Analysis of error propagation in particle filters with approximation

This paper examines the impact of approximation steps that become necessary when particle filters are implemented on resource-constrained platforms. We consider particle filters that perform intermittent approximation, either by subsampling the particles or by generating a parametric approximation. For such algorithms, we derive time-uniform bounds on the weak-sense $L_p$ error and present associated exponential inequalities. We motivate the theoretical analysis by considering the leader node particle filter and present numerical experiments exploring its performance and the relationship to the error bounds.Comment: Published in at http://dx.doi.org/10.1214/11-AAP760 the Annals of Applied Probability (http://www.imstat.org/aap/) by the Institute of Mathematical Statistics (http://www.imstat.org

Efficient delay-tolerant particle filtering

This paper proposes a novel framework for delay-tolerant particle filtering that is computationally efficient and has limited memory requirements. Within this framework the informativeness of a delayed (out-of-sequence) measurement (OOSM) is estimated using a lightweight procedure and uninformative measurements are immediately discarded. The framework requires the identification of a threshold that separates informative from uninformative; this threshold selection task is formulated as a constrained optimization problem, where the goal is to minimize tracking error whilst controlling the computational requirements. We develop an algorithm that provides an approximate solution for the optimization problem. Simulation experiments provide an example where the proposed framework processes less than 40% of all OOSMs with only a small reduction in tracking accuracy

Comparison of forest attributes derived from two terrestrial lidar systems.

Abstract Terrestrial lidar (TLS) is an emerging technology for deriving forest attributes, including conventional inventory and canopy characterizations. However, little is known about the influence of scanner specifications on derived forest parameters. We compared two TLS systems at two sites in British Columbia. Common scanning benchmarks and identical algorithms were used to obtain estimates of tree diameter, position, and canopy characteristics. Visualization of range images and point clouds showed clear differences, even though both scanners were relatively high-resolution instruments. These translated into quantifiable differences in impulse penetration, characterization of stems and crowns far from the scan location, and gap fraction. Differences between scanners in estimates of effective plant area index were greater than differences between sites. Both scanners provided a detailed digital model of forest structure, and gross structural characterizations (including crown dimensions and position) were relatively robust; but comparison of canopy density metrics may require consideration of scanner attributes

Using care plans to better manage multimorbidity

BACKGROUND: The health care for patients having two or more long-term medical conditions is fragmented between specialists, allied health professionals, and general practitioners (GPs), each keeping separate medical records. There are separate guidelines for each disease, making it difficult for the GP to coordinate care. The TrueBlue model of collaborative care to address key problems in managing patients with multimorbidity in general practice previously reported outcomes on the management of multimorbidities. We report on the care plan for patients with depression, diabetes, and/or coronary heart disease that was embedded in the TrueBlue study. METHODS: A care plan was designed around diabetes, coronary heart disease, and depression management guidelines to prompt implementation of best practices and to provide a single document for information from multiple sources. It was used in the TrueBlue trial undertaken by 400 patients (206 intervention and 194 control) from 11 Australian general practices in regional and metropolitan areas. RESULTS: Practice nurses and GPs successfully used the care plan to achieve the guideline-recommended checks for almost all patients, and successfully monitored depression scores and risk factors, kept pathology results up to date, and identified patient priorities and goals. Clinical outcomes improved compared with usual care. CONCLUSION: The care plan was used successfully to manage and prioritise multimorbidity. Downstream implications include improving efficiency in patient management, and better health outcomes for patients with complex multimorbidities

Optimization and Analysis of Distributed Averaging with Short Node Memory

In this paper, we demonstrate, both theoretically and by numerical examples, that adding a local prediction component to the update rule can significantly improve the convergence rate of distributed averaging algorithms. We focus on the case where the local predictor is a linear combination of the node's two previous values (i.e., two memory taps), and our update rule computes a combination of the predictor and the usual weighted linear combination of values received from neighbouring nodes. We derive the optimal mixing parameter for combining the predictor with the neighbors' values, and carry out a theoretical analysis of the improvement in convergence rate that can be obtained using this acceleration methodology. For a chain topology on n nodes, this leads to a factor of n improvement over the one-step algorithm, and for a two-dimensional grid, our approach achieves a factor of n^1/2 improvement, in terms of the number of iterations required to reach a prescribed level of accuracy

FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting

Forecasting of multivariate time-series is an important problem that has applications in traffic management, cellular network configuration, and quantitative finance. A special case of the problem arises when there is a graph available that captures the relationships between the time-series. In this paper we propose a novel learning architecture that achieves performance competitive with or better than the best existing algorithms, without requiring knowledge of the graph. The key element of our proposed architecture is the learnable fully connected hard graph gating mechanism that enables the use of the state-of-the-art and highly computationally efficient fully connected time-series forecasting architecture in traffic forecasting applications. Experimental results for two public traffic network datasets illustrate the value of our approach, and ablation studies confirm the importance of each element of the architecture. The code is available here: https://github.com/boreshkinai/fc-gaga

Optimising expression and extraction of recombinant proteins in plants

Recombinant proteins are of paramount importance for research, industrial and medical use. Numerous expression chassis are available for recombinant protein production, and while bacterial and mammalian cell cultures are the most widely used, recent developments have positioned transgenic plant chassis as viable and often preferential options. Plant chassis are easily maintained at low cost, are hugely scalable, and capable of producing large quantities of protein bearing complex post-translational modification. Several protein targets, including antibodies and vaccines against human disease, have been successfully produced in plants, highlighting the significant potential of plant chassis. The aim of this review is to act as a guide to producing recombinant protein in plants, discussing recent progress in the field and summarising the factors that must be considered when utilising plants as recombinant protein expression systems, with a focus on optimising recombinant protein expression at the genetic level, and the subsequent extraction and purification of target proteins, which can lead to substantial improvements in protein stability, yield and purity

The proposed Caroline ESA M3 mission to a Main Belt Comet

We describe Caroline, a mission proposal submitted to the European Space Agency in 2010 in response to the Cosmic Visions M3 call for medium-sized missions. Caroline would have travelled to a Main Belt Comet (MBC), characterizing the object during a flyby, and capturing dust from its tenuous coma for return to Earth. MBCs are suspected to be transition objects straddling the traditional boundary between volatile–poor rocky asteroids and volatile–rich comets. The weak cometary activity exhibited by these objects indicates the presence of water ice, and may represent the primary type of object that delivered water to the early Earth. The Caroline mission would have employed aerogel as a medium for the capture of dust grains, as successfully used by the NASA Stardust mission to Comet 81P/Wild 2. We describe the proposed mission design, primary elements of the spacecraft, and provide an overview of the science instruments and their measurement goals. Caroline was ultimately not selected by the European Space Agency during the M3 call; we briefly reflect on the pros and cons of the mission as proposed, and how current and future mission MBC mission proposals such as Castalia could best be approached

Colon-available raspberry polyphenols exhibit anti-cancer effects on in vitro models of colon cancer

BACKGROUND: There is a probable association between consumption of fruit and vegetables and reduced risk of cancer, particularly cancer of the digestive tract. This anti-cancer activity has been attributed in part to anti-oxidants present in these foods. Raspberries in particular are a rich source of the anti-oxidant compounds, such as polyphenols, anthocyanins and ellagitannins. METHODS: A "colon-available" raspberry extract (CARE) was prepared that contained phytochemicals surviving a digestion procedure that mimicked the physiochemical conditions of the upper gastrointestinal tract. The polyphenolic-rich extract was assessed for anti-cancer properties in a series of in vitro systems that model important stages of colon carcinogenesis, initiation, promotion and invasion. RESULTS: The phytochemical composition of CARE was monitored using liquid chromatography mass spectrometry. The colon-available raspberry extract was reduced in anthocyanins and ellagitannins compared to the original raspberry juice but enriched in other polyphenols and polyphenol breakdown products that were more stable to gastrointestinal digestion. Initiation – CARE caused significant protective effects against DNA damage induced by hydrogen peroxide in HT29 colon cancer cells measured using single cell microgelelectrophoresis. Promotion – CARE significantly decreased the population of HT29 cells in the G(1 )phase of the cell cycle, effectively reducing the number of cells entering the cell cycle. However, CARE had no effect on epithelial integrity (barrier function) assessed by recording the trans-epithelial resistance (TER) of CACO-2 cell monolayers. Invasion – CARE caused significant inhibition of HT115 colon cancer cell invasion using the matrigel invasion assay. CONCLUSION: The results indicate that raspberry phytochemicals likely to reach the colon are capable of inhibiting several important stages in colon carcinogenesis in vitro