The presence of outliers will affect the parameter estimation results and model accuracy. It also occurs in the spatial regression model, especially the Spatial Autoregressive (SAR) model. Spatial Autoregressive (SAR) is a regression model where spatial effects are attached to the dependent variable. Removing outliers in the analysis will eliminate the necessary information. Therefore, the solution offered is to modify the SAR model, especially by giving special treatment to observations that have potentially become outliers. This study develops to modeling the life expectancy data in Central Java Province using a modified spatial autoregressive model with the Mean-Shift Outlier Model (MSOM) approach. Outliers are detected using the MSOM method. Then the result is used as the basis for modifying the SAR model. This modification, in principle, will reduce or increase the average of the observed data indicated as outliers. The results show that the modified model can improve the model accuracy compared to the original SAR model. It can be proved by the increased coefficient of determination and decreasing the Akaike Information Criterion (AIC) value of the modified model. In addition, the modified model can improve the skewness and kurtosis values of the residuals getting closer to the Normal distribution.

The most studied and cultivated microalgae have a temperature optimum between 20 and 35°C. This temperature range hampers sustainable microalgae growth in countries with colder periods. To overcome this problem, psychrotolerant microalgae, such as the snow alga Chloromonas typhlos, can be cultivated during these colder periods. However, most of the research work has been carried out in the laboratory. The step between laboratory-scale and large-scale cultivation is difficult, making pilot-scale tests crucial to gather more information. Here, we presented a successful pilot-scale growth test of C. typhlos. Seven batch mode growth periods were compared during two longer growth tests in a photobioreactor of 350 L. We demonstrated the potential of this alga to be cultivated at colder ambient temperatures. The tests were performed during winter and springtime to compare ambient temperature and sunlight influences. The growth and CO2 usage were continuously monitored to calculate the productivity and CO2 fixation efficiency. A maximum dry weight of 1.082 g L−1 was achieved while a maximum growth rate and maximum daily volumetric and areal productivities of 0.105 d−1, 0.110 g L−1 d−1, and 2.746 g m−2 d−1, respectively, were measured. Future tests to optimize the cultivation of C. typhlos and production of astaxanthin, for example, will be crucial to explore the potential of biomass production of C. typhlos on a commercial scale.

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