Gastric perforation and pancreatitis manifesting after an inadvertent nissen fundoplication in a patient with superior mesenteric artery syndrome.

Superior mesenteric artery (SMA) syndrome is an uncommon but well-recognized clinical entity. It can lead to proximal small bowel obstruction and severe morbidity and mortality in lieu of late diagnosis and concomitant existing comorbidities. We report a 54-year-old female, with SMA syndrome which manifested itself after Nissen fundoplication along with two major complications. The diagnosis of SMA was established by clinical symptoms and radiological findings

Local climatic changes affect biodiversity responses to land use: a review

Aim Climate and land‐use change, the greatest pressures on biodiversity, can directly influence each other. One key case is the impact land‐use change has on local climatic conditions: human‐altered areas are often warmer and drier than natural habitats. This can have multiple impacts on biodiversity and is a rapidly developing field of research. Here, we summarize the current state of understanding on the impact that local climatic changes have on biodiversity responses to land‐use change, in particular looking at whether human‐altered land uses favour species with certain climatic niches. Location Global. Methods We review studies that have identified links between species' climatic niches and the habitats/land‐use types they inhabit. We also critically discuss the methods used to explore this topic (such as the estimation of fundamental vs. realized climatic niches), identify key knowledge gaps by reference to related macroecological literature and make suggestions for further work. Results Assemblages of vertebrate and invertebrate species in numerous human‐dominated land uses have been found to have higher proportions of individuals affiliated with higher temperatures and lower precipitation levels than assemblages within natural habitats. However, uncertainty surrounds the mechanisms that underlie these observed differences between communities across land‐use types, and it remains unexplored as to whether these trends differ geographically or taxonomically. Main conclusion Shifts are being observed within human‐altered land uses to communities with, on average, warmer and drier climatic niches. A better understanding of the effects of local climatic changes associated with land‐use change will enhance our ability to predict future impacts on biodiversity, identify the species most at risk from interactions between climate and land‐use change and set up suitable management and conservation plans

Vertebrate responses to human land use are influenced by their proximity to climatic tolerance limits

Aim Land‐use change leads to local climatic changes, which can induce shifts in community composition. Indeed, human‐altered land uses favour species able to tolerate greater temperature and precipitation extremes. However, environmental changes do not impact species uniformly across their distributions, and most research exploring the impacts of climatic changes driven by land use has not considered potential within‐range variation. We explored whether a population's climatic position (the difference between species' thermal and precipitation tolerance limits and the environmental conditions a population experiences) influences their relative abundance across land‐use types. Location Global. Methods Using a global dataset of terrestrial vertebrate species and estimating their realized climatic tolerance limits, we analysed how the abundance of species within human‐altered habitats relative to that in natural habitats varied across different climatic positions (controlling for proximity to geographic range edge). Results A population's thermal position strongly influenced abundance within human‐altered land uses (e.g. agriculture). Where temperature extremes were closer to species' thermal limits, population abundances were lower in human‐altered land uses (relative to natural habitat) compared to areas further from these limits. These effects were generally stronger at tropical compared to temperate latitudes. In contrast, the influences of precipitation position were more complex and often differed between land uses and geographic zones. Mapping the outcome of models revealed strong spatial variation in the potential severity of decline for vertebrate populations following conversion from natural habitat to cropland or pasture, due to their climatic position. Main conclusions We highlight within‐range variation in species' responses to land use, driven (at least partly), by differences in climatic position. Accounting for spatial variation in responses to environmental changes is critical when predicting population vulnerability, producing successful conservation plans, and exploring how biodiversity may be impacted by future land‐use and climate change interactions

Prediction Markets, Social Media and Information Efficiency

We consider the impact of breaking news on market prices. We measure activity on the micro-blogging platform Twitter surrounding a unique, newsworthy and identifiable event and investigate subsequent movements of betting prices on the prominent betting exchange, Bet- fair. The event we use is the Bigotgate scandal, which occurred during the 2010 UK General Election campaign. We use recent developments in time series econometric methods to identify and quantify movements in both Twitter activity and Betfair prices, and compare the timings of the two. We find that the response of market prices appears somewhat sluggish and is indicative of market inefficiency, as Betfair prices adjust with a delay, and there is evidence for post-news drift. This slow movement may be explained by the need for corroborating evidence via more traditional forms of media. Once important Tweeters begin to Tweet, including importantly breaking news Twitter feeds from traditional media sources, prices begin to move

