On the Distribution and Fishery Potential of the Japanese Red Crab Chaceon granulatus in the Palauan Archipelago, Western Caroline Islands

A deep-water trapping survey in the Palauan archipelago, Western Caroline Islands, has revealed an abundance of the Japanese red crab, Chaceon granulatus. The recorded depth range (250-900 m) is similar to that of other geryonids, but the large numbers of females caught below 700 m is atypical. Mean yields in excess of 5 kg crabs plus 1 kg shrimp, Heterocarpus laevigatus, by-catch per trap-night were attainable at optimum depths. Chaceon granulatus is apparently a very large geryonid, with maximum weights of 2.02 kg and 1.51 kg recorded for male and female specimens, respectively. A range of body colors was observed: Orange-red shades appear to dominate the deeper waters (below 500 m) while yellow-tan colors are more abundant in the upper reaches. Preliminary evidence suggests that Chaceon granulatus is highly marketable, and the infrastructure in Palau is such that crabs could either be marketed fresh locally or airfreighted to Japan as a quick-frozen product. The high post-trapping survival rates observed indicate that maintaining crabs in live-holding tanks may be a feasible option. The large catches and quality of deep-water crabs taken suggests that the Palauan population of Chaceon granulatus may be able to support a small-scale fishery. It is not yet known whether this population is unusually large or whether these findings typify the deep forereef fauna of the region

Results of the 2004/2005 Hospice Patient Survey: General Report

The National Minimum Standards for Independent Healthcare, published in 2002 by the Care Standards Commission (now the Healthcare Commission) states that hospices are required to conduct an annual patient survey. In response to this, a Patient Survey group (with representation from independent hospices, Marie Curie Cancer Care and with input from the Care Standards Commission) was set up by Help the Hospices. Its goal was to develop a questionnaire suitable for use in all adult hospices

Caring in Kent: Patterns and Profiles, Evidence from the Kent Health and Lifestyle Survey, 2005

The ‘Caring in Kent’ report draws on the results of a Kent wide ‘Health and Lifestyle Survey’ conducted in 2005; this included a module on caring. This enables a picture of caring to be reported including: a general profile of carers, levels and types of care-giving, carers’ health, and the level and types of support they receive. ‘Carers provide unpaid care by looking after an ill, frail or disabled family member, friend or partner’. The increasingly recognised importance of the role of the ‘informal carer’ is - in good part - due to the rising proportion of older people in the UK population. Not only do people live longer but many experience a number of chronic conditions; these require support from family members if the older person is to remain living in the community

Service Development Programme: Maximising Life Opportunities for Teenagers. Teenagers' Views and Experiences of Sex and Relationships Education, Sexual Health Services and Family Support Services in Kent - Survey findings for Year 2

This brief report provides findings from data collected in year 2 of a survey of teenagers' views and experiences of sex and relationships education and sexual health services in Kent. The data in year 2 was collected in Autumn 2005, a year after the data collected in year 1. The purpose of this report is to highlight the results in year 2 which differ from the year 1 survey data. It is to be used in conjunction with the report in year 1 entitled "Service Development Programme: Maximising Life Opportunies for Teenagers: Teenagers' Views and Experiences of Sex and Relationships Educatioon, Sexual Health Services and Family Suupport Services in Kent: Survey Findings July 2005". The final report on the survey will consist of findings from further analysis of the data from year 1 and year 2 merged together, available at the end of 2006

Premium: An R package for profile regression mixture models using dirichlet processes

PReMiuM is a recently developed R package for Bayesian clustering using a Dirichlet process mixture model. This model is an alternative to regression models, nonparametrically linking a response vector to covariate data through cluster membership (Molitor, Papathomas, Jerrett, and Richardson 2010). The package allows binary, categorical, count and continuous response, as well as continuous and discrete covariates. Additionally, predictions may be made for the response, and missing values for the covariates are handled. Several samplers and label switching moves are implemented along with diagnostic tools to assess convergence. A number of R functions for post-processing of the output are also provided. In addition to fitting mixtures, it may additionally be of interest to determine which covariates actively drive the mixture components. This is implemented in the package as variable selection

The influence of perceived causation on judgments of time: an integrative review and implications for decision-making

