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As an important component in transportation maps, three-dimensional (3D) structure information of grade-separated junctions is crucial for applications such as intelligent driving, route planning and traffic control. In order to acquire spatial layouts of road junctions, researchers have developed algorithms to extract planar structures from various data sources. However, it is less common to refine maps of grade-separated junctions with 3D structure information using tracking data. The objective of this study is to find an approach to extracting 3D structures of grade-separated junctions from vehicle trajectories. The proposed method is based on semantic segmentation and data fusion. Trajectories were divided into sections with different trends of elevation by detecting change points. The ranges and elevations of slopes and level sections were derived by seeking consensus among different trajectories using a data fusion technique. Based on semantic segmentation and aggregated elevations, we reconstructed detailed 3D junction structures. This method was validated on multiple crowdsourced trajectory datasets and compared to cluster center linking method. Experiments show that the proposed method had a higher overall accuracy of semantic segmentation than baseline method. The accuracy of vertical relationship at intersections is comparable to baseline. Despite large elevation discrepancy among trajectories, the performance of the proposed method was similar across crowdsourced trajectory datasets from open and commercial projects.

The site-selective modification of peptides and proteins facilitates the preparation of targeted therapeutic agents and tools to interrogate fundamental biochemistry. Among the numerous bioconjugation techniques developed to install groups of interest, those that generate C(sp3)-C(sp3) bonds are significantly underrepresented despite affording proteolytically stable, biogenic linkages. Herein we describe a visible-light-mediated reaction that enables the site-selective modification of peptides and proteins via desulfurative C(sp3)-C(sp3) bond formation. The reaction is rapid and high yielding in peptide systems, with comparable translation to proteins. Using this chemistry, we demonstrate the installation of a range of moieties into model systems and successfully integrate an effective PTM-mimic into a recombinantly expressed histone.

State sequences are a new paradigm to encode and represent contextualised movement data. A state sequence is a temporal succession of characters representing categorical states of the moving entity or its surrounding environment. Eigen decomposition, a principal components analysis method, is an option to reduce and find patterns in such multi-dimensional categorical data through dimensionality reduction. Recurrent patterns can be found by identifying the most relevant eigenbehaviours, which are a set of vectors that characterize the variation in the behaviour of an entity during a time period. Dimensionality reduction techniques have so far not been widely used in movement analytics and in this paper we demonstrate how they could help analyse responses of a moving entity to the dynamic environmental conditions. Specifically, we use sequence-based representation and eigen decomposition to investigate movement patterns of maned wolves (Chrysocyon brachyurus) in relation to vegetation vigour in their habitat. We use a set of GPS-trajectories from a group of maned wolves to which we link multi-source NDVI data as a proxy for the state of vegetation. We find that eigenbehaviours can identify patterns in the wolves’ responses to dynamic environmental conditions that align with the current literature on the species. Our research highlights the potential for dimensionality reduction and sequence-based methods to identify patterns in large tracking databases linked to contextual data.

With increasing levels of outdoor recreation activities, consequences for wildlife through interactions with recreationists are highly variable. Behavioural changes in wildlife are one potential consequence of interactions with outdoor recreationists. In ungulate populations, vigilance and flight responses are well-known antipredator behaviours, and an increase in their level indicates a more intense stress level which, ultimately, can have consequences for animal fitness. In Scotland, the geographical distribution of red deer (Cervus elaphus) overlaps greatly with areas used for popular outdoor activities such as hill walking. In this piece of research, we studied red deer time allocation, vigilance, and flight behaviours near a popular hiking path using camera traps. We positioned the cameras in transects at different distances (25, 75, and 150 m) from the path and recorded hiking activity using an automated people counter. Red deer behaviour was categorized from photo analysis as (1) no response (e.g. feeding and resting), (2) vigilant (i.e. upright head position), and (3) flight response. We also investigated demographic variables (group size and sex) and the direction of red deer movement relative to the trail. We used generalised linear mixed models to analyse behaviour in relation to the distance from the hiking track, hiking activity, time of the day, demographic, and environmental variables. We did not find an increase in vigilance or flight behaviour in relation to the distance from the hiking path or the hiking activity. These results suggest that red deer, in our study area, are habituated to the presence of hikers and may spatially avoid areas close to the hiking path instead of displaying cost-intensive behaviour (i.e. flight or vigilance behaviour). Publisher PDF

