The springs of the Taoura region flow from a syncline shaped structure. All resources in the region were mobilized as a result of increased demand. However, the development of anthropic activities and population growth in the area pose risk for groundwater. Analytical results obtained from a series of samplings in November 2017–April 2018, express the quality of water suitable for the irrigation of agricultural land. The highest values are recorded in April 2018 at 20.5 to 21.6°C and pH of 8.0 to 8.2. The study recorded high electrical conductivity from 1390 to 1495 μS·cm–1 and TDS from 1270 to 1500 mg·dm–3 in November 2017, which shows important mineralization that characterizes spring water. Physical parameters were measured in situ using a HORIBA multi-parameter probe. Chemical analyses were carried out using NFT 90-005 titration, and nitrogen parameters by DIN 38405-D92 spectrophotometry. Maximum levels of nitrates and phosphates were recorded at 228 and 18.4 mg·dm–3 respectively. The principal component analysis (PCA) showed a good correlation of the November 2017 period with mineralization parameters. Moreover, there is a strong correlation between the wet period and pollution factors. The two methods of analysis has allowed to distinguish three groups of geochemical water types: a bicarbonate calcium group typical for waters having transited in carbonate horizons. A second chloride calcium group shows basic exchange between water and clay levels, and the third chloride bicarbonate calcium group reveals an enrichment in calcium and chloride, which reflects water circulation with an exchange of the carbonated and evaporitic sedimentary rock matrix.

Multidimensional exploratory techniques, such as the Principal Component Analysis (PCA), have been used to analyze long-term changes in the flow regime and quality of water of the lowland dam reservoir Turawa (south-west Poland) in the catchment of the Mała Panew river (a tributary of the Odra). The paper proves that during the period of 1998–2016 the Turawa reservoir was equalizing the river’s water flow. Moreover, various physicochemical water quality indicators were analyzed at three measurement points (at the tributary’s mouth into the reservoir, in the reservoir itself and at the outflow from the reservoir). The water quality assessment was performed by analyzing physicochemical indicators such as water temperature, TSS, pH, dissolved oxygen, BOD₅, NH₄⁺, NO₃^-, NO₂^-, N, PO₄^3-, P, electrolytic conductivity, DS, SO₄^2- and Cl^- . Furthermore, the correlations between all these water quality indicators were analyzed statistically at each measurement point, at the statistical signifi cance level of p ≤ 0.05. PCA was used to determine the structures between these water quality variables at each measurement point. As a result, a theoretical model was obtained that describes the regularities in the relationships between the indicators. PCA has shown that biogenic indicators have the strongest influence on the water quality in the Mała Panew. Lastly, the differences between the averages of the water quality indicators of the inflowing and of the outflowing water were considered and their significance was analyzed. PCA unveiled structure and complexity of interconnections between river flow and water quality. The paper shows that such statistical methods can be valuable tools for developing suitable water management strategies for the catchment and the reservoir itself.

The petrographic composition of coal has a significant impact on its technological and sorption properties. That composition is most frequently determined by means of microscope quantitative analyses. Thus, aside from the purely scientific aspect, such measurements have an important practical application in the industrial usage of coal, as well as in issues related to the safety in underground mining facilities. The article discusses research aiming at analyzing the usefulness of selected parameters of a digital image description in the process of automatic identification of macerals of the inertinite group using neural networks. The description of the investigated images was based on statistical parameters determined on the basis of a histogram and co-occurrence matrix (Haralick parameters). Each of the studied macerals was described by means of a 20-element feature vector. An analysis of its principal components (PCA) was conducted, along with establishing the relationship between the number of the applied components and the effectiveness of the MLP network. Based on that, the optimum number of input variables for the investigated classification task was chosen, which resulted in reduction of the size of the network’s hidden layer. As part of the discussed research, the authors also analyzed the process of classification of macerals of the inertinite group using an algorithm based on a group of MLP networks, where each network possessed one output. As a result, average recognition effectiveness of 80.9% was obtained for a single MLP network, and of 93.6% for a group of neural networks. The obtained results indicate that it is possible to use the proposed methodology as a tool supporting microscopic analyses of coal.

This research analysed the availability of phytoplankton and the growth rate of Vannamei shrimp in relation to water quality changes. The research was carried out in February–March 2021 for a half cycle of shrimp cultivation in two ponds of the Brackish Water Fish Culture Probolinggo Laboratory in Probolinggo, East Java, Indonesia. The research used a descriptive method and included a survey. Sampling was made every two weeks for two months. Nine parameters were measured and ten shrimps were taken for a specific growth rate ( SGR) measurement once per sampling. Data were analysed using the principal component analysis (PCA) and canonical correspondence analysis (CCA). Secondary data of water quality were added for the PCA. The results show that the phytoplankton found in the first pond consisted of Chlorophyta, Chrysophyta, and Cyanophyta, whereas the phytoplankton in the other pond included Chlorophyta, Chrysophyta, Cyanophyta, and Dinophyta. The abundance of phytoplankton ranged from 12–80∙10 ³ cell∙cm ^–3, which indicated eutrophic waters. The PCA demonstrated that pH, nitrate, and total organic matter (TOM) significantly influenced phytoplankton abundance in the pond. In addition, water quality parameters, such as temperature, transparency, salinity, nitrite and phosphate levels, were tolerable in both ponds for the growth of shrimps. However, the level of pH was lower than the aquaculture quality standard, whereas those of nitrate, ammonia, and TOM were higher. The growth rate of Vannamei shrimp increased by 0.76–7.34%∙day ^–1.

The article presents an assessment of the effects of anthropogenic activities on the quality of water in four streams flowing through a camp based on a combined assessment of environmental impacts and the water quality index. The quantitative and qualitative assessment of environmental impact was made after identifying the anthropogenic activities carried out in the camp. The water quality index ( WQI) was calculated after monitoring seventeen physicochemical and microbiological variables and the Montoya index was applied. The samples were collected during 48 sampling campaigns, organised over the period of six months in eight stations. Two stations were located in each stream, one before and one after it passed through the camp. The results indicated that streams 1, 3, and 4 show a slight deterioration in water quality, affected by anthropogenic activities carried out in the said camp; meanwhile, stream 2 shows an increasing deterioration in water quality. The water quality of the streams before passing through the camp was determined to be between “uncontaminated” and “acceptable”, while after passing through the camp it was classified between “acceptable” and “slightly contaminated”. The results indicated a non-significant difference between the downstream and upstream WQI values for streams 1, 3, and 4; while stream 2 did show a significant difference in the WQI between upstream and downstream; indicating that anthropogenic activities alter the quality of the water.

Due to an increasing amount of music being made available in digital form in the Internet, an automatic organization of music is sought. The paper presents an approach to graphical representation of mood of songs based on Self-Organizing Maps. Parameters describing mood of music are proposed and calculated and then analyzed employing correlation with mood dimensions based on the Multidimensional Scaling. A map is created in which music excerpts with similar mood are organized next to each other on the two-dimensional display.