Dos intents metodològics d'apropar els recursos arqueològics a l'aula

La voluntat de millorar la infraestructura museística per part dels responsables del Museu d'Alcoi, i el treball coordinat amb un grup de professors adscrits al CEP de la mateixa localitat, ha fet realitat l'elaboració de materials didàctics adients per apropar el museu - i amb ell la història- al públic escolar. Aquesta comunicació mostra les possibilitats divulgatives que emanen d'un treball a dues bandes, ensenyants i arqueòlegs, que fructifica en la realitat d'uns serveis pedagògics a l'abast dels centres educatius que desitgin aproparse al Museu.La voluntad de mejorar la infraestructura museística por parte de los responsables del Museo de Alcoi, y el trabajo coordinado con un grupo de professores adscritos al CEP de la misma localidad, ha hecho realidad la elaboración de materiales didácticos adecuados para acercar el museo - i con él la historia- al público escolar. Esta comunicación muestra las posibilidades divulgativas que emanan de un trabajo a dos bandas, enseñantes y arqueólogos, que fructifica en la realidad de unos servicios pedagógicos al alcance de los centros educativos que deseen acercarse al Museo

Interaction of Hydrogen with Graphitic Surfaces, Clean and Doped with Metal Clusters

Producción CientíficaHydrogen is viewed as a possible alternative to the fossil fuels in transportation. The technology of fuel-cell engines is fully developed, and the outstanding remaining problem is the storage of hydrogen in the vehicle. Porous materials, in which hydrogen is adsorbed on the pore walls, and in particular nanoporous carbons, have been investigated as potential onboard containers. Furthermore, metallic nanoparticles embedded in porous carbons catalyze the dissociation of hydrogen in the anode of the fuel cells. For these reasons the interaction of hydrogen with the surfaces of carbon materials is a topic of high technological interest. Computational modeling and the density functional formalism (DFT) are helping in the task of discovering the basic mechanisms of the interaction of hydrogen with clean and doped carbon surfaces. Planar and curved graphene provide good models for the walls of porous carbons. We first review work on the interaction of molecular and atomic hydrogen with graphene and graphene nanoribbons, and next we address the effects due to the presence of metal clusters on the surface because of the evidence of their role in enhancing hydrogen storage.Ministerio de Economía, Industria y Competitividad (Grant MAT2014-54378-R

Probabilistic Daily ILI Syndromic Surveillance with a Spatio-Temporal Bayesian Hierarchical Model

BACKGROUND: For daily syndromic surveillance to be effective, an efficient and sensible algorithm would be expected to detect aberrations in influenza illness, and alert public health workers prior to any impending epidemic. This detection or alert surely contains uncertainty, and thus should be evaluated with a proper probabilistic measure. However, traditional monitoring mechanisms simply provide a binary alert, failing to adequately address this uncertainty. METHODS AND FINDINGS: Based on the Bayesian posterior probability of influenza-like illness (ILI) visits, the intensity of outbreak can be directly assessed. The numbers of daily emergency room ILI visits at five community hospitals in Taipei City during 2006-2007 were collected and fitted with a Bayesian hierarchical model containing meteorological factors such as temperature and vapor pressure, spatial interaction with conditional autoregressive structure, weekend and holiday effects, seasonality factors, and previous ILI visits. The proposed algorithm recommends an alert for action if the posterior probability is larger than 70%. External data from January to February of 2008 were retained for validation. The decision rule detects successfully the peak in the validation period. When comparing the posterior probability evaluation with the modified Cusum method, results show that the proposed method is able to detect the signals 1-2 days prior to the rise of ILI visits. CONCLUSIONS: This Bayesian hierarchical model not only constitutes a dynamic surveillance system but also constructs a stochastic evaluation of the need to call for alert. The monitoring mechanism provides earlier detection as well as a complementary tool for current surveillance programs

A Hidden Markov Model for Analysis of Frontline Veterinary Data for Emerging Zoonotic Disease Surveillance

Surveillance systems tracking health patterns in animals have potential for early warning of infectious disease in humans, yet there are many challenges that remain before this can be realized. Specifically, there remains the challenge of detecting early warning signals for diseases that are not known or are not part of routine surveillance for named diseases. This paper reports on the development of a hidden Markov model for analysis of frontline veterinary sentinel surveillance data from Sri Lanka. Field veterinarians collected data on syndromes and diagnoses using mobile phones. A model for submission patterns accounts for both sentinel-related and disease-related variability. Models for commonly reported cattle diagnoses were estimated separately. Region-specific weekly average prevalence was estimated for each diagnoses and partitioned into normal and abnormal periods. Visualization of state probabilities was used to indicate areas and times of unusual disease prevalence. The analysis suggests that hidden Markov modelling is a useful approach for surveillance datasets from novel populations and/or having little historical baselines

