Investigation of Ion Release from Ni-Cr Alloy in Various Acidity Conditions

Cytotoxicity is in direct correlation to the level of ion release, with non-precious alloys having higher ion release than that of precious alloys. The most often used non-precious dental alloy is Ni-Cr alloy. The aim of the investigation was to determine the type and quantity of ions released from Ni-Cr alloy (Wiron 99(r), Bego, Germany), in acid solutions with different pH values, and to determine the influence of the type of acid solution, its pH value, and duration of interaction on ion release. The overall sample consisted of 180 pieces of Ni-Cr alloy, 60 samples submerged in each of three different solutions (buffered phosphate solutions pH 3.5 and pH6, and lactic acid solution pH 3.5). Quantity of ion release was measured on solution samples taken at 10 different time intervals by means of the ICP-AES method. Average release of Ni ions in lactic acid solution was 432.42 μg/L, while the highest average Ni+ ions release of 541.67μg/L was measured in buffered phosphate solution pH 6.0. MANOVA demonstrated significant influence of the type of solution on Ni ion release (p<0.01), while the time of exposure was not a significant factor (p=0.23). Zn ions demonstrated the lowest average ion release (88.95 μg/L, phosphate solution pH 3.5). Statistically significant influence of the type of solution and pH value on ion release was determined, except for chromium ions (p<0.05). Dentobacterial plaque acidity is sufficient to start corrosion of Ni-Cr dental alloys

Modelling of Activated Sludge Wastewater Treatment Process in Municipal Plant in Velika Gorica

Obrada otpadne vode s aktivnim muljem izrazito je složen fizikalni, kemijski i biološki proces. Nestalnost sastava i protoka otpadne vode te vremenski promjenjive reakcije mješovite kulture mikroorganizama uvjetuju njegovu nelinearnost i nestacionarnost. Optimalno vođenje procesa je kompleksan zadatak, ali pravilno izrađen matematički model može poslužiti kao osnova za rješavanje. U ovom radu izrađena su dva modela za opis procesa obrade otpadne vode na uređaju grada Velika Gorica, sa zadaćom predviđanja vrijednosti kemijske potrošnje kisika (KPK) na izlazu iz uređaja u zavisnosti od protoka i značajki ulazne neobrađene vode. Korišteni podaci dobiveni su svakodnevnim mjerenjem fizikalnih veličina koji ukazuju na kvalitetu ulazne i izlazne vode, na uvjete pri kojima uređaj radi te na kvalitetu aktivnog mulja. Za modeliranje procesa primijenjena je baza podataka od ukupno 223 skupa podataka sa po 26 parametara za kontinuirano razdoblje tijekom 2004. godine, koji su poslužili kao varijable za izradu modela. Iz ukupnog skupa veličina statističkom analizom odabrane su najuvjerljivije varijable za izradu modela. Izrađeni su viševarijantni linearni model (MLR) sa 16 varijabli te model lokalne linearne regresije (PLR) sa 17 varijabli. Srednja pogreška viševarijantnog linearnog modela iznosi γKPK=20 mg O2 L-1, a za model lokalne linearne regresije srednja pogreška iznosi γKPK = 16 mg O2 L-1.Activated sludge wastewater treatment is a highly complex physical, chemical and biological process, and variations in wastewater flow rate and its composition, combined with time-varying reactions in a mixed culture of microorganisms, make this process non-linear and unsteady. The efficiency of the process is established by measuring the quantities that indicate quality of the treated wastewater, but they can only be determined at the end of the process, which is when the water has already been processed and is at the outlet of the plant and released into the environment. If the water quality is not acceptable, it is already too late for its improvement, which indicates the need for a feed forward process control based on a mathematical model. Since there is no possibility of retracing the process steps back, all the mistakes in the control of the process could induce an ecological disaster of a smaller or bigger extent. Therefore, models that describe this process well may be used as a basis for monitoring and optimal control of the process development. This work analyzes the process of biological treatment of wastewater in the Velika Gorica plant. Two empirical models for the description of the process were established, multiple linear regression model (MLR) with 16 predictor variables and piecewise linear regression model (PLR) with 17 predictor variables. These models were developed with the aim to predict COD value of the effluent wastewater at the outlet, after treatment. The development of the models is based on the statistical analysis of experimental data, which are used to determine the relations among individual variables. In this work are applied linear models based on multiple linear regression (MLR) and partial least squares (PLR) methods. The used data were obtained by everyday measurements of the quantities that indicate the quality of the input and output water, working conditions of the plant and the quality of the activated sludge. The database contains 223 groups, each with 26 parameters, for the entire year of 2004. The variables were analyzed for determination of the most important factors. The analyses were done with significance level of p < 0.05, which is a commonly acceptable error level in the industrial process. The complex nature of the process and its sensitivity, depending on different factors, have been confirmed by the results of the analyses in this work. In all of the developed models the quantities that describe climatic influence, biological components and the quality of the "raw material" i.e. incoming wastewater, have been included as predictors. It is clear that the quality of the treated wastewaters, and thus the efficiency of the process are changing depending on a number of factors that influence the process differently. Even though more intricate models, like artificial intelligence, are used to describe such complex processes, it can be concluded that even such simple models like MLR and PLR can present the complexity and dynamics of this process with acceptable reliability. In this work for the developed models, the obtained average error of multiple linear regression model is γKPK = 16 mg L-1-O2and the average error of piecewise linear regression model is γKPK= 16 mg L-1- O2

