Mining compatibility with other projects in Spain: Solutions and benefits

Mining activities are compatible with other activities in space and time if they are developed together and adapted to each other. If permits are required for two projects that are not considered to be compatible, the authorities will be forced to decide which one has prevalence. In the event of conflict or dispute, it is always preferable to attempt to seek compatibility between projects rather than waste time, effort and money on contesting the prevalence decision, as costly and lengthy lawsuits will only delay the development of both projects, with the resulting loss of business opportunities. In this article, technical solutions designed to achieve mining compatibility with other projects are described in terms of benefits and synergies for the projects and benefits for the government that avoid complex decisions and proceedings and optimize revenues.     

Malaria infection and host behavior: a comparative study of Neotropical primates

Parasites are ubiquitous in populations of free-ranging animals and impact host fitness, but virtually nothing is known about the factors that influence patterns of disease risk across species and the effectiveness of behavioral defenses to reduce this risk. We investigated the correlates of malaria infection (prevalence) in Neotropical primates using data from the literature, focusing on host traits involving group size, body mass, and sleeping behavior. Malaria is spread to these monkeys through anopheline mosquitoes that search for hosts at night using olfactory cues. In comparative tests that used two different phylogenetic trees, we confirmed that malaria prevalence increases with group size in Neotropical primates, as suggested by a previous non-phylogenetic analysis. These results are consistent with the hypothesis that larger groups experience increased risk of attack by mosquitoes, and counter to the hypothesis that primates benefit from the encounter-dilution effect of avoiding actively-seeking insects by living in larger groups. In contrast to non-phylogenetic tests, body mass was significant in fewer phylogeny-based analyses, and primarily when group size was included as a covariate. We also found statistical support for the hypothesis that sleeping in closed microhabitats, such as tree holes or tangles of vegetation, reduces the risk of malaria infection by containing the host cues used by mosquitoes to locate hosts. Due to the small number of evolutionary transitions in sleeping behavior in this group of primates, however, this result is considered preliminary until repeated with a larger sample size. In summary, risk of infection with malaria and other vector-borne diseases are likely to act as a cost of living in groups, rather than a benefit, and sleeping site selection may provide benefits by reducing rates of attack by malaria vectors.Electronic Supplementary Material Supplementary material is available in the online version of this article at and is accessible for authorized users.     

Prevalence-adjusted optimisation of fuzzy models for species distribution

Most performance criteria which have been applied to train ecological models focus on the accuracy of the model predictions. However, these criteria depend on the prevalence of the training set and often do not take into account ecological issues such as the distinction between omission and commission errors. Moreover, a previous study indicated that model training based on different performance criteria results in different optimised models. Therefore, model developers should train models based on different performance criteria and select the most appropriate model depending on the modelling objective. This paper presents a new approach to train fuzzy models based on an adjustable performance criterion, called the adjusted average deviation (aAD). This criterion was applied to develop a species distribution model for spawning grayling in the Aare River near Thun, Switzerland. To analyse the strengths and weaknesses of this approach, it was compared to model training based on other performance criteria. The results suggest that model training based on accuracy-based performance criteria may produce unrealistic models at extreme prevalences of the training set, whereas the aAD allows for the identification of more accurate and more reliable models. Moreover, the adjustable parameter in this criterion enables modellers to situate the optimised models in the search space and thus provides an indication of the ecological model relevance. Consequently, it may support modellers and river managers in the decision making process by improving model reliability and insight into the modelling process. Due to the universality and the flexibility of the approach, it could be applied to any other ecosystem or species, and may therefore be valuable to ecological modelling and ecosystem management in general.     

Ecological relevance of performance criteria for species distribution models

Species distribution models have often been developed based on ecological data. To develop reliable data-driven models, however, a sound model training and evaluation procedures are needed. A crucial step in these procedures is the assessment of the model performance, with as key component the applied performance criterion. Therefore, we reviewed seven performance criteria commonly applied in presence-absence modelling (the correctly classified instances, Kappa, sensitivity, specificity, the normalised mutual information statistic, the true skill statistic and the odds ratio) and analysed their application in both the model training and evaluation process. Although estimates of predictive performance have been used widely to assess final model quality, a systematic overview was missing because most analyses of performance criteria have been empirical and only focused on specific aspects of the performance criteria. This paper provides such an overview showing that different performance criteria evaluate a model differently and that this difference may be explained by the dependency of these criteria on the prevalence of the validation set. We showed theoretically that these prevalence effects only occur if the data are inseparable by an n-dimensional hyperplane, n being the number of input variables. Given this inseparability, different performance criteria focus on different aspects of model performance during model training, such as sensitivity, specificity or predictive accuracy. These findings have important consequences for ecological modelling because ecological data are mostly inseparable due to data noise and the complexity of the studied system. Consequently, it should be very clear which aspect of the model performance is evaluated, and models should be evaluated consistently, that is, independent of, or taking into account, species prevalence. The practical implications of these findings are clear. They provide further insight into the evaluation of ecological presence/absence models and attempt to assist modellers in their choice of suitable performance criteria.     

