A global atmospheric electricity monitoring network for climate and geophysical research

The Global atmospheric Electric Circuit (GEC) is a fundamental coupling network of the climate system connecting electrically disturbed weather regions with fair weather regions across the planet. The GEC sustains the fair weather electric field (or potential gradient, PG) which is present globally and can be measured routinely at the surface using durable instrumentation such as modern electric field mills, which are now widely deployed internationally. In contrast to lightning or magnetic fields, fair weather PG cannot be measured remotely. Despite the existence of many PG datasets (both contemporary and historical), few attempts have been made to coordinate and integrate these fragmented surface measurements within a global framework. Such a synthesis is important elvinin order to fully study major influences on the GEC such as climate variations and space weather effects, as well as more local atmospheric electrical processes such as cloud electrification, lightning initiation, and dust and aerosol charging. The GloCAEM (Global Coordination of Atmospheric Electricity Measurements) project has brought together experts in atmospheric electricity to make the first steps towards an effective global network for atmospheric electricity monitoring, which will provide data in near real time. Data from all sites are available in identically-formatted files, at both one second and one minute temporal resolution, along with meteorological data (wherever available) for ease of interpretation of electrical measurements. This work describes the details of the GloCAEM database and presents what is likely to be the largest single analysis of PG data performed from multiple datasets at geographically distinct locations. Analysis of the diurnal variation in PG from all 17 GloCAEM sites demonstrates that the majority of sites show two daily maxima, characteristic of local influences on the PG, such as the sunrise effect. Data analysis methods to minimise such effects are presented and recommendations provided on the most suitable GloCAEM sites for the study of various scientific phenomena. The use of the dataset for a further understanding of the GEC is also demonstrated, in particular for more detailed characterization of day-to-day global circuit variability. Such coordinated effort enables deeper insight into PG phenomenology which goes beyond single-location PG measurements, providing a simple measurement of global thunderstorm variability on a day-to-day timescale. The creation of the GloCAEM database is likely to enable much more effective study of atmospheric electricity variables than has ever been possible before, which will improve our understanding of the role of atmospheric electricity in the complex processes underlying weather and climate

Propagation of gravity waves and spread F in the low-latitude ionosphere over Tucumán, Argentina, by continuous Doppler sounding: first results

Results of systematic analysis of propagation directions and horizontal velocities of gravity waves (GWs) and spread F structures in low-latitude ionosphere (magnetic inclination ~27°) in Tucumán region, Argentina, are presented. Measurements were carried out by multipoint continuous Doppler system during 1 year from December 2012 to November 2013. It was found that meridian propagation of GWs dominated and that southward propagation prevailed in the local summer. Oblique spread structures observed in Doppler shift spectrograms and associated with spread F propagated roughly eastward at velocities from ~70 to ~180 m/s and were observed at night from ~ September to ~ March. The velocities were computed for 182 events and the azimuths for 64 events. Continuous Doppler sounding makes it possible to analyze more events compared to optical observations often used for propagation studies since the measurements do not depend on weather.Fil: Chum, J.. Institute of Atmospheric Physics; República ChecaFil: Miranda Bonomi, Fernando Alberto. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Electricidad, Electrónica y Computación. Laboratorio de Telecomunicaciones; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Fišer, J.. Institute of Atmospheric Physics; República ChecaFil: Cabrera, M. A.. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Electricidad, Electrónica y Computación. Laboratorio de Telecomunicaciones; Argentina. Universidad Tecnológica Nacional. Facultad Regional Tucuman; ArgentinaFil: Ezquer, Rodolfo Gerardo. Universidad Tecnológica Nacional. Facultad Regional Tucuman; Argentina. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Física. Laboratorio de Ionosfera; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Burešová, D.. Institute of Atmospheric Physics; República ChecaFil: Laštovička, J.. Institute of Atmospheric Physics; República ChecaFil: Baše, J.. Institute of Atmospheric Physics; República ChecaFil: Hruška, F.. Institute of Atmospheric Physics; República ChecaFil: Molina, Maria Graciela. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Ciencias de la Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Ise, Juan Eduardo. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Electricidad, Electrónica y Computación. Laboratorio de Telecomunicaciones; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Cangemi, José Ignacio. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Departamento de Electricidad, Electrónica y Computación. Laboratorio de Telecomunicaciones; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Šindelářová, T.. Institute of Atmospheric Physics; República Chec

BagMinHash - Minwise Hashing Algorithm for Weighted Sets

Minwise hashing has become a standard tool to calculate signatures which allow direct estimation of Jaccard similarities. While very efficient algorithms already exist for the unweighted case, the calculation of signatures for weighted sets is still a time consuming task. BagMinHash is a new algorithm that can be orders of magnitude faster than current state of the art without any particular restrictions or assumptions on weights or data dimensionality. Applied to the special case of unweighted sets, it represents the first efficient algorithm producing independent signature components. A series of tests finally verifies the new algorithm and also reveals limitations of other approaches published in the recent past.Comment: 10 pages, KDD 201

Adherence to Tuberculosis Therapy among Patients Receiving Home-Based Directly Observed Treatment: Evidence from the United Republic of Tanzania.

