Athenea Engineering sciences journal

Impact of Wastewater Treatment Plants: An Assessment from Environmental Engineering

Ruben Martinez Cabrera, Julio Cesar Minga, Maria Mercedes Paricoto Simon — Sun, 18 Jan 2026 03:27:58 +0000

The study analyzed the environmental performance and operational efficiency of wastewater treatment plants from an environmental engineering perspective, aiming to identify the impacts associated with their functioning and technological level. The methodology included direct observation of unit processes and a systematized analysis of operational information, applying technical criteria for environmental assessment and contaminant removal. The results showed significant differences among the plants, highlighting one system with suspended solids removal efficiency below 65\,\%, associated with high environmental impact, in contrast to others with efficiencies above 90\,\% and moderate effects. It is concluded that environmental performance depends on technological level, emission control, and integrated waste management.

Carbonaceous Materials and Cacao Waste Nanomaterials for Heavy Metal Removal

Thu, 22 Jan 2026 23:34:22 +0000

The presence of heavy metals in water poses a critical risk to human health and ecosystems, particularly in cocoa-producing regions where agro-industrial and mining activities converge. This work provides a structured review on the use of cocoa residues as a platform for developing biosorbents, carbonaceous materials, and nanomaterials for heavy metal removal in aqueous systems. A search of scientific databases was conducted, and studies were selected based on clear material characterization and experimental evaluation in aqueous phase. The evidence was organized according to residue type and derived material, analyzing performance, advantages, and limitations. Research gaps were identified regarding the scarcity of tests in real-world matrices, limited information on regeneration and service lifetime, challenges in the treatment of Hg(II), and the lack of comprehensive assessments of sustainability and feasibility in Latin American contexts.

Comparison of the effectiveness between the Wavelet Transform and the Wigner-Ville Transform for the diagnosis of low insulation in the starting transient of induction motors

Alfredo Alejandro Marot Guevara, Sergio Rafael Velasquez Guzman — Wed, 11 Feb 2026 23:59:06 +0000

This study demonstrates the superiority of the Discrete Wavelet Transform over the Wigner-Ville Transform in detecting insulation faults in induction motors during startup transients. The comprehensive analysis of 360 simulated signals revealed that the wavelet technique with Daubechies 10 achieves significantly higher classification accuracy (74.44% vs. 67.78%), substantially outperforming its counterpart. Certain decomposition levels showed maximum sensitivity with variations up to +354%, while diagnostic reliability indicators confirm its robustness. This technique positions itself as an optimal solution for predictive monitoring systems, enabling early fault detection that substantially reduces downtime and industrial maintenance costs.

Everyday Algorithms and Social Subjectivity: How Artificial Intelligence Reconfigures Human Decisions in Daily Life

Sun, 15 Feb 2026 03:02:18 +0000

This study analyzes how artificial intelligence algorithms embedded in everyday life influence human decision-making and the configuration of social subjectivity. A quantitative approach based on socio-technical simulation was adopted, using synthetic data and decision models to assess the impact of algorithmic personalization, exposure diversity, and system explainability. The results show that personalization systematically increases the likelihood of adherence to recommendations, reduces the structural diversity of the choice environment, and modulates subjective variables such as perceived agency and algorithmic dependence. Sensitivity analysis indicates that personalization acts as a highly sensitive parameter, generating predictable and stable changes in decision behavior. These findings confirm that everyday algorithms not only optimize decisions, but also progressively reshape the human decision-making experience.