Scalar-tensor theories, trace anomalies and the QCD-frame

We consider the quantum effects of matter fields in scalar-tensor theories and clarify the role of trace anomaly when switching between conformally related `frames'. We exploit the property that the couplings between the scalar and the gauge fields are not frame-invariant in order to define a `QCD-frame', where the scalar is not coupled to the gluons. We show that this frame is a natural generalization of the `Jordan frame' in the case of non-metric theories and that it is particularly convenient for gravitational phenomenology: test bodies have trajectories that are as close as possible to geodesics with respect to such a metric and equivalence principle violations are directly proportional to the scalar coupling parameters written in this frame. We show how RG flow and decoupling work in metric and non-metric theories. RG-running commutes with the operation of switching between frames at different scales. When only matter loops are considered, our analysis confirms that metricity is stable under radiative corrections and shows that approximate metricity is natural in a technical sense.Comment: 10 pages. Minor changes to the main text, appendix added. To appear on PR

Lead in Our Communities: A Chemical, Sociological and Public Health Analysis

Childhood lead poisoning is still of great concern within the United States, particularly in underprivileged communities that are often home to minority populations. Oneida County, New York has one of the highest instances of childhood lead poisoning per capita in the entire state. There are many pathways to lead exposure. This research looked to confirm the existence of a secondary lead smelter in Utica, New York through the analysis of soil samples and historical documents. It was hypothesized that the site of a former secondary lead smelter, and areas surrounding it, would exhibit high concentrations of lead. Soil samples were prepared for analysis using Environmental Protection Agency guidelines for the acid digestion of soil, after which atomic absorption spectroscopy was used to analyze the samples for concentration of lead content. Lead that is off put into the environment due to the operation of lead smelters shows secondary markers of increased cadmium concentration. The Cornell Nutrient Analysis Laboratory (CNAL) provided secondary analysis of all samples for lead and cadmium concentrations. The historical and chemical findings support the existence of a former lead smelter in downtown Utica, New York. This research has significant implications. One of the largest municipal housing complexes in the city of Utica, New York was located adjacent to the lot of the smelter, with the two coexisting for nine years. Examining various pathways to lead exposure is necessary to inform and shape the response to the public health issue of lead poisoning

Leave-one-out prediction error of systolic arterial pressure time series under paced breathing

In this paper we show that different physiological states and pathological conditions may be characterized in terms of predictability of time series signals from the underlying biological system. In particular we consider systolic arterial pressure time series from healthy subjects and Chronic Heart Failure patients, undergoing paced respiration. We model time series by the regularized least squares approach and quantify predictability by the leave-one-out error. We find that the entrainment mechanism connected to paced breath, that renders the arterial blood pressure signal more regular, thus more predictable, is less effective in patients, and this effect correlates with the seriousness of the heart failure. The leave-one-out error separates controls from patients and, when all orders of nonlinearity are taken into account, alive patients from patients for which cardiac death occurred

Redundant variables and Granger causality

We discuss the use of multivariate Granger causality in presence of redundant variables: the application of the standard analysis, in this case, leads to under-estimation of causalities. Using the un-normalized version of the causality index, we quantitatively develop the notions of redundancy and synergy in the frame of causality and propose two approaches to group redundant variables: (i) for a given target, the remaining variables are grouped so as to maximize the total causality and (ii) the whole set of variables is partitioned to maximize the sum of the causalities between subsets. We show the application to a real neurological experiment, aiming to a deeper understanding of the physiological basis of abnormal neuronal oscillations in the migraine brain. The outcome by our approach reveals the change in the informational pattern due to repetitive transcranial magnetic stimulations.Comment: 4 pages, 5 figures. Accepted for publication in Physical Review

A Cognitive Social IoT Approach for Smart Energy Management in a Real Environment