Occupational injury and psychological distress among U.S. workers: The National Health Interview Survey, 2004–2016

Introduction: Injuries at work may negatively influence mental health due to lost or reduced working hours and financial burden of treatment. Our objective was to investigate, in U.S. workers (a) the prevalence of serious psychological distress (SPD) by injury status (occupational, non-occupational, and no injury) and injury characteristics, and (b) the association between injury status and SPD. Methods: Self-reported injuries within the previous three months were collected annually for 225,331 U.S. workers in the National Health Interview Survey (2004–2016). Psychological distress during the past 30 days was assessed using the Kessler 6 (K6) questions with Likert-type scale (0–4, total score range: 0–24). SPD was defined as K6 ≥ 13. Prevalence ratios (PR) from fitted logistic regression models were used to assess relationships between injury and SPD after controlling for covariates. Results: The prevalence of SPD was 4.74%, 3.58%, and 1.56% in workers reporting occupational injury (OI), non-occupational injury (NOI), and no injury, respectively. Workers with head and neck injury had the highest prevalence of SPD (Prevalence: OI = 7.71%, NOI = 6.17%), followed by workers with scrape/bruise/burn/bite (6.32% for those with OI). Workers reporting OI were two times more likely to have SPD compared to those without injury (PR = 2.19, 95%CI: 1.62–2.96). However, there was no significant difference in SPD between workers with OI and workers with NOI (PR = 0.98, 95%CI: 0.65–1.48). Conclusion: The prevalence of SPD varied by injury status with the highest being among workers reporting OI. We found that the workers reporting OI were significantly more likely to have SPD than those without injury, but not more than those with NOI. Practical Applications: Mental health management programs by employers are necessary for workers who are injured in the workplace.     

Predicting tree distributions in an East African biodiversity hotspot: model selection, data bias and envelope uncertainty

The Eastern Arc Mountains (EAMs) of Tanzania and Kenya support some of the most ancient tropical rainforest on Earth. The forests are a global priority for biodiversity conservation and provide vital resources to the Tanzanian population. Here, we make a first attempt to predict the spatial distribution of 40 EAM tree species, using generalised additive models, plot data and environmental predictor maps at sub 1 km resolution. The results of three modelling experiments are presented, investigating predictions obtained by (1) two different procedures for the stepwise selection of predictors, (2) down-weighting absence data, and (3) incorporating an autocovariate term to describe fine-scale spatial aggregation. In response to recent concerns regarding the extrapolation of model predictions beyond the restricted environmental range of training data, we also demonstrate a novel graphical tool for quantifying envelope uncertainty in restricted range niche-based models (envelope uncertainty maps). We find that even for species with very few documented occurrences useful estimates of distribution can be achieved. Initiating selection with a null model is found to be useful for explanatory purposes, while beginning with a full predictor set can over-fit the data. We show that a simple multimodel average of these two best-model predictions yields a superior compromise between generality and precision (parsimony). Down-weighting absences shifts the balance of errors in favour of higher sensitivity, reducing the number of serious mistakes (i.e., falsely predicted absences); however, response functions are more complex, exacerbating uncertainty in larger models. Spatial autocovariates help describe fine-scale patterns of occurrence and significantly improve explained deviance, though if important environmental constraints are omitted then model stability and explanatory power can be compromised. We conclude that the best modelling practice is contingent both on the intentions of the analyst (explanation or prediction) and on the quality of distribution data; generalised additive models have potential to provide valuable information for conservation in the EAMs, but methods must be carefully considered, particularly if occurrence data are scarce. Full results and details of all species models are supplied in an online Appendix.     

