Archiving multi-epoch data and the discovery of variables in the near infrared

We present a description of the design and usage of a new synoptic pipeline and database model for time series photometry in the VISTA Data Flow System (VDFS). All UKIRT-WFCAM data and most of the VISTA main survey data will be processed and archived by the VDFS. Much of these data are multi-epoch, useful for finding moving and variable objects. Our new database design allows the users to easily find rare objects of these types amongst the huge volume of data being produced by modern survey telescopes. Its effectiveness is demonstrated through examples using Data Release 5 of the UKIDSS Deep Extragalactic Survey (DXS) and the WFCAM standard star data. The synoptic pipeline provides additional quality control and calibration to these data in the process of generating accurate light-curves. We find that 0.6+-0.1% of stars and 2.3+-0.6% of galaxies in the UKIDSS-DXS with K<15 mag are variable with amplitudes \Delta K>0.015 magComment: 30 pages, 31 figures, MNRAS, in press Minor changes from previous version due to refereeing and proof-readin

Integrated methodological framework fos assesing the risk of failure in water supply incorporating drought forecast. Case study: Andean regulated river basin

[EN] Hydroclimatic drought conditions can affect the hydrological services offered by mountain river basins causing severe impacts on the population, becoming a challenge for water resource managers in Andean river basins. This study proposes an integrated methodological framework for assessing the risk of failure in water supply, incorporating probabilistic drought forecasts, which assists in making decisions regarding the satisfaction of consumptive, non-consumptive and environmental requirements under water scarcity conditions. Monte Carlo simulation was used to assess the risk of failure in multiple stochastic scenarios, which incorporate probabilistic forecasts of drought events based on a Markov chains (MC) model using a recently developed drought index (DI). This methodology was tested in the Machángara river basin located in the south of Ecuador. Results were grouped in integrated satisfaction indexes of the system (DSIG). They demonstrated that the incorporation of probabilistic drought forecasts could better target the projections of simulation scenarios, with a view of obtaining realistic situations instead of optimistic projections that would lead to riskier decisions. Moreover, they contribute to more effective results in order to propose multiple alternatives for prevention and/or mitigation under drought conditions.This study was part of the doctoral thesis of Aviles A. at the Technical University of Valencia. This research was funded by the University of Cuenca through its Research Department (DIUC) and the Municipal public enterprise of telecommunications, drinking water, sewage and sanitation of Cuenca (ETAPA) through the projects: BIdentificacion de los procesos hidrometeorologicos que desencadenan inundaciones en la ciudad de Cuenca usando un radar de precipitacion" and "Ciclos meteorologicos y evapotranspiracion a lo largo de una gradiente altitudinal del Parque Nacional Cajas". The authors also thank INAMHI and the CBRM for providing the information for this study. The authors wish to thank the Spanish Ministry of Economy and Competitiveness for its financial support through the ERAS project (CTM2016-77804-P). We thank Angel Vazquez, who helped in the programming of the multiple simulations. Also we thank to the TropiSeca project.Avilés-Añazco, A.; Solera Solera, A.; Paredes Arquiola, J.; Pedro Monzonís, M. (2018). Integrated methodological framework fos assesing the risk of failure in water supply incorporating drought forecast. Case study: Andean regulated river basin. Water Resources Management. 32(4):1209-1223. https://doi.org/10.1007/s11269-017-1863-7S12091223324Andreu J, Capilla J, Sanchís E (1996) AQUATOOL, a generalized decision-support system for water-resources planning and operational management. J Hydrol 177(3-4):269–291. https://doi.org/10.1016/0022-1694(95)02963-XAndreu J, Solera A, Capilla J, Ferrer J (2007) Modelo SIMGES para simulación de cuencas. Manual de usuario v3. 00. Universidad Politécnica de Valencia, ValenciaAndreu J, Ferrer J, Perez MA et al (2013) Drought planning and management in the Júcar River Basin, Spain. In: Schwabe K et al (eds) Drought in arid and semi-arid regions. Springer science, Dordrecht, pp 237–249. https://doi.org/10.1007/978-94-007-6636-5_13Avilés A, Solera A (2013) Análisis de sistemas de recursos hídricos de la cuenca del rio Tomebamba en Ecuador, mediante modelos estocásticos y de gestión. In: Solera A, Paredes J, Andreu J (eds) Aplicaciones de sistemas soporte a la decisión en planificación y gestión integradas de cuencas hidrográficas. Marcombo, Barcelona, España pp 51–61Avilés A, Célleri R, Paredes J, Solera A (2015) Evaluation of Markov chain based drought forecasts in an Andean Regulated River basin using the skill scores RPS and GMSS. Water Resour Manag 29(6):1949–1963. https://doi.org/10.1007/s11269-015-0921-2Avilés A, Célleri R, Solera A, Paredes J (2016) Probabilistic forecasting of drought