A resilient and distributed near real-time traffic forecasting application for Fog computing environments

In this paper we propose an architecture for a city-wide traffic modeling and prediction service based on the Fog Computing paradigm. The work assumes an scenario in which a number of distributed antennas receive data generated by vehicles across the city. In the Fog nodes data is collected, processed in local and intermediate nodes, and finally forwarded to a central Cloud location for further analysis. We propose a combination of a data distribution algorithm, resilient to back-haul connectivity issues, and a traffic modeling approach based on deep learning techniques to provide distributed traffic forecasting capabilities. In our experiments, we leverage real traffic logs from one week of Floating Car Data (FCD) generated in the city of Barcelona by a road-assistance service fleet comprising thousands of vehicles. FCD was processed across several simulated conditions, ranging from scenarios in which no connectivity failures occurred in the Fog nodes, to situations with long and frequent connectivity outage periods. For each scenario, the resilience and accuracy of both the data distribution algorithm, and the learning methods were analyzed. Results show that the data distribution process running in the Fog nodes is resilient to back-haul connectivity issues and is able to deliver data to the Cloud location even in presence of severe connectivity problems. Additionally, the proposed traffic modeling and forecasting method exhibits better behavior when run distributed in the Fog instead of centralized in the Cloud, especially when connectivity issues occur that force data to be delivered out of order to the Cloud.This project is partially supported by the European Research Council (ERC), Spain under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 639595). It is also partially supported by the Ministry of Economy of Spain under contract TIN2015-65316-P and Generalitat de Catalunya, Spain under contract 2014SGR1051, by the ICREA Academia program, and by the BSC-CNS Severo Ochoa program (SEV-2015-0493). The authors gratefully acknowledge the Reial Automvil Club de Catalunya (RACC) for the dataset of Floating Car Data provided.Peer ReviewedPostprint (published version

Next Generation Optical Access Networks: from TDM to WDM

Postprint (author’s final draft

Improving Maritime Traffic Emission Estimations on Missing Data with CRBMs

Maritime traffic emissions are a major concern to governments as they heavily impact the Air Quality in coastal cities. Ships use the Automatic Identification System (AIS) to continuously report position and speed among other features, and therefore this data is suitable to be used to estimate emissions, if it is combined with engine data. However, important ship features are often inaccurate or missing. State-of-the-art complex systems, like CALIOPE at the Barcelona Supercomputing Center, are used to model Air Quality. These systems can benefit from AIS based emission models as they are very precise in positioning the pollution. Unfortunately, these models are sensitive to missing or corrupted data, and therefore they need data curation techniques to significantly improve the estimation accuracy. In this work, we propose a methodology for treating ship data using Conditional Restricted Boltzmann Machines (CRBMs) plus machine learning methods to improve the quality of data passed to emission models. Results show that we can improve the default methods proposed to cover missing data. In our results, we observed that using our method the models boosted their accuracy to detect otherwise undetectable emissions. In particular, we used a real data-set of AIS data, provided by the Spanish Port Authority, to estimate that thanks to our method, the model was able to detect 45% of additional emissions, of additional emissions, representing 152 tonnes of pollutants per week in Barcelona and propose new features that may enhance emission modeling.Comment: 12 pages, 7 figures. Postprint accepted manuscript, find the full version at Engineering Applications of Artificial Intelligence (https://doi.org/10.1016/j.engappai.2020.103793

Mapping of Mycobacterium tuberculosis Complex Genetic Diversity Profiles in Tanzania and Other African Countries

The aim of this study was to assess and characterize Mycobacterium tuberculosis complex (MTBC) genotypic diversity in Tanzania, as well as in neighbouring East and other several African countries. We used spoligotyping to identify a total of 293 M. tuberculosis clinical isolates (one isolate per patient) collected in the Bunda, Dar es Salaam, Ngorongoro and Serengeti areas in Tanzania. The results were compared with results in the SITVIT2 international database of the Pasteur Institute of Guadeloupe. Genotyping and phylogeographical analyses highlighted the predominance of the CAS, T, EAI, and LAM MTBC lineages in Tanzania. The three most frequent Spoligotype International Types (SITs) were: SIT21/CAS1-Kili (n = 76; 25.94%), SIT59/LAM11-ZWE (n = 22; 7.51%), and SIT126/EAI5 tentatively reclassified as EAI3-TZA (n = 18; 6.14%). Furthermore, three SITs were newly created in this study (SIT4056/EAI5 n = 2, SIT4057/T1 n = 1, and SIT4058/EAI5 n = 1). We noted that the East-African-Indian (EAI) lineage was more predominant in Bunda, the Manu lineage was more common among strains isolated in Ngorongoro, and the Central-Asian (CAS) lineage was more predominant in Dar es Salaam (p-value<0.0001). No statistically significant differences were noted when comparing HIV status of patients vs. major lineages (p-value = 0.103). However, when grouping lineages as Principal Genetic Groups (PGG), we noticed that PGG2/3 group (Haarlem, LAM, S, T, and X) was more associated with HIV-positive patients as compared to PGG1 group (Beijing, CAS, EAI, and Manu) (p-value = 0.03). This study provided mapping of MTBC genetic diversity in Tanzania (containing information on isolates from different cities) and neighbouring East African and other several African countries highlighting differences as regards to MTBC genotypic distribution between Tanzania and other African countries. This work also allowed underlining of spoligotyping patterns tentatively grouped within the newly designated EAI3-TZA lineage (remarkable by absence of spacers 2 and 3, and represented by SIT126) which seems to be specific to Tanzania. However, further genotyping information would be needed to confirm this specificity

