The objective of this study was to conduct a detailed analysis of the available flow series in the Chiriquí Viejo River basin in Panama. This paper examines the patterns of variation within these series and calculates various hydrological indexes indicative of the region’s hydrology. Utilizing advanced hydrological indexes within the Chiriquí Viejo River basin in Panama, which spans an area of 1376 km² and supports an estimated population of 100,000 inhabitants, analytical methods were employed to compute indexes such as the Daily Flow Variation Index (QVAR), the Slope of the Flow Duration Curve (R2FDC), the Hydrological Regulation Index (IRH), and the average duration of low (DLQ75) and high (DHQ25) flow pulses. The results indicate moderate flow variability (QVAR of 0.72) and a Hydrological Regulation Index (IRH) of 2.32, signifying a moderate capacity for flow regulation. Notably, low flow events (DLQ75) lasted approximately 3.73 days, while high flow events (DHQ25) lasted around 4.08 days. The study highlights a significant capacity to respond to extreme events, with maximum annual flows reaching 80.25 m³/s and minimum flows dropping to 3.01 m³/s. Despite the significant contribution of the basin to hydroelectric power generation and other economic activities, there is an observed need for sustainable management that accommodates hydrological fluctuations and promotes resource conservation. The conclusions indicate that these findings are critical for future planning and conservation strategies in the region, emphasizing the importance of integrating multidisciplinary approaches for Hydro-Social Sustainability. This novel and holistic approach underscores the interdependence between hydrological dynamics, socio-economic activities, and environmental sustainability, aiming to ensure the long-term resilience of the Chiriquí Viejo basin and its communities.

In this paper we study the on-line system identification process and the proportional-integral-derivative (PID) tuning of a buck converter. The system identification process was performed using a recursive least squares algorithm. The estimation error and parameter error were generated to demonstrate that the system was converging to its true parameters. The estimation error shows an absolute value of approximately 1 × 10-5 in less that 10ms. All the parameters were effectively converging in less that 100μs. Once the system was properly identified, an offline PID controller was designed to further implement it on the adaptive loop. Three different techniques were used to satisfy the requirements of the buck converter: phase and gain margin, pole-zero cancellation and frequency loop shaping. Phase and gain margin still prevails as the easiest method to design controllers. Pole-zero cancellation is based on pole-placement and is fairly easy to implement in order to obtain the gains of a PID controller. However, although these controllers can be easily designed, they do not provide the best response compared to the Frequency Loop Shaping (FLS) technique in terms of frequency and time responses.

Harmonic distortions caused by non-linear loads (NLLs) affect the behavior of electrical systems, creating harmonics in the fundamental signal. As a result, this deteriorates the power quality. Therefore, this work proposes the implementation of a hybrid filter based on an artificial neural network (ANN) control system, focused on subharmonic, interharmonic and odd harmonic distortions generated by a three-pulse cycloconverter. In addition, a passive double tuned filter was implemented to damp even and odd harmonics. As a result, the simulation performed in MATLAB/SIMULINK showed that the responses produced by the ANN are approximate to the distortions present in the electrical system. Consequently, the levels of total voltage distortions (THDV) and total current distortions (THDI) are reduced. Therefore, the ANN control system improves the quality in the electrical network because the current and voltage harmonics comply with the electrical standards.

This paper introduces a two-dimensional (2D) numerical simulation of the amplification of space charge waves using negative differential conductance in a typical MOS silicon–germanium (SiGe)-based field-effect transistors (FET) and complementary metal oxide semiconductor (CMOS) technology at 4.2 K. The hydrodynamic model of electron transport was applied to describe the amplification of space charge waves in this nonlinear medium (i.e., the negative differential conductance). This phenomenon shows up in GaAs thin films at room temperature. However, this can be also observed in a strained Si/SiGe heterostructure at very low temperatures (T < 77 K) and at high electric fields (E > 10 KV/cm). The results show the amplification and non-linear interaction of space charge waves in a strained Si/SiGe heterostructure occurs for frequencies up to approximately 60 GHz at T = 1.3 K, 47 GHz at T = 4.2 K, and 40 GHz at T = 77 K. The variation of concentration and electric field in the Z and Y directions are calculated at 4.2 K. The electric field in the Z direction is greater than in the Y direction. This is due to the fact that this is the direction of electron motion. In addition to deep space applications, these types of devices have potential uses in terrestrial applications which include magnetic levitation transportation systems, medical diagnostics, cryogenic instrumentation, and superconducting magnetic energy storage systems.

This study evaluated spatial and seasonal patterns of physicochemical water quality in the Chiriquí Viejo River basin (western Panama), a tropical watershed characterized by strong seasonal variability. A total of 90 water samples were collected at ten stations during the rainy season (May to October 2024) and dry season (January to March 2025). Dissolved oxygen (DO), turbidity, potential of hydrogen (pH), apparent color, total dissolved solids (TDS), and electrical conductivity (EC) were analyzed following ISO/IEC 17025:2017 accredited methods, and precipitation patterns were characterized using spatial interpolation of meteorological data. Spatio-temporal variability was assessed using linear mixed-effects models, with season and basin position as fixed effects and sampling site as a random factor. Results showed a spatial and seasonal structuring of water quality, with the upper basin exhibiting high and stable DO concentrations and low turbidity and apparent color. In contrast, the middle and lower basin showed rainy-season increases in turbidity and apparent color, supported by a significant season × basin interaction, indicating that precipitation driven impacts are heterogeneous along the basin. EC and TDS displayed spatial gradients, while DO remained relatively stable across seasons and basin levels. These findings highlight turbidity and apparent color as sensitive indicators of precipitation-driven impacts.