Crises such as Hurricane Maria and the coronavirus disease 2019 (COVID-19) pandemic have revealed that untimely reporting of the death toll results in inadequate interventions, impacts communication, and fuels distrust on response agencies. Delays in establishing mortality are due to the contested definition of deaths attributable to a disaster and lack of rapid collection of vital statistics data from inadequate health system infrastructure. Readily available death counts, combined with geographic, demographic, and socioeconomic data, can serve as a baseline to build a continuous mortality surveillance system. In an emergency setting, real-time Total, All-cause, Excess Mortality (TEM) can be a critical tool, granting authorities timely information ensuring a targeted response and reduce disaster impact. TEM measurement can identify spikes in mortality, including geographic disparities and disproportionate deaths in vulnerable populations. This study recommends that measuring total, all-cause, excess mortality as a first line of response should become the global standard for measuring disaster impact.

Following substantial progress achieved recently, the Galileo constellation provides a considerable satellite resource for the GNSS applications. In this regard, the performance assessment of real-time single-frequency precise positioning with Galileo satellites is the main objective of this research. For this purpose, several experimental tests were conducted in this study with two single-frequency positioning models, namely single-frequency code-based positioning and code-phase combination. The results show that Galileo presents an adequate number of visible satellites sufficient for single-frequency positioning. Also, the study demonstrates that, in comparison to GPS observations, Galileo observations have a significantly lower noise level. For the single-frequency code-based positioning, Galileo presents a better positioning accuracy than GPS by 25⋅8% on average. When compared with GPS, a 9⋅4% better positioning accuracy is acquired from Galileo for the single-frequency code-phase combination, with its average convergence time shorter than GPS by a ratio of 24⋅4%.

Syndromic surveillance is a form of surveillance that generates information for public health action by collecting, analysing and interpreting routine health-related data on symptoms and clinical signs reported by patients and clinicians rather than being based on microbiologically or clinically confirmed cases. In England, a suite of national real-time syndromic surveillance systems (SSS) have been developed over the last 20 years, utilising data from a variety of health care settings (a telehealth triage system, general practice and emergency departments). The real-time systems in England have been used for early detection (e.g. seasonal influenza), for situational awareness (e.g. describing the size and demographics of the impact of a heatwave) and for reassurance of lack of impact on population health of mass gatherings (e.g. the London 2012 Olympic and Paralympic Games).We highlight the lessons learnt from running SSS, for nearly two decades, and propose questions and issues still to be addressed. We feel that syndromic surveillance is an example of the use of ‘big data’, but contend that the focus for sustainable and useful systems should be on the added value of such systems and the importance of people working together to maximise the value for the public health of syndromic surveillance services.

Scanning transmission electron microscopy (STEM) has become the main stay for materials characterization on atomic level, with applications ranging from visualization of localized and extended defects to mapping order parameter fields. In recent years, attention has focused on the potential of STEM to explore beam induced chemical processes and especially manipulating atomic motion, enabling atom-by-atom fabrication. These applications, as well as traditional imaging of beam sensitive materials, necessitate increasing the dynamic range of STEM in imaging and manipulation modes, and increasing the absolute scanning speed which can be achieved by combining sparse sensing methods with nonrectangular scanning trajectories. Here we have developed a general method for real-time reconstruction of sparsely sampled images from high-speed, noninvasive and diverse scanning pathways, including spiral scan and Lissajous scan. This approach is demonstrated on both the synthetic data and experimental STEM data on the beam sensitive material graphene. This work opens the door for comprehensive investigation and optimal design of dose efficient scanning strategies and real-time adaptive inference and control of e-beam induced atomic fabrication.

Real-time Precise Point Positioning (PPP) relies on the use of accurate satellite orbit and clock corrections. If these corrections contain large errors or faults, either from the system or by meaconing, they will adversely affect positioning. Therefore, such faults have to be detected and excluded. In traditional PPP, measurements that have faulty corrections are typically excluded as they are merged together. In this contribution, a new PPP model that encompasses the orbit and clock corrections as quasi-observations is presented such that they undergo the fault detection and exclusion process separate from the observations. This enables the use of measurements that have faulty corrections along with predicted values of these corrections in place of the excluded ones. Moreover, the proposed approach allows for inclusion of the complete stochastic information of the corrections. To facilitate modelling of the orbit and clock corrections as quasi-observations, International Global Navigation Satellite System Service (IGS) real-time corrections were characterised over a six-month period. The proposed method is validated and its benefits are demonstrated at two sites using three days of data.

