Social identity,safety climate and self-reported accidents among construction workers

The construction industry has one of the highest frequencies of work-related accidents. We examined whether construction workers predominantly identify themselves in terms of their workgroup or in terms of the construction site. In addition, we examined the associations between social identity and safety climate, and how these constructs are associated with work-related accidents. The analyses were based on questionnaire responses from 478 construction workers from two large construction sites, and the methods involved structural equation modeling. Results showed that the workers identified themselves primarily with their workgroup, and to a lesser degree with the construction site. Social identity and safety climate were related both at the workgroup and construction site levels, meaning that social identity may be an antecedent for safety climate. The association between social identity and safety climate was stronger at the workgroup level than at the construction site level. Finally, safety climate at both levels was inversely associated with self-reported accidents, with the strongest association at the workgroup level. A focus on improving safety climate, particularly by integrating initiatives at both the workgroup and management level, may have the potential to improve safety performance and thus decrease the risk of accidents and injuries on construction sites.     

In situ studies of the decomposition of ammonium uranyl carbonate in an electron microscope

An electron microscope has been used to study the reduction of ammonium uranyl carbonate (AUC) to UO₂. The reactions could be followed both in the diffraction and the lattice image mode. The first intermediate obtained was amorphous UO₃. Depending on the experimental conditions, either crystalline UO₂ was formed directly from this phase, or several other intermediates were indicated.Properties like crystallinity and crystallite size of final UO₂ were found to be a function of experimental conditions. Comparisons with properties of UO₂ from the industrial process have been made.     

Catalytic Encounters at the Molecular Level: Gabor A. Somorjai Award Symposium for Creative Research in Catalysis in Honor of Professor Manos Mavrikakis

Topics in Catalysis -     

Assessment of extreme and metocean conditions in the Maldives for OTEC applications

The Maldives is a group of tropical atolls, considered globally to be one of the most desirable holiday destinations. There is an urgent requirement to decrease their dependency on fossil fuels that are currently the main source of energy, and a number of renewable energy alternatives are being evaluated. Among these, due to the favorable oceanographic and bathymetric conditions, ocean thermal energy conversion (OTEC) systems represent a viable opportunity for clean and reliable power. However, the stresses the OTEC platform will need to endure during adverse environmental conditions are not well defined. The magnitude of these stresses will then have a direct influence on the design of the OTEC device. In order to overcome this uncertainty, this paper uses hindcast data sets from global weather and ocean models to assess the metocean conditions of the Maldives, with particular reference to extreme conditions. After selecting a suitable location for the deployment of the devices, return values calculated using the peaks‐over‐threshold (POT) methodology are estimated for wind, waves, and currents. The 100‐year return value for the significant wave height is found to be 4.5 m, with a joint occurrence of energy periods between 7.5 and 8.5 seconds, whereas the 100‐year return wind has a velocity of 17.8 m/s and the 100‐year return current of 1.9 m/s. The directionality of these extreme events is also considered, showing the southern and western sub‐quadrants as the prevailing sources, which provides essential information for positioning of the platform. Additional evaluations of tropical revolving storms (TRS) and variations in temperature and salinity patterns are also provided over a 1500‐m water column; temperature varies by approximately 24°C, and salinity by around 2 ppt, showing the suitability of OTEC platforms in the Maldives. This work is therefore of interest to offshore renewable energy stakeholders interested in developing a project in the Maldives or those conducting an analogous analysis in other locations.     

Status of Mysis diluviana in Lake Ontario in 2013: Lower abundance but higher fecundity than in the 1990s

Mysis diluviana is a major component of prey fish diets in the Great Lakes, so annual production of M. diluviana is important for understanding and modeling energy flow through Great Lakes food webs. However, only three lake-wide measurements of M. diluviana annual production in Lake Ontario are currently available (1971, 1990, 1995). During 2013, lake-wide coverage of Lake Ontario was achieved during four periods from April to November. Annual mean density and biomass of M. diluviana in 2013 were 99?#/m² (SE: 8) and 318?mg?dw/m² (SE: 28) – approximately half of values observed in 1990s. M. diluviana comprised 13–30% of offshore zooplankton biomass in each period. Reproduction peaked in fall, with mean brood size of 32 embryos (range: 11–49), at least 10% larger than in 1990s. Generation time was two years from embryo to initial reproduction. Growth rates were 0.052?mm/d for the age-0 cohort and 0.027?mm/d for the age-1 cohort. Age-0 growth rate was significantly higher than in 1980s–90s (0.035?mm/d). Annual production in 2013 was 0.85?g?dw/m²/yr (SE: 0.03) which was 30–40% of values observed in 1990 and 1995 (2.23 and 2.53?g/m²/yr). Annual production to biomass ratio (P/B) in 2013 was 2.65?/yr which was 80–85% of values observed in 1990 and 1995 (3.24 and 3.11?/yr), but this difference was not statistically significant. Our results suggest that changes in annual production over time can be estimated using changes in biomass over time and a mean P/B ratio.     

Seed Vigour In Relation To Heat Sensitivity And Heat Resistance In Barley Evaluated By Multivariate Data Analysis

The vigour loss model based on normal distribution after artificially ageing by heat treatment of barley seeds developed by Ellis and Roberts and further developed at Carlsberg by Aastrup et al. introducing vigour potential (VP), does not adequately describe seed vigour for all barley samples. In a preliminary investigation we have identified heat‐resistant barley samples. In this investigation we found untreated barley samples from the field where heat treatment as high as 68°C for 4 h at 12% water content only decreases germination from 99.0% to 93.8% compared with 94.8% to 0.0% for some of the heat‐sensitive barleys following the above mentioned model. The correlation between germination velocity measured by the germination index (GI) of untreated samples and VP is not consistent when comparing different barley material. It is concluded that the classic vigour loss model for heat treatment may be used as a worst case prediction for germination, but it does not address the variation found in practice, including the possible advantage of exploiting the naturally occurring heat resistance.     

Hypoxia in the Baltic Sea and basin-scale changes in phosphorus biogeochemistry

Deep-water oxygen concentrations in the Baltic Sea are influenced by eutrophication, but also by saltwater inflows from the North Sea. In the last two decades, only two major inflows have been recorded and the lack of major inflows is believed to have resulted in a long-term stagnation of the deepest bottom water. Analyzing data from 1970 to 2000 at the basin scale, we show that the estimated volume of water with oxygen, <2 mL L(-1), was actually at a minimum at the end of the longest so-called stagnation period on record. We also show that annual changes in dissolved inorganic phosphate water pools were positively correlated to the area of bottom covered by hypoxic water, but not to changes in total phosphorus load, thus addressing the legacy of eutrophication on a basinwide scale. The variations in phosphorus pools that have occurred during the past decades do not reflect any human action to reduce inputs. The long residence time and internally controlled variation of the large P pool in the Baltic Sea has important implications for management of both N and P inputs into this eutrophicated enclosed basin.     

Classification of Amyloidosis by Model-Assisted Mass Spectrometry-Based Proteomics

Amyloidosis is a rare disease caused by the misfolding and extracellular aggregation of proteins as insoluble fibrillary deposits localized either in specific organs or systemically throughout the body. The organ targeted and the disease progression and outcome is highly dependent on the specific fibril-forming protein, and its accurate identification is essential to the choice of treatment. Mass spectrometry-based proteomics has become the method of choice for the identification of the amyloidogenic protein. Regrettably, this identification relies on manual and subjective interpretation of mass spectrometry data by an expert, which is undesirable and may bias diagnosis. To circumvent this, we developed a statistical model-assisted method for the unbiased identification of amyloid-containing biopsies and amyloidosis subtyping. Based on data from mass spectrometric analysis of amyloid-containing biopsies and corresponding controls. A Boruta method applied on a random forest classifier was applied to proteomics data obtained from the mass spectrometric analysis of 75 laser dissected Congo Red positive amyloid-containing biopsies and 78 Congo Red negative biopsies to identify novel “amyloid signature” proteins that included clusterin, fibulin-1, vitronectin complement component C9 and also three collagen proteins, as well as the well-known amyloid signature proteins apolipoprotein E, apolipoprotein A4, and serum amyloid P. A SVM learning algorithm were trained on the mass spectrometry data from the analysis of the 75 amyloid-containing biopsies and 78 amyloid-negative control biopsies. The trained algorithm performed superior in the discrimination of amyloid-containing biopsies from controls, with an accuracy of 1.0 when applied to a blinded mass spectrometry validation data set of 103 prospectively collected amyloid-containing biopsies. Moreover, our method successfully classified amyloidosis patients according to the subtype in 102 out of 103 blinded cases. Collectively, our model-assisted approach identified novel amyloid-associated proteins and demonstrated the use of mass spectrometry-based data in clinical diagnostics of disease by the unbiased and reliable model-assisted classification of amyloid deposits and of the specific amyloid subtype.