sea ice models struggle to make accurate seasonal forecasts. We develop a linear mixed effects model to provide forecast of sea ice retreat over five major regions of the Arctic â Beaufort, Chukchi, East Siberian, Laptev, and Kara Seas. In this, the fixed effect â i.e. the mean influence of the atmosphere on sea ice retreat â is modeled using predictors that directly influence the dynamics or thermodynamics of sea ice, and random effects are grouped regionally to capture the local-scale effects on sea ice. The model exhibits very good skill in forecast of sea ice retreat at lead times of up to half a year over these regions
DRIVERS OF INFORMATION QUANTITY: THE CASE OF MERGER-ACQUISITION EVENTS
Business and research likewise acknowledge the potential and economic value of information exchange in social media (i.e. the quality and the quantity of user-generated content). While existing research has mainly focused on the analysis of the impact of online information exchange, little attention has been devoted to the drivers of information exchange in social media related to major business events. In this study we explore drivers of information exchange relating to such events. In the context of merger-acquisition events, we posit that firm visibility based on firm characteristics and information needs triggered by the event itself influence the information quantity generated in social media. We test these hypotheses using a rich data set that includes a wide range of social media types and platforms. Our results show that both firm visibility and information needs are driving information quantity in social media in the context of corporate actions. Both of these driving factors are highly significant in explaining the information quantity in social media
Automatic eduction and statistical analysis of coherent structures in the wall region of a confine plane
This paper describes a vortex detection algorithm used to expose and statistically characterize the
coherent flow patterns observable in the velocity vector fields measured by Particle Image
Velocimetry (PIV) in the impingement region of air curtains. The philosophy and the architecture of
this algorithm are presented. Its strengths and weaknesses are discussed. The results of a
parametrical analysis performed to assess the variability of the response of our algorithm to the 3
user-specified parameters in our eduction scheme are reviewed. The technique is illustrated in the
case of a plane turbulent impinging twin-jet with an opening ratio of 10. The corresponding jet
Reynolds number, based on the initial mean flow velocity U0 and the jet width e, is 14000. The
results of a statistical analysis of the size, shape, spatial distribution and energetic content of the
coherent eddy structures detected in the impingement region of this test flow are provided.
Although many questions remain open, new insights into the way these structures might form,
organize and evolve are given. Relevant results provide an original picture of the plane turbulent
impinging jet
A Bayesian Logistic Regression for Probabilistic Forecasts of the Minimum September Arctic Sea Ice Cover
This study introduces a Bayesian logistic regression framework that is capable of providing skillful probabilistic forecasts of Arctic sea ice cover, along with quantifying the attendant uncertainties. The presence or absence of ice (absence defined as ice concentration below 15%) is modeled using a categorical regression model, with atmospheric, oceanic, and sea ice covariates at 1â to 7âmonth lead times. The model parameters are estimated in a Bayesian framework, thus enabling the posterior predictive probabilities of the minimum sea ice cover and parametric uncertainty quantification. The model is fitted and validated to September minimum sea ice cover data from 1980 through 2018. Results show overall skillful forecasts of the minimum sea ice cover at all lead times, with higher skills at shorter lead times, along with a direct measure of forecast uncertainty to aide in assessing the reliability
Deep Eyes: Binocular Depth-from-Focus on Focal Stack Pairs
Human visual system relies on both binocular stereo cues and monocular
focusness cues to gain effective 3D perception. In computer vision, the two
problems are traditionally solved in separate tracks. In this paper, we present
a unified learning-based technique that simultaneously uses both types of cues
for depth inference. Specifically, we use a pair of focal stacks as input to
emulate human perception. We first construct a comprehensive focal stack
training dataset synthesized by depth-guided light field rendering. We then
construct three individual networks: a Focus-Net to extract depth from a single
focal stack, a EDoF-Net to obtain the extended depth of field (EDoF) image from
the focal stack, and a Stereo-Net to conduct stereo matching. We show how to
integrate them into a unified BDfF-Net to obtain high-quality depth maps.