Connecting the dots in pharmacy education: The FIP International Pharmaceutical Federation Global Competency Framework for Educators and Trainers in Pharmacy (FIP-GCFE)

The FIP (International Pharmaceutical Federation) Global Competency Framework for Educators and Trainers in Pharmacy (FIP-GCFE) is an ongoing project of the Academic Pharmacy Section of FIP in cooperation and collaboration with Sections, Special Interest Groups and Working Groups across the Federation. It was developed by a group of experts in pharmaceutical education to enable and promote the continuing professional development of pharmacists and pharmaceutical scientists who plan to advance their competence as educators and trainers in pharmacy and the pharmaceutical sciences, whether in a formal or informal context, and at all levels of education and professional development. The FIP-GCFE will be an essential resource for multiple stakeholders including individual educators, faculties of pharmacy, and accreditation agencies. This article presents the introductory text of the GCFE first version, connecting previously launched concepts and tools and explaining the integration with all other FIP workforce support frameworks, to provide a holistic approach to global workforce development

Erratum: Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017

Interpretation: By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning

An ontology-based approach to information retrieval

We define a general framework for ontology-based information retrieval (IR). In our approach, document and query expansion rely on a base taxonomy that is extracted from a lexical database or a Linked Data set (e.g. WordNet, Wiktionary etc.). Each term from a document or query is modelled as a vector of base concepts from the base taxonomy. We define a set of mapping functions which map multiple ontological layers (dimensions) onto the base taxonomy. This way, each concept from the included ontologies can also be represented as a vector of base concepts from the base taxonomy. We propose a general weighting schema which is used for the vector space model. Our framework can therefore take into account various lexical and semantic relations between terms and concepts (e.g. synonymy, hierarchy, meronymy, antonymy, geo-proximity, etc.). This allows us to avoid certain vocabulary problems (e.g. synonymy, polysemy) as well as to reduce the vector size in the IR tasks

Nucleation Kinetics of Cis-Entacapone

The solubility curve and the metastable zone width for the system cis-entacapone –2-propanol have been determined in defined process conditions. These results along with values of induction period for the constant feed concentration at different levels of supersaturation were used for evaluating interfacial energy according to the classical nucleation theory. The results obtained were used for calculation of the critical nucleus size, nucleation rate, and prediction of crystal growth mechanism. Solubility data and metastable zone width determines the way to achieve the essential supersaturation level, as well as provides information necessary for control of the crystallization process. Knowledge of the fundamental parameters of nucleation kinetics led to the better understanding of the crystallization process in order to obtain a product with desired solid state characteristics