events using Markov chain-and Bayesian network-based models: a case study of an Andean Regulated River Basin. Water 8:1–16Barua S, Ng A, Perera B (2012) Drought assessment and forecasting: a case study on the Yarra River catchment in Victoria, Australia. Aust J Water Resour 15(2):95–108. https://doi.org/10.7158/W10-848.2012.15.2Bazaraa MS, Jarvis JJ, Sherali HD (2011) Linear programming and network flows, fourth Edi. John Wiley & Sons, New JerseyBrown C, Baroang KM, Conrad E et al (2010) IRI technical report 10–15, managing climate risk in water supply systems. Palisades, NYCancelliere A, Di Mauro G, Bonaccorso B, Rossi G (2007) Drought forecasting using the standardized precipitation index. Water Resour Manag 21(5):801–819. https://doi.org/10.1007/s11269-006-9062-yCancelliere A, Nicolosi V, Rossi G (2009) Assessment of drought risk in water supply systems in coping with drought risk in agriculture and water supply systems. Advances in natural and technological hazards research 26. In: Coping with drought risk in agriculture. Springer, pp 93–109. https://doi.org/10.1007/978-1-4020-9045-5_8Chen YD, Zhang Q, Xiao M, Singh VP, Zhang S (2016) Probabilistic forecasting of seasonal droughts in the Pearl River basin, China. Stoch Environ Res Risk Assess 30(7):2031–2040. https://doi.org/10.1007/s00477-015-1174-6Gong G, Wang L, Condon L, Shearman A, Lall U (2010) A simple framework for incorporating seasonal Streamflow forecasts into existing water resource management practices. JAWRA J Am Water Resour Assoc 46(3):574–585. https://doi.org/10.1111/j.1752-1688.2010.00435.xHaro D, Solera A, Paredes J, Andreu J (2014) Methodology for drought risk assessment in within-year regulated reservoir systems. Application to the Orbigo River system (Spain). Water Resour Manag 28(11):3801–3814. https://doi.org/10.1007/s11269-014-0710-3Haro-Monteagudo D, Solera A, Andreu J (2017) Drought early warning based on optimal risk forecasts in regulated river systems: application to the Jucar River basin (Spain). J Hydrol 544:36–45. https://doi.org/10.1016/j.jhydrol.2016.11.022Hashimoto T, Loucks DP, Stedinger JR (1982) Reliability, resiliency, and vulnerability criteria. Water Resour Res 18(1):14–20. https://doi.org/10.1029/WR018i001p00014Hwang Y, Carbone GJ (2009) Ensemble forecasts of drought indices using a conditional residual resampling technique. J Appl Meteorol Climatol 48(7):1289–1301. https://doi.org/10.1175/2009JAMC2071.1Kao S-C, Govindaraju RS (2010) A copula-based joint deficit index for droughts. J Hydrol 380(1-2):121–134. https://doi.org/10.1016/j.jhydrol.2009.10.029Keyantash JA, Dracup JA (2004) An aggregate drought index: assessing drought severity based on fluctuations in the hydrologic cycle and surface water storage. Water Resour Res 40(9):1–13. https://doi.org/10.1029/2003WR002610Khadr M (2016) Forecasting of meteorological drought using hidden Markov model (case study: the upper Blue Nile river basin, Ethiopia). Ain Shams Eng J 7(1):47–56. https://doi.org/10.1016/j.asej.2015.11.005Madadgar S, Moradkhani H (2013) A Bayesian framework for probabilistic seasonal drought forecasting. J Hydrometeorol 14(6):1685–1706. https://doi.org/10.1175/JHM-D-13-010.1Madadgar S, Moradkhani H (2014) Spatio-temporal drought forecasting within Bayesian networks. J Hydrol 512:134–146. https://doi.org/10.1016/j.jhydrol.2014.02.039Mahmoudzadeh H, Mahmoudzadeh H, Afshar M, Yousefi S (2016) Applying first-order Markov chains and SPI drought index to monitor and forecast drought in West Azerbaijan Province of Iran. Int J Geo Sci Environ Plan 1:44–53. 10.22034/ijgsep.2016.40669Mishra AK, Singh VP (2010) Review paper a review of drought concepts. J Hydrol 391(1-2):202–216. https://doi.org/10.1016/j.jhydrol.2010.07.012Nalbantis I, Tsakiris G (2009) Assessment of hydrological drought revisited. Water Resour Manag 23(5):881–897. https://doi.org/10.1007/s11269-008-9305-1Ochola WO, Kerkides P (2003) A Markov chain simulation model for predicting critical wet and dry spells in Kenya: Analysing rainfall events in the kano plains. Irrig Drain 52(4):327–342. https://doi.org/10.1002/ird.094Paulo AA, Pereira LS (2007) Prediction of SPI drought class transitions using Markov chains. Water Resour Manag 21(10):1813–1827. https://doi.org/10.1007/s11269-006-9129-9Phan TD, Smart JCR, Capon SJ, Hadwen WL, Sahin O (2016) Applications of Bayesian belief networks in water resource management: a systematic review. Environ Model Softw 85:98–111. https://doi.org/10.1016/j.envsoft.2016.08.006Pouget L, Roldán T, Gómez M et al (2015) Use of seasonal climate predictions in the water sector—preliminary results from the EUPORIAS project. In: Andreu J, Solera A, Paredes J et al (eds) Drought: research and science-policy interfacing. Taylor & Francis Group, London, UK, p 247Rossi G, Cancelliere A (2013) Managing drought risk in water supply systems in Europe: a review. Int J Water Resour Dev 29(2):272–289. https://doi.org/10.1080/07900627.2012.713848Rossi G, Caporali E, Garrote L (2012) Definition of risk indicators for reservoirs management optimization. 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Daily egg consumption in hyperlipidemic adults - Effects on endothelial function and cardiovascular risk

