Assessing heterogeneous groundwater systems: Geostatistical interpretation of well logging data for estimating essential hydrogeological parameters.

This research presents an unsupervised learning approach for interpreting well-log data to characterize the hydrostratigraphical units within the Quaternary aquifer system in  Debrecen area, Eastern Hungary. The study applied factor analysis (FA) to extract factor logs from spontaneous potential (SP), natural gamma ray (NGR), and resistivity (RS) logs and correlate it to the petrophysical and hydrogeological parameters of shale volume and hydraulic conductivity. This research indicated a significant exponential relationship between the shale volume and the scaled first factor derived through factor analysis. As a result, a universal FA-based equation for shale volume estimation is derived that shows a close agreement with the deterministic shale volume estimation. Furthermore, the first scaled factor is correlated to the decimal logarithm of hydraulic conductivity estimated with the Csókás method. Csókás method is modified from the Kozeny-Carman equation that continuously estimates the hydraulic conductivity. FA and Csókás method-based estimations showed high similarity with a correlation coefficient of 0.84. The use of factor analysis provided a new strategy for geophysical well-logs interpretation that bridges the gap between traditional and data-driven machine learning techniques. This approach is beneficial in characterizing heterogeneous aquifer systems for successful groundwater resource development.

The Dynamics of Mastery Motivation and Its Relationship with Self-Concept in Music Education.

Musical education hinges on students' mastery motivation and self-concept, which are crucial for effective musical learning. Despite the acknowledgement of their individual importance, the relationship between these factors within music education remains unexplored. Hence, this study aimed to investigate the dynamics of mastery motivation (MM) and its relationship with self-concept (SC) in the context of music education. A survey was administered to 139 Hungarian grade 7 students, employing a musical MM questionnaire, a musical SC inquiry, and the collection of demographic information collection. We employed descriptive statistics (IBM SPSS 23), a Rasch analysis (WINSTEPS), and correlational and regression analyses (R programming and SmartPLS4) for data analysis. The findings demonstrated that the utilized instruments were reliable and valid in measuring students' MM and SC in music education. This study revealed a strong positive correlation (r = 0.778) between students' MM and SC, with moderate to strong inter-relationships among various subfactors. Furthermore, comparisons unveiled significant disparities in musical MM across school levels, with higher MM and SC observed among female students. Furthermore, gender, a musical family background, and awareness of musical lesson usefulness were predictive factors for both students' MM and SC within music education. This study provides valuable insights for professionals and policy makers to enhance music education, nurturing students' musical growth effectively. By understanding the relationship between MM and SC and considering predictive factors, stakeholders can develop strategies that optimize the impact of music education on students' musical development.

Multivariate statistical and hydrochemical approaches for evaluation of groundwater quality in north Bahri city-Sudan.

Groundwater has recently been considered one of the primary sources of water supply in Sudan. However, groundwater quality is continuously degraded due to overexploitation and long-term agricultural operations. The fossilized Cretaceous Nubian sandstone is the principal aquifer in the study area. This research aims to determine the major factors influencing groundwater quality and detect the suitability of groundwater for drinking and irrigation purposes by integrating hydrochemical and multivariate statistical methods. Hydrochemical plots such as Piper, Chadha, and Durov diagrams were applied to detect the groundwater facies and hydrochemical processes controlling the groundwater quality. They indicated Ca-Mg-HCO3 water type as a dominant groundwater facies followed by Na-HCO3 and Na-Cl types. Gibbs plots suggested that the dissolution of the minerals is the main factor influencing the water quality. The results of the Gibbs plot were further interpreted using saturation indices (SI). The SI values indicated that aragonite, calcite, and dolomite precipitated respectively in 58.33%, 75%, and 75% of groundwater samples. Multivariate statistical analyses, including Pearson's correlation analysis, hierarchical cluster analysis (HCA), and principal component analyses (PCA), were jointly employed to identify the structure of water quality data and deduce the main factors controlling groundwater quality. The statistical analysis revealed the effect of the physical and human-induced activities as the main factors influencing groundwater chemistry. These factors are rock-water interaction, agricultural practice, and organic contamination from septic tanks. Further, the suitability of groundwater for irrigation is determined using sodium adsorption ratio (SAR) and sodium percent (Na+%) indices. They carefully indicated that 75% of the groundwater samples in the study area are excellent for irrigation except for some sample location where the salinity hazard is stimulated by ion exchange. This integrated approach was effective in calibrating water quality assessment methodologies. The current research concluded that the implication of a groundwater quality monitoring scheme is crucial to ensure water supply sustainability in north Bahri city.

Ectoparasitic fungi of Myrmica ants alter the success of parasitic butterflies.

Exploitation of organisms by multiple parasite species is common in nature, but interactions among parasites have rarely been studied. Myrmica ants are rich in parasites. Among others, the ectoparasitic Rickia wasmannii fungus and the parasitic caterpillars of myrmecophilous Phengaris butterflies often infect the same Myrmica colonies. In this study, we examined the effects of R. wasmannii on the adoption, long-term development, and survival of P. alcon. In laboratory conditions, caterpillars introduced into nests of Myrmica scabrinodis uninfected with R. wasmannii survived significantly longer compared to caterpillars introduced into infected nests. In the field, joint infection was less common than expected if both parasites exploited M. scabrinodis colonies independently. Pre-pupal caterpillars of P. alcon were somewhat larger in nests infected with R. wasmannii than those found in uninfected nests. Based on these results it seems that R. wasmannii infection of M. scabrinodis affects the survival and development of P. alcon caterpillars, suggesting competition between these two ant parasites.