One "shape" fits all: The orientation bandwidth of contour integration

The ability of human participants to integrate fragmented stimulus elements into perceived coherent contours (amidst a field of distracter elements) has been intensively studied across a large number of contour element parameters, ranging from luminance contrast and chromaticity to motion and stereo. The evidence suggests that contour integration performance depends on the low-level Fourier properties of the stimuli. Thus, to understand contour integration, it would be advantageous to understand the properties of the low-level filters that the visual system uses to process contour stimuli. We addressed this issue by examining the role of stimulus element orientation bandwidth in contour integration, a previously unexplored area. We carried out three psychophysical experiments, and then simulated all of the experiments using a recently developed two-stage filter-overlap model whereby the contour grouping occurs by virtue of the overlap between the filter responses to different elements. The first stage of the model responds to the elements, while the second stage integrates the responses along the contour. We found that the first stage had to be fairly broadly tuned for orientation to account for our results. The model showed a very good fit to a large data set with relatively few free parameters, suggesting that this class of model may have an important role to play in helping us to better understand the mechanisms of contour integration

Can sacrificial feeding areas protect aquatic plants from herbivore grazing? Using behavioural ecology to inform wildlife management

Effective wildlife management is needed for conservation, economic and human well-being objectives. However, traditional population control methods are frequently ineffective, unpopular with stakeholders, may affect non-target species, and can be both expensive and impractical to implement. New methods which address these issues and offer effective wildlife management are required. We used an individual-based model to predict the efficacy of a sacrificial feeding area in preventing grazing damage by mute swans (Cygnus olor) to adjacent river vegetation of high conservation and economic value. The accuracy of model predictions was assessed by a comparison with observed field data, whilst prediction robustness was evaluated using a sensitivity analysis. We used repeated simulations to evaluate how the efficacy of the sacrificial feeding area was regulated by (i) food quantity, (ii) food quality, and (iii) the functional response of the forager. Our model gave accurate predictions of aquatic plant biomass, carrying capacity, swan mortality, swan foraging effort, and river use. Our model predicted that increased sacrificial feeding area food quantity and quality would prevent the depletion of aquatic plant biomass by swans. When the functional response for vegetation in the sacrificial feeding area was increased, the food quantity and quality in the sacrificial feeding area required to protect adjacent aquatic plants were reduced. Our study demonstrates how the insights of behavioural ecology can be used to inform wildlife management. The principles that underpin our model predictions are likely to be valid across a range of different resource-consumer interactions, emphasising the generality of our approach to the evaluation of strategies for resolving wildlife management problems

Strategy complexity of concurrent safety games

We consider two player, zero-sum, finite-state concurrent reachability games, played for an infinite number of rounds, where in every round, each player simultaneously and independently of the other players chooses an action, whereafter the successor state is determined by a probability distribution given by the current state and the chosen actions. Player 1 wins iff a designated goal state is eventually visited. We are interested in the complexity of stationary strategies measured by their patience, which is defined as the inverse of the smallest non-zero probability employed. Our main results are as follows: We show that: (i) the optimal bound on the patience of optimal and -optimal strategies, for both players is doubly exponential; and (ii) even in games with a single non-absorbing state exponential (in the number of actions) patience is necessary

Prediction of the Atomization Energy of Molecules Using Coulomb Matrix and Atomic Composition in a Bayesian Regularized Neural Networks

Exact calculation of electronic properties of molecules is a fundamental step for intelligent and rational compounds and materials design. The intrinsically graph-like and non-vectorial nature of molecular data generates a unique and challenging machine learning problem. In this paper we embrace a learning from scratch approach where the quantum mechanical electronic properties of molecules are predicted directly from the raw molecular geometry, similar to some recent works. But, unlike these previous endeavors, our study suggests a benefit from combining molecular geometry embedded in the Coulomb matrix with the atomic composition of molecules. Using the new combined features in a Bayesian regularized neural networks, our results improve well-known results from the literature on the QM7 dataset from a mean absolute error of 3.51 kcal/mol down to 3.0 kcal/mol.Comment: Under review ICANN 201

Involvement in emergency situations by primary care doctors on-call in Norway - a prospective population-based observational study

