Nuclear localization of NPR1 is required for activation of PR gene expression

Systemic acquired resistance (SAR) is a broad-spectrum resistance in plants that involves the upregulation of a battery of pathogenesis-related (PR) genes. NPR1 is a key regulator in the signal transduction pathway that leads to SAR. Mutations in NPR1 result in a failure to induce PR genes in systemic tissues and a heightened susceptibility to pathogen infection, whereas overexpression of the NPR1 protein leads to increased induction of the PR genes and enhanced disease resistance. We analyzed the subcellular localization of NPR1 to gain insight into the mechanism by which this protein regulates SAR. An NPR1–green fluorescent protein fusion protein, which functions the same as the endogenous NPR1 protein, was shown to accumulate in the nucleus in response to activators of SAR. To control the nuclear transport of NPR1, we made a fusion of NPR1 with the glucocorticoid receptor hormone binding domain. Using this steroid-inducible system, we clearly demonstrate that nuclear localization of NPR1 is essential for its activity in inducing PR genes.

Optimal-stopping control for airborne collision avoidance and return-to-course flight

This paper considers an aircraft collision avoidance design problem that also incorporates design of the aircraft’s return-to-course flight. This control design problem is formulated as a non-linear optimal-stopping control problem; a formulation that does not require a prior knowledge of time taken to perform the avoidance and return-to-course manoeuvre. A dynamic programming solution to the avoidance and return-to-course problem is presented, before a Markov chain numerical approximation technique is described. Simulation results are presented that illustrate the proposed collision avoidance and return-to-course flight approach.

Proactive detection of high collision concentration locations on highways

In previous research (Chung et al., 2009), the potential of the continuous risk profile (CRP) to proactively detect the systematic deterioration of freeway safety levels was presented. In this paper, this potential is investigated further, and an algorithm is proposed for proactively detecting sites where the collision rate is not sufficiently high to be classified as a high collision concentration location but where a systematic deterioration of safety level is observed. The approach proposed compares the weighted CRP across different years and uses the cumulative sum (CUSUM) algorithm to detect the sites where changes in collision rate are observed. The CRPs of the detected sites are then compared for reproducibility. When high reproducibility is observed, a growth factor is used for sequential hypothesis testing to determine if the collision profiles are increasing over time. Findings from applying the proposed method using empirical data are documented in the paper together with a detailed description of the method.

Detection versus false alarm characterisation of a vision-based airborne dim-target collision detection system

This paper presents a preliminary flight test based detection range versus false alarm performance characterisation of a morphological-hidden Markov model filtering approach to vision-based airborne dim-target collision detection. On the basis of compelling in-flight collision scenario data, we calculate system operating characteristic (SOC) curves that concisely illustrate the detection range versus false alarm rate performance design trade-offs. These preliminary SOC curves provide a more complete dim-target detection performance description than previous studies (due to the experimental difficulties involved, previous studies have been limited to very short flight data sample sets and hence have not been able to quantify false alarm behaviour). The preliminary investigation here is based on data collected from 4 controlled collision encounters and supporting non-target flight data. This study suggests head-on detection ranges of approximately 2.22 km under blue sky background conditions (1.26 km in cluttered background conditions), whilst experiencing false alarms at a rate less than 1.7 false alarms/hour (ie. less than once every 36 minutes). Further data collection is currently in progress.

Reactive image-based collision avoidance system for unmanned aircraft systems

Approximately 20 years have passed now since the NTSB issued its original recommendation to expedite development, certification and production of low-cost proximity warning and conflict detection systems for general aviation [1]. While some systems are in place (TCAS [2]), ¡¨see-and-avoid¡¨ remains the primary means of separation between light aircrafts sharing the national airspace. The requirement for a collision avoidance or sense-and-avoid capability onboard unmanned aircraft has been identified by leading government, industry and regulatory bodies as one of the most significant challenges facing the routine operation of unmanned aerial systems (UAS) in the national airspace system (NAS) [3, 4]. In this thesis, we propose and develop a novel image-based collision avoidance system to detect and avoid an upcoming conflict scenario (with an intruder) without first estimating or filtering range. The proposed collision avoidance system (CAS) uses relative bearing ƒÛ and angular-area subtended ƒê , estimated from an image, to form a test statistic AS C . This test statistic is used in a thresholding technique to decide if a conflict scenario is imminent. If deemed necessary, the system will command the aircraft to perform a manoeuvre based on ƒÛ and constrained by the CAS sensor field-of-view. Through the use of a simulation environment where the UAS is mathematically modelled and a flight controller developed, we show that using Monte Carlo simulations a probability of a Mid Air Collision (MAC) MAC RR or a Near Mid Air Collision (NMAC) RiskRatio can be estimated. We also show the performance gain this system has over a simplified version (bearings-only ƒÛ ). This performance gain is demonstrated in the form of a standard operating characteristic curve. Finally, it is shown that the proposed CAS performs at a level comparable to current manned aviations equivalent level of safety (ELOS) expectations for Class E airspace. In some cases, the CAS may be oversensitive in manoeuvring the owncraft when not necessary, but this constitutes a more conservative and therefore safer, flying procedures in most instances.

