A space-time rainfall generator for highly convective Mediterranean rainstorms

Distributed hydrological models require fine resolution rainfall inputs, enhancing the practical interest of space-time rainfall models, capable of generating through numerical simulation realistic space-time rainfall intensity fields. Among different mathematical approaches, those based on point processes and built upon a convenient analytical description of the raincell as the fundamental unit, have shown to be particularly suitable and well adapted when extreme rainfall events of convective nature are considered. Starting from previous formulations, some analytical refinements have been considered, allowing practical generation of space-time rainfall intensity fields for that type of rainstorm events. Special attention is placed on the analytical description of the spatial and temporal evolution of the rainfall intensities produced by the raincells. After deriving the necessary analytical results, the seven parameters of the model have been estimated by the method of moments, for each of the 30 selected rainfall events in the Jucar River Basin (ValenciaSpain) – period 1991 to 2000, using 5-min aggregated rainfall data series from an automatic raingauge network

Multivariate synthetic streamflow generation using a hybrid model based on artificial neural networks

International audienceA model for multivariate streamflow generation is presented, based on a multilayer feedforward neural network. The structure of the model results from two components, the neural network (NN) deterministic component and a random component which is assumed to be normally distributed. It is from this second component that the model achieves the ability to incorporate effectively the uncertainty associated with hydrological processes, making it valuable as a practical tool for synthetic generation of streamflow series. The NN topology and the corresponding analytical explicit formulation of the model are described in detail. The model is calibrated with a series of monthly inflows to two reservoir sites located in the Tagus River basin (Spain), while validation is performed through estimation of a set of statistics that is relevant for water resources systems planning and management. Among others, drought and storage statistics are computed and compared for both the synthetic and historical series. The performance of the NN-based model was compared to that of a standard autoregressive AR(2) model. Results show that NN represents a promising modelling alternative for simulation purposes, with interesting potential in the context of water resources systems management and optimisation. Keywords: neural networks, perceptron multilayer, error backpropagation, hydrological scenario generation, multivariate time-series.

Climate and hydrological variability: the catchment filtering role

Abstract. Measuring the impact of climate change on flood frequency is a complex and controversial task. Identifying hydrological changes is difficult given the factors, other than climate variability, which lead to significant variations in runoff series. The catchment filtering role is often overlooked and thus may hinder the correct identification of climate variability signatures on hydrological processes. Does climate variability necessarily imply hydrological variability? This research aims to analytically derive the flood frequency distribution based on realistic hypotheses about the rainfall process and the rainfall–runoff transformation. The annual maximum peak flow probability distribution is analytically derived to quantify the filtering effect of the rainfall–runoff process on climate change. A sensitivity analysis is performed according to typical semi-arid Mediterranean climatic and hydrological conditions, assuming a simple but common scheme for the rainfall–runoff transformation in small-size ungauged catchments, i.e. the CN-SCS model. Variability in annual maximum peak flows and its statistical significance are analysed when changes in the climatic input are introduced. Results show that depending on changes in the annual number of rainfall events, the catchment filtering role is particularly significant, especially when the event rainfall volume distribution is not strongly skewed. Results largely depend on the return period: for large return periods, peak flow variability is significantly affected by the climatic input, while for lower return periods, infiltration processes smooth out the impact of climate change

Multivariate synthetic streamflow generation using a hybrid model based on artificial neural networks

A model for multivariate streamflow generation is presented, based on a multilayer feedforward neural network. The structure of the model results from two components, the neural network (NN) deterministic component and a random component which is assumed to be normally distributed. It is from this second component that the model achieves the ability to incorporate effectively the uncertainty associated with hydrological processes, making it valuable as a practical tool for synthetic generation of streamflow series. The NN topology and the corresponding analytical explicit formulation of the model are described in detail. The model is calibrated with a series of monthly inflows to two reservoir sites located in the Tagus River basin (Spain), while validation is performed through estimation of a set of statistics that is relevant for water resources systems planning and management. Among others, drought and storage statistics are computed and compared for both the synthetic and historical series. The performance of the NN-based model was compared to that of a standard autoregressive AR(2) model. Results show that NN represents a promising modelling alternative for simulation purposes, with interesting potential in the context of water resources systems management and optimisation.</p> <p style='line-height: 20px;'><b>Keywords: </b>neural networks, perceptron multilayer, error backpropagation, hydrological scenario generation, multivariate time-series.</p>

Relationship between epistasis and aggressiveness in resistance of pepper (Capsicum annuum L.) to Phytophthora nicotianae

