Visualization of Big Spatial Data using Coresets for Kernel Density Estimates

The size of large, geo-located datasets has reached scales where visualization of all data points is inefficient. Random sampling is a method to reduce the size of a dataset, yet it can introduce unwanted errors. We describe a method for subsampling of spatial data suitable for creating kernel density estimates from very large data and demonstrate that it results in less error than random sampling. We also introduce a method to ensure that thresholding of low values based on sampled data does not omit any regions above the desired threshold when working with sampled data. We demonstrate the effectiveness of our approach using both, artificial and real-world large geospatial datasets

Bayesian Decision Trees Inspired from Evolutionary Algorithms

Bayesian Decision Trees (DTs) are generally considered a more advanced and accurate model than a regular Decision Tree (DT) because they can handle complex and uncertain data. Existing work on Bayesian DTs uses Markov Chain Monte Carlo (MCMC) with an accept-reject mechanism and sample using naive proposals to proceed to the next iteration, which can be slow because of the burn-in time needed. We can reduce the burn-in period by proposing a more sophisticated way of sampling or by designing a different numerical Bayesian approach. In this paper, we propose a replacement of the MCMC with an inherently parallel algorithm, the Sequential Monte Carlo (SMC), and a more effective sampling strategy inspired by the Evolutionary Algorithms (EA). Experiments show that SMC combined with the EA can produce more accurate results compared to MCMC in 100 times fewer iterations.Comment: arXiv admin note: text overlap with arXiv:2301.0909

Evaluation of terrain collision risks for flight style autonomous underwater vehicles

Photographic surveys of the seafloor with flight style autonomous underwater vehicles are a very effective tool for discovery and exploration. Due to the high terrain collision risk for the survey vehicle, they are employed with caution. The extent of this risk remains unquantified. For mission planning, researchers and vehicle operators have to rely on their experience. This paper introduces measures for vehicle risk and success and analyses how previously mapped terrains and artificially generated terrain maps can be used to categorize terrains. The developed measures are applied to a simulation of the Autosub6000 flight style AUV terrain following system. Based on quantitative parameters, changes to the obstacle avoidance system and survey mission plans can be better informed

Extending the diabetic retinopathy screening interval beyond 1 year : systematic review

To determine whether the recommended screening interval for diabetic retinopathy (DR) in the UK can safely be extended beyond 1 year. Systematic review of clinical and cost-effectiveness studies. Nine databases were searched with no date restrictions. Randomised controlled trials (RCTs), cohort studies, prognostic or economic modelling studies which described the incidence and progression of DR in populations with type 1 diabetes mellitus or type 2 diabetes mellitus of either sex and of any age reporting incidence and progression of DR in relation to screening interval (vs annual screening interval) and/or prognostic factors were included. Narrative synthesis was undertaken. 14 013 papers were identified, of which 11 observational studies, 5 risk stratification modelling studies and 9 economic studies were included. Data were available for 262 541 patients of whom at least 228 649 (87%) had type 2 diabetes. There were no RCTs. Studies concluded that there is little difference between clinical outcomes from screening 1 yearly or 2 yearly in low-risk patients. However there was high loss to follow-up (13–31%), heterogeneity in definitions of low risk and variation in screening and grading protocols for prior retinopathy results. Observational and economic modelling studies in low-risk patients show little difference in clinical outcomes between 1-year and 2-year screening intervals. The lack of experimental research designs and heterogeneity in definition of low risk considerably limits the reliability and validity of this conclusion. Cost-effectiveness findings were mixed. There is insufficient evidence to recommend a move to extend the screening interval beyond 1 year

Ecological Drivers of Habitat Use by Meso Mammals in a Miombo Ecosystem in the Issa Valley, Tanzania

