Online Inverse Optimal Control for Control-Constrained Discrete-Time Systems on Finite and Infinite Horizons

In this paper, we consider the problem of computing parameters of an objective function for a discrete-time optimal control problem from state and control trajectories with active control constraints. We propose a novel method of inverse optimal control that has a computationally efficient online form in which pairs of states and controls from given state and control trajectories are processed sequentially without being stored or processed in batches. We establish conditions guaranteeing the uniqueness of the objective-function parameters computed by our proposed method from trajectories with active control constraints. We illustrate our proposed method in simulation.Comment: 10 pages, 4 figures, Accepted for publication in Automatic

Below Horizon Aircraft Detection Using Deep Learning for Vision-Based Sense and Avoid

Commercial operation of unmanned aerial vehicles (UAVs) would benefit from an onboard ability to sense and avoid (SAA) potential mid-air collision threats. In this paper we present a new approach for detection of aircraft below the horizon. We address some of the challenges faced by existing vision-based SAA methods such as detecting stationary aircraft (that have no relative motion to the background), rejecting moving ground vehicles, and simultaneous detection of multiple aircraft. We propose a multi-stage, vision-based aircraft detection system which utilises deep learning to produce candidate aircraft that we track over time. We evaluate the performance of our proposed system on real flight data where we demonstrate detection ranges comparable to the state of the art with the additional capability of detecting stationary aircraft, rejecting moving ground vehicles, and tracking multiple aircraft

A Prognostic Gene Expression Profile That Predicts Circulating Tumor Cell Presence in Breast Cancer Patients

The detection of circulating tumor cells (CTCs) in the peripheral blood and microarray gene expression profiling of the primary tumor are two promising new technologies able to provide valuable prognostic data for patients with breast cancer. Meta-analyses of several established prognostic breast cancer gene expression profiles in large patient cohorts have demonstrated that despite sharing few genes, their delineation of patients into “good prognosis” or “poor prognosis” are frequently very highly correlated, and combining prognostic profiles does not increase prognostic power. In the current study, we aimed to develop a novel profile which provided independent prognostic data by building a signature predictive of CTC status rather than outcome. Microarray gene expression data from an initial training cohort of 72 breast cancer patients for which CTC status had been determined in a previous study using a multimarker QPCR-based assay was used to develop a CTC-predictive profile. The generated profile was validated in two independent datasets of 49 and 123 patients and confirmed to be both predictive of CTC status, and independently prognostic. Importantly, the “CTC profile” also provided prognostic information independent of the well-established and powerful ‘70-gene’ prognostic breast cancer signature. This profile therefore has the potential to not only add prognostic information to currently-available microarray tests but in some circumstances even replace blood-based prognostic CTC tests at time of diagnosis for those patients already undergoing testing by multigene assays

Optimal Bayesian Quickest Detection for Hidden Markov Models and Structured Generalisations

In this paper we consider the problem of quickly detecting changes in hidden Markov models (HMMs) in a Bayesian setting, as well as several structured generalisations including changes in statistically periodic processes, quickest detection of a Markov process across a sensor array, quickest detection of a moving target in a sensor network and quickest change detection (QCD) in multistream data. Our main result establishes an optimal Bayesian HMM QCD rule with a threshold structure. This framework and proof techniques allow us to to elegantly establish optimal rules for several structured generalisations by showing that these problems are special cases of the Bayesian HMM QCD problem. We develop bounds to characterise the performance of our optimal rule and provide an efficient method for computing the test statistic. Finally, we examine the performance of our rule in several simulation examples and propose a technique for calculating the optimal threshold