<p>Abstract</p> <p>Background</p> <p>Limiting consumption of eggs, which are high in cholesterol, is generally recommended to reduce risk of cardiovascular disease. However, recent evidence suggests that dietary cholesterol has limited influence on serum cholesterol or cardiac risk.</p> <p>Objective</p> <p>To assess the effects of egg consumption on endothelial function and serum lipids in hyperlipidemic adults.</p> <p>Methods</p> <p>Randomized, placebo-controlled crossover trial of 40 hyperlipidemic adults (24 women, 16 men; average age = 59.9 ± 9.6 years; weight = 76.3 ± 21.8 kilograms; total cholesterol = 244 ± 24 mg/dL). In the acute phase, participants were randomly assigned to one of the two sequences of a single dose of three medium hardboiled eggs and a sausage/cheese breakfast sandwich. In the sustained phase, participants were then randomly assigned to one of the two sequences of two medium hardboiled eggs and 1/2 cup of egg substitute daily for six weeks. Each treatment assignment was separated by a four-week washout period. Outcome measures of interest were endothelial function measured as flow mediated dilatation (FMD) and lipid panel.</p> <p>Results</p> <p>Single dose egg consumption had no effects on endothelial function as compared to sausage/cheese (0.4 ± 1.9 vs. 0.4 ± 2.4%; <it>p </it>= 0.99). Daily consumption of egg substitute for 6 weeks significantly improved endothelial function as compared to egg (1.0 ± 1.2% vs. -0.1 ± 1.5%; <it>p </it>< 0.01) and lowered serum total cholesterol (-18 ± 18 vs. -5 ± 21 mg/dL; <it>p </it>< 0.01) and LDL (-14 ± 20 vs. -2 ± 19 mg/dL; <it>p </it>= 0.01). Study results (positive or negative) are expressed in terms of change relative to baseline.</p> <p>Conclusions</p> <p>Egg consumption was found to be non-detrimental to endothelial function and serum lipids in hyperlipidemic adults, while egg substitute consumption was beneficial.</p

Search for large missing transverse momentum in association with one top-quark in proton-proton collisions at √s = 13 TeV with the ATLAS detector

This paper describes a search for events with one top-quark and large missing transverse momentum in the final state. Data collected during 2015 and 2016 by the ATLAS experiment from 13 TeV proton–proton collisions at the LHC corresponding to an integrated luminosity of 36.1 fb−1 are used. Two channels are considered, depending on the leptonic or the hadronic decays of the W boson from the top quark. The obtained results are interpreted in the context of simplified models for dark-matter production and for the single production of a vector-like T quark. In the absence of significant deviations from the Standard Model background expectation, 95% confidence-level upper limits on the corresponding production cross-sections are obtained and these limits are translated into constraints on the parameter space of the models considered

Correlated long-range mixed-harmonic fluctuations measured in pp, p+Pb and low-multiplicity Pb+Pb collisions with the ATLAS detector