Avian malaria, caused by Plasmodium spp., is an emerging disease in New Zealand (NZ). To detect Plasmodium spp. infection and quantify parasite load in NZ birds, a real-time polymerase chain reaction (PCR) (qPCR) protocol was used and compared with a nested PCR (nPCR) assay. A total of 202 blood samples from 14 bird species with known nPCR results were tested. The qPCR prevalences for introduced, native and endemic species groups were 70, 11 and 21%, respectively, with a sensitivity and specificity of 96·7 and 98%, respectively, for the qPCR, while a sensitivity and specificity of 80·9 and 85·4% were determined for the nPCR. The qPCR appeared to be more sensitive in detecting lower levels of parasitaemia. The mean parasite load was significantly higher in introduced bird species (2245 parasites per 10 000 erythrocytes) compared with endemic species (31·5 parasites per 10 000 erythrocytes). In NZ robins (Petroica longipes), a significantly lower packed cell volume was found in birds that were positive for Plasmodium spp. compared with birds that were negative. Our data suggest that introduced bird species, such as blackbirds (Turdus merula), have a higher tolerance for circulating parasite stages of Plasmodium spp., indicating that introduced species are an important reservoir of avian malaria due to a high infection prevalence and parasite load.

The goal of the project was to supply growers with knowledge on how incorporation of machine vision technology can affect the wild blueberry crop, disease pressures, and the overall savings of select agrochemical inputs. A machine vision system was developed and mounted on a rear sprayer boom in front of the sprayer nozzles capable of targeting the agrochemical application on an as-needed basis. Results showed that plants that received the proper fungicide application were less prone to premature leaf drop resulting in larger stem diameters and higher bud counts and harvestable fruit yield. Fungicide application savings using the smart sprayer for spot-application was 12% as compared to a uniform application.

Path planning can be difficult and time consuming for inchworm robots especially when operating in complex 3D environments such as steel bridges. Confined areas may prevent a robot from extensively searching the environment by limiting its mobility. An approach for real-time path planning is presented. This approach first uses the concept of line-of-sight (LoS) to find waypoints from the start pose to the end node. It then plans smooth, collision-free motion for a robot to move between waypoints using a 3D-F2 algorithm. Extensive simulations and experiments are conducted in 2D and 3D scenarios to verify the approach.

This paper presents a new approach to accurately track a moving vehicle with a multiview setup of red–green–blue depth (RGBD) cameras. We first propose a correction method to eliminate a shift, which occurs in depth sensors when they become worn. This issue could not be otherwise corrected with the ordinary calibration procedure. Next, we present a sensor-wise filtering system to correct for an unknown vehicle motion. A data fusion algorithm is then used to optimally merge the sensor-wise estimated trajectories. We implement most parts of our solution in the graphic processor. Hence, the whole system is able to operate at up to 25 frames per second with a configuration of five cameras. Test results show the accuracy we achieved and the robustness of our solution to overcome uncertainties in the measurements and the modelling.

