Bats, Bat Flies, and Fungi: Exploring Uncharted Waters

Bats serve as hosts to many lineages of arthropods, of which the blood-sucking bat flies (Nycteribiidae and Streblidae) are the most conspicuous. Bat flies can in turn be parasitized by Laboulbeniales fungi, which are biotrophs of arthropods. This is a second level of parasitism, hyperparasitism, a severely understudied phenomenon. Four genera of Laboulbeniales are known to occur on bat flies, Arthrorhynchus on Nycteribiidae in the Eastern Hemisphere, Dimeromyces on Old World Streblidae, Gloeandromyces on New World Streblidae, and Nycteromyces on Streblidae in both hemispheres. In this chapter, we introduce the different partners of the tripartite interaction and discuss their species diversity, ecology, and patterns of specificity. We cover parasite prevalence of Laboulbeniales fungi on bat flies, climatic effects on parasitism of bat flies, and coevolutionary patterns. One of the most important questions in this tripartite system is whether habitat has an influence on parasitism of bat flies by Laboulbeniales fungi. We hypothesize that habitat disturbance causes parasite prevalence to increase, in line with the “dilution effect.” This can only be resolved based on large, non-biased datasets. To obtain these, we stress the importance of multitrophic field expeditions and international collaborations

Flexible modelling of spatial variation in agricultural field trials with the R package INLA

The objective of this paper was to fit different established spatial models for analysing agricultural field trials using the open-source R package INLA. Spatial variation is common in field trials, and accounting for it increases the accuracy of estimated genetic effects. However, this is still hindered by the lack of available software implementations. We compare some established spatial models and show possibilities for flexible modelling with respect to field trial design and joint modelling over multiple years and locations. We use a Bayesian framework and for statistical inference the integrated nested Laplace approximations (INLA) implemented in the R package INLA. The spatial models we use are the well-known independent row and column effects, separable first-order autoregressive ( AR1⊗AR1 ) models and a Gaussian random field (Matérn) model that is approximated via the stochastic partial differential equation approach. The Matérn model can accommodate flexible field trial designs and yields interpretable parameters. We test the models in a simulation study imitating a wheat breeding programme with different levels of spatial variation, with and without genome-wide markers and with combining data over two locations, modelling spatial and genetic effects jointly. The results show comparable predictive performance for both the AR1⊗AR1 and the Matérn models. We also present an example of fitting the models to a real wheat breeding data and simulated tree breeding data with the Nelder wheel design to show the flexibility of the Matérn model and the R package INLA

Total Dose and Single Event Effects (SEE) in a 0.25μm CMOS Technology

Individual transistors, resistors and shift registers have been designed using radiation tolerant layout practices in a commercial quarter micron process. A modelling effort has led to a satisfactory formulation for the effective aspect ratio of the enclosed transistors used in these layout practices. All devices have been tested up to a total dose of 30Mrad(SiO 2 ). The threshold voltage shift after irradiation and annealing was about +45mV for NMOS and-55mV for PMOS transistors, no leakage current appeared, and the mobility degradation was below 6%. The value of resistors increased by less than 10%. Noise measurements made on transistors with W=2mm and L varying between 0.36 and 0.64Pm revealed a corner noise frequency of about 200kHz for the NMOS and 12kHz for the PMOS. Irradiation up to 30Mrad(SiO 2 ) did not significantly affect the noise performance. The shift registers continuously operated at 1.25MHz during the irradiation, and no error was detected in the pattern propagation...