This study evaluated the types of gene action governing the inheritance of resistance to Phytophthora nicotianae necrosis in populations derived from two crosses involving two susceptible (Beldi and Nabeul II) and one resistant (CM334) cultivars of pepper (Capsicum annuum L.). Populations, composed of Pr, Ps, F1 , F 2 , BC 1 Pr, and BC 1 Ps generations, were inoculated with six P. nicotianae isolates. Generation means analysis indicated that an additive-dominance model was appropriate for P. nicotianae isolates Pn Ko1 , Pn Ko2 and Pn Kr1 , which showed low aggressiveness in the two crosses. For the more aggressive isolates Pn Bz1 , Pn Bz2 and Pn Kr2 , epistasis was an integral component of resistance in the two crosses. The presence of epistasis in the resistance of pepper to P. nicotianae was dependent on the level of aggressiveness of the isolates. Selection in pepper with less aggressive isolates was efficient, but not with more aggressive isolates; on the other hand, selection with more aggressive isolates was more stable. The minimum number of genes controlling resistance was estimated at up to 2.71. In the majority of cases, the additive variance was significant and greater than the environmental and dominance variance

Human With No Lysine Kinase 3 (WNK3): A Target Enabling Package (TEP)

The Target Enabling Package (TEP) programme's foundation is built upon the recognition that genetic data is proving to be a powerful tool for target validation. As such, TEPs provide a critical mass of reagents and knowledge on a protein target to allow rapid biochemical and chemical exploration and characterisation of proteins with genetic linkage to key disease areas. TEPs provide an answer to the missing link between genomics and chemical biology, provide a starting point for chemical probe generation and therefore catalyse new biology and disease understanding with the ultimate aim of enabling translation collaborations and target/ drug discovery. We are committed to generating and making available 24 high-quality TEPs by June 2020.SUMMARY OF PROJECT Kinases WNK1-4 regulate cation-chloride cotransporters via phosphorylation of SPAK and OSR1 and thereby control salt homeostasis, cell volume and blood pressure. Gain of function mutations in WNK kinases are found in Gordon’s hypertension syndrome suggesting the WNK pathway as a therapeutic target. WNK3 inhibition in particular has also been shown to reduce cerebral injury after Ischemic stroke. Here we present assays and crystal structures that define (i) the molecular basis for disease mutations; (ii) the multiple functional domains of WNK kinases and their protein interactions; (iii) the binding of small molecule kinase inhibitors and a potential allosteric pocket.The work performed at the SGC has been funded by a grant from the Wellcome [106169/ZZ14/Z]

Analysis of efficiency and profitability of franchise services

The present study analyses the relative efficiency of franchise services and characterises the best companies, confirming the relationship between efficiency and profit. These companies are from the trade and other services sector , the main group of service-providing companies in the Spanish economy. The methodology calls for first comparing the relative efficiency of franchisers and ownership enterprises. Second, the focus turns to the most efficient franchise services, using a super-efficiency model to rank them. The paper then goes on to cover the analysis of the main characteristics of the best franchise enterprises, the number of own establishments in a franchise business and the profitability of the company. This paper presents arguments as to why companies from the trade and other services sector are included. The main conclusion is that, whilst the number of establishments is irrelevant in achieving greater efficiency, many of the most efficient enterprises have high returns.García Martin, CJ.; Medal Bartual, A.; Peris-Ortiz, M. (2014). Analysis of efficiency and profitability of franchise services. Service Industries Journal. 34(9):796-810. doi:10.1080/02642069.2014.905921S79681034

Multidrug-Resistant Acinetobacter baumannii Harboring OXA-24 Carbapenemase, Spain

In February 2006, a patient colonized with a multidrug-resistant sequence type 56 Acinetobacter baumannii strain was admitted to a hospital in Madrid, Spain. This strain spread rapidly and caused a large outbreak in the hospital. Clinicians should be alert for this strain because its spread would have serious health consequences

A General Model for Multilocus Epistatic Interactions in Case-Control Studies

Background: Epistasis, i.e., the interaction of alleles at different loci, is thought to play a central role in the formation and progression of complex diseases. The complexity of disease expression should arise from a complex network of epistatic interactions involving multiple genes. Methodology: We develop a general model for testing high-order epistatic interactions for a complex disease in a casecontrol study. We incorporate the quantitative genetic theory of high-order epistasis into the setting of cases and controls sampled from a natural population. The new model allows the identification and testing of epistasis and its various genetic components. Conclusions: Simulation studies were used to examine the power and false positive rates of the model under different sampling strategies. The model was used to detect epistasis in a case-control study of inflammatory bowel disease, in which five SNPs at a candidate gene were typed, leading to the identification of a significant three-locus epistasis