Shore-level size gradients in Tegula funebralis (A. Adams) : seasonal changes influenced by interaction of predator preference and prey behavior

Aspects of the Pisaster-Tegula interaction are re-examined. Reproductive portions of T. funebrallis populations are shown to be immune to seastar predation through a combination of predator preference for larger snails and a withdrawal behavior that favors the escape of smaller snails after capture by a seastar . Experimental addition of p. ochraaceus in winter causes changes in the intertidal distribution of T. funebralis similar to those observed during the summer increase in seastar numbers. It is suggested that these results supplant the hypothesis that lowered prereproductive mortality influences formation and maintenance of vertical size gradients in the lower intertidal

Intelligent Camera Control Using Behavior Trees

Automatic camera systems produce very basic animations for virtual worlds. Users often view environments through two types of cameras: a camera that they control manually, or a very basic automatic camera that follows their character, minimizing occlusions. Real cinematography features much more variety producing more robust stories. Cameras shoot establishing shots, close-ups, tracking shots, and bird’s eye views to enrich a narrative. Camera techniques such as zoom, focus, and depth of field contribute to framing a particular shot. We present an intelligent camera system that automatically positions, pans, tilts, zooms, and tracks events occurring in real-time while obeying traditional standards of cinematography. We design behavior trees that describe how a single intelligent camera might behave from low-level narrative elements assigned by “smart events”. Camera actions are formed by hierarchically arranging behavior sub-trees encapsulating nodes that control specific camera semantics. This approach is more modular and particularly reusable for quickly creating complex camera styles and transitions rather then focusing only on visibility. Additionally, our user interface allows a director to provide further camera instructions, such as prioritizing one event over another, drawing a path for the camera to follow, and adjusting camera settings on the fly.We demonstrate our method by placing multiple intelligent cameras in a complicated world with several events and storylines, and illustrate how to produce a well-shot “documentary” of the events constructed in real-time

Automated group assignment in large phylogenetic trees using GRUNT: GRouping, Ungrouping, Naming Tool

<p>Abstract</p> <p>Background</p> <p>Accurate taxonomy is best maintained if species are arranged as hierarchical groups in phylogenetic trees. This is especially important as trees grow larger as a consequence of a rapidly expanding sequence database. Hierarchical group names are typically manually assigned in trees, an approach that becomes unfeasible for very large topologies.</p> <p>Results</p> <p>We have developed an automated iterative procedure for delineating stable (monophyletic) hierarchical groups to large (or small) trees and naming those groups according to a set of sequentially applied rules. In addition, we have created an associated ungrouping tool for removing existing groups that do not meet user-defined criteria (such as monophyly). The procedure is implemented in a program called GRUNT (GRouping, Ungrouping, Naming Tool) and has been applied to the current release of the Greengenes (Hugenholtz) 16S rRNA gene taxonomy comprising more than 130,000 taxa.</p> <p>Conclusion</p> <p>GRUNT will facilitate researchers requiring comprehensive hierarchical grouping of large tree topologies in, for example, database curation, microarray design and pangenome assignments. The application is available at the greengenes website <abbrgrp><abbr bid="B1">1</abbr></abbrgrp>.</p

Searching for the Kuhnian moment : the Black-Scholes-Merton formula and the evolution of modern finance theory

The Black-Scholes-Merton formula has been put to widespread use by options traders because it provides a means of calculating the theoretically 'correct' price of stock options. Traders can therefore see whether the market price of stock options undervalues or overvalues them compared with their hypothetical Black-Scholes-Merton price, before choosing to buy or sell options accordingly. As a consequence of this close relationship between options pricing theory and options pricing practice, a strong performativity loop was activated, whereby market prices quickly converged on the hypothetical Black-Scholes-Merton prices following the dissemination of the formula. The theory has therefore had significant real-world effects, but how should we characterize the initial instinct to derive the theory from a philosophy of science perspective? The two books under review suggest that a Kuhnian reading of the advancement of scientific knowledge might well be the most appropriate. But, on closer inspection, it becomes clear that the publication of the Black-Scholes-Merton formula should not be seen as a Kuhnian moment with paradigm-shaping attributes. It is shown that, at most, the formula acts as an important exemplar which, via its use in the training of options pricing theorists and options pricing practitioners, reinforces the entrenchment of finance theory within the orthodox economics worldview

Virtually Real, But Not Quite There: Social and Economic Barriers to Meeting Virtual Reality’s True Potential for Mental Health

7 pagesStrategies to mitigate the spread of COVID-19, namely quarantine and social distancing protocols, have exposed a troubling paradox: mandated isolation meant to preserve well-being has inadvertently contributed to its decline. Prolonged isolation has been associated with widespread loneliness and diminished mental health, with effects compounded by limited face-to-face access to clinical and social support systems. While remote communication technologies (e.g., video chat) can connect individuals with healthcare providers and social networks, remote technologies might have limited effectiveness in clinical and social contexts. In this review, we articulate the promise of Virtual Reality as a conduit to clinical resources and social connection. Furthermore, we outline various social and economic factors limiting the virtual reality industry’s ability to maximize its potential to address mental health issues brought upon by the pandemic. These barriers are delineated across five dimensions: sociocultural, content, affordability, supply chain, and equitable design. After examining potential short- and long-term solutions to these hurdles, we outline potential avenues for applied and theoretical research seeking to validate these solutions. Through this evaluation we seek to (a) emphasize virtual reality’s capacity to improve mental health by connecting communities to clinical and social support systems, (b) identify socioeconomic barriers preventing users from accessing these systems through virtual reality, and (c) discuss solutions that ensure these systems can be equitably accessed via changes to existing and future virtual reality infrastructures

