Ergonomic factors and production target evaluation in eucalyptus timber harvesting operations in mountainous terrains

There are several forest operations involved in Eucalyptus timber harvesting. This study was carried out during brush-cutting; tree felling, bucking, delimbing, piling and manual extraction operations, with the following objectives: a) analyzing, ergonomically, two systems of brush-cutting: one manual and the other semi-mechanized, using two different machines; b) ergonomically evaluating three different brands of pruner machines used in delimbing felled trees. c) determining the feasible target of productivity as a function of ergonomic factors relevant to establish the time of resting pauses for workers in manual and semi-mechanized timber harvesting systems in mountainous terrain. Brush-cutting, either manual or semimechanized, is an activity carried out prior to timber harvesting. It is usually a hard work, with low productivity when compared with mechanized systems. Pruner machines have been used by forest companies, due to the great possibilities to improve productivity, quality and the health of workers. Ergonomics is a discipline that promotes the adequacy of work to the physical and mental characteristics of human beings, seeking to design production systems and products considering relevant aspects, including social, organizational and environmental factors. Companies should consider the ergonomic factor in the determination of daily worker production targets.     

Nurses' working tasks and MSDs back symptoms: results from a national survey

Healthcare workers, namely registered nurses (RN), are frequently exposed to work-related musculoskeletal disorders (WRMSDs) risk factors. Identifying the symptoms of these disorders is one of the first epidemiological steps to managing them. This study aims to identify WRMSDs prevalence symptoms in Portuguese RN. During 8 months (2010-2011) the National Public Health School and the Portuguese Registered Nurses Board made a call to all RN to answer an online WRMSDs questionnaire. Respondents (n=2140) are mostly females (77.4%) and work mainly in hospitals (n=1396) and in primary healthcare centers (n=421). Results show high symptoms prevalence (last 12 months) in the lower back (60.6%), the upper back (44.5%), and the neck (48.6%). Nurses' activity, especially patient hygiene in bed, is a strong contributor (p>0.05) to pain in the upper back (OR=1.39 [1.09-1.80]) and lower back (OR=1.4 [1.08-1.84]). Patient holdup without mechanical support has the highest relationship (p>0.05) between work tasks and symptoms in the last 12 months in the upper back (OR=1.50 [1.19-1.90]). Prevalence rates of WRMSDs symptoms in Portuguese nurses are no different from other studies with Swedish, Italian and Greek nurses. Maybe changes in healthcare systems didn't change the way care is delivered and we must rethink how to prevent nurses WRMSDs.     

A method to investigate drivers' acceptance of Blind Spot Detection System®

Lately, with the goal of improving road safety, car makers developed and commercialised some Advanced Driver Assistance Systems (ADAS) which, through the detection of blind spot areas on the vehicle's sides, could help the drivers during the overtaking and the change lane task. Despite the possible benefits to reduce lateral crashes, the overall impact on road safety of such systems have not been deeply studied yet; notably, despite some researches have been carried out, there is a lack of studies regarding the long-term usage and drivers' acceptance of those systems. In order to fill the research gap, a methodology, based on the combination of focus groups interviews, questionnaires and a small-scale field operational test (FOT), has been designed in this study; such a methodology aims at evaluating drivers' acceptance of Blind Spot Information System? and at proposing some ideas to improve the usability and user-friendliness of this (or similar) device in their future development.     

Climate change and population migration in Brazil’s Northeast: scenarios for 2025–2050

This research contributes to an understanding of the relationship between climate change, economic impacts and migration. We model the long-term relationship (up to 45 years of projection) between demographic dynamics—particularly migration—driven by changes in the performance of the economy due to climate changes in the Northeast region of Brazil. The region is of particular relevance to the study of climate change impacts given its large human population (28% of Brazil’s population) and high levels of impoverishment, having an extensive semi-dry area which will be severely impacted by growing temperatures. Ultimately, the integrated model generates state- and municipal-level migration scenarios based on climate change impacts on the primary economic sectors and their articulations with other sectors. Results suggest that the predicted climate changes will impact severely the agriculture sector in the region, acting as a potential migration push factor to other regions in the country. Finally, we discuss how the increased vulnerability of some groups, particularly migrants, can be factored into Brazilian public policy and planning.     

100 key research questions for the post‐2015 development agenda

The Sustainable Development Goals (SDGs) herald a new phase for international development. This article presents the results of a consultative exercise to collaboratively identify 100 research questions of critical importance for the post‐2015 international development agenda. The final shortlist is grouped into nine thematic areas and was selected by 21 representatives of international and non‐governmental organisations and consultancies, and 14 academics with diverse disciplinary expertise from an initial pool of 704 questions submitted by 110 organisations based in 34 countries. The shortlist includes questions addressing long‐standing problems, new challenges and broader issues related to development policies, practices and institutions. Collectively, these questions are relevant for future development‐related research priorities of governmental and non‐governmental organisations worldwide and could act as focal points for transdisciplinary research collaborations.     

Likelihood-free approximate Gibbs sampling

Likelihood-free methods such as approximate Bayesian computation (ABC) have extended the reach of statistical inference to problems with computationally intractable likelihoods. Such approaches perform well for small-to-moderate dimensional problems, but suffer a curse of dimensionality in the number of model parameters. We introduce a likelihood-free approximate Gibbs sampler that naturally circumvents the dimensionality issue by focusing on lower-dimensional conditional distributions. These distributions are estimated by flexible regression models either before the sampler is run, or adaptively during sampler implementation. As a result, and in comparison to Metropolis-Hastings-based approaches, we are able to fit substantially more challenging statistical models than would otherwise be possible. We demonstrate the sampler’s performance via two simulated examples, and a real analysis of Airbnb rental prices using a intractable high-dimensional multivariate nonlinear state-space model with a 36-dimensional latent state observed on 365 time points, which presents a real challenge to standard ABC techniques.     

The International Crisis of Confidence in Corporations

Journal of Management and Governance -     

Smoothed empirical likelihood confidence intervals for the relative distribution with left‐truncated and right‐censored data

The study of differences among groups is an interesting statistical topic in many applied fields. It is very common in this context to have data that are subject to mechanisms of loss of information, such as censoring and truncation. In the setting of a two‐sample problem with data subject to left truncation and right censoring, we develop an empirical likelihood method to do inference for the relative distribution. We obtain a nonparametric generalization of Wilks' theorem and construct nonparametric pointwise confidence intervals for the relative distribution. Finally, we analyse the coverage probability and length of these confidence intervals through a simulation study and illustrate their use with a real data set on gastric cancer. The Canadian Journal of Statistics 38: 453–473; 2010 © 2010 Statistical Society of Canada