For abstract see published article

Performance of top-quark and W -boson tagging with ATLAS in Run 2 of the LHC

The performance of identification algorithms (“taggers”) for hadronically decaying top quarks and W bosons in pp collisions at √s=13 TeV recorded by the ATLAS experiment at the Large Hadron Collider is presented. A set of techniques based on jet shape observables are studied to determine a set of optimal cut-based taggers for use in physics analyses. The studies are extended to assess the utility of combinations of substructure observables as a multivariate tagger using boosted decision trees or deep neural networks in comparison with taggers based on two-variable combinations. In addition, for highly boosted top-quark tagging, a deep neural network based on jet constituent inputs as well as a re-optimisation of the shower deconstruction technique is presented. The performance of these taggers is studied in data collected during 2015 and 2016 corresponding to 36.1 fb −1 for the tt ¯ and γ+jet and 36.7 fb −1 −1 for the dijet event topologies

In situ calibration of large-radius jet energy and mass in 13 TeV proton–proton collisions with the ATLAS detector

The response of the ATLAS detector to largeradius jets is measured in situ using 36.2 fb−1 of √s = 13 TeV proton–proton collisions provided by the LHC and recorded by the ATLAS experiment during 2015 and 2016. The jet energy scale is measured in events where the jet recoils against a reference object, which can be either a calibrated photon, a reconstructed Z boson, or a system of well-measured small-radius jets. The jet energy resolution and a calibration of forward jets are derived using dijet balance measurements. The jet mass response is measured with two methods: using mass peaks formed by W bosons and top quarks with large transverse momenta and by comparing the jet mass measured using the energy deposited in the calorimeter with that using the momenta of charged-particle tracks. The transversemomentum and mass responses in simulations are found to be about 2–3% higher than in data. This difference is adjusted for with a correction factor. The results of the different methods are combined to yield a calibration over a large range of transverse momenta (pT). The precision of the relative jet energy scale is 1–2% for 200 GeV < pT < 2 TeV, while that of the mass scale is 2–10%. The ratio of the energy resolutions in data and simulation is measured to a precision of 10–15% over the same pT range

Measurement of the nuclear modification factor for muons from charm and bottom hadrons in Pb+Pb collisions at 5.02 TeV with the ATLAS detector

Heavy-flavour hadron production provides information about the transport properties and microscopic structure of the quark-gluon plasma created in ultra-relativistic heavy-ion collisions. A measurement of the muons from semileptonic decays of charm and bottom hadrons produced in Pb+Pb and pp collisions at a nucleon-nucleon centre-of-mass energy of 5.02 TeV with the ATLAS detector at the Large Hadron Collider is presented. The Pb+Pb data were collected in 2015 and 2018 with sampled integrated luminosities of 208 mu b(-1) and 38 mu b(-1), respectively, and pp data with a sampled integrated luminosity of 1.17 pb(-1) were collected in 2017. Muons from heavy-flavour semileptonic decays are separated from the light-flavour hadronic background using the momentum imbalance between the inner detector and muon spectrometer measurements, and muons originating from charm and bottom decays are further separated via the muon track's transverse impact parameter. Differential yields in Pb+Pb collisions and differential cross sections in pp collisions for such muons are measured as a function of muon transverse momentum from 4 GeV to 30 GeV in the absolute pseudorapidity interval vertical bar eta vertical bar &lt; 2. Nuclear modification factors for charm and bottom muons are presented as a function of muon transverse momentum in intervals of Pb+Pb collision centrality. The bottom muon results are the most precise measurement of b quark nuclear modification at low transverse momentum where reconstruction of B hadrons is challenging. The measured nuclear modification factors quantify a significant suppression of the yields of muons from decays of charm and bottom hadrons, with stronger effects for muons from charm hadron decays

A search for an unexpected asymmetry in the production of e+μ− and e−μ+ pairs in proton-proton collisions recorded by the ATLAS detector at root s = 13 TeV

This search, a type not previously performed at ATLAS, uses a comparison of the production cross sections for e(+)mu(-) and e(-)mu(+) pairs to constrain physics processes beyond the Standard Model. It uses 139 fb(-1) of proton-proton collision data recorded at root s = 13 TeV at the LHC. Targeting sources of new physics which prefer final states containing e(+)mu(-) and e(-)mu(+), the search contains two broad signal regions which are used to provide model-independent constraints on the ratio of cross sections at the 2% level. The search also has two special selections targeting supersymmetric models and leptoquark signatures. Observations using one of these selections are able to exclude, at 95% confidence level, singly produced smuons with masses up to 640 GeV in a model in which the only other light sparticle is a neutralino when the R-parity-violating coupling lambda(23)(1)' is close to unity. Observations using the other selection exclude scalar leptoquarks with masses below 1880 GeV when g(1R)(eu) = g(1R)(mu c) = 1, at 95% confidence level. The limit on the coupling reduces to g(1R)(eu) = g(1R)(mu c) = 0.46 for a mass of 1420 GeV