Improved high-speed de-excitation system for brushless synchronous machines tested on a 20 MVA hydro-generator

Synchronous machines with brushless excitation have the disadvantage that the field winding is not accessible for the de-excitation of the machine. This means that, despite the proper operation of the protection system, the slow de-excitation time constant may produce severe damage in the event of an internal short circuit. A high-speed de-excitation system for these machines was developed, and this study presents the continuation of a previously published study. This study presents the design by computer simulation and the results of the first commissioning of this de-excitation system in a commercial 20 MVA hydro-generator. The de-excitation is achieved by inserting resistance in the field circuit, obtaining a dynamic response similar to that achieved in machines with static excitation. In this case, a non-linear discharge resistor was used, making the dynamic response even better.

Field-winding fault detection in synchronous machines with static excitation through frequency response analysis.

Frequency Response Analysis is a well-known technique for the diagnosis of power transformers. Currently, this technique is under research for its application in rotary electrical machines. This paper presents significant results on the application of Frequency Response Analysis to fault detection in field winding of synchronous machines with static excitation. First, the influence of the rotor position on the frequency response is evaluated. Secondly, some relevant test results are shown regarding ground fault and inter-turn fault detection in field windings at standstill condition. The influence of the fault resistance value is also taken into account. This paper also studies the applicability of Frequency Response Analysis in fault detection in field windings while rotating. This represents an important feature because some defects only appear with the machine rated speed. Several laboratory test results show the applicability of this fault detection technique in field windings at full speed with no excitation current.

New Fault-Resistance Estimation Algorithm for Rotor-Winding Ground-Fault Online Location in Synchronous Machines With Static Excitation

New Fault-Resistance Estimation Algorithm for Rotor-Winding Ground-Fault Online Location in Synchronous Machines With Static Excitation

Reciprocal secretion of proteins by the bacterial type III machines of plant and animal pathogens suggests universal recognition of mRNA targeting signals

Bacterial pathogens of both animals and plants use type III secretion machines to inject virulence proteins into host cells. Although many components of the secretion machinery are conserved among different bacterial species, the substrates for their type III pathways are not. The Yersinia type III machinery recognizes some secretion substrates via a signal that is encoded within the first 15 codons of yop mRNA. These signals can be altered by frameshift mutations without affecting secretion of the encoded polypeptides, suggesting a mechanism whereby translation of yop mRNA is coupled to the translocation of newly synthesized polypeptide. We report that the type III machinery of Erwinia chrysanthemi cloned in Escherichia coli recognizes the secretion signals of yopE and yopQ. Pseudomonas syringae AvrB and AvrPto, two proteins exported by the recombinant Erwinia machine, can also be secreted by the Yersinia type III pathway. Mapping AvrPto sequences sufficient for the secretion of reporter fusions in Yersinia revealed the presence of an mRNA secretion signal. We propose that 11 conserved components of type III secretion machines may recognize signals that couple mRNA translation to polypeptide secretion.

Knowledge-based analysis of microarray gene expression data by using support vector machines

We introduce a method of functionally classifying genes by using gene expression data from DNA microarray hybridization experiments. The method is based on the theory of support vector machines (SVMs). SVMs are considered a supervised computer learning method because they exploit prior knowledge of gene function to identify unknown genes of similar function from expression data. SVMs avoid several problems associated with unsupervised clustering methods, such as hierarchical clustering and self-organizing maps. SVMs have many mathematical features that make them attractive for gene expression analysis, including their flexibility in choosing a similarity function, sparseness of solution when dealing with large data sets, the ability to handle large feature spaces, and the ability to identify outliers. We test several SVMs that use different similarity metrics, as well as some other supervised learning methods, and find that the SVMs best identify sets of genes with a common function using expression data. Finally, we use SVMs to predict functional roles for uncharacterized yeast ORFs based on their expression data.

Energy metabolism, enzymatic flux capacities, and metabolic flux rates in flying honeybees.

Honeybees rely primarily on the oxidation of hexose sugars to provide the energy required for flight. Measurement of VCO2 (equal to VO2, because VCO2/VO2 = 1.0 during carbohydrate oxidation) during flight allowed estimation of steady-state flux rates through pathways of flight muscle energy metabolism. Comparison of Vmax values for flight muscle hexokinase, phosphofructokinase, citrate synthase, and cytochrome c oxidase with rates of carbon and O2 flux during flight reveal that these enzymes operate closer to Vmax in the flight muscles of flying honeybees than in other muscles previously studied. Possible mechanistic and evolutionary implications of these findings are discussed.

Female Psychopaths: Are We Flying Under the Radar?

The study of psychopathy is still in early stages with regard to gender differences. Historically, the majority of research has been conducted on male populations, resulting in a gender-biased construct that does not appear to be generalizable to female populations. This paper provides a review of the existing literature on psychopathy, as well as research on inherent gender differences (biology, chemistry, socialization, etc.). Connections between these bodies of research are supposed and suggestions for future study are provided.

Reverse Vending Machines: A Potential Solution for the Florida Plastic Waste Management Challenge

The waste of plastic beverage bottles creates environmental problems and takes up a large volume of landfill space. The high rate of consumption of plastics in the State of Florida is challenging the disposal capacity of waste authorities. The lack of the reverse vending machines in the State of Florida, including applicable scientific or technical literature represented an opportunity for this research to discuss the applicability of this equipment as a potential solution for the management of the plastic waste in Florida. With this research document, I will propose a recycling system for plastic bottles made with PET based on the implementation of reverse vending machines, stressing the importance of the creation of policies that promote recycling and public participation.