Existing methods for estimating individual dairy cow energy balance typically either need information on feed intake, that is, the traditional input–output method, or frequent measurements of BW and body condition score (BCS), that is, the body reserve changes method (EBbody). The EBbody method holds the advantage of not requiring measurements of feed intake, which are difficult to obtain in practice. The present study aimed first to investigate whether the EBbody method can be simplified by basing EBbody on BW measurements alone, that is, removing the need for BCS measurements, and second to adapt the EBbody method for real-time use, thus turning it into a true on-farm tool. Data came from 77 cows (primiparous or multiparous, Danish Holstein, Red or Jersey) that took part in an experiment subjecting them to a planned change in concentrate intake during milking. BW was measured automatically during each milking and real-time smoothed using asymmetric double-exponential weighting and corrected for the weight of milk produced, gutfill and the growing conceptus. BCS assessed visually with 2-week intervals was also smoothed. EBbody was calculated from BW changes only, and in conjunction with BCS changes. A comparison of the increase in empty body weight (EBW) estimated from EBbody with EBW measured over the first 240 days in milk (DIM) for the mature cows showed that EBbody was robust to changes in the BCS coefficients, allowing functions for standard body protein change relative to DIM to be developed for breeds and parities. These standard body protein change functions allow EBbody to be estimated from frequent BW measurements alone, that is, in the absence of BCS measurements. Differences in EBbody levels before and after changes in concentrate intake were calculated to test the real-time functionality of the EBbody method. Results showed that significant EBbody increases could be detected 10 days after a 0.2 kg/day increase in concentrate intake. In conclusion, a real-time method for deriving EBbody from frequent BW measures either alone or in conjunction with BCS measures has been developed. This extends the applicability of the EBbody method, because real-time measures can be used for decision support and early intervention.

Novel technologies have prompted a new paradigm in disease surveillance. Advances in computation, communications and materials enable new technologies such as mobile phones and microfluidic chips. In this paper we illustrate examples of new technologies that can augment disease detection. We describe technologies harnessing the internet, mobile phones, point of care diagnostic tools and methods that facilitate detection from passively collected unstructured data. We demonstrate how these can all assist in quicker detection, investigation and response to emerging infectious events. Novel technologies enable collection and dissemination of epidemic intelligence data to both public health practitioners and the general public, enabling finer temporal and spatial resolution of disease monitoring than through traditional public health processes.

Hazardous terrains pose a crucial challenge to mobile robots. To operate safely and efficiently, it is necessary to detect the terrain type and modify operation strategies in real-time. Fast analytical models of wheeled locomotion on deformable terrains are thus important. Based on classic terramechanics, a closed-form wheel–soil interaction model was derived by quadratic approximation of stresses along the wheel–soil interface. The bulldozing resistance and the effects of grousers were also added for more accurate prediction of wheel contact forces. A non-iterative method was proposed to estimate the entry angle, by using approximated vertical pressure acting on the wheels. The computational efficiency was improved by avoiding traditional recursive search. Real-time computation of the wheel contact forces is achieved by the terramechanics-based formula (TBF), which was developed by integrating the wheel–soil interaction model and the entry angle estimator. In addition, an automotive-inspired approach was used to integrate the TBF and the simplified vehicle dynamics model for fast simulation of mobile robots. Stability problems in numerical simulation could be avoided by this method. The above models were verified by comparing simulation results and experiment data, including single-wheel experiments and full-vehicle experiments.

An in situ time-resolved XRD system for hydrothermal reaction has been developed in order to investigate the phase evolution during autoclave process in autoclaved aerated concrete (AAC) formation. The system includes a novel autoclave cell for transmission XRD with thin beryllium windows, a two-dimensional photon-counting pixel array detector, and uses high energy X-rays from a synchrotron radiation source. The temperature and pressure inside the cell are extremely stable during hydrothermal reaction over the course of several hours. The system was utilized for the formation reaction of AAC. Phase evolution was clearly observed, including several intermediate phases, and detailed information on the structural changes during the hydrothermal reaction were obtained.

Alternative measures of the UK output gap are considered for 1984–2007. The real-time series is strongly affected by the rolling-time estimation of the trend, and produces a picture of the business cycle which is not consistent with contemporary perceptions of the large fluctuations of the late 1980s and early 1990s. A new, ‘nearly-real’, measure developed here may be better for estimating historical reaction functions. In the context of the current recession, none of these mechanically derived measures of the output gap are useful. Policymakers should make careful estimates of the likely fall in potential output on the basis of other information.

