Artrosis vertebral en la población de La Encantada (Granátula de Calatrava, Ciudad Real, II milenio a. C.)

X Congreso Nacional de Paleopatología. Univesidad Autónoma de Madrid, septiembre de 200

Ideas de los alumnos acerca del mol. Estudio curricular

In this paper a display is made of the controversy about the concept of m01 and the convenience of introducing it in the school "curricula" at the age in which nowadays is made. The results we have obtained from the research carried out on the difficulties experienced by 15 to 19 year old students in understanding this concept and other related concepts are given

Tool Supported Error Detection and Explanations on Feature Models

Automated analysis of feature models (FM) is a field of interest in recent years. Many operations over FMs have been proposed and developed, and many researchers and industrial companies have adopted FMs as a way to express variability. This last makes more necessary having support to detect, explain and fix errors on FMs. The notation of FMs makes very easy to express variability, but makes hard detecting errors and find their cause manually. and these errors may cause the model does not express the variability what we want of it. Therefore, we need support to detect errors and find their causes. The contribution of this paper is a method to detect errors in FMs, based on the concept of observation. We also present implementations of this approach and of an approach to explain errors, in FaMa Framework [1] tool. To detect FM errors, firstly we have to identify the different error types and what it means each of them. Void FM error means that the FM does not represent any product, dead feature error means that a feature of the FM does not appear in any product, false optional error means that an optional feature appears in every product that its parent feature also appears, and wrong cardinality error means that one or more values of a set relationship cardinality are not reachable. We can check for these errors in a intuitive way. For instance, to detect if a FM has dead features, we can calculate every product and check if each feature appears in, at least, one product. But further, we propose a method based on observations, it means, FM configurations associated with a specific element (feature or cardinality). Each type of error has its type of observation associated too. With an algorithm, we calculate the set of observations of a FM. Then, for each observation, we check if FM has at least one product. If not, we have found an error. For instance, dead feature observation sets its feature as selected. If the FM with a dead feature observation is not valid, it means the feature we are checking is dead. When we have found the errors, explanations tell us what is the cause of each error. An explanation is a set of relationships that originates one or more errors. Changing or removing these relationships we can fix a error. However, explanations by themselves do not provide information about how to change the relationship. For instance, if an explanation about a dead feature is a mandatory relationship, we can turn it into a optional relationship, but the explanation does not tell us directly. We have implemented observations and explanations approaches in FaMa Framework, a tool for the automated analysis of FMs. The observations approach implemented is the previously mentioned, while the explanations approach implemented is the one described by Trinidad et al. [3] [4]. With these approaches, we have detected errors in SPLOT FM repository [2], and we have obtained explanations for them also

Time for global action: an optimised cooperative approach towards effective climate change mitigation

The difficulties in climate change negotiations together with the recent withdrawal of the U.S. from the Paris Agreement call for new cooperative mechanisms to enable a resilient international response. In this study we propose an approach to aid such negotiations based on quantifying the benefits of interregional cooperation and distributing them among the participants in a fair manner. Our approach is underpinned by advanced optimisation techniques that automate the screening of millions of alternatives for differing levels of cooperation, ultimately identifying the most cost-effective solutions for meeting emission targets. We apply this approach to the Clean Power Plan, a related act in the U.S. aiming at curbing carbon emissions from electricity generation, but also being withdrawn. We find that, with only half of the states cooperating, the cost of electricity generation could be reduced by US$41 billion per year, while simultaneously cutting carbon emissions by 68% below 2012 levels. These win–win scenarios are attained by sharing the emission targets and trading electricity among the states, which allows exploiting regional advantages. Fair sharing of dividends may be used as a key driver to spur cooperation since the global action to mitigate climate change becomes beneficial for all participants. Even if global cooperation remains elusive, it is worth trying since the mere cooperation of a few states leads to significant benefits for both the U.S. economy and the climate. These findings call on the U.S. to reconsider its withdrawal but also boost individual states to take initiative even in the absence of federal action

Perturbation expansion for 2-D Hubbard model

We develop an efficient method to calculate the third-order corrections to the self-energy of the hole-doped two-dimensional Hubbard model in space-time representation. Using the Dyson equation we evaluate the renormalized spectral function in various parts of the Brillouin zone and find significant modifications with respect to the second-order theory even for rather small values of the coupling constant U. The spectral function becomes unphysical for $U \simeq W$, where W is the half-width of the conduction band. Close to the Fermi surface and for U<W, the single-particle spectral weight is reduced in a finite energy interval around the Fermi energy. The increase of U opens a gap between the occupied and unoccupied parts of the spectral function.Comment: 17 pages, 11 Postscript figures, Phys. Rev. B, accepte

A low-pass filter with automatic frequency tuning for a bluetooth receiver

A third-order Gm-C Chebyshev low-pass filter with high linearity and automatic frequency programmability has been designed. The filter is intended to be used as a channel-select filter for a zero-IF Bluetooth receiver. The frequency tuning scheme is simpler and has more relaxed specifications than conventional ones. The filter bandwidth is 0.5 MHz and the overall scheme dissipates 1.1 mA from a 1.8-V supply. The third-order intermodulation (IM3) distortion of the filter for a 1Vpp two-tone signal centered at 350 kHz is -67dB.Ministerio de Ciencia y Tecnología TEC2007-67460-C03-02

Association between heavy metals and metalloids in topsoil and mental health in the adult population of Spain

Despite the biological plausibility of the association between heavy metal exposure and mental health disorders, epidemiological evidence remains scarce. The objective was to estimate the association between heavy metals and metalloids in soil and the prevalence of mental disorders in the adult population of Spain. Methods Individual data came from the Spanish National Health Survey 2011–2012, 18,073 individuals residing in 1772 census sections. Mental health was measured with the 12-item General Health Questionnaire. The concentration estimates of heavy metal and metalloid levels in topsoil (upper soil horizon) came from the Geochemical Atlas of Spain based on 13,317 soil samples. Levels of lead (Pb), arsenic (As), cadmium (Cd) and manganese (Mn) were estimated in each census section by “ordinary Kriging”. Odds ratios (OR) were calculated by multilevel logistic regression models. Results Compared with the lowest Pb concentration levels quartile, the OR for the second quartile was 1.29 (95%CI: 1.11–1.50), increasing progressively to 1.37 (95%CI: 1.17–1.60) and 1.51 (95%CI: 1.27–1.79) in the third and fourth quartiles, respectively. For As, the association was observed in the third and fourth quartiles: 1.21 (95%CI: 1.04–1.41) and 1.42 (95% CI: 1.21–1.65), respectively. Cd was associated also following a gradient from the second quartile: 1.34 (95%CI: 1.15–1.57) through the fourth: 1.84 (95%CI: 1.56–2.15). In contrast, Mn only showed a positive association at the second quartile. Additionally, individuals consuming vegetables > once a day the OR for the fourth quartile of Pb concentration, vs. the first, increased to 2.93 (95%CI: 1.97–4.36); similarly for As: 3.00 (95%CI: 2.08–4.31), and for Cd: 3.49 (95%CI: 2.33–5.22). Conclusions Living in areas with a higher concentration of heavy metals and metalloids in soil was associated with an increased probability of having a mental disorder. These relationships were strengthened in individuals reporting consuming vegetables > once a dayThis work was supported by the Institute of Health Carlos III, Ministry of Science Innovation and Universities [grant number PI15CIII/00034, PI14CIII/00065 and PI17CIII/00040