Vast stretches of East and Southern Africa are characterized by a mosaic of deciduous woodlands and evergreen riparian forests, commonly referred to as “miombo,” hosting a high diversity of plant and animal life. However, very little is known about the communities of small-sized mammals inhabiting this heterogeneous biome. We here document the diversity and abundance of 0.5–15 kg sized mammals (“meso-mammals”) in a relatively undisturbed miombo mosaic in western Tanzania, using 42 camera traps deployed over a 3 year-period. Despite a relatively low diversity of meso-mammal species (n = 19), these comprised a mixture of savanna and forest species, with the latter by far the most abundant. Our results show that densely forested sites are more intensely utilized than deciduous woodlands, suggesting riparian forest within the miombo matrix might be of key importance to meso-mammal populations. Some species were captured significantly more often in proximity to (and sometimes feeding on) termite mounds (genus Macrotermes), as they are a crucial food resource. There was some evidence of temporal partitioning in activity patterns, suggesting hetero-specific avoidance to reduce foraging competition. We compare our findings to those of other miombo sites in south-central Africa

Rotational Excitation of HC_3N by H_2 and He at low temperatures

Rates for rotational excitation of HC3N by collisions with He atoms and H2 molecules are computed for kinetic temperatures in the range 5-20K and 5-100K, respectively. These rates are obtained from extensive quantum and quasi-classical calculations using new accurate potential energy surfaces (PES)

How should we measure psychological resilience in sport performers?

Psychological resilience is important in sport because athletes must constantly withstand a wide range of pressures to attain and sustain high performance. To advance psychologists’ understanding of this area, there exists an urgent need to develop a sport-specific measure of resilience. The purpose of this paper is to review psychometric issues in resilience research and to discuss the implications for sport psychology. Drawing on the wider general psychology literature to inform the discussion, the narrative is divided into three main sections relating to resilience and its assessment: adversity, positive adaptation, and protective factors. The first section reviews the different ways that adversity has been measured and considers the potential problems of using items with varying degrees of controllability and risk. The second section discusses the different approaches to assessing positive adaptation and examines the issue of circularity pervasive in resilience research. The final section explores the various issues related to the assessment of protective factors drawing directly from current measures of resilience in other psychology sub-disciplines. The commentary concludes with key recommendations for sport psychology researchers seeking to develop a measure of psychological resilience in athletes

HST Imaging of the Host Galaxies of High Redshift Radio-Loud Quasars

We present rest-frame UV and Ly-alpha images of spatially-resolved structures around five high-redshift radio-loud quasars obtained with the WFPC2 camera on the Hubble Space Telescope. We find that all five quasars are extended and this "fuzz" contains ~5-40% of the total continuum flux and 15-65% of the Ly-alpha flux within a radius of about 1.5 arcsec. The rest-frame UV luminosities of the hosts are log lambda P_lambda = 11.9 to 12.5 solar luminosities (assuming no internal dust extinction), comparable to the luminous radio galaxies at similar redshifts and a factor 10 higher than both radio-quiet field galaxies at z~2-3 and the most UV-luminous low redshift starburst galaxies. The Ly-alpha luminosities of the hosts are (in the log) approximately 44.3-44.9 erg/s which are also similar to the those of luminous high redshift radio galaxies and considerably larger than the Ly-alpha luminosities of high redshift field galaxies. To generate the Ly-alpha luminosities of the hosts would require roughly a few percent of the total observed ionizing luminosity of the quasar. We find good alignment between the extended Ly-alpha and the radio sources, strong evidence for jet-cloud interactions in two cases, again resembling radio galaxies, and what is possibly the most luminous radio-UV synchrotron jet in one of the hosts at z=2.110.Comment: 36 pages (latex, aas macros), 3 figures (3 gif and 10 postscript files), accepted for publication in the the Astrophysical Journal Supplement Serie

Bayesian Decision Trees Inspired from Evolutionary Algorithms

Bayesian Decision Trees (DTs) are generally considered a more advanced and accurate model than a regular Decision Tree (DT) as they can handle complex and uncertain data. Existing work on Bayesian DTs uses Markov Chain Monte Carlo (MCMC) with an accept-reject mechanism and sample using naive proposals to proceed to the next iteration. This method can be slow because of the burn-in time needed. We can reduce the burn-in period by proposing a more sophisticated way of sampling or by designing a different numerical Bayesian approach. In this paper, we propose a replacement of the MCMC with an inherently parallel algorithm, the Sequential Monte Carlo (SMC), and a more effective sampling strategy inspired by the Evolutionary Algorithms (EA). Experiments show that SMC combined with the EA can produce more accurate results compared to MCMC in 100 times fewer iterations