Comprehensive experiments show that our approach outperforms the
state-of-the-art in both accuracy and speed and effectively emulates human
vision systems
Arctic sea ice melt onset favored by an atmospheric pressure pattern reminiscent of the North American-Eurasian Arctic pattern
The timing of melt onset in the Arctic plays a key role in the evolution of sea ice throughout Spring, Summer and Autumn. A major catalyst of early melt onset is increased downwelling longwave radiation, associated with increased levels of moisture in the atmosphere. Determining the atmospheric moisture pathways that are tied to increased downwelling longwave radiation and melt onset is therefore of keen interest. We employed Self Organizing Maps (SOM) on the daily sea level pressure for the period 1979â2018 over the Arctic during the melt season (AprilâJuly) and identified distinct circulation patterns. Melt onset dates were mapped on to these SOM patterns. The dominant moisture transport to much of the Arctic is enabled by a broad low pressure region stretching over Siberia and a high pressure over northern North America and Greenland. This configuration, which is reminiscent of the North American-Eurasian Arctic dipole pattern, funnels moisture from lower latitudes and through the Bering and Chukchi Seas. Other leading patterns are variations of this which transport moisture from North America and the Atlantic to the Central Arctic and Canadian Arctic Archipelago. Our analysis further indicates that most of the early and late melt onset timings in the Arctic are strongly related to the strong and weak emergence of these preferred circulation patterns, respectively
The effect of COVID-19 isolation measures on the cognition and mental health of people living with dementia: A rapid systematic review of one year of quantitative evidence
BACKGROUND:
COVID-19 prevention and control policies have entailed lockdowns and confinement. This study aimed to summarize the global research evidence describing the effect of COVID-19 isolation measures on the health of people living with dementia.
METHODS:
We searched Pubmed, PsycINFO and CINAHL up to 27th of February 2021 for peer-reviewed quantitative studies about the effects of isolation during COVID-19 on the cognitive, psychological and functional symptoms of people with dementia or mild cognitive impairment. The Joanna Briggs Institute critical appraisal tool was used to conduct the quality assessment. PROSPERO registration: CRD42021229259.
FINDINGS:
15 eligible papers were identified, examining a total of 6442 people with dementia. 13/15 studies investigated people living in the community and 2 in care homes. Out of 15 studies, 9 (60%) reported changes in cognition and 14 (93%) worsening or new onset of behavioral and psychological symptoms. Six studies (46%) reported a functional decline in daily activities in a variable proportion of the population analyzed.
INTERPRETATION:
COVID-19 isolation measures have damaged the cognitive and mental health of people with dementia across the world. It is urgent to issue guidance that balances infection control measures against the principles of non-maleficence to guarantee fair and appropriate care during pandemic times for this population
Sub-micron, Metal Gate, High-Đș Dielectric, Implant-free, Enhancement-mode III-V MOSFETs
The performance of 300nm, 500nm and 1ĂÂŒm metal gate, implant free, enhancement mode III-V MOSFETs are reported. Devices are realised using a 10nm MBE grown Ga2O3/(GaxGd1-x)2O3 high-ĂÂș (ĂÂș=20) dielectric stack grown upon a ĂÂŽ-doped AlGaAs/InGaAs/AlGaAs/GaAs heterostructure. Enhancement mode operation is maintained across the three reported gate lengths with a reduction in threshold voltage from 0.26 V to 0.08 V as the gate dimension is reduced from 1 ĂÂŒm to 300 nm. An increase in transconductance is also observed with reduced gate dimension. Maximum drain current of 420 ĂÂŒA/ĂÂŒm and extrinsic transconductance of 400 Ă”S/Ă”m are obtained from these devices. Gate leakage current of less than 100pA and subthreshold slope of 90 mV/decade were obtained for all gate lengths. These are believed to be the highest performance submicron enhancement mode III-V MOSFETs reported to date
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