This paper introduces HLOA, a novel metaheuristic optimization algorithm that mathematically mimics crypsis, skin darkening or lightening, blood-squirting, and move-to-escape defense methods. In crypsis behavior, the lizard changes its color by becoming translucent to avoid detection by its predators. The horned lizard can lighten or darken its skin, depending on whether or not it needs to decrease or increase its solar thermal gain. The skin darkening or lightening strategy is modeled by including the stimulating hormone melanophore rate( $$\alpha$$α -MHS) that influences these skin color changes. Further, the move-to-evasion strategy is also mathematically described. The horned lizard’s shooting blood defense mechanism, described as a projectile motion, is also modeled. These strategies balance exploitation and exploration mechanisms for local and global search over the solution space. HLOA performance is benchmarked with sixty-three optimization problems from the literature, testbench problems provided in IEEE CEC- 2017 “Constrained Real-Parameter Optimization”, analyzed for dimensions 10, 30, 50, and 100, as well as testbench functions from IEEE CEC-06 2019 “100-Digit Challenge”. Moreover, three real-world constraint optimization applications from IEEE CEC2020 and two engineering problems, the multiple gravity assist optimization and the optimal power flow problem, are also studied. Wilcoxon and Friedman statistics tests compare the HLOA algorithm results against ten recent bio-inspired algorithms. Wilcoxon shows that HLOA provides the optimal solution for most testbench functions more effectively than competing algorithms. At the same time, the Friedman statistics test ranks the HLOA first, and the n-dimensional analysis shows that it performs better on the constrained optimization problems for dimensions 50 and 100. The source code is free and available from https://www.mathworks.com/matlabcentral/fileexchange/159658-horned-lizard-optimization-algorithm-hloa.

This paper shows the effect of electrical conductivity on the vascular system of plants through the utilization of silver nanoparticles supported by nanocellulose. The plant Epipremnum aureum, also known as pothos, was used in the experimentation. The main characteristics of the plant are its vigorous growth, remarkable adaptability to thrive in both soil and aquatic environments, simple propagation, and noteworthy resilience against diseases. The experiment used a polarization voltage ranging from − 1.5 to 1.5 V and shunt resistors of 1, 10, 100, and 1000 ohms. The scan polarization rate was 15 mV/s. Methods like environmental scanning electron microscopy and energy-dispersive X-ray analysis were used for chemical and structural analysis. The findings demonstrate that adding silver nanoparticles held together by nanocellulose enhances the vascular system's capacity to conduct electricity. Moreover, the Wilcoxon signed-rank test results revealed no statistically significant difference between the root-steam and stem-leaf output voltage values. These findings imply that silver nanoparticles are distributed throughout the vascular system and act as conductive pathways in plants. Additionally, electrolysis-Faraday's law was used to calculate the recovery of silver material, yielding 40 mg/mm² per hour. These discoveries open new avenues for comprehending and manipulating plant physiological processes, potentially leading to beneficial outcomes in agriculture and contaminant recovery.

La Zona Metropolitana del Sur de Tamaulipas tiene características particulares para el estudio de la contaminación atmosférica: en su extremo sureste está instalada una refinería; al norte se encuentran un corredor industrial petroquímico, una termoeléctrica y el puerto industrial de Altamira; al oeste se encuentra una empresa minera y un amplio sistema lagunario; y al este, el Golfo de México. Ante la falta de una red de monitoreo de la calidad del aire, en este trabajo se presenta la Red Ciudadana de Monitoreo de la Calidad del Aire en la Zona Metropolitana Altamira-Tampico-Cd. Madero que tiene instaladas estaciones meteorológicas en varias ubicaciones de la ciudad generando datos de viento, precipitación, temperatura y humedad, que permitirán generar un patrón local de vientos para la simulación de la dispersión de la contaminación. Los datos están siendo recopilados en una base de datos y están accesibles al público a través de la página web de la Red. La página permite la interacción con la ciudadanía para incluir sus estaciones meteorológicas, subir fotografías georreferenciadas de fuentes de emisión, compartir rutas para la estimación de emisiones, participar en encuestas de percepción de calidad del aire y estar informados sobre los resultados del análisis de datos.

This study presents the design and evaluation of a plant-based bio-battery, specifically a plant microbial fuel cell (plant-MFC), utilizing peppermint plants and monitored by an open-source electronic system. The goal was to develop a sustainable, low-cost bioenergy solution by integrating plant-MFCs into clay pots and equipping them with an Arduino-based monitoring system. This system features an OLED display, capacitive soil moisture sensors, and data logging capabilities via a microSD card. Four plant-MFCs were constructed and tested over 30 days. Voltage and soil moisture data were recorded every 10 minutes, and polarization experiments were conducted to assess power output. The results demonstrated consistent open-circuit voltages averaging 1.1 V, with peaks reaching 1.2 V. The maximum power densities achieved were 645.91 mW/m³, indicating the effectiveness of the design. The system's performance highlights the importance of soil moisture and plant health in maximizing energy generation. Its open-source nature allows for easy replication and modification, making it suitable for educational purposes and encouraging collaboration within scientific and maker communities. This interdisciplinary approach, which merges biology, electronics, and renewable energy, demonstrates the potential of plant-MFCs for off-grid power generation, environmental monitoring, and science education. The findings contribute to ongoing efforts to develop accessible and sustainable bioelectrochemical energy technologies.

Recently, plant-based bioelectronic systems have been explored for environmental sensing applications. However, their intrinsically low electrical conductivity often limits signal sensitivity and measurement reliability. In this work, the electrothermal behavior of living Epipremnum aureum plants incorporating Ag/AgCl nanoparticles supported on nanocellulose was investigated. Electrical and thermal responses were simultaneously measured under controlled environmental conditions using external shunt resistances of 1, 10, 100, and 1000 Ω. Compared with the control without nanoparticle incorporation, the nanoparticle-incorporated plant exhibited stronger electrical responses and distinct electrothermal behavior over the studied temperature range. The measured signals showed nonlinear responses, temporal asymmetry, and resistance-dependent modulation, suggesting changes in charge transport within the plant tissues. Silver-enriched regions and the co-detection of chlorine within the nanoparticle-incorporated plant tissues were identified by environmental scanning electron microscopy and energy-dispersive X-ray spectroscopy. Five machine-learning regression models were trained to estimate temperature using the measured electrothermal voltage signals as predictors. The best-performing model, MLP FitRNet, achieved a mean absolute error of 0.598 °C, a root mean square error of 0.748 °C, and an $R^2$ value of 0.974. These results demonstrate the potential of nanoparticle-incorporated biohybrid plant systems for electrothermal signal analysis and data-driven temperature estimation, while providing a foundation for future intelligent environmental monitoring applications.