Direct electroanalytical determination of fluvastatin in a pharmaceutical dosage form: batch and flow analysis

The reduction of luvastatin (FLV) at a hanging mercury-drop electrode (HMDE) was studied by square-wave adsorptive-stripping voltammetry (SWAdSV). FLV can be accumulated and reduced at the electrode, with a maximum peak current intensity at a potential of approximately 1.26V vs. AgCl=Ag, in an aqueous electrolyte solution of pH 5.25. The method shows linearity between peak current intensity and FLV concentration between 1.0 10 8 and 2.7 10 6 mol L 1. Limits of detection (LOD) and quantification (LOQ) were found to be 9.9 10 9 mol L 1 and 3.3 10 8 mol L 1, respectively. Furthermore, FLV oxidation at a glassy carbon electrode surface was used for its hydrodynamic monitoring by amperometric detection in a flow-injection system. The amperometric signal was linear with FLV concentration over the range 1.0 10 6 to 1.0 10 5 mol L 1, with an LOD of 2.4 10 7 mol L 1 and an LOQ of 8.0 10 7 mol L 1. A sample rate of 50 injections per hour was achieved. Both methods were validated and showed to be precise and accurate, being satisfactorily applied to the determination of FLV in a commercial pharmaceutical.

Risk Acceptance in the Furniture Sector: Analysis of Acceptance Level and Relevant Influence Factors

Risk acceptance has been broadly discussed in relation to hazardous risk activities and/or technologies. A better understanding of risk acceptance in occupational settings is also important; however, studies on this topic are scarce. It seems important to understand the level of risk that stakeholders consider sufficiently low, how stakeholders form their opinion about risk, and why they adopt a certain attitude toward risk. Accordingly, the aim of this study is to examine risk acceptance in regard to occupational accidents in furniture industries. The safety climate analysis was conducted through the application of the Safety Climate in Wood Industries questionnaire. Judgments about risk acceptance, trust, risk perception, benefit perception, emotions, and moral values were measured. Several models were tested to explain occupational risk acceptance. The results showed that the level of risk acceptance decreased as the risk level increased. High-risk and death scenarios were assessed as unacceptable. Risk perception, emotions, and trust had an important influence on risk acceptance. Safety climate was correlated with risk acceptance and other variables that influence risk acceptance. These results are important for the risk assessment process in terms of defining risk acceptance criteria and strategies to reduce risks.