Anti-PLN (N-terminal) polyclonal antibody

This paper analyses the impact of German macroeconomic news announcements and ECB meeting days on the conditional volatility of the Czech, Polish, and Hungarian Foreign Exchange markets as proxied by CZK/EUR, PLN/EUR, and HUF/EUR exchange rate returns over six years (2010-2015). A currency intervention period (11/2013-2015) in the Czech Republic is examined separately. EGARCH-type models with normal and Student's t-distributions are employed. The comprehensive analysis shows the following results. (i) The IFO index, Factory Orders increase and the PMI index from the Service Sector, the labour market data decrease conditional volatility of PLN/EUR. (ii) The IFO index and Industrial Production increase conditional volatility of HUF/EUR on the day of the announcement. (iii) Data from the labour market has a calming effect on CZK/EUR after the central bank launched currency interventions. (iv) IFO index increases and the PMI index from the Manufacturing Sector decreases conditional volatility of CZK/EUR before currency interventions were introduced (2010-11/2013).

Despite the recognized benefits of cycling as a sustainable mode of transportation, cyclists are considered vulnerable road users and there are concerns about their safety. Therefore, it is essential to investigate the factors affecting cyclist safety. The goal of this study is to evaluate and compare different approaches of modeling macro-level cyclist safety as well as investigating factors that contribute to cyclist crashes using a comprehensive list of covariates. Data from 134 traffic analysis zones (TAZs) in the City of Vancouver were used to develop macro-level crash models (CM) incorporating variables related to actual traffic exposure, socio-economics, land use, built environment, and bike network. Four types of CMs were developed under a full Bayesian framework: Poisson lognormal model (PLN), random intercepts PLN model (RIPLN), random parameters PLN model (RPPLN), and spatial PLN model (SPIN). The SPLN model had the best goodness of fit, and the results highlighted the significant effects of spatial correlation. The models showed that the cyclist crashes were positively associated with bike and vehicle exposure measures, households, commercial area density, and signal density. On the other hand, negative associations were found between cyclist crashes and some bike network indicators such as average edge length, average zonal slope, and off-street bike links.