6,224 research outputs found

    Numerical understanding of regional scale water table behavior in the Guadalupe Valley aquifer, Baja California, Mexico

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    International audienceA regional groundwater flow model was developed, in order to evaluate the water table behavior in the region of the Guadalupe Valley, in Baja California, Mexico. The State of Baja California has been subject to an increment of the agricultural, urban and industrials activities, implicating a growing water-demand. However, the State is characterized by its semi-arid climate with low surface water availability; resulting in an extensive use of groundwater in local aquifer. Based on historic piezometric information of the last two decades, however, a negative evolution could be observed, resulting a negative storage volume. So far, there is not an integral hydrogeological evaluation that determine the real condition of the groundwater resource, and that permit to planning a management of the Guadalupe Valley Aquifer. A steady-state calibration model was carried out in order to obtain the best possible match to measured levels at the Guadalupe Valley Aquifer. The contours of calculated water table elevations for January 1983 were reproduced. Generally, the comparison of the observed and calculated water table configurations have a good qualitative and quantitatively adjustment. Nowadays, it is count with a hydrogeological model that can be used for simulates the groundwater flow in the region of the Guadalupe Valley

    Which solar EUV indices are best for reconstructing the solar EUV irradiance ?

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    The solar EUV irradiance is of key importance for space weather. Most of the time, however, surrogate quantities such as EUV indices have to be used by lack of continuous and spectrally resolved measurements of the irradiance. The ability of such proxies to reproduce the irradiance from different solar atmospheric layers is usually investigated by comparing patterns of temporal correlations. We consider instead a statistical approach. The TIMED/SEE experiment, which has been continuously operating since Feb. 2002, allows for the first time to compare in a statistical manner the EUV spectral irradiance to five EUV proxies: the sunspot number, the f10.7, Ca K, and Mg II indices, and the He I equivalent width. Using multivariate statistical methods such as multidimensional scaling, we represent in a single graph the measure of relatedness between these indices and various strong spectral lines. The ability of each index to reproduce the EUV irradiance is discussed; it is shown why so few lines can be effectively reconstructed from them. All indices exhibit comparable performance, apart from the sunspot number, which is the least appropriate. No single index can satisfactorily describe both the level of variability on time scales beyond 27 days, and relative changes of irradiance on shorter time scales.Comment: 6 figures, to appear in Adv. Space. Re

    Separated Oscillatory Fields for High-Precision Penning Trap Mass Spectrometry

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    Ramsey's method of separated oscillatory fields is applied to the excitation of the cyclotron motion of short-lived ions in a Penning trap to improve the precision of their measured mass. The theoretical description of the extracted ion-cyclotron-resonance line shape is derived out and its correctness demonstrated experimentally by measuring the mass of the short-lived 38^{38}Ca nuclide with an uncertainty of 1.6⋅10−81.6\cdot 10^{-8} using the ISOLTRAP Penning trap mass spectrometer at CERN. The mass value of the superallowed beta-emitter 38^{38}Ca is an important contribution for testing the conserved-vector-current hypothesis of the electroweak interaction. It is shown that the Ramsey method applied to mass measurements yields a statistical uncertainty similar to that obtained by the conventional technique ten times faster.Comment: 5 pages, 4 figures, 0 table

    The role of learning in complex problem solving using MicroDYN

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    It is still an open question which cognitive and non-cognitive personality traits are useful for describing and explaining behaviour and performance in complex problems. During complex problem solving (CPS), problem solvers have to interact with the task in a way in which learning ability might be beneficial for successful task completion. By investigating the relationship between learning ability and CPS, while accounting for interactions between complex system characteristics and person characteristics, this paper aims to understand the role of learning processes in CPS more closely. In a sample of N = 241 participants, we performed a preregistered analysis to investigate the relationship between knowledge acquisition performance in a CPS test (MicroDYN) and learning test performance (ADAFI) with a multilevel modeling approach across 10 CPS systems with various characteristics. In line with our expectations, we replicated previous findings on a relationship between learning test and MicroDYN performance and found this relationship to be more pronounced in systems with (vs. without) autonomous changes. Further system and person characteristics also showed effects as expected, with better performance in systems with lower complexity, with more experience with the task, and with more strategic exploration behaviour. Our results provide further evidence for the notion that learning is an important component for the successful completion of CPS tasks

    Contact Profiles in Eight European Countries and Implications for Modelling the Spread of Airborne Infectious Diseases

