M _split estimation is a novel method developed to process observation sets that include two (or more) observation aggregations. The main objective of the method is to estimate the location parameters of each aggregation without any preliminary assumption concerning the division of the observation set into respective subsets. Up to now, two different variants of M _split estimation have been derived. The first and basic variant is the squared M _split estimation, which can be derived from the assumption about the normal distribution of observations. The second variant is the absolute M _split estimation, which generally refers to the least absolute deviation method. The main objective of the paper is to compare both variants of M _split estimation by showing similarities and differences between the methods. The main dissimilarity stems from the different influence functions, making the absolute M _split estimation less sensitive to gross errors of moderate magnitude. The empirical analyses presented confirm that conclusion and show that the accuracy of the methods is similar, in general. The absolute M _split estimation is more accurate than the squared M _split estimation for less accurate observations. In contrast, the squared M _split estimation is more accurate when the number of observations in aggregations differs much. Concerning all advantages and disadvantages of M _split estimation variants, we recommend using the absolute M _split estimation in most geodetic applications.

Environmental contamination is an urgent topic to be solved for sustainable society. Among various pollutants, microorganisms are believed to be the most dangerous and difficult to be completely inactivated. In this research, a new hybrid photoreactor assisted with rotating magnetic field (RMF) has been proposed for the efficient removal of two types of bacteria, i.e., gram-negative Escherichia coli and gram-positive Staphylococcus epidermidis. Three selfsynthesized photocatalysts were used, based on commercial titanium(IV) oxide - P25, homogenized and then modified with copper by photodeposition, as follows: 0.5Cu@HomoP25, 2.0Cu@HomoP25 and 5.0Cu@HomoP25 containg 0.5, 2.0 and 5.0 wt% of deposited copper, respectively. The response surface methodology (RSM) was employed to design the experiments and to deteremine the optimal conditions. The effects of various parameters such as copper concentration [% w/w], time [h] and frequency of RMF [Hz] were studied. Results: Analysis of variance (ANOVA), revealed a good agreement between experimental data and proposed quadratic polynomial model ((R2=0.86 for E. coli and R2=0.69 for S. epidermidis). Experimental results showed that with increasing copper concentration, time and decreasing of frequency of RMF removal efficiency was increased. Accordingly, the water disinfection efficiency of 100% in terms of the independent variables was optimized, including cooper concentration c =5 % and 2.5% w/w, time t = 3 h and 1.3 h and frequency of rotating magnetic field f = 50 Hz and 26.6 for E.coli and S. epidermidis, respectively. This study showed that response surface methodology is a useful tool for optimizing the operating parameters for photocatalytic disinfection process.