Short-term rainfall nowcasting: using rainfall radar imaging

As one of the most useful sources of quantitative precipitation measurement, rainfall radar analysis can be a very useful focus for research into developing methods for rainfall prediction. Because radar can estimate rainfall distribution over a wide range, it is thus very attractive for weather prediction over a large area. Short lead time rainfall prediction is often needed in meteorological and hydrological applications where accurate prediction of rainfall can help with flood relief, with agriculture and with event planning. A system of short-term rainfall prediction over Ireland using rainfall radar image processing is presented in this paper. As the only input, consecutive rainfall radar images are processed to predict the development of rainfall by means of morphological methods and movement extrapolation. The results of a series of experimental evaluations demonstrate the ability and efficiency of using our rainfall radar imaging in a nowcasting system

Dynamic and Quantitative Method of Analyzing Service Consistency Evolution Based on Extended Hierarchical Finite State Automata

This paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA). Traditional methods are mostly qualitative and empirical, and they do not consider the dynamic disturbances among factors in service’s evolution behaviors such as producing, publishing, calling, and maintenance. Moreover, SODSA are rapidly evolving in terms of large-scale, reusable, compositional, pervasive, and flexible features, which presents difficulties in the usage of traditional analysis methods. To resolve these problems, a novel dynamic evolution model extended hierarchical service-finite state automata (EHS-FSA) is constructed based on finite state automata (FSA), which formally depict overall changing processes of service consistency states. And also the service consistency evolution algorithms (SCEAs) based on EHS-FSA are developed to quantitatively assess these impact factors. Experimental results show that the bad reusability (17.93% on average) is the biggest influential factor, the noncomposition of atomic services (13.12%) is the second biggest one, and the service version’s confusion (1.2%) is the smallest one. Compared with previous qualitative analysis, SCEAs present good effectiveness and feasibility. This research can guide the engineers of service consistency technologies toward obtaining a higher level of consistency in SODSA

Extended Traffic Alert Information to Improve TCAS Performance by means of Causal Models

Near-midair collisions (NMACs) between aircraft have long been a primary safety concern and have incessantly motivated the development of ingenious onboard collision avoidance (CA) systems to reduce collision risk. The Traffic Alert and Collision Avoidance System (TCAS) acts as a proverbially accepted last-resort means to resolve encounters, while it also has been proved to potentially induce a collision in the hectic and congested traffic. This paper aims to improve the TCAS collision avoidance performance by enriching traffic alert information, which strictly fits with present TCAS technological requirements and extends the threat detection considering induced collisions and probabilistic pilot response. The proposed model is specified in coloured Petri net (CPN) formalism, to generate by simulation all the future possible downstream reachable states to enhance the follow-up decision making of pilots via synthesising relevant information related to collision states. With the complete state space, the potential collision scenarios can be identified together with those manoeuvres that may transform a conflict into a collision. The causal TCAS model is demonstrated to work effectively for complex multiaircraft scenarios and to identify the feasible manoeuvres that contribute to reduce the nonzero TCAS-induced collision risk

Extended Traffic Alert Information to Improve TCAS Performance by means of Causal Models

Near-midair collisions (NMACs) between aircraft have long been a primary safety concern and have incessantly motivated the development of ingenious onboard collision avoidance (CA) systems to reduce collision risk. The Traffic Alert and Collision Avoidance System (TCAS) acts as a proverbially accepted last-resort means to resolve encounters, while it also has been proved to potentially induce a collision in the hectic and congested traffic. This paper aims to improve the TCAS collision avoidance performance by enriching traffic alert information, which strictly fits with present TCAS technological requirements and extends the threat detection considering induced collisions and probabilistic pilot response. The proposed model is specified in coloured Petri net (CPN) formalism, to generate by simulation all the future possible downstream reachable states to enhance the followup decision making of pilots via synthesising relevant information related to collision states. With the complete state space, the potential collision scenarios can be identified together with those manoeuvres that may transform a conflict into a collision. The causal TCAS model is demonstrated to work effectively for complex multiaircraft scenarios and to identify the feasible manoeuvres that contribute to reduce the nonzero TCAS-induced collision risk

A synthetic arabinose-inducible promoter confers high levels of recombinant protein expression in hyperthermophilic archaeon <em>Sulfolobus islandicus</em>

Despite major progresses in genetic studies of hyperthermophilic archaea, recombinant protein production in these organisms always suffers from low yields and a robust expression system is still in great demand. Here we report a versatile vector that confers high levels of protein expression in Sulfolobus islandicus, a hyperthermophilic crenarchaeon. Two expression vectors, pSeSD and pEXA, harboring 11 unique restriction sites were constructed. They contain coding sequences of two hexahistidine (6×His) peptide tags and those coding for two protease sites, the latter of which make it possible to remove the peptide tags from expressed recombinant proteins. While pEXA employed an araS promoter for protein expression, pSeSD utilized P(araS-SD), an araS derivative promoter carrying an engineered ribosome-binding site (RBS; a Shine-Dalgarno [SD] sequence). We found that P(araS-SD) directed high levels of target gene expression. More strikingly, N-terminal amino acid sequencing of recombinant proteins unraveled that the protein synthesized from pEXA-N-lacS lacked the designed 6×His tag and that translation initiation did not start at the ATG codon of the fusion gene. Instead, it started at multiple sites downstream of the 6×His codons. Intriguingly, inserting an RBS site upstream of the ATG codon regained the expression of the 6×His tag, as shown with pSeSD-N-lacS. These results have yielded novel insight into the archaeal translation mechanism. The crenarchaeon Sulfolobus can utilize N-terminal coding sequences of proteins to specify translation initiation in the absence of an RBS site