3,068 research outputs found
Optimization flow control -- I: Basic algorithm and convergence
We propose an optimization approach to flow control where the objective is to maximize the aggregate source utility over their transmission rates. We view network links and sources as processors of a distributed computation system to solve the dual problem using a gradient projection algorithm. In this system, sources select transmission rates that maximize their own benefits, utility minus bandwidth cost, and network links adjust bandwidth prices to coordinate the sources' decisions. We allow feedback delays to be different, substantial, and time varying, and links and sources to update at different times and with different frequencies. We provide asynchronous distributed algorithms and prove their convergence in a static environment. We present measurements obtained from a preliminary prototype to illustrate the convergence of the algorithm in a slowly time-varying environment. We discuss its fairness property
Leveraging Physical Layer Capabilites: Distributed Scheduling in Interference Networks with Local Views
In most wireless networks, nodes have only limited local information about
the state of the network, which includes connectivity and channel state
information. With limited local information about the network, each node's
knowledge is mismatched; therefore, they must make distributed decisions. In
this paper, we pose the following question - if every node has network state
information only about a small neighborhood, how and when should nodes choose
to transmit? While link scheduling answers the above question for
point-to-point physical layers which are designed for an interference-avoidance
paradigm, we look for answers in cases when interference can be embraced by
advanced PHY layer design, as suggested by results in network information
theory.
To make progress on this challenging problem, we propose a constructive
distributed algorithm that achieves rates higher than link scheduling based on
interference avoidance, especially if each node knows more than one hop of
network state information. We compare our new aggressive algorithm to a
conservative algorithm we have presented in [1]. Both algorithms schedule
sub-networks such that each sub-network can employ advanced
interference-embracing coding schemes to achieve higher rates. Our innovation
is in the identification, selection and scheduling of sub-networks, especially
when sub-networks are larger than a single link.Comment: 14 pages, Submitted to IEEE/ACM Transactions on Networking, October
201
ATP Synthase: Motoring to the Finish Line
Protonmotive force produced by the electron transport chain is harnessed by the rotary molecular nanomotor ATP synthase to generate ATP. In this issue of Cell, Adachi et al. (2007), in a dazzling display of technical sophistication, now disentangle the coupling between the mechanical force generated by rotation of the ATP synthase subunits and the chemical reactions that occur simultaneously at the enzyme's three catalytic sites
Combined EISCAT radar and optical multispectral and tomographic observations of black aurora
Black auroras are recognized as spatially well-defined regions within a uniform diffuse auroral background where the optical emission is significantly reduced. Black auroras typically appear post-magnetic midnight and during the substorm recovery phase, but not exclusively so. We report on the first combined multimonochromatic optical imaging, bistatic white-light TV recordings and incoherent scatter radar observations of black aurora by EISCAT of the phenomenon. From the relatively larger reduction in luminosity at 4278 Å than at 8446 Å we show that nonsheared black auroras are most probably not caused by downward directed electrical fields at low altitude. From the observations, we determine this by relating the height and intensity of the black aurora to precipitating particle energy within the surrounding background diffuse aurora. The observations are more consistent with an energy selective loss cone. Hence the mechanism causing black aurora is most probably active in the magnetosphere rather than close to Earth
Adaptive Langevin Sampler for Separation of t-Distribution Modelled Astrophysical Maps
We propose to model the image differentials of astrophysical source maps by
Student's t-distribution and to use them in the Bayesian source separation
method as priors. We introduce an efficient Markov Chain Monte Carlo (MCMC)
sampling scheme to unmix the astrophysical sources and describe the derivation
details. In this scheme, we use the Langevin stochastic equation for
transitions, which enables parallel drawing of random samples from the
posterior, and reduces the computation time significantly (by two orders of
magnitude). In addition, Student's t-distribution parameters are updated
throughout the iterations. The results on astrophysical source separation are
assessed with two performance criteria defined in the pixel and the frequency
domains.Comment: 12 pages, 6 figure
Anaerobic digestion in a multi-stage plug flow bioreactor: Revisiting an age-old process with modern molecular tools
To address knowledge gaps in the complex interacting microbial associations that underpin anaerobic digestion, a mesophilic (25°C) continuous-flow four-stage reactor was constructed to separate both spatially and temporally the component microbial groups. The reactor influent consisted of primary settled sewage sludge (PSSS) and the organic fraction of municipal solid waste (OFMSW). Chemical (volatile fatty acids, sulphate, sulphide, chemical oxygen demand, gas) and molecular analyses were made during an operation period of 15 months. Spatial separation of the microbial groups resulted in process instability where acidogenesis/acetogenesis produced an effluent with a pH between 2 and 4 that inhibited the subsequent catabolic steps. An organic loading rate of 6.5 g COD d-1 prevented reactor acidification but resulted in low biogas production (0.04-0.12 l biogas l-1 hydraulic load d-1). Fluctuations in chemical and molecular profiles/characteristics, which may have been due to the inherently heterogeneous PSSS and OFMSW, were recorded and these were countered by the development of a model medium. The medium was then used to: explore reactor efficacy; and study pertinent microbial diversity and functional interactions
Prevalence and risk factors of sarcopenia among adults living in nursing homes
Objectives: Sarcopenia is a progressive loss of skeletal muscle and muscle function, with significant healthand disability consequences for older adults. We aimed to evaluate the prevalence and risk factors ofsarcopenia among older residential aged care adults using the European Working Group on Sarcopeniain Older People (EWGSOP) criteria.Study design: A cross-sectional study design that assessed older people (n = 102, mean age 84.5 ± 8.2 years)residing in 11 long-term nursing homes in Australia.Main outcome measurements: Sarcopenia was diagnosed from assessments of skeletal mass index bybioelectrical impedance analysis, muscle strength by handheld dynamometer, and physical performanceby the 2.4 m habitual walking speed test. Secondary variables where collected to inform a risk factoranalysis.Results: Forty one (40.2%) participants were diagnosed as sarcopenic, 38 (95%) of whom were categorizedas having severe sarcopenia. Univariate logistic regression found that body mass index (BMI) (Oddsratio (OR) = 0.86; 95% confidence interval (CI) 0.78–0.94), low physical performance (OR = 0.83; 95% CI0.69–1.00), nutritional status (OR = 0.19; 95% CI 0.05–0.68) and sitting time (OR = 1.18; 95% CI 1.00–1.39)were predictive of sarcopenia. With multivariate logistic regression, only low BMI (OR = 0.80; 95% CI0.65–0.97) remained predictive.Conclusions: The prevalence of sarcopenia among older residential aged care adults is very high. Inaddition, low BMI is a predictive of sarcopenia
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