Sound communication inNezara viridula (L.) (Heteroptera: Pentatomidae): Further evidence that signal transmission is substrate-borne

We investigated the sound communication associated with mating inNezara viridula (L.) to clarify conflicting reports on the medium through which acoustic signals are borne. Recordings made from virgin pairs ofN. viridula during precopulatory and compulatory behaviour have revealed that signals transmitted as vibrations through the substrate are a more likely means of communication than signals transmitted by a radiation of sound pressure waves through the air (at least in Australian populations). We present evidence (additional to that already in the literature) that air-borne acoustics are an unlikely mechanism of sexual communication in this species. Specifically, the recorded pulse train patterns showed no consistency or repeatability in relation to different stages of mating behaviour. In contrast, frequency spectrograms of substrate-borne signals reveal repeatable patterns that do correspond with the stage of mating behaviour.     

A latent class probit model for analyzing pick any/N data

A latent class probit model is developed in which it is assumed that the binary data of a particular subject follow a finite mixture of multivariate Bermoulli distributions. An EM algorithm for fitting the model is described and a Monte Carlo procedure for testing the number of latent classes that is required for adequately describing the data is discussed. In the final section, an application of the latent class probit model to some intended purchase data for residential telecommunication devices is reported. Geert De Soete is supported as “Bevoegdverklaard Navorser” of the Belgian “Nationaal Fonds voor Wetenschappelijk Onderzoek.”     

Aspirin-like drugs may block pain independently of prostaglandin synthesis inhibition

Summary Using flurbiprofen, a chiral anti-inflammatory and analgesic 2-arylpropionic acid derivative, the enantiomers of which are not converted to each other (less than 5%) in rats or man, we obtained evidence that prostaglandin synthesis inhibition is primarily mediating the anti-inflammatory activity but prostaglandin synthesis independent mechanisms contribute to the analgesic effects. Thus, the S-form inhibited prostaglandin synthesis, inflammation and nociception in rats. The R-form had much less effect on prostaglandin synthesis and did not affect inflammation. It did, however, block nociception in rats almost as potently as the S-form. S-flurbiprofen, in contrast to the R-form, was clearly ulcerogenic in the gastrointestinal mucosa. These results indicate additional molecular mechanisms of analgesia and suggest the use of R-arylpropionic acids as analgesics.     

Non-Minimum Phase Nonlinear System Predictive Control Based on Local Recurrent Neural Networks

Abstract: After a recursive multi-step-ahead predictor for nonlinear systems based on local recurrent neural networks isintroduced, an intelligent PID controller is adopted to correct the errors including identified model errors and accumulatederrors produced in the recursive process. Characterized by predictive control, this method can achieve a good controlaccuracy and has good robustness. A simulation study shows that this control algorithm is very effective.     

Dynamic Characteristics of Inter-Satellite Links in LEO Networks

To establish an efficient inter-satellite link (ISL) in an LEO network, the effect of geometric characteristics of ISL on the ISLs and the devices on the LEO satellite should be examined. Because of the continuous movement of the LEO satellite, the time-varying behaviours of the ISL's geometric charactersistics continuously change with the changes of the satellite's position on the orbit. These dynamic geometric characteristics of the ISLs are important for ISL's performance analyzing and the design of the devices on the LEO satellite. This paper describes dynamic geometric characteristics of ISL, analyzes the impact of these regulations on the tracking system of the satellite's antenna and the power adjusting system of the satellite's transmitter, with the Iridium system as an example.     

Development and function of T cells in mice rendered interleukin-2 deficient by gene targeting.

Interleukin-2 (IL-2) is a lymphocytotropic hormone which is thought to have a key role in the immune response of mammalian cells. It is produced by a subpopulation of activated T-lymphocytes and acts in vitro as the principal auto- and paracrine T-cell growth factor (for reviews see refs 1-3). IL-2 is, however, not the sole T-cell growth factor, nor does it act exclusively on T cells, also promoting growth of NK cells and differentiation of B cells. A role for IL-2 in T-cell development has been postulated but remains controversial. Here we test the requirement for IL-2 in vivo using IL-2-deficient mice generated by targeted recombination. We find that mice homozygous for the IL-2 gene mutation are normal with regard to thymocyte and peripheral T-cell subset composition, but that a dysregulation of the immune system is manifested by reduced polyclonal in vitro T-cell responses and by dramatic changes in the isotype levels of serum immunoglobulins.     

Radar Imaging Based on Iterative Algorithms

It has long been realized that the problem of radar imaging is a special case of image reconstruction in which the data are incomplete and noisy. In other fields, iterative reconstruction algorithms have been used successfully to improve the image quality. This paper studies the application of iterative algorithms in radar imaging. A discrete model is first derived, and the iterative algorithms are then adapted to radar imaging. Although such algorithms are usually time consuming, this paper shows that, if the algorithms are appropriately simplified, it is possible to realize them even in real time. The efficiency of iterative algorithms is shown through computer simulations.     

Face Recognition Based on Support Vector Machine and Nearest Neighbor Classifier

Support vector machine (SVM), as a novel approach in pattern recognition, has demonstrated a success in face detection and face recognition. In this paper, a face recognition approach based on the SVM classifier with the nearest neighbor classifier (NNC) is proposed. The principal component analysis (PCA) is used to reduce the dimension and extract features. Then one-against-all stratedy is used to train the SVM classifiers. At the testing stage, we propose an al-