Locally Inertial Reference Frames in Lorentzian and Riemann-Cartan Spacetimes

In this paper we scrutinize the concept of locally inertial reference frames (LIRF) in Lorentzian and Riemann-Cartan spacetime structures. We present rigorous mathematical definitions for those objects, something that needs preliminary a clear mathematical distinction between the concepts of observers, reference frames, naturally adapted coordinate functions to a given reference frame and which properties may characterize an inertial reference frame (if any) in the Lorentzian and Riemann-Cartan structures. We hope to have clarified some eventual obscure issues associated to the concept of LIRF appearing in the literature, in particular the relationship between LIRFs in Lorentzian and Riemann-Cartan spacetimes and Einstein's most happy though, i.e., the equivalence principle.Comment: In this version a new reference has been added, some misprints and typos have been corrected and some few sentences in two remarks and in the conclusions have been changed for better intelligibilit

E-MDAV: A Framework for Developing Data-Intensive Web Applications

The ever-increasing adoption of innovative technologies, such as big data and cloud computing, provides significant opportunities for organizations operating in the IT domain, but also introduces considerable challenges. Such innovations call for development processes that better align with stakeholders needs and expectations. In this respect, this paper introduces a development framework based on the OMG's Model Driven Architecture (MDA) that aims to support the development lifecycle of data-intensive web applications. The proposed framework, named E-MDAV (Extended MDA-VIEW), defines a methodology that exploits a chain of model transformations to effectively cope with both forward- and reverse-engineering aspects. In addition, E-MDAV includes the specification of a reference architecture for driving the implementation of a tool that supports the various professional roles involved in the development and maintenance of data-intensive web applications. In order to evaluate the effectiveness of the proposed E-MDAV framework, a tool prototype has been developed. E-MDAV has then been applied to two different application scenarios and the obtained results have been compared with historical data related to the implementation of similar development projects, in order to measure and discuss the benefits of the proposed approach

Gravitation and Electromagnetism as Geometrical Objects of a Riemann-Cartan Spacetime Structure

In this paper we first show that any coupled system consisting of a gravitational plus a free electromagnetic field can be described geometrically in the sense that both Maxwell equations and Einstein equation having as source term the energy-momentum of the electromagnetic field can be derived from a geometrical Lagrangian proportional to the scalar curvature R of a particular kind of Riemann-Cartan spacetime structure, where those fields are identified as geometrical objects of the structure. We show moreover that the contorsion tensor of the particular Riemann-Cartan spacetime structure of our theory encodes the same information as the one contained in Chern-Simons term that is proportional to the spin density of the electromagnetic field. Next we show that by adding to the geometrical Lagrangian a term describing the interaction of a electromagnetic current with a general electromagnetic plus the gravitational field and a term describing the matter carrier of the current we get Maxwell equations with source term and Einstein equation having as source term the sum of the energy-momentum tensors of the electromagnetic and matter terms. Finally modeling by dust charged matter the carrier of the electromagnetic current we get the Lorentz force equation. Moreover, we prove that our theory is gauge invariant. We also briefly discuss our reasons for the present enterprise.Comment: In this version some few misprints have been corrected and a remark has changed place. Paper will appear in Advances in Applied Clifford Algebra

A Deep Learning Method for Automatic Identification of Drusen and Macular Hole from Optical Coherence Tomography

Deep Learning methods have become dominant in various fields of medical imaging, including ophthalmology. In this preliminary study, we investigated a method based on Convolutional Neural Network for the identification of drusen and macular hole from Optical Coherence Tomography scans with the aim to assist ophthalmologists in diagnosing and assessing retinal diseases

Oral contraceptives combined with interferon β in multiple sclerosis

Objective: To test the effect of oral contraceptives (OCs) in combination with interferon b (IFN-b) on disease activity in patients with relapsing-remitting multiple sclerosis (RRMS). Methods: One hundred fifty women with RRMS were randomized in a 1:1:1 ratio to receive IFNb-1a subcutaneously (SC) only (group 1), IFN-b-1a SC plus ethinylstradiol 20 mg and desogestrel 150 mg (group 2), or IFN-b-1a SC plus ethinylestradiol 40 mg and desogestrel 125 mg (group 3). The primary endpoint was the cumulative number of combined unique active (CUA) lesions on brain MRI at week 96. Secondary endpoints included MRI and clinical and safety measures. Results: The estimated number of cumulative CUA lesions at week 96 was 0.98 (95% confidence interval [CI] 0.81–1.14) in group 1, 0.84 (95% CI 0.66–1.02) in group 2, and 0.72 (95% CI 0.53–0.91) in group 3, with a decrease of 14.1% (p 5 0.24) and 26.5% (p 5 0.04) when comparing group 1 with groups 2 and 3, respectively. The number of patients with no gadoliniumenhancing lesions was greater in group 3 than in group 1 (p 5 0.03). No significant differences were detected in other secondary endpoints. IFN-b or OC discontinuations were equally distributed across groups. Conclusions: Our results translate the observations derived from experimental models to patients, supporting the anti-inflammatory effects of OCs with high-dose estrogens, and suggest possible directions for future research

