Newly discovered viruses of flying foxes

Flying foxes have been the focus of research into three newly described viruses from the order Mononegavirales, namely Hendra virus (HeV), Menangle virus and Australian Bat Lyssavirus (ABL). Early investigations indicate that flying foxes are the reservoir host for these viruses. In 1994, two outbreaks of a new zoonotic disease affecting horses and humans occurred in Queensland. The virus which was found to be responsible was called equine morbillivirus (EMV) and has since been renamed HeV. Investigation into the reservoir of HeV has produced evidence that antibodies capable of neutralising HeV have only been detected in flying foxes. Over 20% of flying foxes in eastern Australia have been identified as being seropositive. Additionally six species of flying foxes in Papua New Guinea have tested positive for antibodies to HeV. In 1996 a virus from the family Paramyxoviridae was isolated from the uterine fluid of a female flying fox. Sequencing of 10 000 of the 18 000 base pairs (bp) has shown that the sequence is identical to the HeV sequence. As part of investigations into HeV, a virus was isolated from a juvenile flying fox which presented with neurological signs in 1996. This virus was characterised as belonging to the family Rhabdoviridae, and was named ABL. Since then four flying fox species and one insectivorous species have tested positive for ABL. The third virus to be detected in flying foxes is Menangle virus, belonging to the family Paramyxoviridae. This virus was responsible for a zoonotic disease affecting pigs and humans in New South Wales in 1997. Antibodies capable of neutralising Menangle virus, were detected in flying foxes. (C) 1999 Elsevier Science B.V. All rights reserved.

Authorship Attribution with Support Vector Machines

In this paper we explore the use of text-mining methods for the identification of the author of a text. We apply the support vector machine (SVM) to this problem, as it is able to cope with half a million of inputs it requires no feature selection and can process the frequency vector of all words of a text. We performed a number of experiments with texts from a German newspaper. With nearly perfect reliability the SVM was able to reject other authors and detected the target author in 60–80% of the cases. In a second experiment, we ignored nouns, verbs and adjectives and replaced them by grammatical tags and bigrams. This resulted in slightly reduced performance. Author detection with SVMs on full word forms was remarkably robust even if the author wrote about different topics.

Optimization of PCB component placements for the collect-and-place machines

This paper presents two hybrid genetic algorithms (HGAs) to optimize the component placement operation for the collect-and-place machines in printed circuit board (PCB) assembly. The component placement problem is to optimize (i) the assignment of components to a movable revolver head or assembly tour, (ii) the sequence of component placements on a stationary PCB in each tour, and (iii) the arrangement of component types to stationary feeders simultaneously. The objective of the problem is to minimize the total traveling time spent by the revolver head for assembling all components on the PCB. The major difference between the HGAs is that the initial solutions are generated randomly in HGA1. The Clarke and Wright saving method, the nearest neighbor heuristic, and the neighborhood frequency heuristic are incorporated into HGA2 for the initialization procedure. A computational study is carried out to compare the algorithms with different population sizes. It is proved that the performance of HGA2 is superior to HGA1 in terms of the total assembly time.

An integrated scheduling problem of PCB components on sequential pick-and-place machines:mathematical models and heuristic solutions

This paper formulates several mathematical models for determining the optimal sequence of component placements and assignment of component types to feeders simultaneously or the integrated scheduling problem for a type of surface mount technology placement machines, called the sequential pick-andplace (PAP) machine. A PAP machine has multiple stationary feeders storing components, a stationary working table holding a printed circuit board (PCB), and a movable placement head to pick up components from feeders and place them to a board. The objective of integrated problem is to minimize the total distance traveled by the placement head. Two integer nonlinear programming models are formulated first. Then, each of them is equivalently converted into an integer linear type. The models for the integrated problem are verified by two commercial packages. In addition, a hybrid genetic algorithm previously developed by the authors is adopted to solve the models. The algorithm not only generates the optimal solutions quickly for small-sized problems, but also outperforms the genetic algorithms developed by other researchers in terms of total traveling distance.