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

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

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

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

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