\ud \ud Non-adherence to tuberculosis (TB) treatment is the leading contributor to the selection of drug-resistant strains of Mycobacterium tuberculosis and subsequent treatment failure. Tanzania introduced a TB Patient Centred Treatment (PCT) approach which gives new TB patients the choice between home-based treatment supervised by a treatment supporter of their own choice, and health facility-based treatment observed by a medical professional. The aim of this study was to assess the extent and determinants of adherence to anti-TB therapy in patients opting for home-based treatment under the novel PCT approach. In this cross-sectional study, the primary outcome was the percentage of patients adherent to TB therapy as detected by the presence of isoniazid in urine (IsoScreen assay). The primary analysis followed a non-inferiority approach in which adherence could not be lower than 75%. Logistic regression was used to examine the influence of potentially predictive factors. A total of 651 new TB patients were included. Of these, 645 (99.1%) provided urine for testing and 617 patients (95.7%; 90%CI 94.3-96.9) showed a positive result. This result was statistically non-inferior to the postulated adherence level of 75% (p<0.001). Adherence to TB therapy under home-based Directly Observed Treatment can be ensured in programmatic settings. A reliable supply of medication and the careful selection of treatment supporters, who preferably live very close to the patient, are crucial success factors. Finally, we recommend a cohort study to assess the rate of adherence throughout the full course of TB treatment

Chapter 7 - Energy systems

Stabilizing greenhouse gas (GHG) concentrations will require large-scale transformations in human societies, from the way that we produce and consume energy to how we use the land surface. A natural question in this context is what will be the .transformation pathway. towards stabilization; that is, how do we get from here to there? The topic of this chapter is transformation pathways. The chapter is primarily motivated by three questions. First, what are the near-term and future choices that define transformation pathways, including the goal itself, the emissions pathway to the goal, technologies used for and sectors contributing to mitigation, the nature of international coordination, and mitigation policies? Second, what are the key characteristics of different transformation pathways, including the rates of emissions reductions and deployment of low-carbon energy, the magnitude and timing of aggregate economic costs, and the implications for other policy objectives such as those generally associated with sustainable development? Third, how will actions taken today influence the options that might be available in the future? As part of the assessment in this chapter, data from over 1000 new scenarios published since the IPCC Fourth Assessment Report (AR4) were collected from integrated modelling research groups, many from large-scale model intercomparison studies. In comparison to AR4, new scenarios, both in this AR5 dataset and more broadly in the literature assessed in this chapter, consider more ambitious concentration goals, a wider range of assumptions about technology, and more possibilities for delays in additional global mitigation beyond that of today and fragmented international action

Biorefining of wheat straw:accounting for the distribution of mineral elements in pretreated biomass by an extended pretreatment–severity equation

BACKGROUND: Mineral elements present in lignocellulosic biomass feedstocks may accumulate in biorefinery process streams and cause technological problems, or alternatively can be reaped for value addition. A better understanding of the distribution of minerals in biomass in response to pretreatment factors is therefore important in relation to development of new biorefinery processes. The objective of the present study was to examine the levels of mineral elements in pretreated wheat straw in response to systematic variations in the hydrothermal pretreatment parameters (pH, temperature, and treatment time), and to assess whether it is possible to model mineral levels in the pretreated fiber fraction. RESULTS: Principal component analysis of the wheat straw biomass constituents, including mineral elements, showed that the recovered levels of wheat straw constituents after different hydrothermal pretreatments could be divided into two groups: 1) Phosphorus, magnesium, potassium, manganese, zinc, and calcium correlated with xylose and arabinose (that is, hemicellulose), and levels of these constituents present in the fiber fraction after pretreatment varied depending on the pretreatment-severity; and 2) Silicon, iron, copper, aluminum correlated with lignin and cellulose levels, but the levels of these constituents showed no severity-dependent trends. For the first group, an expanded pretreatment-severity equation, containing a specific factor for each constituent, accounting for variability due to pretreatment pH, was developed. Using this equation, the mineral levels could be predicted with R(2) > 0.75; for some with R(2) up to 0.96. CONCLUSION: Pretreatment conditions, especially pH, significantly influenced the levels of phosphorus, magnesium, potassium, manganese, zinc, and calcium in the resulting fiber fractions. A new expanded pretreatment-severity equation is proposed to model and predict mineral composition in pretreated wheat straw biomass

Toward an improved representation of middle atmospheric dynamics thanks to the ARISE project

This paper reviews recent progress toward understanding the dynamics of the middle atmosphere in the framework of the Atmospheric Dynamics Research InfraStructure in Europe (ARISE) initiative. The middle atmosphere, integrating the stratosphere and mesosphere, is a crucial region which influences tropospheric weather and climate. Enhancing the understanding of middle atmosphere dynamics requires improved measurement of the propagation and breaking of planetary and gravity waves originating in the lowest levels of the atmosphere. Inter-comparison studies have shown large discrepancies between observations and models, especially during unresolved disturbances such as sudden stratospheric warmings for which model accuracy is poorer due to a lack of observational constraints. Correctly predicting the variability of the middle atmosphere can lead to improvements in tropospheric weather forecasts on timescales of weeks to season. The ARISE project integrates different station networks providing observations from ground to the lower thermosphere, including the infrasound system developed for the Comprehensive Nuclear-Test-Ban Treaty verification, the Lidar Network for the Detection of Atmospheric Composition Change, complementary meteor radars, wind radiometers, ionospheric sounders and satellites. This paper presents several examples which show how multi-instrument observations can provide a better description of the vertical dynamics structure of the middle atmosphere, especially during large disturbances such as gravity waves activity and stratospheric warming events. The paper then demonstrates the interest of ARISE data in data assimilation for weather forecasting and re-analyzes the determination of dynamics evolution with climate change and the monitoring of atmospheric extreme events which have an atmospheric signature, such as thunderstorms or volcanic eruptions