Time trends in municipal distribution patterns of cancer mortality in Spain

BACKGROUND: New disease mapping techniques widely used in small-area studies enable disease distribution patterns to be identified and have become extremely popular in the field of public health. This paper reports on trends in the geographical mortality patterns of the most frequent cancers in Spain, over a period of 20 years. METHODS: We studied the municipal spatial pattern of stomach, colorectal, lung, breast, prostate and urinary bladder cancer mortality in Spain across four quinquennia, spanning the period 1989-2008. Case data were broken down by town (8073 municipalities), period and sex. Expected cases for each town were calculated using reference rates for each five-year period. For map plotting purposes, smoothed municipal relative risks were calculated using the conditional autoregressive model proposed by Besag, York and Mollié, with independent data for each quinquennium. We evaluated the presence of spatial patterns in maps on the basis of models, calculating the variance in relative risk corresponding to the structured spatial component and the unstructured component, as well as the proportion of variance explained by the structured spatial component. RESULTS: The mortality patterns observed for stomach, colorectal and lung cancer were maintained over the 20 years covered by the study. Prostate cancer and the tumours studied in women showed no defined spatial pattern, with the single exception of stomach cancer. The trend in spatial fractional variance indicated the possibility of a change in the spatial pattern in breast, bladder and colorectal cancer in women during the last five-year period. The paper goes on to discuss ways in which spatio-temporal data are depicted in the case of cancer, and review the risk factors that may possibly influence the respective tumours’ spatial patterns. CONCLUSION: In men, the marked geographical patterns of stomach, colorectal, lung and bladder cancer remained stable over time. Breast, colorectal and bladder cancer in women show signs of the possible appearance of a spatial pattern in Spain and should therefore be monitored. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2407-14-535) contains supplementary material, which is available to authorized users

Women’s gainful employment in ‘gher’ farming system (prawn–carp–rice integrated culture) in Bangladesh: trends and determinants

© 2019, Springer Nature Switzerland AG. The paper examines trends in women’s gainful employment in ‘prawn-carp’ and ‘high yield variety (HYV) rice’ enterprises of the ‘gher’ farming system and jointly identifies the determinants of employing female and male labor in these enterprises using a farm-level panel data of 90 producers covering a 14-year period (2002–2015) from southwest Bangladesh by applying a multivariate Tobit approach. Results revealed that women’s gainful employment and real wage increased significantly with a substantial reduction in wage gap between female and male labor. The decision to employ female and male labor was found to be positively correlated thereby confirming jointness in decision-making and validity of our chosen approach. Prices and socio-economic factors exerted varied influences on female and male labor demand. Output prices, cultivated area, education, and experience positively increased women’s gainful employment whereas larger family size reduced it. Policy implications include investments in education targeted at the ‘gher’ farming households and land reform policies to consolidate farm size and facilitate smooth functioning of the land market to increase women’s gainful employment

Spatial Random Slope Multilevel Modeling Using Multivariate Conditional Autoregressive Models: A Case Study of Subjective Travel Satisfaction in Beijing

This article explores how to incorporate a spatial dependence effect into the standard multilevel modeling (MLM). The proposed method is particularly well suited to the analysis of geographically clustered survey data where individuals are nested in geographical areas. Drawing on multivariate conditional autoregressive models, we develop a spatial random slope MLM approach to account for the within-group dependence among individuals in the same area and the spatial dependence between areas simultaneously. Our approach improves on recent methodological advances in the integrated spatial and MLM literature, offering greater flexibility in terms of model specification by allowing regression coefficients to be spatially varied. Bayesian Markov chain Monte Carlo (MCMC) algorithms are derived to implement the proposed model. Using two-level travel satisfaction data in Beijing, we apply the proposed approach as well as the standard nonspatial random slope MLM to investigate subjective travel satisfaction of residents and its determinants. Model comparison results show strong evidence that the proposed method produces a significant improvement against a nonspatial random slope MLM. A fairly large spatial correlation parameter suggests strong spatial dependence in district-level random effects. Moreover, spatial patterns of district-level random effects of locational variables have been identified, with high and low values clustering together

Modelling the covariance structure in marginal multivariate count models: Hunting in Bioko Island.

The main goal of this article is to present a flexible statistical modelling framework to deal with multivariate count data along with longitudinal and repeated measures structures. The covariance structure for each response variable is defined in terms of a covariance link function combined with a matrix linear predictor involving known matrices. In order to specify the joint covariance matrix for the multivariate response vector, the generalized Kronecker product is employed. We take into account the count nature of the data by means of the power dispersion function associated with the Poisson–Tweedie distribution. Furthermore, the score information criterion is extended for selecting the components of the matrix linear predictor. We analyse a data set consisting of prey animals (the main hunted species, the blue duiker Philantomba monticola and other taxa) shot or snared for bushmeat by 52 commercial hunters over a 33-month period in Pico Basilé, Bioko Island, Equatorial Guinea. By taking into account the severely unbalanced repeated measures and longitudinal structures induced by the hunters and a set of potential covariates (which in turn affect the mean and covariance structures), our method can be used to indicate whether there was statistical evidence of a decline in blue duikers and other species hunted during the study period. Determining whether observed drops in the number of animals hunted are indeed true is crucial to assess whether species depletion effects are taking place in exploited areas anywhere in the world. We suggest that our method can be used to more accurately understand the trajectories of animals hunted for commercial or subsistence purposes and establish clear policies to ensure sustainable hunting practices