Compassion fade and the challenge of environmental conservation

Compassion shown towards victims often decreases as the number of individuals in need of aid increases, identifiability of the victims decreases, and the proportion of victims helped shrinks. Such “compassion fade” may hamper individual-level and collective responses to pressing large-scale crises. To date, research on compassion fade has focused on humanitarian challenges; thus, it remains unknown whether and to what extent compassion fade emerges when victims are non-human others. Here we show that compassion fade occurs in the environmental domain, but only among non-environmentalists. These findings suggest that compassion fade may challenge our collective ability and willingness to confront the major environmental problems we face, including climate change. The observed moderation effect of environmental identity further indicates that compassion fade may present a significant psychological barrier to building broad public support for addressing these problems. Our results highlight the importance of bringing findings from the field of judgment and decision making to bear on pressing societal issues

Discovery of soft and hard X-ray time lags in low-mass AGNs

The scaling relations between the black hole (BH) mass and soft lag properties for both active galactic nuclei (AGNs) and BH X-ray binaries (BHXRBs) suggest the same underlying physical mechanism at work in accreting BH systems spanning a broad range of mass. However, the low-mass end of AGNs has never been explored in detail. In this work, we extend the existing scaling relations to lower-mass AGNs, which serve as anchors between the normal-mass AGNs and BHXRBs. For this purpose, we construct a sample of low-mass AGNs ($M_{\rm BH}<3\times 10^{6} M_{\rm \odot}$) from the XMM-Newton archive and measure frequency-resolved time delays between the soft (0.3-1 keV) and hard (1-4 keV) X-ray emissions. We report that the soft band lags behind the hard band emission at high frequencies $\sim[1.3-2.6]\times 10^{-3}$ Hz, which is interpreted as a sign of reverberation from the inner accretion disc in response to the direct coronal emission. At low frequencies ($\sim[3-8]\times 10^{-4}$ Hz), the hard band lags behind the soft band variations, which we explain in the context of the inward propagation of luminosity fluctuations through the corona. Assuming a lamppost geometry for the corona, we find that the X-ray source of the sample extends at an average height and radius of $\sim 10r_{\rm g}$ and $\sim 6r_{\rm g}$, respectively. Our results confirm that the scaling relations between the BH mass and soft lag amplitude/frequency derived for higher-mass AGNs can safely extrapolate to lower-mass AGNs, and the accretion process is indeed independent of the BH mass.Comment: 11 pages, 5 figures, 4 tables, Published in MNRA

Incorporating Breast Cancer Recurrence Events Into Population-Based Cancer Registries Using Medical Claims: Cohort Study.

BACKGROUND: There is a need for automated approaches to incorporate information on cancer recurrence events into population-based cancer registries. OBJECTIVE: The aim of this study is to determine the accuracy of a novel data mining algorithm to extract information from linked registry and medical claims data on the occurrence and timing of second breast cancer events (SBCE). METHODS: We used supervised data from 3092 stage I and II breast cancer cases (with 394 recurrences), diagnosed between 1993 and 2006 inclusive, of patients at Kaiser Permanente Washington and cases in the Puget Sound Cancer Surveillance System. Our goal was to classify each month after primary treatment as pre- versus post-SBCE. The prediction feature set for a given month consisted of registry variables on disease and patient characteristics related to the primary breast cancer event, as well as features based on monthly counts of diagnosis and procedure codes for the current, prior, and future months. A month was classified as post-SBCE if the predicted probability exceeded a probability threshold (PT); the predicted time of the SBCE was taken to be the month of maximum increase in the predicted probability between adjacent months. RESULTS: The Kaplan-Meier net probability of SBCE was 0.25 at 14 years. The month-level receiver operating characteristic curve on test data (20% of the data set) had an area under the curve of 0.986. The person-level predictions (at a monthly PT of 0.5) had a sensitivity of 0.89, a specificity of 0.98, a positive predictive value of 0.85, and a negative predictive value of 0.98. The corresponding median difference between the observed and predicted months of recurrence was 0 and the mean difference was 0.04 months. CONCLUSIONS: Data mining of medical claims holds promise for the streamlining of cancer registry operations to feasibly collect information about second breast cancer events

Functional analysis of metagenomes and metatranscriptomes using SEED and KEGG

Background: Metagenomics is the study of microbial organisms using sequencing applied directly to environmental samples. Technological advances in next-generation sequencing methods are fueling a rapid increase in the number and scope of metagenome projects. While metagenomics provides information on the gene content, metatranscriptomics aims at understanding gene expression patterns in microbial communities. The initial computational analysis of a metagenome or metatranscriptome addresses three questions: (1) Who is out there? (2) What are they doing? and (3) How do different datasets compare? There is a need for new computational tools to answer these questions. In 2007, the program MEGAN (MEtaGenome ANalyzer) was released, as a standalone interactive tool for analyzing the taxonomic content of a single metagenome dataset. The program has subsequently been extended to support comparative analyses of multiple datasets. Results: The focus of this paper is to report on new features of MEGAN that allow the functional analysis of multiple metagenomes (and metatranscriptomes) based on the SEED hierarchy and KEGG pathways. We have compared our results with the MG-RAST service for different datasets. Conclusions: The MEGAN program now allows the interactive analysis and comparison of the taxonomical and functional content of multiple datasets. As a stand-alone tool, MEGAN provides an alternative to web portals for scientists that have concerns about uploading their unpublished data to a website