<p>Abstract</p> <p>Background</p> <p>Primary care doctors on-call in the emergency primary health care services in Norway are, together with the ambulances, the primary resources for handling emergencies outside hospitals. There is a lack of reliable data for Norway on how often the primary care doctors are alerted and on their responses in the most urgent emergency cases. The aim of this study was to investigate how doctors on-call are involved in red responses (highest priority), using three different emergency medical communication centres (EMCC) as catchment area for a prospective population-based study.</p> <p>Methods</p> <p>In the period from October to December 2007 three dispatch centres covering approximately 816 000 inhabitants prospectively recorded all acute emergency cases. Ambulance records, air ambulance records and records from the doctors on-call were collected. NACA score was used to define the severity of the emergencies.</p> <p>Results</p> <p>5 105 cases were classified as red responses during the period. We have complete basic recordings (AMIS forms) from all and resaved ambulance records, air ambulance records and records from doctors on-call in 89% of the cases. Ambulances were alerted in 96% and doctors on-call in 47% of the cases, but there were large differences between the three EMCCs. Doctors on-call responded with call-out in 42% of the alerted cases. 28% of all patients were taken to a casualty clinic, 46% were admitted to hospital by a doctor and 24% were taken directly to hospital by ambulances. In total, primary care doctors on-call took active part in 42% of all red response cases, and together with GPs' daytime activity the primary health care services were involved in 50% of the cases. 29% of the cases were classified as life-threatening. Call-out by doctors on-call were found to be more frequent in life-threatening situations compared with not life-threatening situations.</p> <p>Conclusion</p> <p>Doctors on-call and GPs on daytime were involved in half of all red responses. There were large differences between the EMCCs in the frequency of doctors alerted. The inhabitants in the three EMMCs were thus offered different levels of professional competency in emergency situations outside hospitals.</p

How a Diverse Research Ecosystem Has Generated New Rehabilitation Technologies: Review of NIDILRR’s Rehabilitation Engineering Research Centers

Over 50 million United States citizens (1 in 6 people in the US) have a developmental, acquired, or degenerative disability. The average US citizen can expect to live 20% of his or her life with a disability. Rehabilitation technologies play a major role in improving the quality of life for people with a disability, yet widespread and highly challenging needs remain. Within the US, a major effort aimed at the creation and evaluation of rehabilitation technology has been the Rehabilitation Engineering Research Centers (RERCs) sponsored by the National Institute on Disability, Independent Living, and Rehabilitation Research. As envisioned at their conception by a panel of the National Academy of Science in 1970, these centers were intended to take a “total approach to rehabilitation”, combining medicine, engineering, and related science, to improve the quality of life of individuals with a disability. Here, we review the scope, achievements, and ongoing projects of an unbiased sample of 19 currently active or recently terminated RERCs. Specifically, for each center, we briefly explain the needs it targets, summarize key historical advances, identify emerging innovations, and consider future directions. Our assessment from this review is that the RERC program indeed involves a multidisciplinary approach, with 36 professional fields involved, although 70% of research and development staff are in engineering fields, 23% in clinical fields, and only 7% in basic science fields; significantly, 11% of the professional staff have a disability related to their research. We observe that the RERC program has substantially diversified the scope of its work since the 1970’s, addressing more types of disabilities using more technologies, and, in particular, often now focusing on information technologies. RERC work also now often views users as integrated into an interdependent society through technologies that both people with and without disabilities co-use (such as the internet, wireless communication, and architecture). In addition, RERC research has evolved to view users as able at improving outcomes through learning, exercise, and plasticity (rather than being static), which can be optimally timed. We provide examples of rehabilitation technology innovation produced by the RERCs that illustrate this increasingly diversifying scope and evolving perspective. We conclude by discussing growth opportunities and possible future directions of the RERC program

Removal of ecotoxicity of 17α-ethinylestradiol using TAML/peroxide water treatment

