166 research outputs found
Large-distance behaviour of the graviton two-point function in de Sitter spacetime
It is known that the graviton two-point function for the de Sitter invariant
"Euclidean" vacuum in a physical gauge grows logarithmically with distance in
spatially-flat de Sitter spacetime. We show that this logarithmic behaviour is
a gauge artifact by explicitly demonstrating that the same behaviour can be
reproduced by a pure-gauge two-point function.Comment: 19 pages, no figures, misprints and minor errors correcte
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Seismic retrofitting and health monitoring of school buildings of Cyprus
The vulnerability of existing buildings to seismic forces and their retrofitting is an international problem. The majority of structures in seismic-prone areas worldwide are structures that have been designed either without the consideration of seismic forces, or with previous codes of practice specifying lower levels of seismic forces. In Cyprus, after the three earthquakes that occurred in 1995, 1996, and 1999, the Cyprus State, acting in a pioneering way internationally, has decided the seismic retrofitting of all school buildings, taking into account the sensitivity of the society towards these structures, which house the future generation of the society. In this paper the overall assessment methodology is presented, along with details of the over 10 year ongoing retrofitting program of the school buildings of Cyprus, with emphasis on the description of the program and the development of a wireless monitoring system. In addition, mathematical models of selected school buildings are presented and comparison is made with in-situ measurement
On the scalar sector of the covariant graviton two-point function in de Sitter spacetime
We examine the scalar sector of the covariant graviton two-point function in
de Sitter spacetime. This sector consists of the pure-trace part and another
part described by a scalar field. We show that it does not contribute to
two-point functions of gauge-invariant quantities. We also demonstrate that the
long-distance growth present in some gauges is absent in this sector for a wide
range of gauge parameters.Comment: 15 pages, no figures, LaTeX, considerably shortene
Sulfur-Oxidizing Symbionts without Canonical Genes for Autotrophic CO2 Fixation
Many animals and protists depend on symbiotic sulfur-oxidizing bacteria as their main food source. These bacteria use energy from oxidizing inorganic sulfur compounds to make biomass autotrophically from CO2, serving as primary producers for their hosts. Here we describe a clade of nonautotrophic sulfur-oxidizing symbionts, “Candidatus Kentron,” associated with marine ciliates. They lack genes for known autotrophic pathways and have a carbon stable isotope fingerprint heavier than other symbionts from similar habitats. Instead, they have the potential to oxidize sulfur to fuel the uptake of organic compounds for heterotrophic growth, a metabolic mode called chemolithoheterotrophy that is not found in other symbioses. Although several symbionts have heterotrophic features to supplement primary production, in Kentron they appear to supplant it entirely.Since the discovery of symbioses between sulfur-oxidizing (thiotrophic) bacteria and invertebrates at hydrothermal vents over 40 years ago, it has been assumed that autotrophic fixation of CO2 by the symbionts drives these nutritional associations. In this study, we investigated “Candidatus Kentron,” the clade of symbionts hosted by Kentrophoros, a diverse genus of ciliates which are found in marine coastal sediments around the world. Despite being the main food source for their hosts, Kentron bacteria lack the key canonical genes for any of the known pathways for autotrophic carbon fixation and have a carbon stable isotope fingerprint that is unlike other thiotrophic symbionts from similar habitats. Our genomic and transcriptomic analyses instead found metabolic features consistent with growth on organic carbon, especially organic and amino acids, for which they have abundant uptake transporters. All known thiotrophic symbionts have converged on using reduced sulfur to gain energy lithotrophically, but they are diverse in their carbon sources. Some clades are obligate autotrophs, while many are mixotrophs that can supplement autotrophic carbon fixation with heterotrophic capabilities similar to those in Kentron. Here we show that Kentron bacteria are the only thiotrophic symbionts that appear to be entirely heterotrophic, unlike all other thiotrophic symbionts studied to date, which possess either the Calvin-Benson-Bassham or the reverse tricarboxylic acid cycle for autotrophy
Computed tomography-osteoabsorptiometry for assessing the density distribution of subchondral bone as a measure of long-term mechanical adaptation in individual joints
To estimate subchondral mineralisation patterns which represent the long-term loading history of individual joints, a method has been developed employing computed tomography (CT) which permits repeated examination of living joints. The method was tested on 5 knee, 3 sacroiliac, 3 ankle and 5 shoulder joints and then investigated with X-ray densitometry. A CT absorptiometric presentation and maps of the area distribution of the subchondral bone density areas were derived using an image analyser. Comparison of the results from both X-ray densitometry and CT-absorptiometry revealed almost identical pictures of distribution of the subchondral bone density. The method may be used to examine subchondral mineralisation as a measure of the mechanical adaptability of joints in the living subject
SPINN: Synergistic Progressive Inference of Neural Networks over Device and Cloud
Despite the soaring use of convolutional neural networks (CNNs) in mobile
applications, uniformly sustaining high-performance inference on mobile has
been elusive due to the excessive computational demands of modern CNNs and the
increasing diversity of deployed devices. A popular alternative comprises
offloading CNN processing to powerful cloud-based servers. Nevertheless, by
relying on the cloud to produce outputs, emerging mission-critical and
high-mobility applications, such as drone obstacle avoidance or interactive
applications, can suffer from the dynamic connectivity conditions and the
uncertain availability of the cloud. In this paper, we propose SPINN, a
distributed inference system that employs synergistic device-cloud computation
together with a progressive inference method to deliver fast and robust CNN
