Catching the Right Wave: Evaluating Wave Energy Resources and Potential Compatibility with Existing Marine and Coastal Uses

Many hope that ocean waves will be a source for clean, safe, reliable and affordable energy, yet wave energy conversion facilities may affect marine ecosystems through a variety of mechanisms, including competition with other human uses. We developed a decision-support tool to assist siting wave energy facilities, which allows the user to balance the need for profitability of the facilities with the need to minimize conflicts with other ocean uses. Our wave energy model quantifies harvestable wave energy and evaluates the net present value (NPV) of a wave energy facility based on a capital investment analysis. The model has a flexible framework and can be easily applied to wave energy projects at local, regional, and global scales. We applied the model and compatibility analysis on the west coast of Vancouver Island, British Columbia, Canada to provide information for ongoing marine spatial planning, including potential wave energy projects. In particular, we conducted a spatial overlap analysis with a variety of existing uses and ecological characteristics, and a quantitative compatibility analysis with commercial fisheries data. We found that wave power and harvestable wave energy gradually increase offshore as wave conditions intensify. However, areas with high economic potential for wave energy facilities were closer to cable landing points because of the cost of bringing energy ashore and thus in nearshore areas that support a number of different human uses. We show that the maximum combined economic benefit from wave energy and other uses is likely to be realized if wave energy facilities are sited in areas that maximize wave energy NPV and minimize conflict with existing ocean uses. Our tools will help decision-makers explore alternative locations for wave energy facilities by mapping expected wave energy NPV and helping to identify sites that provide maximal returns yet avoid spatial competition with existing ocean uses

Sr-Nd isotope geochemistry of the early Precambrian sub-alkaline mafic igneous rocks from the southern Bastar craton, Central India

Sr–Nd isotope data are reported for the early Precambrian sub-alkaline mafic igneous rocks of the southern Bastar craton, central India. These mafic rocks are mostly dykes but there are a few volcanic exposures. Field relationships together with the petrological and geochemical characteristics of these mafic dykes divide them into two groups; Meso-Neoarchaean sub-alkaline mafic dykes (BD1) and Paleoproterozoic (1.88 Ga) sub-alkaline mafic dykes (BD2). The mafic volcanics are Neoarchaean in age and have very close geochemical relationships with the BD1 type. The two groups have distinctly different concentrations of high-field strength (HFSE) and rare earth elements (REE). The BD2 dykes have higher concentrations of HFSE and REE than the BD1 dykes and associated volcanics and both groups have very distinctive petrogenetic histories. These rocks display a limited range of initial 143Nd/144Nd but a wide range of apparent initial 87Sr/86Sr. Initial 143Nd/144Nd values in the BD1 dykes and associated volcanics vary between 0.509149 and 0.509466 and in the BD2 dykes the variation is between 0.510303 and 0.510511. All samples have positive εNd values the BD1 dykes and associated volcanics have εNd values between +0.3 and +6.5 and the BD2 dykes between +1.9 to +6.0. Trace element and Nd isotope data do not suggest severe crustal contamination during the emplacement of the studied rocks. The positive εNd values suggest their derivation from a depleted mantle source. Overlapping positive εNd values suggest that a similar mantle source tapped by variable melt fractions at different times was responsible for the genesis of BD1 (and associated volcanics) and BD2 mafic dykes. The Rb–Sr system is susceptible to alteration and resetting during post-magmatic alteration and metamorphism. Many of the samples studied have anomalous apparent initial 87Sr/86Sr suggesting post-magmatic changes of the Rb–Sr system which severely restricts the use of Rb–Sr for petrogenetic interpretation

Tumours in 177 pet hamsters

Background: Even though tumours are considered to occur frequently in pet hamsters, there is only a small number of scientific reports in current literature. Methods: Pathological reports from 177 hamsters were evaluated. Results: Of these, 78 were male and 75 were female. Median age of affected hamsters was 12 months (range 2–34). Integumental tumours were the most common neoplasms (62%, 109/177). As far as species was known, the number of Syrian hamsters (52%, 30/58) affected by tumours seemed to be lower than the number of affected dwarf hamsters (85%, 47/55). Tumours of the hematopoietic system were the second most frequently neoplasms (17%, 30/177). Relative number of neoplasms of the endocrine system, tumours of the digestive system (1.7%, 3/177) and other tumours (4%, 7/177 each) was low. The majority of integumental tumours were epithelial (66%; 91/126). Conclusion: This study aimed to analyze data from veterinary surgeries and pathological institutes about the occurrence of spontaneous tumours in Syrian hamsters and dwarf hamsters to give information about the frequency of tumours, prognosis and survival time. This is the first study about tumours in pet hamsters in Germany so far

