93,391 research outputs found
Modelling transport energy demand : a socio-technical approach
Peer reviewedPostprin
A Case for Time Slotted Channel Hopping for ICN in the IoT
Recent proposals to simplify the operation of the IoT include the use of
Information Centric Networking (ICN) paradigms. While this is promising,
several challenges remain. In this paper, our core contributions (a) leverage
ICN communication patterns to dynamically optimize the use of TSCH (Time
Slotted Channel Hopping), a wireless link layer technology increasingly popular
in the IoT, and (b) make IoT-style routing adaptive to names, resources, and
traffic patterns throughout the network--both without cross-layering. Through a
series of experiments on the FIT IoT-LAB interconnecting typical IoT hardware,
we find that our approach is fully robust against wireless interference, and
almost halves the energy consumed for transmission when compared to CSMA. Most
importantly, our adaptive scheduling prevents the time-slotted MAC layer from
sacrificing throughput and delay
The role of type 4 phosphodiesterases in generating microdomains of cAMP: Large scale stochastic simulations
Cyclic AMP (cAMP) and its main effector Protein Kinase A (PKA) are critical for several aspects of neuronal function including synaptic plasticity. Specificity of synaptic plasticity requires that cAMP activates PKA in a highly localized manner despite the speed with which cAMP diffuses. Two mechanisms have been proposed to produce localized elevations in cAMP, known as microdomains: impeded diffusion, and high phosphodiesterase (PDE) activity. This paper investigates the mechanism of localized cAMP signaling using a computational model of the biochemical network in the HEK293 cell, which is a subset of pathways involved in PKA-dependent synaptic plasticity. This biochemical network includes cAMP production, PKA activation, and cAMP degradation by PDE activity. The model is implemented in NeuroRD: novel, computationally efficient, stochastic reaction-diffusion software, and is constrained by intracellular cAMP dynamics that were determined experimentally by real-time imaging using an Epac-based FRET sensor (H30). The model reproduces the high concentration cAMP microdomain in the submembrane region, distinct from the lower concentration of cAMP in the cytosol. Simulations further demonstrate that generation of the cAMP microdomain requires a pool of PDE4D anchored in the cytosol and also requires PKA-mediated phosphorylation of PDE4D which increases its activity. The microdomain does not require impeded diffusion of cAMP, confirming that barriers are not required for microdomains. The simulations reported here further demonstrate the utility of the new stochastic reaction-diffusion algorithm for exploring signaling pathways in spatially complex structures such as neurons
Ab initio atomistic thermodynamics and statistical mechanics of surface properties and functions
Previous and present "academic" research aiming at atomic scale understanding
is mainly concerned with the study of individual molecular processes possibly
underlying materials science applications. Appealing properties of an
individual process are then frequently discussed in terms of their direct
importance for the envisioned material function, or reciprocally, the function
of materials is somehow believed to be understandable by essentially one
prominent elementary process only. What is often overlooked in this approach is
that in macroscopic systems of technological relevance typically a large number
of distinct atomic scale processes take place. Which of them are decisive for
observable system properties and functions is then not only determined by the
detailed individual properties of each process alone, but in many, if not most
cases also the interplay of all processes, i.e. how they act together, plays a
crucial role. For a "predictive materials science modeling with microscopic
understanding", a description that treats the statistical interplay of a large
number of microscopically well-described elementary processes must therefore be
applied. Modern electronic structure theory methods such as DFT have become a
standard tool for the accurate description of individual molecular processes.
Here, we discuss the present status of emerging methodologies which attempt to
achieve a (hopefully seamless) match of DFT with concepts from statistical
mechanics or thermodynamics, in order to also address the interplay of the
various molecular processes. The new quality of, and the novel insights that
can be gained by, such techniques is illustrated by how they allow the
description of crystal surfaces in contact with realistic gas-phase
environments.Comment: 24 pages including 17 figures, related publications can be found at
http://www.fhi-berlin.mpg.de/th/paper.htm
A physical model of cell metabolism
Cell metabolism is characterized by three fundamental energy demands: to sustain cell maintenance, to trigger aerobic fermentation and to achieve maximum metabolic rate. The transition to aerobic fermentation and the maximum metabolic rate are currently understood based on enzymatic cost constraints. Yet, we are lacking a theory explaining the maintenance energy demand. Here we report a physical model of cell metabolism that explains the origin of these three energy scales. Our key hypothesis is that the maintenance energy demand is rooted on the energy expended by molecular motors to fluidize the cytoplasm and counteract molecular crowding. Using this model and independent parameter estimates we make predictions for the three energy scales that are in quantitative agreement with experimental values. The model also recapitulates the dependencies of cell growth with extracellular osmolarity and temperature. This theory brings together biophysics and cell biology in a tractable model that can be applied to understand key principles of cell metabolism
Green Cellular Networks: A Survey, Some Research Issues and Challenges
Energy efficiency in cellular networks is a growing concern for cellular
operators to not only maintain profitability, but also to reduce the overall
environment effects. This emerging trend of achieving energy efficiency in
cellular networks is motivating the standardization authorities and network
operators to continuously explore future technologies in order to bring
improvements in the entire network infrastructure. In this article, we present
a brief survey of methods to improve the power efficiency of cellular networks,
explore some research issues and challenges and suggest some techniques to
enable an energy efficient or "green" cellular network. Since base stations
consume a maximum portion of the total energy used in a cellular system, we
will first provide a comprehensive survey on techniques to obtain energy
savings in base stations. Next, we discuss how heterogeneous network deployment
based on micro, pico and femto-cells can be used to achieve this goal. Since
cognitive radio and cooperative relaying are undisputed future technologies in
this regard, we propose a research vision to make these technologies more
energy efficient. Lastly, we explore some broader perspectives in realizing a
"green" cellular network technologyComment: 16 pages, 5 figures, 2 table
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