The motivation for citizens’ involvement in life sciences research is predicted by age and gender

Open Science is an umbrella term encompassing multiple concepts as open access to publications, open data, open education and citizen science that aim to make science more open and transparent. Citizen science, an important facet of Open Science, actively involves nonscientists in the research process, and can potentially be beneficial for multiple actors, such as scientists, citizens, policymakers and society in general. However, the reasons that motivate different segments of the public to participate in research are still understudied. Therefore, based on data gathered from a survey conducted in Czechia, Germany, Italy, Spain, Sweden, and the UK (N = 5,870), this study explores five types of incentives that can motivate individuals to become involved in life sciences research. The results demonstrate that men and younger individuals are more persuaded by extrinsic motives (external benefits or rewards), as compared with women and older people, who are driven by intrinsic motives (that originates from within an individual). This paper shows that specific strata of the population are differentially motivated to engage in research, thereby providing relevant knowledge for effectively designing public involvement activities that target various groups of the public in research projects

Rapid method for the determination of moisture content in biodiesel using FTIR spectroscopy

A new, rapid, and direct method was developed for the determination of moisture content in biodiesel produced from various types of oils using Fourier transform infrared (FTIR) spectroscopy with an attenuated total reflectance (ATR) element. Samples of biodiesels used in this study were produced using sludge palm oil (SPO). The calibration set was prepared by spiking double-distilled water into dried biodiesel samples in ratios (w/w) between 0 and 10% moisture. Absorbance values from the wavelength regions 3,700–3,075 and 1,700–1,500 cm-1, and the partial least square (PLS) regression method were used to derive a FTIR spectroscopic calibration model for moisture content in biodiesel samples. The coefficient of determinations (R2) for the models was computed by comparing the results obtained from FTIR spectroscopy against the values of the moisture concentrations (%) determined using the American Oil Chemists’ Society (AOCS) oven method Ca 2d-25. Same comparison was done using International Union of Pure and Applied Chemistry (IUPAC) distillation method 2.602. R2 was 0.9793 and 0.9700 using AOCS and IUPAC methods, respectively. The standard error (SE) of calibration was 1.84. The calibration model was cross validated within the same set of samples, and the standard deviation (SD) of the difference for repeatability (SDDr) and accuracy (SDDa) of the FTIR method was determined. With its speed and ease of data manipulation, FTIR spectroscopy is a useful alternative method to other methods for rapid and routine determination of moisture content in biodiesel for quality control