The aim of the present paper is to quantify water quality in the Lower Danube Region by using a series of multivariate techniques and the Water Quality Index (WQI). In this paper were measured 18 parameters upstream and downstream the city of Galati along the Danube River, namely: pH, Dissolved Oxygen (DO), Chemical Oxygen Demand (COD), Biochemical Oxygen Demand (BOD), N-NH4+, N-NO2−, N-NO3−, N total, P-PO43−, SO42−, Cl−, Fe-total, Cr-total, Pb2+, Ni2+, Mn2+, Zn2+, As2+, in the interval winter 2013–winter 2016. The samples were either analyzed on the field, or sent for testing to the laboratory. The physicochemical parameters mentioned above were analyzed in accordance with the Romanian and International standards in force. The WQI was calculated according to Weighted Arithmetic Water Quality Index Method. The interdependencies between the selected physicochemical parameters were used for determining potential sources of pollution. Monitoring water quality dynamics in the period mentioned above favoured a series of relevant conclusions about the anthropic influence on water quality. Water quality was assessed by processing the measurements results, by calculating the water quality index (WQI), and by using the principal component analyses (PCA) and the response surface method (RSM) with the aim of correlating the indices for the physico-chemical parameters.

A novel approach for nonlinear complex system identification based on internal recurrent neural networks (IRNN) is proposed in this paper. The computational complexity of neural identification can be greatly reduced if the whole system is decomposed into several subsystems. This approach employs internal state estimation when no measurements coming from the sensors are available for the system states. A modified backpropagation algorithm is introduced in order to train the IRNN for nonlinear system identification. The performance of the proposed design approach is proven on a car simulator case study.

The context of the COVID-19 pandemic required the implementation of special measures to ensure the continuity and quality of teaching in higher education. The study presented here aims to identify the differences of opinion between the age categories of students in the first year of the Faculty of Physical Education and Sports in Galati, Romania, regarding teaching, learning and assessment activities on online platforms. A total of 147 students divided into three age groups (under 20 years, 20–30 years and over 30 years) filled out a questionnaire composed of items with closed and free answers, structured on four factors (attractiveness, accessibility, motivation and efficiency), after participating in the online teaching and evaluation act during the first semester of the academic year 2020–2021. Multivariate and univariate tests were applied, identifying the influence of the independent age variable on the dependent variables (aspects measured by the items of the questionnaire). Values were obtained at significant thresholds of F for some of the investigated aspects: boredom induced by online activities, stress value, participation, involvement, motivation and adaptation to the online program, usefulness and quality of teaching process, value of professional training and involvement in disruptive activities. The analysis of the differences between the average scores of the items for the pairs formed by age categories highlighted insignificant values between those under 20 and those aged 20–30, but multiple significant differences between the group of those over 30 and the other two groups. The centralization of free answers by environment (rural and urban) identified the advantages perceived by the students about the online activities (increasing the amount of free time, low financial costs, high accessibility, personal learning pace), the reported disadvantages (technical problems, low concentration, poor socialization) and contradictory proposals to improve activities (continuing online, returning to classical teaching, simplifying the subject, using video materials, involving all students in activities). The paper aims to evaluate the performance of teaching activities performed in the first year of study for the students of physical education and sports, in the context of the COVID-19 pandemic, involving questionnaires validated by the specialty center at the university. The analysis of the results highlighted a series of extremely important aspects that have a role in the future design of activities and courses.

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In order to determine the water quality of Danube River, in the Galati area, the Water Quality Index was calculated. Water Quality Index is a useful number of overall qualities of water. Galati is a Danube port city located in south-eastern of Romania. Samples were taken from 9 places along the Danube starting with the place where the Siret flows into the Danube to the Profiland Steel Plant. Profiland Steel is a company in Galai whose main activities are: sheet and zinc strips; treatment and coating of metals. The monitoring period was one year, from November 2016 to December 2017. Every month, thirty physical - chemical parameters were investigated. In this study the assessment of surface water quality was determined on the basis of various indicators such as: potassium and calcium ions, nitrites, nitrates, total nitrogen, ammonium, chlorides, total phosphorus, sulphates, cadmium, chrome, copper, lead, iron, zinc, density, dissolved oxygen, chemical oxygen demand (CCO-Cr), biochemical oxygen demand (CBO5), electrical conductivity, the density of the conductivity, resistivity, pH, salinity, total dissolved solids. The water quality index (WQI) has been calculated by using Weighted Arithmetic Water Quality Index Method. Two types of correlations were developed: Pearson correlation matrix and Spearman correlation.

Understanding soil moisture and its relationship with different climatic and soil characteristics is essential for better analysing the interactions between forest and soil water dynamics, allowing us to more precisely predict climatic changes. The present paper investigates the temporal variability of soil moisture in three different forest ecosystems (LTER -long term ecological research site) with the same soil type (Eutric Cambisol). Soil moisture was measured daily from 2011 to 2016 by using three sensors at three different depths (20, 40, 70 cm). We identified the interactions between soil properties, vegetation type, local climatic conditions and soil moisture. In order to establish the temporal variability of the soil moisture content, we have applied two procedures, namely the Fourier series and the neural network fitting. A high variability in time and depth for soil volumetric water content was identified. The highest soil moisture levels were recorded at higher depths (70 cm) for almost all surfaces, with the exception of the Fundata surface because of the occurrence of limestone. In the mountainous areas, with higher precipitation (Fundata and Predeal sites), volumetric soil water content was mainly influenced by soil physical characteristics. Soil moisture levels below the drought level were only recorded for the Stalpeni site from September to October 2012. There was a delay between the precipitation event and soil humidification of 0.4-0.8 time units (days). We also found a significant correlation between soil moisture and soil texture and a weak correlation with vegetation type. Temperature influenced soil moisture levels at almost all depths, while precipitation only had an impact when there was a delay of 1 or 2 days. Our results can serve as a scientific base in the monitoring and analysing of soil moisture against the background of a changing climate.

The optical reflectance of Bi 2 O 3 was measured, and the optical properties were estimated by Kramers–Kronig analysis. The novelty of the present study is due to the implementation of a MAPLE software approach to the complex computations implied by this extrapolation. The analytical fit of the reflectance spectrum is applied, accompanied by a careful extrapolation, which is necessary within the Kramers–Kronig method. In this way starting from the reflectance samples data, using this transformation, a very good agreement is obtained between the main optical parameters, namely the refractive index and the absorbtion coefficient. The study is implemented for Bi 2 O 3 films deposited by thermal vacuum evaporation at different temperatures of the glass substrates and the comparison with the experimental data set being made using the transmission and the reflection optical spectra.