De novo identification of differentially methylated regions in the human genome

Background: The identification and characterisation of differentially methylated regions (DMRs) between phenotypes in the human genome is of prime interest in epigenetics. We present a novel method, DMRcate, that fits replicated methylation measurements from the Illumina HM450K BeadChip (or 450K array) spatially across the genome using a Gaussian kernel. DMRcate identifies and ranks the most differentially methylated regions across the genome based on tunable kernel smoothing of the differential methylation (DM) signal. The method is agnostic to both genomic annotation and local change in the direction of the DM signal, removes the bias incurred from irregularly spaced methylation sites, and assigns significance to each DMR called via comparison to a null model. Results: We show that, for both simulated and real data, the predictive performance of DMRcate is superior to those of Bumphunter and Probe Lasso, and commensurate with that of comb-p. For the real data, we validate all array-derived DMRs from the candidate methods on a suite of DMRs derived from whole-genome bisulfite sequencing called from the same DNA samples, using two separate phenotype comparisons. Conclusions: The agglomeration of genomically localised individual methylation sites into discrete DMRs is currently best served by a combination of DM-signal smoothing and subsequent threshold specification. The findings also suggest the design of the 450K array shows preference for CpG sites that are more likely to be differentially methylated, but its overall coverage does not adequately reflect the depth and complexity of methylation signatures afforded by sequencing. For the convenience of the research community we have created a user-friendly R software package called DMRcate, downloadable from Bioconductor and compatible with existing preprocessing packages, which allows others to apply the same DMR-finding method on 450K array data

Comparing rates of adverse events detected in incident reporting and the Global Trigger Tool: a systematic review

Many hospitals continue to use incident reporting systems (IRSs) as their primary patient safety data source. The information IRSs collect on the frequency of harm to patients [adverse events (AEs)] is generally of poor quality, and some incident types (e.g. diagnostic errors) are under-reported. Other methods of collecting patient safety information using medical record review, such as the Global Trigger Tool (GTT), have been developed. The aim of this study was to undertake a systematic review to empirically quantify the gap between the percentage of AEs detected using the GTT to those that are also detected via IRSs. The review was conducted in adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Studies published in English, which collected AE data using the GTT and IRSs, were included. In total, 14 studies met the inclusion criteria. All studies were undertaken in hospitals and were published between 2006 and 2022. The studies were conducted in six countries, mainly in the USA (nine studies). Studies reviewed 22 589 medical records using the GTT across 107 institutions finding 7166 AEs. The percentage of AEs detected using the GTT that were also detected in corresponding IRSs ranged from 0% to 37.4% with an average of 7.0% (SD 9.1; median 3.9 and IQR 5.2). Twelve of the fourteen studies found 10-fold gap between the detection rates of the GTT and IRSs is strong evidence that the rate of AEs collected in IRSs in hospitals should not be used to measure or as a proxy for the level of safety of a hospital. IRSs should be recognized for their strengths which are to detect rare, serious, and new incident types and to enable analysis of contributing and contextual factors to develop preventive and corrective strategies. Health systems should use multiple patient safety data sources to prioritize interventions and promote a cycle of action and improvement based on data rather than merely just collecting and analysing information

\u3ci\u3eAquastella gen. nov.\u3c/i\u3e: A new genus of saprolegniaceous oomycete rotifer parasites related to \u3ci\u3eAphanomyces\u3c/i\u3e, with unique sporangial outgrowths

The oomycete genus Aquastella is described to accommodate two new species of parasites of rotifers observed in Brooktrout Lake, New York State, USA. Three rotifer species – Keratella taurocephala,Polyarthra vulgaris, and Ploesoma truncatum – were infected, and this is the first report of oomycete infection in these species. Aquastella attenuata was specific to K. taurocephala and Aquastella aciculariswas specific to P. vulgaris and P. truncatum. The occurrence of infections correlated with peak host population densities and rotifers were infected in the upper layers of the water column. Sequencing of 18S rRNA and phylogenetic analysis of both species placed them within the order Saprolegniales, in a clade closely related to Aphanomyces. The Aquastella species were morphologically distinct from other rotifer parasites as the developing sporangia penetrated out through the host body following its death to produce unique tapered outgrowths. Aquastella attenuata produced long, narrow, tapering, finger-like outgrowths, whilst A. acicularis produced shorter, spike-like outgrowths. We hypothesize that the outgrowths serve to deter predation and slow descent in the water column. Spore cleavage was intrasporangial with spore release through exit tubes. Aquastella attenuata produced primary zoospores, whereas A. acicularisreleased spherical primary aplanospores, more typical of other genera in the Aphanomyces clade