Polls to probabilities: comparing prediction markets and opinion polls

Forecasting election outcomes is a hugely popular activity, and not without reason: outcomes can have significant economic impacts, for example on stock prices. As such, it is economically important, as well as of academic interest, to determine the forecasting methods that have historically performed best. However, forecasts are often incompatible, as some are in terms of vote shares, and others are probabilistic outcome forecasts. In this paper we set out an empirical method for transforming opinion poll vote shares into probabilistic forecasts, and then evaluate the performance of prediction markets and opinion polls. We compare along two dimensions: bias and precision. We find that converted opinion polls perform well in terms of bias, and prediction markets on precision

Use of an online interactive space analysis tool to understand student perceptions of four secondary schools

With the sheer complexity of the built environment, understanding the aspects of the building that directly impact the occupants can be prohibitively difficult. Previous methods have been largely split between low-number, high-detail methods (photo-surveys or interviews), or high-number, low-detail methods (questionnaires). This study presents an alternative to these methods; creating an online tool that represents a navigable building, enabling the occupants to freely identify any aspect of the building that they feel is important. This online tool deliberately works in a manner similar to Google Street View, taking advantage of this familiarity to reduce the learning curve and maximise immersion. Using spherical images captured with a special camera or smartphone, each space in the building is captured and then uploaded into the online tool. Whilst in the online version of their building, the respondent can navigate through the building, make unguided comments about any part of the building. Using this tool, four recently built secondary schools were imaged and online versions created. In each school, students from three ICT lessons aged between 11 and 14 explored the online version of their school and marked parts of the building that were important to them. The students were asked to follow a typical day in the school, moving from lesson to lesson and to the spaces they use at breaks. The tool collected both the movement data and the comments, allowing analysis of not just the occupant attitudes, but also the route the students take through the building. The movement data for each school was compared to the visual graph analysis of the building, showing that the movement of the students within the tool resembles patterns seen elsewhere; configurational logic with attractors. The rich data that is generated in parallel with the movement data allowed insights into the way in which the students moved through the space and what was important to them

RiPPLE: A crowdsourced adaptive platform for recommendation of learning activities

© 2019, UTS ePRESS. All rights reserved. This paper presents a platform called RiPPLE (Recommendation in Personalised Peer-Learning Environments) that recommends personalized learning activities to students based on their knowledge state from a pool of crowdsourced learning activities that are generated by educators and the students themselves. RiPPLE integrates insights from crowdsourcing, learning sciences, and adaptive learning, aiming to narrow the gap between these large bodies of research while providing a practical platform-based implementation that instructors can easily use in their courses. This paper provides a design overview of RiPPLE, which can be employed as a standalone tool or embedded into any learning management system (LMS) or online platform that supports the Learning Tools Interoperability (LTI) standard. The platform has been evaluated based on a pilot in an introductory course with 453 students at The University of Queensland. Initial results suggest that the use of the RiPPLE platform led to measurable learning gains and that students perceived the platform as beneficially supporting their learning

Eotaxin: a potent eosinophil chemoattractant cytokine detected in a guinea pig model of allergic airways inflammation.

Eosinophil accumulation is a prominent feature of allergic inflammatory reactions, such as those occurring in the lung of the allergic asthmatic, but the endogenous chemoattractants involved have not been identified. We have investigated this in an established model of allergic inflammation, using in vivo systems both to generate and assay relevant activity. Bronchoalveolar lavage (BAL) fluid was taken from sensitized guinea pigs at intervals after aerosol challenge with ovalbumin. BAL fluid was injected intradermally in unsensitized assay guinea pigs and the accumulation of intravenously injected 111In-eosinophils was measured. Activity was detected at 30 min after allergen challenge, peaking from 3 to 6 h and declining to low levels by 24 h. 3-h BAL fluid was purified using high performance liquid chromatography techniques in conjunction with the skin assay. Microsequencing revealed a novel protein from the C-C branch of the platelet factor 4 superfamily of chemotactic cytokines. The protein, eotaxin, exhibits homology of 53% with human MCP-1, 44% with guinea pig MCP-1, 31% with human MIP-1α, and 26% with human RANTES. Laser desorption time of flight mass analysis gave four different signals (8.15, 8.38, 8.81, and 9.03 kD), probably reflecting differential O-glycosylation. Eotaxin was highly potent, inducing substantial 111In-eosinophil accumulation at a 1-2-pmol dose in the skin, but did not induce significant 111In-neutrophil accumulation. Eotaxin was a potent stimulator of both guinea pig and human eosinophils in vitro. Human recombinant RANTES, MIP-1α, and MCP-1 were all inactive in inducing 111In-eosinophil accumulation in guinea pig skin; however, evidence was obtained that eotaxin shares a binding site with RANTES on guinea pig eosinophils. This is the first description of a potent eosinophil chemoattractant cytokine generated in vivo and suggests the possibility that similar molecules may be important in the human asthmatic lung