Recent research has shown that the perception of causality affects the judgment of elapsed time: an interval between an action and a subsequent event seems to be shorter when people believe that action has caused the event. This article reviews past work on the phenomenon and integrates the findings from the different settings in which it has been observed. The effect is found for actions people have personally taken, as well as for those they have simply read or heard about. It occurs for very short intervals (e.g., milliseconds) as well as longer periods (e.g., months or years). Beliefs and expectations about different types of causal forces and their trajectories over time can affect the degree of time compression in some settings. But the tendency toward compression of time is the default and dominant response: It persists when people think of generic causal relations and is enhanced when people opt for the quickest interpretation of causal relations. This robust influence of causality on time judgment appears to be linked to the basic tendency to rely on temporal proximity in processing causal relations and to people's early experience with the physical-mechanical world. Past work has focused primarily on the implications of time compression for the sense of agency, but this phenomenon has implications also for decisions that depend on time judgment. The compression of subjective time elapsed between actions and outcomes makes people more optimistically plan the timing of a focal action in the future, experience its effect earlier in the future, and be less likely to switch to an alternative course of action. The tendency toward compression can thus endow an action with a sort of privileged status or advantage

Expected exponential loss for gaze-based video and volume ground truth annotation

Many recent machine learning approaches used in medical imaging are highly reliant on large amounts of image and ground truth data. In the context of object segmentation, pixel-wise annotations are extremely expensive to collect, especially in video and 3D volumes. To reduce this annotation burden, we propose a novel framework to allow annotators to simply observe the object to segment and record where they have looked at with a \$200 eye gaze tracker. Our method then estimates pixel-wise probabilities for the presence of the object throughout the sequence from which we train a classifier in semi-supervised setting using a novel Expected Exponential loss function. We show that our framework provides superior performances on a wide range of medical image settings compared to existing strategies and that our method can be combined with current crowd-sourcing paradigms as well.Comment: 9 pages, 5 figues, MICCAI 2017 - LABELS Worksho

Machine Learning for Quantum Mechanical Properties of Atoms in Molecules

We introduce machine learning models of quantum mechanical observables of atoms in molecules. Instant out-of-sample predictions for proton and carbon nuclear chemical shifts, atomic core level excitations, and forces on atoms reach accuracies on par with density functional theory reference. Locality is exploited within non-linear regression via local atom-centered coordinate systems. The approach is validated on a diverse set of 9k small organic molecules. Linear scaling of computational cost in system size is demonstrated for saturated polymers with up to sub-mesoscale lengths

A General Optimization Technique for High Quality Community Detection in Complex Networks

Recent years have witnessed the development of a large body of algorithms for community detection in complex networks. Most of them are based upon the optimization of objective functions, among which modularity is the most common, though a number of alternatives have been suggested in the scientific literature. We present here an effective general search strategy for the optimization of various objective functions for community detection purposes. When applied to modularity, on both real-world and synthetic networks, our search strategy substantially outperforms the best existing algorithms in terms of final scores of the objective function; for description length, its performance is on par with the original Infomap algorithm. The execution time of our algorithm is on par with non-greedy alternatives present in literature, and networks of up to 10,000 nodes can be analyzed in time spans ranging from minutes to a few hours on average workstations, making our approach readily applicable to tasks which require the quality of partitioning to be as high as possible, and are not limited by strict time constraints. Finally, based on the most effective of the available optimization techniques, we compare the performance of modularity and code length as objective functions, in terms of the quality of the partitions one can achieve by optimizing them. To this end, we evaluated the ability of each objective function to reconstruct the underlying structure of a large set of synthetic and real-world networks.Comment: MAIN text: 14 pages, 4 figures, 1 table Supplementary information: 19 pages, 8 figures, 5 table

1.6 W continuous-wave Raman laser using low-loss synthetic diamond

Low-birefringence (Δn<2x10−6), low-loss (absorption coefficient <0.006cm−1 at 1064nm), single-crystal, synthetic diamond has been exploited in a CW Raman laser. The diamond Raman laser was intracavity pumped within a Nd:YVO4 laser. At the Raman laser wavelength of 1240nm, CW output powers of 1.6W and a slope efficiency with respect to the absorbed diode-laser pump power (at 808nm) of ~18% were measured. In quasi-CW operation, maximum on-time output powers of 2.8W (slope efficiency ~24%) were observed, resulting in an absorbed diode-laser pump power to the Raman laser output power conversion efficiency of 13%