Energy usage inside buildings is a critical problem, especially considering high loads such as Heating, Ventilation and Air Conditioning (HVAC) systems: around 50% of the buildings’ energy demand resides in HVAC usage which causes a significant waste of energy resources due to improper uses. Usage awareness and efficient management have the potential to reduce related costs. However, strict saving policies may contrast with users’ comfort. In this sense, this paper proposes a multi-user multi-room smart energy management approach where a trade-off between the energy cost and the users’ thermal comfort is achieved. The proposed user-centric approach takes advantage of the novel paradigm of the Social Internet of Things to leverage a social consciousness and allow automated interactions between objects. Accordingly, the system automatically obtains the thermal profiles of both rooms and users. All these profiles are continuously updated based on the system experience and are then analysed through an optimization model to drive the selection of the most appropriate working times for HVACs. Experimental results in a real environment demonstrated the cognitive behaviour of the system which can adapt to users’ needs and ensure an acceptable comfort level while at the same time reducing energy costs compared to traditional usage

Using a distributed Shapley-value based approach to ensure navigability in a social network of smart objects

The huge number of nodes that is expected to join the Internet of Things in the short term will add major scalability issues to several procedures. A recent promising approach to these issues is based on social networking solutions to allow objects to autonomously establish social relationships. Every object in the resulting Social IoT (SIoT) exchanges data with its friend objects in a distributed manner to avoid the need for centralized solutions to implement major functionalities, such as: node discovery, information search and trustworthiness management. However, the number and types of established friendship affects network navigability. This paper addresses this issue proposing an efficient, distributed and dynamic strategy for the objects to select the right friends for the benefit of the overall network connectivity. The proposed friendship selection model relies on a Shapley-value based algorithm mapping the friendship selection process in the SIoT onto the coalition formation problem in a corresponding cooperative game. The obtained results show that the proposed solution is able to ensure global navigability, measured in terms of average path length among two nodes in the network, by means of a distributed and wise selection of the number of friend objects a node has to handle

IoT Architecture for a sustainable tourism application in a smart city environment

In the past few years, the Smart Cities concept has become one of the main driving forces for the urban transition towards a low carbon environment, sustainable economy, andmobility. Tourism, as one of the fastest growing industries, is also an important generator of carbon emissions; therefore, the recently emerging sustainable tourism concept is envisioned as an important part of the Smart Cities paradigm.Within this context, the Internet-of-Things (IoT) concept is the key technological point for the development of smart urban environments through the use of aggregated data, integrated in a single decisional platform. This paper performs the first analysis on the feasibility of the use of an IoT approach and proposes a specific architecture for a sustainable tourism application. The architecture is tailored for the optimisation of the movement of cruise ship tourists in the city of Cagliari (Italy), by taking into consideration factors such as transport information and queue waiting times. A first set of simulations is performed using 67-point of interest, real transportation data, and an optimisation algorithm

How to exploit the Social Internet of Things: Query Generation Model and Device Profiles’ Dataset

The future Internet of Things (IoT) will be characterized by an increasing number of object-to-object interactions for the implementation of distributed applications running in smart environments. The Social IoT (SIoT) is one of the possible paradigms that is proposed to make the objects’ interactions easier by facilitating the search of services and the management of objects’ trustworthiness. In this scenario, we address the issue of modeling the queries that are generated by the objects when fulfilling applications’ requests that could be provided by any of the peers in the SIoT. To this, the defined model takes into account the objects’ major features in terms of typology and associated functionalities, and the characteristics of the applications. We have then generated a dataset, by extracting objects’ information and positions from the city of Santander in Spain. We have classified all the available devices according to the FIWARE Data Models, so as to enable the portability of the dataset among different platforms. The dataset and the proposed query generation model are made available to the research community to study the navigability of the SIoT network, with an application also to other IoT networks. Experimental analyses have also been conducted, which give some key insights on the impact of the query model parameters on the average number of hops needed for each search

Holographic neutrino transport in dense strongly-coupled matter

A (toy) model for cold and luke-warm strongly-coupled nuclear matter at finite baryon density and isospin chemical potential is used to study neutrino transport. The complete charged current two-point correlators are computed in the strongly-coupled medium and their impact on neutrino transport is analyzed. The full result is compared with various approximations for the current correlators and the distributions, including the degenerate approximation, the hydrodynamic approximation as well as the diffusive approximation and we comment on their successes. Further improvements are discussed.Comment: 69 pages + Appendix; 27 figure