Anthropogenic activities, such as outdoor recreation, have the potential to change complex interactions between wildlife and livestock, with further consequences for the management of both animals, the environment, and disease transmission. We present the interaction amongst wildlife, livestock, and outdoor recreationists as a three-way interaction. Little is known about how recreational activities alter the interaction between herbivores in areas extensively used of recreational purposes. We investigate how hiking activity affects spatio-temporal co-occurrence between domestic sheep (Ovis aries) and red deer (Cervus elaphus). We used camera traps to capture the spatio-temporal distribution of red deer and sheep at varying distances from a popular hiking trail. We used the distance from the hiking path as a proxy of hiking activity. We used generalized linear models to investigate the spatial distribution of sheep and deer. We analysed the activity patterns of sheep and deer and then calculated their coefficients of temporal overlap for each camera trap location using a non-parametric kernel density estimation method. We compared these coefficients in relation to the distance from the hiking path. Finally, we used a generalized linear mixed-model to investigate which factors influence the spatio-temporal succession between deer and sheep. We do not find that sheep and red deer spatially avoid each other, but we did find that sheep temporally avoid red deer, while red deer do not appear to temporally avoid sheep. The coefficient of temporal overlap varied with distance from the hiking trail, with stronger temporal co-occurrence at greater distances from the hiking trail. Red deer were more likely to be detected further from the path during the day, which increased the temporal overlap with sheep in these areas. This suggests that hiking pressure influences spatio-temporal interactions between sheep and deer, leading to greater temporal overlap in areas further from the hiking path due to red deer spatial avoidance of hikers. This impact of recreationists on the wildlife – livestock interaction can have consequences for the animals’ welfare, the vegetation they graze, their management and disease transmission.

This study applies a new methodology using the location of tweets from creatives to study where economic creativity takes place in a city. Based on a Twitter network in Brighton and Hove (United Kingdom), a creative hub, we identify freelancers and entrepreneurs in the creative industries that form the ‘core’ of the ‘creative class’ but have rarely been captured in existing spatial research. We use a comprehensive geodatabase of ‘Points-of-Interest’ and Census of Population residence and workplace locations to match tweets with types of places. Findings show that practices of economic creativity are less spatially clustered in central parts of the city and more spatially distributed across the city than studies that used business register data or cluster approaches suggested. Residential areas, which proxy for home locations, have a high incident of creative activities besides urban amenities and coworking spaces. It is concluded that local economic development should support the creation and maintenance of attractive places of social interactions across the city to foster creativity and innovation which has become even more important with the surge in homeworking due to Covid-19.

Regionally targeted interventions are being used by governments to slow the spread of COVID-19. In areas where free movement is not being actively restricted, there is uncertainty about how effective such regionally targeted interventions are due to the free movement of people between regions. We use mobile-phone network mobility data to test two hypotheses: 1) do regions targeted by exhibit increased outflows into other regions and 2) do regions targeted by interventions increase outflows specifically into areas with lesser restrictions. Our analysis focuses on two well-defined regionally targeted interventions in Ontario, Canada the first intervention as the first wave subsided (July 17, 2020) and the second intervention as we entered into new restrictions during the onset of the second wave (November 23, 2020). We use a difference-in-difference model to investigate hypothesis 1 and an interrupted time series model to investigate hypothesis 2, controlling for spatial effects (using a spatial-error model) in both cases. Our findings suggest that there that the regionally targeted interventions had a neutral effect (or no effect) on inter-regional mobility, with no significant differences associated with the interventions. We also found that overall inter-regional mobility was associated with socio-economic factors and the distance to the boundary of the intervention region. These findings are important as they should guide how governments design regionally targeted interventions (from a geographical perspective) considering observed patterns of mobility.

IntroductionInfectious diseases pose a risk to public health, requiring efficient strategies for disease prevention. Digital health surveillance technologies provide new opportunities to enhance disease prevention, detection, tracking, reporting and analysis. However, in addition to concerns regarding the effectiveness of these technologies in meeting public health goals, there are also concerns regarding the ethics, legality, safety and sustainability of digital surveillance technologies. This scoping review examines the literature on digital surveillance for public health purposes during the COVID-19 pandemic to identify health-related applications of digital surveillance technologies, and to highlight discussions of the implications of these technologies.Methods and analysisThe scoping review will be guided by the framework proposed by Arksey and O’Malley and the guidelines outlined by Colquhoun et al and Levac et al. We will search Medline (Ovid), PsycInfo, PubMed, Scopus, CINAHL (EBSCOhost), ACM Digital Library, Google Scholar and IEEE Explore for relevant studies published between December 2019 and December 2020. The review will also include grey literature. Data will be managed and analysed through an extraction table and thematic analysis.Ethics and disseminationFindings will be disseminated through traditional academic channels, as well as social media channels and research briefs and infographics. We will target our dissemination to provincial and federal public health organisations, as well as technology companies and community-based organisations managing the public response to the COVID-19 pandemic.

