Recent research data on the removal of pharmaceuticals from sewage treatment plants (STP)

Pharmaceutical compounds have been detected in sewage treatment plant (STP) effluents, surface waters and, less frequently, in groundwater and drinking water, all over the world. Different sources are responsible for their appearance in the aquatic environment, however, it is widely accepted that the main sources of this type of pollutant are STP effluents. The adverse effects of pharmaceuticals in the environment include aquatic toxicity, development of resistance in pathogenic bacteria, genotoxicity and endocrine disruption. Thus, the discharge of these compounds to the environment in STP effluents should be minimized.

Scientific data dissemination a data catalogue to assist research organizations

The constant scientific production in the universities and in the research centers makes these organizations produce and acquire a great amount of data in a short period of time. Due to the big quantity of data, the research organizations become potentially vulnerable to the impacts on information booms that may cause a chaos as far as information management is concerned. In this context, the development of data catalogues comes up as one possible solution to the problems such as (I) the organization and (II) the data management. In the scientific scope, the data catalogues are implemented with the standard for digital and geospatial metadata and are broadly utilized in the process of producing a catalogue of scientific information. The aim of this work is to present the characteristics of access and storage of metadata in databank systems in order to improve the description and dissemination of scientific data. Relevant aspects will be considered and they should be analyzed during the stage of planning, once they can determine the success of implementation. The use of data catalogues by research organizations may be a way to promote and facilitate the dissemination of scientific data, avoid the repetition of efforts while being executed, as well as incentivate the use of collected, processed an also stored.

Analysis of variables that are not directly observable: influence on decision-making during the research process

The sample dimension, types of variables, format used for measurement, and construction of instruments to collect valid and reliable data must be considered during the research process. In the social and health sciences, and more specifically in nursing, data-collection instruments are usually composed of latent variables or variables that cannot be directly observed. Such facts emphasize the importance of deciding how to measure study variables (using an ordinal scale or a Likert or Likert-type scale). Psychometric scales are examples of instruments that are affected by the type of variables that comprise them, which could cause problems with measurement and statistical analysis (parametric tests versus non-parametric tests). Hence, investigators using these variables must rely on suppositions based on simulation studies or recommendations based on scientific evidence in order to make the best decisions.