17α -ethinylestradiol (EE2), a synthetic oestrogen in oral contraceptives, is one of many pharmaceuticals found in inland waterways worldwide as a result of human consumption and excretion into wastewater treatment systems. At low parts per trillion (ppt), EE2 induces feminisation of male fish, diminishing reproductive success and causing fish population collapse. Intended water quality standards for EE2 set a much needed global precedent. Ozone and activated carbon provide effective wastewater treatments, but their energy intensities and capital/operating costs are formidable barriers to adoption. Here we describe the technical and environmental performance of a fast- developing contender for mitigation of EE2 contamination of wastewater based upon smallmolecule, full-functional peroxidase enzyme replicas called “TAML activators”. From neutral to basic pH, TAML activators with H2O2 efficiently degrade EE2 in pure lab water, municipal effluents and EE2-spiked synthetic urine. TAML/H2O2 treatment curtails estrogenicity in vitro and substantially diminishes fish feminization in vivo. Our results provide a starting point for a future process in which tens of thousands of tonnes of wastewater could be treated per kilogram of catalyst. We suggest TAML/H2O2 is a worthy candidate for exploration as an environmentally compatible, versatile, method for removing EE2 and other pharmaceuticals from municipal wastewaters.Heinz Endowments, the Swiss National Science Foundation, the Steinbrenner Institute for a Steinbrenner Doctoral Fellowship. NMR instrumentation at CMU was partially supported by NSF (CHE-0130903 and CHE-1039870)

Multi-omics differentially classify disease state and treatment outcome in pediatric Crohn's disease

Background: Crohn's disease (CD) has an unclear etiology, but there is growing evidence of a direct link with a dysbiotic microbiome. Many gut microbes have previously been associated with CD, but these have mainly been confounded with patients' ongoing treatments. Additionally, most analyses of CD patients' microbiomes have focused on microbes in stool samples, which yield different insights than profiling biopsy samples. Results: We sequenced the 16S rRNA gene (16S) and carried out shotgun metagenomics (MGS) from the intestinal biopsies of 20 treatment-naïve CD and 20 control pediatric patients. We identified the abundances of microbial taxa and inferred functional categories within each dataset. We also identified known human genetic variants from the MGS data. We then used a machine learning approach to determine the classification accuracy when these datasets, collapsed to different hierarchical groupings, were used independently to classify patients by disease state and by CD patients' response to treatment. We found that 16S-identified microbes could classify patients with higher accuracy in both cases. Based on follow-ups with these patients, we identified which microbes and functions were best for predicting disease state and response to treatment, including several previously identified markers. By combining the top features from all significant models into a single model, we could compare the relative importance of these predictive features. We found that 16S-identified microbes are the best predictors of CD state whereas MGS-identified markers perform best for classifying treatment response. Conclusions: We demonstrate for the first time that useful predictors of CD treatment response can be produced from shotgun MGS sequencing of biopsy samples despite the complications related to large proportions of host DNA. The top predictive features that we identified in this study could be useful for building an improved classifier for CD and treatment response based on sufferers' microbiome in the future. The BISCUIT project is funded by a Clinical Academic Fellowship from the Chief Scientist Office (Scotland)-CAF/08/01

Ten Years of Experience Training Non-Physician Anesthesia Providers in Haiti.

Surgery is increasingly recognized as an effective means of treating a proportion of the global burden of disease, especially in resource-limited countries. Often non-physicians, such as nurses, provide the majority of anesthesia; however, their training and formal supervision is often of low priority or even non-existent. To increase the number of safe anesthesia providers in Haiti, Médecins Sans Frontières has trained nurse anesthetists (NAs) for over 10 years. This article describes the challenges, outcomes, and future directions of this training program. From 1998 to 2008, 24 students graduated. Nineteen (79%) continue to work as NAs in Haiti and 5 (21%) have emigrated. In 2008, NAs were critical in providing anesthesia during a post-hurricane emergency where they performed 330 procedures. Mortality was 0.3% and not associated with lack of anesthesiologist supervision. The completion rate of this training program was high and the majority of graduates continue to work as nurse anesthetists in Haiti. Successful training requires a setting with a sufficient volume and diversity of operations, appropriate anesthesia equipment, a structured and comprehensive training program, and recognition of the training program by the national ministry of health and relevant professional bodies. Preliminary outcomes support findings elsewhere that NAs can be a safe and effective alternative where anesthesiologists are scarce. Training non-physician anesthetists is a feasible and important way to scale up surgical services resource limited settings