Use of selective serotonin reuptake inhibitors and risk of re-operation due to post-surgical bleeding in breast cancer patients: a Danish population-based cohort study

<p>Abstract</p> <p>Background</p> <p>Selective serotonin reuptake inhibitors (SSRI) decrease platelet-function, which suggests that SSRI use may increase the risk of post-surgical bleeding. Few studies have investigated this potential association.</p> <p>Methods</p> <p>We conducted a population-based study of the risk of re-operation due to post-surgical bleeding within two weeks of primary surgery among Danish women with primary breast cancer. Patients were categorised according to their use of SSRI: never users, current users (SSRI prescription within 30 days of initial breast cancer surgery), and former users (SSRI prescription more than 30 days before initial breast cancer surgery). We calculated the risk of re-operation due to post-surgical bleeding within 14 days of initial surgery, and the relative risk (RR) of re-operation comparing SSRI users with never users of SSRI adjusting for potential confounders.</p> <p>Results</p> <p>389 of 14,464 women (2.7%) were re-operated. 1592 (11%) had a history of SSRI use. Risk of re-operation was 2.6% among never users, 7.0% among current SSRI users, and 2.7% among former users. Current users thus had an increased risk of re-operation due to post-operative bleeding (adjusted relative risk = 2.3; 95% confidence interval (CI) = 1.4, 3.9) compared with never users. There was no increased risk of re-operation associated with former use of SSRI (RR = 0.93, 95% CI = 0.66, 1.3).</p> <p>Conclusions</p> <p>Current use of SSRI is associated with an increased risk of re-operation due to bleeding after surgery for breast cancer.</p

Changes in physical health among participants in a multidisciplinary health programme for long-term unemployed persons

Background. The relationship between poor health and unemployment is well established. Health promotion among unemployed persons may improve their health. The aims of this study were to investigate characteristics of non-participants and drop-outs in a multidisciplinary health promotion programme for long-term unemployed persons with health complaints, to evaluate changes in physical health among participants, and to investigate determinants of improvement in physical health. Methods. A longitudinal, non-controlled design was used. The programme consisted of two weekly exercise sessions and one weekly cognitive session during 12 weeks. The main outcome measures were body mass index, blood pressure, cardiorespiratory fitness, abd

Automated Discovery of Food Webs from Ecological Data Using Logic-Based Machine Learning

Networks of trophic links (food webs) are used to describe and understand mechanistic routes for translocation of energy (biomass) between species. However, a relatively low proportion of ecosystems have been studied using food web approaches due to difficulties in making observations on large numbers of species. In this paper we demonstrate that Machine Learning of food webs, using a logic-based approach called A/ILP, can generate plausible and testable food webs from field sample data. Our example data come from a national-scale Vortis suction sampling of invertebrates from arable fields in Great Britain. We found that 45 invertebrate species or taxa, representing approximately 25% of the sample and about 74% of the invertebrate individuals included in the learning, were hypothesized to be linked. As might be expected, detritivore Collembola were consistently the most important prey. Generalist and omnivorous carabid beetles were hypothesized to be the dominant predators of the system. We were, however, surprised by the importance of carabid larvae suggested by the machine learning as predators of a wide variety of prey. High probability links were hypothesized for widespread, potentially destabilizing, intra-guild predation; predictions that could be experimentally tested. Many of the high probability links in the model have already been observed or suggested for this system, supporting our contention that A/ILP learning can produce plausible food webs from sample data, independent of our preconceptions about “who eats whom.” Well-characterised links in the literature correspond with links ascribed with high probability through A/ILP. We believe that this very general Machine Learning approach has great power and could be used to extend and test our current theories of agricultural ecosystem dynamics and function. In particular, we believe it could be used to support the development of a wider theory of ecosystem responses to environmental change

Effect of perceived default risk and accounting information quality on the decision to grant credit to SMEs

ABSTRACT: The present study analyses the influence that perceived default risk and accounting information quality have on the process of credit granting to SMEs. Empirical evidence was obtained from a survey of 471 bank loan officers in Spain, in which they were asked to answer questions relating to audited and not-audited firms. Through a Structural Equations Modeling (SEM) approach, the results confirm that the likelihood that the loan officers are more willing to provide access to credit to SMEs, and to do so in more favourable conditions, is negatively influenced by perceived default risk and positively influenced by the general perception about accounting information quality. Besides, we find that information quality is an antecedent of perceived risk, so that the latter becomes the central element of the research model. Additionally, the perceptions of the decision-makers regarding all the analysed variables are better for the audited SMEs than for the unaudited ones