Integrated restructurable flight control system demonstration results

The purpose of this study was to examine the complementary capabilities of several restructurable flight control system (RFCS) concepts through the integration of these technologies into a complete system. Performance issues were addressed through a re-examination of RFCS functional requirements, and through a qualitative analysis of the design issues that, if properly addressed during integration, will lead to the highest possible degree of fault-tolerant performance. Software developed under previous phases of this contract and under NAS1-18004 was modified and integrated into a complete RFCS subroutine for NASA's B-737 simulation. The integration of these modules involved the development of methods for dealing with the mismatch between the outputs of the failure detection module and the input requirements of the automatic control system redesign module. The performance of this demonstration system was examined through extensive simulation trials

Predicting floods in a large karst river basin by coupling PERSIANN-CCS QPEs with a physically based distributed hydrological model

In general, there are no long-term meteorological or hydrological data available for karst river basins. The lack of rainfall data is a great challenge that hinders the development of hydrological models. Quantitative precipitation estimates (QPEs) based on weather satellites offer a potential method by which rainfall data in karst areas could be obtained. Furthermore, coupling QPEs with a distributed hydrological model has the potential to improve the precision of flood predictions in large karst watersheds. Estimating precipitation from remotely sensed information using an artificial neural network-cloud classification system (PERSIANN-CCS) is a type of QPE technology based on satellites that has achieved broad research results worldwide. However, only a few studies on PERSIANN-CCS QPEs have occurred in large karst basins, and the accuracy is generally poor in terms of practical applications. This paper studied the feasibility of coupling a fully physically based distributed hydrological model, i.e., the Liuxihe model, with PERSIANN-CCS QPEs for predicting floods in a large river basin, i.e., the Liujiang karst river basin, which has a watershed area of 58 270 km-2, in southern China. The model structure and function require further refinement to suit the karst basins. For instance, the sub-basins in this paper are divided into many karst hydrology response units (KHRUs) to ensure that the model structure is adequately refined for karst areas. In addition, the convergence of the underground runoff calculation method within the original Liuxihe model is changed to suit the karst water-bearing media, and the Muskingum routing method is used in the model to calculate the underground runoff in this study. Additionally, the epikarst zone, as a distinctive structure of the KHRU, is carefully considered in the model. The result of the QPEs shows that compared with the observed precipitation measured by a rain gauge, the distribution of precipitation predicted by the PERSIANN-CCS QPEs was very similar. However, the quantity of precipitation predicted by the PERSIANN-CCS QPEs was smaller. A post-processing method is proposed to revise the products of the PERSIANN-CCS QPEs. The karst flood simulation results show that coupling the post-processed PERSIANN-CCS QPEs with the Liuxihe model has a better performance relative to the result based on the initial PERSIANN-CCS QPEs. Moreover, the performance of the coupled model largely improves with parameter re-optimization via the post-processed PERSIANN-CCS QPEs. The average values of the six evaluation indices change as follows: the Nash-Sutcliffe coefficient increases by 14 %, the correlation coefficient increases by 15 %, the process relative error decreases by 8 %, the peak flow relative error decreases by 18 %, the water balance coefficient increases by 8 %, and the peak flow time error displays a 5 h decrease. Among these parameters, the peak flow relative error shows the greatest improvement; thus, these parameters are of page1506 the greatest concern for flood prediction. The rational flood simulation results from the coupled model provide a great practical application prospect for flood prediction in large karst river basins

Undetermined states: how to find them and their applications

We investigate the undetermined sets consisting of two-level, multi-partite pure quantum states, whose reduced density matrices give absolutely no information of their original states. Two approached of finding these quantum states are proposed. One is to establish the relation between codewords of the stabilizer quantum error correction codes (SQECCs) and the undetermined states. The other is to study the local complementation rules of the graph states. As an application, the undetermined states can be exploited in the quantum secret sharing scheme. The security is guaranteed by their undetermineness.Comment: 6 pages, no figur

Temporal expectancies driven by self- and externally generated rhythms

The dynamic attending theory proposes that rhythms entrain periodic fluctuations of attention which modulate the gain of sensory input. However, temporal expectancies can also be driven by the mere passage of time (foreperiod effect). It is currently unknown how these two types of temporal expectancy relate to each other, i.e. whether they work in parallel and have distinguishable neural signatures. The current research addresses this issue. Participants either tapped a 1Hz rhythm (active task) or were passively presented with the same rhythm using tactile stimulators (passive task). Based on this rhythm an auditory target was then presented early, in synchrony, or late. Behavioural results were in line with the dynamic attending theory as RTs were faster for in- compared to out-of-synchrony targets. Electrophysiological results suggested self-generated and externally induced rhythms to entrain neural oscillations in the delta frequency band. Auditory ERPs showed evidence of two distinct temporal expectancy processes. Both tasks demonstrated a pattern which followed a linear foreperiod effect. In the active task, however, we also observed an ERP effect consistent with the dynamic attending theory. This study shows that temporal expectancies generated by a rhythm and expectancy generated by the mere passage of time can work in parallel and sheds light on how these mechanisms are implemented in the brain

Draft Genome Sequence of Mycobacterium arupense Strain GUC1.

We report the draft genome sequence of Mycobacterium arupense strain GUC1 from a sputum sample of a patient with bronchiectasis. This is the first draft genome sequence of Mycobacterium arupense, a rapidly growing nonchromogenic mycobacteria

Draft Genome Sequence of Mycobacterium elephantis Strain Lipa.

We report the draft genome sequence of Mycobacterium elephantis strain Lipa from a sputum sample of a patient with pulmonary disease. This is the first draft genome sequence of M. elephantis, a rapidly growing mycobacterium