Trihalomethane concentrations in tap water as determinant of bottled water use in the city of Barcelona

Bottled water consumption is increasing worldwide, despite its huge economic and environmental cost. We aim to describe personal and tap water quality determinants of bottled water use in the city of Barcelona. This cross-sectional study used data from the Health Survey of Barcelona in 2006(N = 5417 adults). The use of bottled water to drink and to cook was evaluated in relation to age, gender, educational level, district and levels of trihalomethanes(THMs), free chlorine, conductivity, chloride, sodium, p H, nitrate and aluminium in municipal tap water using Robust Poisson Regression. The prevalence of bottled water use to drink and cook was 53.9% and 6.7%, respectively. Chemical parameters in water had a large variability(interquartile range of THMs concentrations: 83.2–200.8 μg/L)and were correlated between them, except aluminium. Drinking bottled water increased with educational level, while cooking with bottled water was higher among men than among women and decreased with age. After adjusting by these personal determinants, a dose–response relationship was found between concentrations of all chemicals except aluminium in tap water and bottled water use. The highest association was found for THMs,with a Prevalence Ratio of 2.00(95%CI = 1.86, 2.15) for drinking bottled water and 2.80(95%CI = 1.72, 4.58) for cooking with bottled water, among those with 150 μg/L vs. 100 μg/L THMs in tap water. Conclusion: More than half of Barcelona residents regularly drank bottled water, and the main determinant was the chemical composition of tap water,particularly THM level.     

Needle stick and sharps injuries among health care workers in Gondar city, Ethiopia

Background

All employees in health care settings handling needles or other sharps are at risk for needle stick and sharps injuries (NSSIs). Health care workers in under developed countries are at greater risk of infection from blood borne pathogens because of the lack of safety devices and the high prevalence of these pathogens.

Objectives

The aim of this study was to assess the prevalence of NSSIs and associated factors among health care workers in government health institutions in Gondar city, Ethiopia.

Methods

Institution based cross sectional study was conducted from May-December, 2010. The study included 344 health care workers who were selected from the source population using simple random sampling technique. Data were collected through interviews using structured and pre-tested questionnaire and the collected data were entered and analyzed using SPSS version 16.0.

Results

The prevalence of NSSIs among health care workers in the preceding 12 months was 106 (30.8%), of which 58 (54.7%) was reported by females. Lack of training on occupational health and safety, working more than 48 h/week, dissatisfaction with work environment and work culture, greater than 10 years of work experience and having low and moderate perception of risk were found to be significantly associated with NSSIs.

Conclusion

The study found high prevalence of NSSIs among health care workers. Effective training, ongoing awareness on the risk of hazards, preventive measures such as engineering control, and post-exposure prophylaxis following NSSIs are essential to reduce the risk of such injuries.     

铁路职工糖尿病流行病学调查分析

为进一步精准开展糖尿病防控提供依据,采用分层整群抽样的方法对某地区铁路职工体检情况进行调查分析。结果表明:糖尿病患病率为14.96%,知晓率为24.46%,糖尿病前期患病率为30.03%;糖尿病前期和新诊断糖尿病患者中,单纯糖负荷后2 h血糖升高者分别占91.22%和74.29%;确诊的糖尿病人HbA1c控制率为30.86%。说明该地区铁路职工糖尿病发病率较高,知晓率低,控制率低;应重视糖负荷后2 h血糖检测;建立"疾病预防控制所+职工单位+职工"防控机制,以有效防控糖尿病。     

Aggressive driving: a survey of attitudes, opinions and behaviors

INTRODUCTION: Aggressive driving encompasses a continuum of behaviors that range from extreme acts, such as shootings, to less severe manifestations, such as arguments and gestures. It is clear from the available data that aggressive driving is not uncommon and very risky. However, little is known about the opinions and practices of drivers. The purpose of this study was to help bridge these gaps. METHODS: The data were gathered by means of a public opinion poll among a representative sample of 1,201 Canadian drivers. Univariate frequency distributions and 95% confidence intervals were calculated and logistic regression and generalized linear latent models were used to summarize the data. RESULTS: It was found that the issue of aggressive driving is a significant one as a considerable percentage of drivers admits to it. The results coming from the logistic regression and the generalized linear latent model suggest that male and younger drivers are more likely to behave aggressively in traffic and that behaving more aggressively is associated with a history of traffic tickets. DISCUSSION: When gauging people's attitudes, opinions, and behaviors, it becomes clear that aggressive driving is a considerable problem. There also seems to be a need for a better understanding of which specific behaviors respondents associate with the generic term "aggressive driving." IMPACT ON INDUSTRY: Results from this study further emphasize the need of increasing the aggressive driving knowledge base.