Sequence based typing of Legionella pneumophila sg 1 isolated in nosocomial acquired infections in Apulia, Southern Italy

Objective. The present report aims to molecularly characterize seven clinical L. pneumophila (L. pn.) sg 1 isolated from noso- comial acquired infections in Apulia region, using the European Working Group on Legionella Infections (EWGLI), sequence- based typing (SBT) and amplified fragment length polymorphism (AFLP) protocols and to compare the identified sequence types (STs) with those available in the EWGLI database. Methods. In the period, January 2000 - December 2012, 151 cases (136 of community and 15 of nosocomial origin) of Legion- naires? disease were notified to the Regional Center for Epide- miology. With regard to nosocomial cases, 8 were confirmed by the isolation of Legionella spp. from respiratory secretions. These clinical isolates were characterized by amplified fragment length polymorphism (AFLP) and sequence-based typing (SBT), using the EWGLI standardized protocol. Results. The clinical isolates belong to ST42, ST23 and ST1. The AFLP confirms the SBT results. Comparing the STs herein detected with those already in the EWGLI SBT database, the 3 STs are frequent in other European countries. Conclusions. The molecular analysis demonstrates that the 3 STs are the most frequent in Italy and in Europe, supporting the hypothesis that some specific L. pn. sg 1 clones have gained widespread dissemination probably due to a common ecological niche. Further researches are required to investigate the potential changing incidence of STs and the fitness of emerging strains or clonal groups in environmental strains

Ensemble consensus: An unsupervised algorithm for anomaly detection in network security data

Unsupervised network traffic monitoring is of paramount importance in cyber security. It allows to detect suspicious events that are defined as non-normal and report or block them. In this work the Anomaly Consensus algorithm for unsupervised network analysis is presented. The algorithm aim is to fuse the three most important anomaly detection techniques for unsupervised detection of suspicious events. Tests are performed against the KDD Cup'99 dataset, one of the most famous supervised datasets for automatic intrusion detection created by DARPA. Accuracies reveal that Anomaly Consensus performs on-par with respect to state-of-the-art supervised learning techniques, ensuring high generalization power also in borderline tests when small amount of data (5%) is used for training and the rest is for validation and testing

Satellite-based Assessment of Climate Controls on US Burned Area

Climate regulates fire activity through the buildup and drying of fuels and the conditions for fire ignition and spread. Understanding the dynamics of contemporary climate-fire relationships at national and sub-national scales is critical to assess the likelihood of changes in future fire activity and the potential options for mitigation and adaptation. Here, we conducted the first national assessment of climate controls on US fire activity using two satellite-based estimates of monthly burned area (BA), the Global Fire Emissions Database (GFED, 1997 2010) and Monitoring Trends in Burn Severity (MTBS, 1984 2009) BA products. For each US National Climate Assessment (NCA) region, we analyzed the relationships between monthly BA and potential evaporation (PE) derived from reanalysis climate data at 0.5 resolution. US fire activity increased over the past 25 yr, with statistically significant increases in MTBS BA for entire US and the Southeast and Southwest NCA regions. Monthly PE was strongly correlated with US fire activity, yet the climate driver of PE varied regionally. Fire season temperature and shortwave radiation were the primary controls on PE and fire activity in the Alaska, while water deficit (precipitation PE) was strongly correlated with fire activity in the Plains regions and Northwest US. BA and precipitation anomalies were negatively correlated in all regions, although fuel-limited ecosystems in the Southern Plains and Southwest exhibited positive correlations with longer lead times (6 12 months). Fire season PE in creased from the 1980s 2000s, enhancing climate-driven fire risk in the southern and western US where PE-BA correlations were strongest. Spatial and temporal patterns of increasing fire season PE and BA during the 1990s 2000s highlight the potential sensitivity of US fire activity to climate change in coming decades. However, climatefire relationships at the national scale are complex, based on the diversity of fire types, ecosystems, and ignition sources within each NCA region. Changes in the seasonality or magnitude of climate anomalies are therefore unlikely to result in uniform changes in US fire activity

Continental-Scale Partitioning of Fire Emissions During the 1997 to 2001 El Niño/La Niña Period

During the 1997 to 1998 El Niño, drought conditions triggered widespread increases in fire activity, releasing CH_4 and CO_2 to the atmosphere. We evaluated the contribution of fires from different continents to variability in these greenhouse gases from 1997 to 2001, using satellite-based estimates of fire activity, biogeochemical modeling, and an inverse analysis of atmospheric CO anomalies. During the 1997 to 1998 El Niño, the fire emissions anomaly was 2.1 ± 0.8 petagrams of carbon, or 66 ± 24% of the CO_2 growth rate anomaly. The main contributors were Southeast Asia (60%), Central and South America (30%), and boreal regions of Eurasia and North America (10%)