What happens when you trust your supervisor? Mediators of individual performance in trust relationships

To understand how trust in supervisor translates into individual job performance, we hypothesize that trust in supervisor facilitates positive psychological conditions of meaningfulness, safety, and availability, which in turn predict individual job performance. We assert that each of the three mediating paths in our model represents a distinct mechanism by which trust in supervisor contributes to individual job performance. We test our hypotheses with 206 supervisor–subordinate dyads and find that trust in supervisor contributes to job performance through psychological availability and psychological safety but not psychological meaningfulness. By examining three different psychological mechanisms within the same frame, we provide a test that compares and contrasts the uniqueness of the three pathways. Our findings suggest practical ways for managers to build trust with subordinates and guidance for the design of productive work conditions. Copyright © 2012 John Wiley & Sons, Ltd.     

Simulating the meteorology and PM10 concentrations in Arizona dust storms using the Weather Research and Forecasting model with Chemistry (Wrf-Chem)

Nine dust storms in south-central Arizona were simulated with the Weather Research and Forecasting with Chemistry model (WRF-Chem) at 2 km resolution. The windblown dust emission algorithm was the Air Force Weather Agency model. In comparison with ground-based PM₁₀ observations, the model unevenly reproduces the dust-storm events. The model adequately estimates the location and timing of the events, but it is unable to precisely replicate the magnitude and timing of the elevated hourly concentrations of particles 10 µm and smaller ([PM₁₀]).Furthermore, the model underestimated [PM₁₀] in highly agricultural Pinal County because it underestimated surface wind speeds and because the model’s erodible fractions of the land surface data were too coarse to effectively resolve the active and abandoned agricultural lands. In contrast, the model overestimated [PM₁₀] in western Arizona along the Colorado River because it generated daytime sea breezes (from the nearby Gulf of California) for which the surface-layer speeds were too strong. In Phoenix, AZ, the model’s performance depended on the event, with both under- and overestimations partly due to incorrect representation of urban features. Sensitivity tests indicate that [PM₁₀] highly relies on meteorological forcing. Increasing the fraction of erodible surfaces in the Pinal County agricultural areas improved the simulation of [PM₁₀] in that region. Both 24-hr and 1-hr measured [PM₁₀] were, for the most part, and especially in Pinal County, extremely elevated, with the former exceeding the health standard by as much as 10-fold and the latter exceeding health-based guidelines by as much as 70-fold. Monsoonal thunderstorms not only produce elevated [PM₁₀], but also cause urban flash floods and disrupt water resource deliveries. Given the severity and frequency of these dust storms, and conceding that the modeling system applied in this work did not produce the desired agreement between simulations and observations, additional research in both the windblown dust emissions model and the weather research/physicochemical model is called for.

Implications: While many dust storms can be considered to be natural, in semi-arid climates such storms often have an anthropogenic component in their sources of dust. Applying the natural, exceptional events policy to these storms with strong signatures of anthropogenic sources would appear not only to be misguided but also to stifle genuine regulatory efforts at remediation. Those dust storms that have resulted, in part, from passage over abandoned farm land should no longer be considered “natural”; policymakers and lawmakers need to compel the owners of such land to reduce its potential for windblown dust.     

Investigation of low-level <Superscript>242</Superscript>Pu contamination on nutrition disturbance and oxidative stress in <Emphasis Type="Italic">Solanum tuberosum</Emphasis> L.

Plutonium associated with higher molecular weight molecules is presumed to be poorly mobile and hardly plant available. In our present study, we investigate the uptake and effects of Pu treatments on Solanum tuberosum plants in amended Hoagland medium at concentrations of [²⁴²Pu] = 100 and 500 nm, respectively. We found a direct proof of oxidative stress in the plants caused by these rather low concentrations. For the confirmation of oxidative stress, we explored the production of nitric oxide (NO) and hydrogen peroxide (H₂O₂) by epifluorescence microscopy. Oxidative stress markers like lipid peroxidation and superoxide radicals (O₂ ^??) are monitored through histochemical analysis. The biochemical parameters i.e. chlorophyll and carotenoids are measured as an indicator of cellular damage in the tested plants including the enzymatic parameters such as catalase and glutathione reductase. From our work, we conclude that Pu in low concentration has no significant effects on the uptake of many trace and macroelements. In contrast, the content of O₂ ^?? , malondialdehyde (MDA), and H₂O₂ increases with increasing Pu concentration in the solution, while the opposite effects was found for NO, catalase, and glutathione reductase. These findings prove that even low concentration of Pu regulates ROS production and generate oxidative stress in S. tuberosum L.     

Waste battery disposal and recycling behavior: a study on the Australian perspective

Environmental Science and Pollution Research - Consumer behavior is a critical consideration for the development of sustainable waste management systems, including waste batteries, which pose a...     

Info-gap theory and robust design of surveillance for invasive species: The case study of Barrow Island

Surveillance for invasive non-indigenous species (NIS) is an integral part of a quarantine system. Estimating the efficiency of a surveillance strategy relies on many uncertain parameters estimated by experts, such as the efficiency of its components in face of the specific NIS, the ability of the NIS to inhabit different environments, and so on. Due to the importance of detecting an invasive NIS within a critical period of time, it is crucial that these uncertainties be accounted for in the design of the surveillance system. We formulate a detection model that takes into account, in addition to structured sampling for incursive NIS, incidental detection by untrained workers. We use info-gap theory for satisficing (not minimizing) the probability of detection, while at the same time maximizing the robustness to uncertainty. We demonstrate the trade-off between robustness to uncertainty, and an increase in the required probability of detection. An empirical example based on the detection of Pheidole megacephala on Barrow Island demonstrates the use of info-gap analysis to select a surveillance strategy.     

A systematic review of systematic reviews and meta-analyses of animal experiments with guidelines for reporting

To maximize the findings of animal experiments to inform likely health effects in humans, a thorough review and evaluation of the animal evidence is required. Systematic reviews and, where appropriate, meta-analyses have great potential in facilitating such an evaluation, making efficient use of the animal evidence while minimizing possible sources of bias. The extent to which systematic review and meta-analysis methods have been applied to evaluate animal experiments to inform human health is unknown. Using systematic review methods, we examine the extent and quality of systematic reviews and meta-analyses of in vivo animal experiments carried out to inform human health. We identified 103 articles meeting the inclusion criteria: 57 reported a systematic review, 29 a systematic review and a meta-analysis, and 17 reported a meta-analysis only. The use of these methods to evaluate animal evidence has increased over time. Although the reporting of systematic reviews is of adequate quality, the reporting of meta-analyses is poor. The inadequate reporting of meta-analyses observed here leads to questions on whether the most appropriate methods were used to maximize the use of the animal evidence to inform policy or decision-making. We recommend that guidelines proposed here be used to help improve the reporting of systematic reviews and meta-analyses of animal experiments. Further consideration of the use and methodological quality and reporting of such studies is needed.     

Nitrogen cycling through swine production systems: ammonia, dinitrogen, and nitrous oxide emissions

Ammonia (NH(3)) emissions from animal systems have become a primary concern for all of livestock production. The purpose of this research was to establish the relationship of nitrogen (N) emissions to specific components of swine production systems and to determine accurate NH(3) emission factors appropriate for the regional climate, geography, and production systems. Micrometeorological instrumentation and gas sensors were placed over two lagoons in North Carolina during 1997-1999 to obtain information for determining ammonia emissions over extended periods and without interfering with the surrounding climate. Ammonia emissions varied diurnally and seasonally and were related to lagoon ammonium concentration, acidity, temperature, and wind turbulence. Conversion of significant quantities of ammonium NH(4)(+) to dinitrogen gas (N(2)) were measured in all lagoons with the emission rate largely dependent on NH(4)(+) concentration. Lagoon NH(4)(+) conversion to N(2) accounted for the largest loss component of the N entering the farm (43% as N(2)); however, small amounts of N(2)O were emitted from the lagoon (0.1%) and from field applications (0.05%) when effluent was applied nearby. In disagreement with previous and current estimates of NH(3) emissions from confined animal feeding operation (CAFO) systems, and invalidating current assumptions that most or all emissions are in the form of NH(3), we found much smaller NH(3) emissions from animal housing (7%), lagoons (8%), and fields (2%) using independent measurements of N transformation and transport. Nitrogen input and output in the production system were evaluated, and 95% of input N was accounted for as output N from the system.     

Toluene removal biofilter modeling: Optimization and case study

Based on the model proposed by De Visscher and Van Cleemput for methane oxidation in landfill cover soils, a simulation model for biofiltration of toluene-contaminated air has been developed for biofilters with substrate inhibition. A convenient way to optimize biofilter performance was developed assuming Haldane kinetics. It was calculated that for a typical oilsands operation emitting 200 ton of toluene annually, 90% of the toluene can be removed by a 740 m³ biofilter, if the waste gas sent to the biofilter has a toluene concentration of 2.25 g m⁻³. The optimal initial concentration increases with increasing target efficiency.     

A Rapid Response Survey to Characterize the Impacts of the 2017 High Water Event on Lake Ontario

In the spring and summer of 2017, communities along the Lake Ontario shoreline suffered from the worst flood event on record. In late May, daily water levels reached their highest point in over 100 years, and flooding continued throughout much of the summer as lake levels slowly declined, with inundation and erosion significantly impacting shoreline homes and businesses. In this work, we present results from a rapid response online survey of property owners along the New York Lake Ontario shoreline to quantify the perceived flood impacts of the 2017 extended high water event. The survey focused on the degree and spatial distribution of inundation and erosion; the duration and drivers of inundation; the associated damages to different property features, with an emphasis on shoreline protection; and the degree of disruption to business and other activities and services. Photographic documentation of inundation extent and property damage also was provided by survey respondents. We demonstrate the potential utility of this dataset by characterizing key features of inundation and erosion impacts across the shoreline, and by using classification and regression trees to explore the predictability of inundation and erosion based on property characteristics. This work is part of a larger effort to develop models of inundation and erosion that can support flood impact assessments across the shoreline and help communities better prepare for future extended high water events.