For more than four decades, the New Zealand Institute of Economic Research (NZIER) has conducted a two-question, quarterly survey of architect forecasts of public and private sector construction expenditure. This qualitative survey is published one week after the end of each quarter and nine weeks ahead of the official quantitative data thereby giving architect opinion nowcasting status. This paper covers selected aspects of this unexplored series with particular reference to residential housing construction and the value-added information from architects as nowcasters. Specifically, we consider several qualitative-to-quantitative conversion methods, in-sample and out-of-sample performance, cyclical features and respondent dynamics. Although our work relates to architects — a sub-sector of the service industry — our results have a wider application to business survey questions using ordered qualitative responses.

This paper proposes a new algorithm, known as the Segmentation Algorithm, which provides model-based, real-time, whole-arm collision avoidance for telerobotic applications. The work presented here is an extension and modification of potential field theory. Novel aspects of the algorithm include the application of a hierarchical segmentation technique to minimize on-line processing and the development of procedures which account for workspace object translation, rotation, and grasping. The'SA outputs torques, which, when applied to the control arm, prevent the teleoperator from driving the remote arm into a collision. The teleoperator actually feels workspace objects that are spatially close to the remote arm—an experience known as virtual force-reflection. The SA's performance has been analyzed in terms of its speed and efficiency vis a vis various system parameters, including workspace object distribution, size, and number. Simulation results show that the SA succeeds in providing real-time collision avoidance where less elegant brute force algorithms fail.

Structural flexibility is an inherent characteristic of a class of macro-micro manipulators consisting of a rigid micro manipulator mounted on a long-reach (flexible) macro manipulator. Vibrations caused by flexibility make it difficult to achieve accurate control of the end-point of the micro manipulator. In this paper, we develop a control strategy that can be applied to such a system. An experimental test-bed has been developed in which a 6 DOF PUMA 560 manipulator is mounted on a compliant platform. The control strategy consists of a rigid body inverse dynamics controller together with a neural network based strategy for damping out the oscillations due to the flexible base. Experimental results obtained from the test-bed are presented to show the effectiveness of the proposed control scheme.

Using the real time microscope (RTM), a system applying new developments in light microscopy, we documented the spatial and temporal dynamics of mitochondrial behavior in human cultured skin fibroblasts. Without the use of stains or probes, we resolved fibroblast mitochondria as dark slender filaments of approximately 0.2 μm wide and up to 10 μm long, as well as a few smaller ovoid forms. In the living cell, the three most common mitochondrial movements were: (1) small oscillatory movements; (2) larger movements including filament extension, retraction, and branching as well as combinations of these actions; and (3) whole transit movements of single mitochondrial filaments. Skin fibroblasts from patients with mitochondrial complex I deficiency and normal fibroblasts during incubation with rotenone, or antimycin A, contained higher proportions of mitochondria in the swollen filamentous forms, nodal filaments, and ovoid forms rather than the slender filamentous forms in normal cells. Interestingly, decreased motility was observed with the more ovoid mitochondrial forms compared to the filamentous forms. We conclude that mitochondrial morphology and dynamic motion are strongly associated with changes in mitochondrial energy metabolism. Images documenting our observations are presented both at single time points and as QuickTime videos.Abbreviations: EM: electron microscope; L/P: lactate/pyruvate; QT: QuickTime; CCCP: carbonyl cyanide 3-chloro-phenylhydrazone; CMXRos, chloromethyl-X-rosamine; Rh123, Rhodamine 123; RTM, real time microscope

Cone-beam X-ray microtomography attracts increasing attention due to its applications in biomedical sciences, material engineering, and industrial nondestructive evaluation. Rapid volumetric image reconstruction is highly desirable in all these areas for prompt visualization and analysis of complex structures of interest. In this article, we reformulate a generalized Feldkamp cone-beam image reconstruction algorithm, utilize curved voxels and mapping tables, improve the reconstruction efficiency by an order of magnitude relative to a direct implementation of the standard algorithm, and demonstrate the feasibility with numerical simulation and experiments using a prototype cone-beam X-ray microtomographic system. Our fast algorithm reconstructs a 256-voxel cube from 100 projections within 2 min on an Intel Pentium II® 233 MHz personal computer, produces satisfactory image quality, and can be further accelerated using special hardware and/or parallel processing techniques.