Collision warning dissemination in vehicles strings : an empirical measurement

Inter-Vehicular Communications (IVC) are considered a promising technological approach for enhancing transportation safety and improving highway efficiency. Previous theoretical work has demonstrated the benefits of IVC in vehicles strings. Simulations of partially IVC-equipped vehicles strings showed that only a small equipment ratio is sufficient to drastically reduce the number of head on collisions. However, these results are based on the assumptions that IVC exhibit lossless and instantaneous messages transmission. This paper presents the research design of an empirical measurement of a vehicles string, with the goal of highlighting the constraints introduced by the actual characteristics of communication devices. A warning message diffusion system based on IEEE 802.11 wireless technology was developed for an emergency breaking scenario. Preliminary results are presented as well, showing the latencies introduced by using 802.11a and discussing early findings and experimental limitations

Using cooperative vehicle systems to collect near collision incidents events : a simulation study

On the road, near collision events (also close calls or near-miss incidents) largely outnumber actual crashes, yet most of them can never be recorded by current traffic data collection technologies or crashes analysis tools. The analysis of near collisions data is an important step in the process of reducing the crash rate. There have been several studies that have investigated near collisions; to our knowledge, this is the first study that uses the functionalities provided by cooperative vehicles to collect near misses information. We use the VISSIM traffic simulator and a custom C++ engine to simulate cooperative vehicles and their ability to detect near collision events. Our results showed that, within a simple simulated environment, adequate information on near collision events can be collected using the functionalities of cooperative perception systems. The relationship between the ratio of detected events and the ratio of equipped vehicle was shown to closely follow a squared law, and the largest source of nondetection was packet loss instead of packet delays and GPS imprecision.

Combined mitochondrial and nuclear DNA sequences resolve the interrelations of the major Australasian marsupial radiations

Australasian marsupials include three major radiations, the insectivorous/carnivorous Dasyuromorphia, the omnivorous bandicoots (Peramelemorphia), and the largely herbivorous diprotodontians. Morphologists have generally considered the bandicoots and diprotodontians to be closely related, most prominently because they are both syndactylous (with the 2nd and 3rd pedal digits being fused). Molecular studies have been unable to confirm or reject this Syndactyla hypothesis. Here we present new mitochondrial (mt) genomes from a spiny bandicoot (Echymipera rufescens) and two dasyurids, a fat-tailed dunnart (Sminthopsis crassicaudata) and a northern quoll (Dasyurus hallucatus). By comparing trees derived from pairwise base-frequency differences between taxa with standard (absolute, uncorrected) distance trees, we infer that composition bias among mt protein-coding and RNA sequences is sufficient to mislead tree reconstruction. This can explain incongruence between trees obtained from mt and nuclear data sets. However, after excluding major sources of compositional heterogeneity, both the “reduced-bias” mt and nuclear data sets clearly favor a bandicoot plus dasyuromorphian association, as well as a grouping of kangaroos and possums (Phalangeriformes) among diprotodontians. Notably, alternatives to these groupings could only be confidently rejected by combining the mt and nuclear data. Elsewhere on the tree, Dromiciops appears to be sister to the monophyletic Australasian marsupials, whereas the placement of the marsupial mole (Notoryctes) remains problematic. More generally, we contend that it is desirable to combine mt genome and nuclear sequences for inferring vertebrate phylogeny, but as separately modeled process partitions. This strategy depends on detecting and excluding (or accounting for) major sources of nonhistorical signal, such as from compositional nonstationarity.

Modeling perceived collision risk in port water navigation

An increase in the likelihood of navigational collisions in port waters has put focus on the collision avoidance process in port traffic safety. The most widely used on-board collision avoidance system is the automatic radar plotting aid which is a passive warning system that triggers an alert based on the pilot’s pre-defined indicators of distance and time proximities at the closest point of approaches in encounters with nearby vessels. To better help pilot in decision making in close quarter situations, collision risk should be considered as a continuous monotonic function of the proximities and risk perception should be considered probabilistically. This paper derives an ordered probit regression model to study perceived collision risks. To illustrate the procedure, the risks perceived by Singapore port pilots were obtained to calibrate the regression model. The results demonstrate that a framework based on the probabilistic risk assessment model can be used to give a better understanding of collision risk and to define a more appropriate level of evasive actions.