Post-translational modifications (PTMs) enhance the repertoire of protein function and mediate or influence the activity of many cellular processes. The preparation of site-specifically and homogeneously modified proteins, to apply as tools to understand the biological role of PTMs, is a challenging task. Herein, we describe a visible-light-mediated desulfurative C(sp

Background Different theories suggest birds may use compass or map navigational systems associated with Earth’s magnetic intensity or inclination, especially during migratory flights. These theories have only been tested by considering properties of the Earth’s magnetic field at coarse temporal scales, typically ignoring the temporal dynamics of geomagnetic values that may affect migratory navigational capacity. Methods We designed a simulation experiment to study if and how birds use the geomagnetic field during migration by using both high resolution GPS tracking data and geomagnetic data at relatively fine spatial and temporal resolutions in comparison to previous studies. Our simulations use correlated random walks (CRW) and correlated random bridge (CRB) models to model different navigational strategies based on underlying dynamic geomagnetic data. We translated navigational strategies associated with geomagnetic cues into probability surfaces that are included in the random walk models. Simulated trajectories from these models were compared to the actual GPS trajectories of migratory birds using 3 different similarity measurements to evaluate which of the strategies was most likely to have occurred. Results and conclusion We designed a simulation experiment which can be applied to different wildlife species under varying conditions worldwide. In the case of our example species, we found that a compass-type strategy based on taxis, defined as movement towards an extreme value, produced the closest and most similar trajectories when compared to original GPS tracking data in CRW models. Our results indicate less evidence for map navigation (constant heading and bi-gradient taxis navigation). Additionally, our results indicate a multifactorial navigational mechanism necessitating more than one cue for successful navigation to the target. This is apparent from our simulations because the modelled endpoints of the trajectories of the CRW models do not reach close proximity to the target location of the GPS trajectory when simulated with geomagnetic navigational strategies alone. Additionally, the magnitude of the effect of the geomagnetic cues during navigation in our models was low in our CRB models. More research on the scale effects of the geomagnetic field on navigation, along with temporally varying geomagnetic data could be useful for further improving future models.

Incorporating hard and soft barriers into individual space-use measures in wildlife tracking studies remains an ongoing challenge in movement ecology. Randomized shortest paths are proposed as a new tool for estimating wildlife utilization distributions—termed the RSPUD. The RSPUD model requires a single parameter (θ) which controls the trade-off between random exploration of the landscape and deterministic movement along the least-cost path. Synthetic data are used to demonstrate the flexibility of RSPUDs across a range of scenarious that could be encountered with wildlife tracking data. A case-study using GPS tracking data of an individual caribou (Rangifer tarandus) in British Columbia, Canada is used to demonstrate the method in an applied setting. The synthetic data examples highlight the properties of RSPUD across a range or scenarios. In the empirical data, we found that the RPSUD method more appropriately delineated individual space use and the avoidance of obvious barriers on the landscape in comparison to the Brownian bridge model. The calculation of RSPUDs provides new opportunities for more sophisticated spatial analysis of individual measures of space use (home range and utilization distributions), by explicitly taking into consideration the role of hard and soft barriers constraining individual movement opportunities. The approach should be attractive to movement ecologists as it takes a similar approach to existing methods (e.g., Brownian bridges and biased random bridges). The method is made accessible to other researchers as part of the wildlifeTG R package.

The acquisition of human trajectories facilitates movement data analytics and location-based services, but gaps in trajectories limit the extent in which many tracking datasets can be utilized. We present a model to estimate place visit probabilities at time points within a gap, based on empirical mobility patterns derived from past trajectories. Different from previous models, our model makes use of prior information from historical data to build a chain of empirically biased random walks. Therefore, it is applicable to gaps of varied lengths and can be fitted to empirical data conveniently. In this model, long gaps are broken into a chain of multiple episodes according to past patterns, while short episodes are estimated with anisotropic location transition probabilities. Experiments show that our model is able to hit almost 60% of the ground truth for short gaps of several minutes and over 40% for longer gaps up to weeks. In comparison, existing models are only able to hit less than 10% and 1% for short and long gaps, respectively. Visit probability distributions estimated by the model are useful for generating paths in data gaps, and have potential for disaggregated movement data analysis in uncertain environments.

Funding: This project is funded through a joint James Hutton Institute & University of St Andrews collaborative PhD Studentship, the Carnegie Trust and the British Deer Society. Outdoor recreation has the potential to impact the spatial and temporal distribution of animals. We explore interactions between red deer Cervus elaphus and hikers along a popular hiking path in the Scottish Highlands. We placed camera traps in transects at different distances (25, 75 and 150 m) from the path to study whether distance from hiker activity influences the number of deer detected. We compared this with the detection of red deer in an additional, spatially isolated area (one km away from any other transects and the hiking path). We collected count data on hikers at the start of the path and explored hourly (red deer detection during daytime), daily, diurnal (day versus night) and monthly spatial distributions of red deer. Using generalized linear mixed models with forward model selection, we found that the distribution of deer changed with the hiking activity. We found that fewer red deer were detected during busy hourly hiking periods. We found that during daytime, more red deer were detected at 150 m than at 25 m. Moreover, during the day, red deer were detected at a greater rate in the isolated area than around the transects close to the path and more likely to be found close to the path at night. This suggests that avoidance of hikers by red deer, in this study area, takes place over distances greater than 75 m and that red deer are displaced into less disturbed areas when the hiking path is busy. Our results suggest that the impact of hikers is short-term, as deer return to the disturbed areas during the night. Publisher PDF