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    BACKGROUND: For understanding the spread of infectious diseases it is crucial to have knowledge of the patterns of contacts in a population during which the infection can be transmitted. Besides contact rates and mixing between age groups, the way individuals distribute their contacts across different locations may play an important role in determining how infections spread through a population. METHODS AND FINDINGS: Representative surveys were performed in eight countries to assess the number of social contacts (talking to another person at close distance either with or without physical contact), using a diary approach in which participants recorded individual contacts. The overall sample size was 7290 respondents. We analyzed the reported numbers of contacts per respondent in six different settings (household, work, school, leisure, transportation and others) to define different contact profiles. The identification of the profiles and classification of respondents according to these profiles was conducted using a two-step cluster analysis algorithm as implemented in SPSS. We identified seven distinct contact profiles: respondents having (1) mixed: contacts predominantly at school, during transportation and leisure time, (2) contacts during leisure time, (3) contacts mainly in the household (large family), (4) contacts at work, (5) contacts solely at school, (6) contacts in other places and finally (7) respondents having a low number of contacts in any setting. Similar contact profiles can be found in all eight European countries which participated in the study. The distributions of respondents across the profiles were similar in all countries. The profiles are dominated by work, school and household contacts. But also contacts during leisure activities play an important role in the daily lives of a large fraction of individuals. A surprisingly large number of individuals has only few contacts in all locations. There was a distinct age-dependence in the distribution of the population across contact profiles. CONCLUSIONS: In contrast with earlier studies that focussed on the contribution of different age groups to the spread of an infectious disease, our results open up the opportunity to analyze how an infection spreads between locations and how locations as work or school are interconnected via household contacts. Mathematical models that take these local contact patterns into account can be used to assess the effect of intervention measures like school closure and cancelling of leisure activities on the spread of influenza

    Phasing for medical sequencing using rare variants and large haplotype reference panels.

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    Motivation: There is growing recognition that estimating haplotypes from high coverage sequencing of single samples in clinical settings is an important problem. At the same time very large datasets consisting of tens and hundreds of thousands of high-coverage sequenced samples will soon be available. We describe a method that takes advantage of these huge human genetic variation resources and rare variant sharing patterns to estimate haplotypes on single sequenced samples. Sharing rare variants between two individuals is more likely to arise from a recent common ancestor and, hence, also more likely to indicate similar shared haplotypes over a substantial flanking region of sequence.Results: Our method exploits this idea to select a small set of highly informative copying states within a Hidden Markov Model (HMM) phasing algorithm. Using rare variants in this way allows us to avoid iterative MCMC methods to infer haplotypes. Compared to other approaches that do not explicitly use rare variants we obtain significant gains in phasing accuracy, less variation over phasing runs and improvements in speed. For example, using a reference panel of 7420 haplotypes from the UK10K project, we are able to reduce switch error rates by up to 50% when phasing samples sequenced at high-coverage. In addition, a single step rephasing of the UK10K panel, using rare variant information, has a downstream impact on phasing performance. These results represent a proof of concept that rare variant sharing patterns can be utilized to phase large high-coverage sequencing studies such as the 100 000 Genomes Project dataset.</br

    Link and subgraph likelihoods in random undirected networks with fixed and partially fixed degree sequence

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    The simplest null models for networks, used to distinguish significant features of a particular network from {\it a priori} expected features, are random ensembles with the degree sequence fixed by the specific network of interest. These "fixed degree sequence" (FDS) ensembles are, however, famously resistant to analytic attack. In this paper we introduce ensembles with partially-fixed degree sequences (PFDS) and compare analytic results obtained for them with Monte Carlo results for the FDS ensemble. These results include link likelihoods, subgraph likelihoods, and degree correlations. We find that local structural features in the FDS ensemble can be reasonably well estimated by simultaneously fixing only the degrees of few nodes, in addition to the total number of nodes and links. As test cases we use a food web, two protein interaction networks (\textit{E. coli, S. cerevisiae}), the internet on the autonomous system (AS) level, and the World Wide Web. Fixing just the degrees of two nodes gives the mean neighbor degree as a function of node degree, k_k, in agreement with results explicitly obtained from rewiring. For power law degree distributions, we derive the disassortativity analytically. In the PFDS ensemble the partition function can be expanded diagrammatically. We obtain an explicit expression for the link likelihood to lowest order, which reduces in the limit of large, sparse undirected networks with LL links and with kmaxâ‰ȘLk_{\rm max} \ll L to the simple formula P(k,kâ€Č)=kkâ€Č/(2L+kkâ€Č)P(k,k') = kk'/(2L + kk'). In a similar limit, the probability for three nodes to be linked into a triangle reduces to the factorized expression PΔ(k1,k2,k3)=P(k1,k2)P(k1,k3)P(k2,k3)P_{\Delta}(k_1,k_2,k_3) = P(k_1,k_2)P(k_1,k_3)P(k_2,k_3).Comment: 17 pages, includes 11 figures; first revision: shortened to 14 pages (7 figures), added discussion of subgraph counts, deleted discussion of directed network
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