Towards FAIR principles for research software

The FAIR Guiding Principles, published in 2016, aim to improve the findability, accessibility, interoperability and reusability of digital research objects for both humans and machines. Until now the FAIR principles have been mostly applied to research data. The ideas behind these principles are, however, also directly relevant to research software. Hence there is a distinct need to explore how the FAIR principles can be applied to software. In this work, we aim to summarize the current status of the debate around FAIR and software, as basis for the development of community-agreed principles for FAIR research software in the future. We discuss what makes software different from data with regard to the application of the FAIR principles, and which desired characteristics of research software go beyond FAIR. Then we present an analysis of where the existing principles can directly be applied to software, where they need to be adapted or reinterpreted, and where the definition of additional principles is required. Here interoperability has proven to be the most challenging principle, calling for particular attention in future discussions. Finally, we outline next steps on the way towards definite FAIR principles for research software

Adjunctive long-acting risperidone in patients with bipolar disorder who relapse frequently and have active mood symptoms

<p>Abstract</p> <p>Background</p> <p>The objective of this exploratory analysis was to characterize efficacy and onset of action of a 3-month treatment period with risperidone long-acting injection (RLAI), adjunctive to an individual's treatment regimen, in subjects with symptomatic bipolar disorder who relapsed frequently and had significant symptoms of mania and/or depression.</p> <p>Methods</p> <p>Subjects with bipolar disorder with ≥4 mood episodes in the past 12 months entered the open-label stabilization phase preceding a placebo-controlled, double-blind study. Subjects with significant depressive or manic/mixed symptoms at baseline were analyzed. Significant depressive symptoms were defined as Montgomery-Åsberg Depression Rating Scale (MADRS) ≥16 and Young Mania Rating Scale (YMRS) < 16; manic/mixed symptoms were YMRS ≥16 with any MADRS score. Subjects received open-label RLAI (25-50 mg every 2 weeks) for 16 weeks, adjunctive to a subject's individualized treatment for bipolar disorder (mood stabilizers, antidepressants, and/or anxiolytics). Clinical status was evaluated with the Clinical Global Impressions of Bipolar Disorder-Severity (CGI-BP-S) scale and changes on the MADRS and YMRS scales. Within-group changes were evaluated using paired <it>t </it>tests; categorical differences were assessed using Fisher exact test. No adjustment was made for multiplicity.</p> <p>Results</p> <p>162 subjects who relapsed frequently met criteria for significant mood symptoms at open-label baseline; 59/162 (36.4%) had depressive symptoms, 103/162 (63.6%) had manic/mixed symptoms. Most subjects (89.5%) were receiving ≥1 medication for bipolar disorder before enrollment. Significant improvements were observed for the total population on the CGI-BP-S, MADRS, and YMRS scales (p < .001 vs. baseline, all variables). Eighty-two (53.3%) subjects achieved remission at the week 16 LOCF end point. The subpopulation with depressive symptoms at open-label baseline experienced significant improvement on the CGI-BP-S and MADRS scales (p < .001 vs. baseline, all variables). Subjects with manic/mixed symptoms at baseline had significant improvements on the CGI-BP-S and YMRS scales (p < .001 vs. baseline, all variables). No unexpected tolerability findings were observed.</p> <p>Conclusions</p> <p>Exploratory analysis of changes in overall clinical status and depression/mania symptoms in subjects with symptomatic bipolar disorder who relapse frequently showed improvements in each of these areas after treatment with RLAI, adjunctive to a subject's individualized treatment. Prospective controlled studies are needed to confirm these findings.</p

Search for CP violation in D+→ϕπ+ and D+s→K0Sπ+ decays

A search for CP violation in D + → ϕπ + decays is performed using data collected in 2011 by the LHCb experiment corresponding to an integrated luminosity of 1.0 fb−1 at a centre of mass energy of 7 TeV. The CP -violating asymmetry is measured to be (−0.04 ± 0.14 ± 0.14)% for candidates with K − K + mass within 20 MeV/c 2 of the ϕ meson mass. A search for a CP -violating asymmetry that varies across the ϕ mass region of the D + → K − K + π + Dalitz plot is also performed, and no evidence for CP violation is found. In addition, the CP asymmetry in the D+s→K0Sπ+ decay is measured to be (0.61 ± 0.83 ± 0.14)%

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal