Relationship of safety climate perceptions and job satisfaction among employees in the construction industry: the moderating role of age

This study examines the degree to which construction sector employees perceive that safety is important in their organizations/sites and how job satisfaction affects these perceptions when age is introduced as a moderator variable. Two-way analysis of variance demonstrated that job satisfaction has a strong effect on perceived management commitment to work safety and that this relationship was moderated by respondents’ age. Job satisfaction was associated with perceived accident rate and safety inspection frequency, but the proposed role of age in this linkage was not confirmed. Consequently, the findings indicated that by increasing the level of job satisfaction, perceptions of these safety climate aspects proved to be more positive. The conclusion is that these relationships could further lead to a lower percentage of accidents and injuries in the workplace and better health among employees. A significant relationship between job satisfaction, age and perceived co-workers’ commitment to work safety was not found.     

Using single- and multi-target regression trees and ensembles to model a compound index of vegetation condition

An important consideration in conservation and biodiversity planning is an appreciation of the condition or integrity of ecosystems. In this study, we have applied various machine learning methods to the problem of predicting the condition or quality of the remnant indigenous vegetation across an extensive area of south-eastern Australia—the state of Victoria. The field data were obtained using the ‘habitat hectares’ approach. This rapid assessment technique produces multiple scores that describe the condition of various attributes of the vegetation at a given site. Multiple sites were assessed and subsequently circumscribed with GIS and remote-sensed data.     

Zoo Animal Welfare

The continuing existence of zoos and their good purposes such as conservation, science, education, and recreation, can be ethically justified only if zoos guarantee the welfare of their animals. The usual criteria for measuring animal welfare in zoos are physical health, long life, and reproduction. This paper looks at these criteria and finds them insufficient. Additional criteria are submitted to expand the range of welfare considerations: natural and abnormal behavior; freedom and choice; and dignity. All these criteria should play a role in analyzing zoo animal welfare and interests but dignity has the overriding part because it impacts on both animal and human interests.     

Types of Ectomycorrhiza as Pollution Stress Indicators: Case Studies in Slovenia

Mycorrhiza is the main spatial and temporal linkage between different constituents in a forest ecosystem. The functional compatibility and stress tolerance of ectomycorrhizal types is species specific, and therefore the information on the ectomycorrhizal community structure can add to the understanding of processes in forest ecosystems and can also be applied as tools for bioindication of pollution stress in forest soils. We have studied the effects of pollution (N and S) on trees and forest soils by: (1) quantification of ECM types diversity as in situ indicators in forest stands, (2) determination and quantification of pollution-sensitive or -insensitive ECM types as passive monitors, (3) root growth and development of ECM on nonmycorrhizal spruce seedlings, planted at the studied sites (active monitors), and (4) ECM infection (a bioassay based on mycorrhizal inoculum potential) of seedlings in an experimental set-up as ex situ testers. ECM species richness for Norway spruce trees (Picea abies) showed higher values in unpolluted sites than in polluted ones, while the differences were not significant for European beech trees (Fagus sylvatica). As pollution-sensitive or -insensitive ECM species in spruce forests, we suggest Hydnum rufescens (sensitive) and Paxillus involutus (unsensitive). Mycorrhizal potential in Norway spruce seedlings as a bioassay for soil N and S pollution was effective, and is suggested as an additional, standardized and widely comparable system in bioindication of soil pollution.     

Atmospheric aerosol growth rates at different background station types

Environmental Science and Pollution Research - Highly time-resolved particle number size distributions (PNSDs) were evaluated during 5 years (2013–2017) at four background stations in the...     

Using multi-objective classification to model communities of soil microarthropods

In agricultural soil, a suite of anthropogenic events shape the ecosystem processes and populations. However, the impact from anthropogenic sources on the soil environment is almost exclusively assessed for chemicals, although other factors like crop and tillage practices have an important impact as well. Thus, the farming system as a whole should be evaluated and ranked according to its environmental benefits and impacts. Our starting point is a data set describing agricultural events and soil biological parameters. Using machine learning methods for inducing regression and model trees, we produce empirical models able to predict the soil quality from agricultural measures in terms of quantities describing the soil microarthropod community. We are also interested in discovering additional higher level knowledge. In particular, we have identified the most important factors influencing the population densities of springtails and mites and their biodiversity. We also identify to which agricultural actions different microarthropods react distinctly. To obtain this higher level knowledge, we employ multi-objective regression trees.     

Determination of selected neonicotinoid insecticides by liquid chromatography with thermal lens spectrometric detection

We studied the analysis of trace amounts of neonicotinoid insecticides by liquid chromatography coupled with a thermal lens spectrometric detector (TLS). This multi-residue analysis method is based on the reversed phase separation on C₁₈ column, isocratic elution and collinear dual beam TLS detection. The insecticides thiamethoxam, imidacloprid, acetamiprid and thiacloprid were detected with retention times of 4.4, 5.7, 6.5 and 8.5 min and limits of quantifications of 50, 89, 10, and 25 μg/L, respectively. The retention times agreed well with those obtained by the same chromatographic method but using a diode-array detector (DAD). The limits of quantifications for imidacloprid were identical in both techniques. However, the limits of quantifications for thiamethoxam, acetamiprid and thiacloprid were up to 8.5 times lower using the TLS detector compared to the diode-array detector. The applicability of the developed procedure was tested on spiked river water and potato samples.     

Automatic construction of concept hierarchies: The case of foliage-dwelling spiders

In this paper, we present the hierarchical variable dependencies that were obtained from raw data with the use of two machine learning techniques on an ecological data set. The data set contains features of field margins and the corresponding number of spider species inhabiting them. This data set was used before by domain experts to construct a fuzzy qualitative model with hierarchical variable dependencies, which we use for comparison with our results. One of the machine learning methods constructs a hierarchical structure similar to the one in the experts’ model, while revealing some additional interesting relations of environmental features with respect to the number of spider species. The other method constructs a different hierarchy from the one proposed by the experts, which, according to our classification performance experiments, might be even more appropriate.