inference across diverse settings. The proposed system introduces a novel
scheduler that co-optimises the early-exit policy and the CNN splitting at run
time, in order to adapt to dynamic conditions and meet user-defined
service-level requirements. Quantitative evaluation illustrates that SPINN
outperforms its state-of-the-art collaborative inference counterparts by up to
2x in achieved throughput under varying network conditions, reduces the server
cost by up to 6.8x and improves accuracy by 20.7% under latency constraints,
while providing robust operation under uncertain connectivity conditions and
significant energy savings compared to cloud-centric execution.Comment: Accepted at the 26th Annual International Conference on Mobile
Computing and Networking (MobiCom), 202
Development of algorithms and software for forecasting, nowcasting and variability of TEC
Total Electron Content (TEC) is an important characteristic of the ionosphere relevant to communications. Unpredictable variability of the ionospheric parameters due to various disturbances limits the efficiencies of communications, radar and navigation systems. Therefore forecasting and nowcasting of TEC are important in the planning and operation of Earth-space and satellite-to-satellite communication systems. Near-Earth space processes are complex being highly nonlinear and time
varying with random variations in parameters where mathematical modeling is extremely difficult if not impossible. Therefore data driven models such as Neural Network (NN) based models are considered
and found promising in modeling such processes. In this paper the NN based METU-NN model is introduced to forecast TEC values for the intervals ranging from 1 to 24 h in advance. Forecast and nowcast of TEC values are also considered based on TEC database. Day-to-day and hour to-hour variability of TEC are also estimated using statistical methods. Another statistical approach based on the clustering technique is developed and a preprocessing approach is demonstrated for the forecast of ionospheric critical frequency foF2
Seismic behaviour of traditional timber frame walls: experimental results on unreinforced walls
Timber frame buildings are well known as an efficient seismic resistant structure
and they are used worldwide. Moreover, they have been specifically adopted in codes and
regulations during the XVIII and XIX centuries in the Mediterranean area. These structures
generally consist of exterior masonry walls with timber elements embedded which tie the
walls together and internal walls which have a timber frame with masonry infill and act as
shearwalls. In order to preserve these structureswhich characterizemany cities in theworld it
is important to better understand their behaviour under seismic actions. Furthermore, historic
technologies could be used even in modern constructions to build seismic resistant buildings
using more natural materials with lesser costs. Generally, different types of infill could be
applied to timber frame walls depending on the country, among which brick masonry, rubble
masonry, hay and mud. The focus of this paper is to study the seismic behaviour of the walls
considering different types of infill, specifically: masonry infill, lath and plaster and timber
frame with no infill. Static cyclic tests have been performed on unreinforced timber frame
walls in order to study their seismic capacity in terms of strength, stiffness, ductility and
energy dissipation. The tests showed how in the unreinforced condition, the infill is able to
guarantee a greater stiffness, ductility and ultimate capacity of the wall.The authors would like to acknowledge Eng. Filipe Ferreira and A.O.F. (Augusto Oliveira Ferreira &
C Lda.) for their expertise and collaboration in the construction of the wall specimens.
The first author would also like to acknowledge the Portuguese Science and Technology
Foundation (FCT) for its financial support through grant SFRH / BD / 61908 / 2009
Near-Earth space plasma modelling and forecasting
In the frame of the European COST 296 project (Mitigation of Ionospheric Effects on Radio Systems, MIERS)in the Working Package 1.3, new ionospheric models, prediction and forecasting methods and programs as well as ionospheric imaging techniques have been developed. They include (i) topside ionosphere and meso-scale irregularity models, (ii) improved forecasting methods for real time forecasting and for prediction of foF2,
M(3000)F2, MUF and TECs, including the use of new techniques such as Neurofuzzy, Nearest Neighbour, Cascade Modelling and Genetic Programming and (iii) improved dynamic high latitude ionosphere models through tomographic imaging and model validation. The success of the prediction algorithms and their improvement over
existing methods has been demonstrated by comparing predictions with later real data. The collaboration between different European partners (including interchange of data) has played a significant part in the development and validation of these new prediction and forecasting methods, programs and algorithms which can be applied to a variety of practical applications leading to improved mitigation of ionosphereic and space weather effects.Published255-2713.9. Fisica della magnetosfera, ionosfera e meteorologia spazialeJCR Journalope
Near-Earth space plasma modelling and forecasting
In the frame of the European COST 296 project (Mitigation of Ionospheric Effects on Radio Systems, MIERS)in the Working Package 1.3, new ionospheric models, prediction and forecasting methods and programs as well as ionospheric imaging techniques have been developed. They include (i) topside ionosphere and meso-scale irregularity models, (ii) improved forecasting methods for real time forecasting and for prediction of foF2,
M(3000)F2, MUF and TECs, including the use of new techniques such as Neurofuzzy, Nearest Neighbour, Cascade Modelling and Genetic Programming and (iii) improved dynamic high latitude ionosphere models through tomographic imaging and model validation. The success of the prediction algorithms and their improvement over
existing methods has been demonstrated by comparing predictions with later real data. The collaboration between different European partners (including interchange of data) has played a significant part in the development and validation of these new prediction and forecasting methods, programs and algorithms which can be applied to a variety of practical applications leading to improved mitigation of ionosphereic and space weather effects
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