Artificial light at night (ALAN) has become a problem for fireflies because it disrupts their natural processes and threatens the conservation of their populations. In this regard, the aim of the study was to determine the effects of ALAN on firefly species through a systematic review. The PRISMA 2020 statement was fundamental for the review of the databases, and the inclusion and exclusion criteria for specifying the subject of study. On the other hand, the annual growth of scientific production was determined using the digital tool (Calcuvio). The year and country with the highest scientific production were 2021 and the United States, respectively, and the annual growth (2005−2025) was 16%. The most studied species was Lampyris noctiluca, and the effect of ALAN on the most common fireflies was a change in the intensity and frequency of their flashes in females. It is concluded that investment should be made in research in countries with abundant and diverse populations of fireflies. Furthermore, studies should be conducted on trophic interactions or sublethal physiological effects of fireflies, as well as on diversifying the species under study.

Accurate prediction of the thermal ablation zone in hepatic radiofrequency ablation (RFA) is critical for preventing the recurrence of local tumor, yet it is complicated by the convective heat sink effect of blood perfusion. Traditional numerical solvers, such as the finite difference method (FDM), are inherently limited by time-step constraints which require greater computational cost and impede real-time clinical applications. This study proposed a mesh-free Physics-Informed Neural Network (PINN) framework to simulate the spatiotemporal dynamics of Pennes bioheat equation. By embedding the governing partial differential equation (PDE) directly into the loss function of the neural network, the model learnt the continuous temperature field without spatial discretization or labeled training data. A comparative analysis against an explicit FDM baseline yielded a relative L2 error norm of 1.9%. Although PINN’s continuous functional approximation slightly dampened the theoretical singularity at the tip of the electrode, it accurately resolved the critical 50 °C isotherm that defined the boundary of irreversible coagulative necrosis. Furthermore, the framework effectively decoupled computational cost from the time of physical simulation. While offline training required approximately 6 minutes, the optimized network executed online inference in milliseconds. This capability to provide physically consistent and near-instantaneous thermal predictions demonstrates the potential of the PINN framework for intraoperative decision support systems.

Carbon dioxide emissions from power plants and industrial producers are a major driver of global warming, leading to rising temperatures and numerous adverse impacts on ecosystems and human life. In response, various strategies have been developed to mitigate greenhouse gas emissions. This review paper examines the three main stages of energy conversion for carbon dioxide capture: pre-combustion, oxy-fuel combustion, and post-combustion, with particular emphasis on the latter. Several capture techniques have been explored, including chemical and physical absorption, membranes, adsorption on porous materials, and cryogenic freezing. Among these, membrane-based methods have attracted significant attention due to their advantages in energy efficiency, operational simplicity, and potential integration with hybrid systems. Comparing the efficiency of different capture technologies, membranes achieve 85–90% efficiency at a lower cost (\$25–45/ton CO$_2$), while deep cooling technology boasts high purity ($>$99%) but comes at the cost of high energy consumption ($>$3.5 GJ/ton CO$_2$). Absorption technology, on the other hand, ranges between 90–95% efficiency at a cost of \$40–60/ton CO$_2$. Membranes have been successfully combined with absorption, desorption, and cryogenic processes to achieve higher purity in CO$_2$ capture. This study reviews twenty research papers on membrane technology, focusing on hybrid membrane systems and their performance. Carbon capture and storage (CCS) is widely recognized as a key strategy for achieving climate goals by reducing carbon emissions from thermal energy production and industrial processes, while also enabling the net removal of CO$_2$ from the atmosphere.

This research examines The Electron Energy Distribution Function (EEDF) of electrons in plasma discharge for (CHF$_3$-He) gas combinations. The Fortran programming language was used to solve the Boltzmann equation. A two-term approximation was used to solve the Boltzmann transport equation for both pure gases and mixtures. Using this method of solution, the electron energy distribution function was computed, and electric transport parameters were evaluated with range of E/N varying from (10–600) Td. The electron energy distribution function of the CHF$_3$-He gas mixture is nearly Maxwellian at E/N values (10–20) Td, the distribution function is non-Maxwellian when E/N is raising. Also, the energy values of the mixtures largely depend on the transport energy between electron and molecule through collisions. In compared to mixtures, Helium gas has a high energy characteristic. At higher helium ratios, the mean electron energy to mixture is increasing. The mean electron energy in a gas mixture (35% CHF$_3$ + 65% He) and the behavior variation in electron mobility at this ratio both have larger values than other ratios.

This study proposes a fuzzy-based adaptive temperature management system for hydroponic cultivation in tropical climates. Unlike conventional fixed-setpoint controllers, the proposed Mamdani fuzzy system utilizes pH and electrical conductivity (EC) as contextual inputs to dynamically adjust temperature control strategies. The underlying hypothesis is that maintaining lower root-zone temperatures (RZTs) during suboptimal pH/EC conditions may increase dissolved oxygen availability, partially compensating for nutrient stress. The Internet of Things (IoT)-enabled system employs Long Range wireless protocol (LoRa) communication for long-range, low-power data transmission, with fuzzy inference executed at the gateway for offline resilience. A five-month field validation (April–August 2024) in Ho Chi Minh City demonstrated effective temperature regulation, maintaining solution temperature within the 18–28 °C operational target range for 88.7% of the trial period, with zero exceedance of the 35 °C critical threshold. The system maintained pH at 5.72 ± 0.32 (86.4% time in optimal range) and EC at 1.87 ± 0.28 mS/cm (81.3% time in optimal range). Retrospective simulation comparing the proposed controller against On/Off, proportional-integral (PI) baselines, and temperature-only FLC baselines, demonstrated a 15–16% reduction in chiller runtime while maintaining equivalent thermal safety. Operational crop assessment across three cultivation cycles indicated commercially viable lettuce production. A dedicated system engineering analysis addresses architecture trade-offs, reliability, scalability, and cost-effectiveness for practical deployment in tropical commercial operations.

This study explores the macroeconomic impact of the Zero Over-Dimension Over-Load (ODOL) policy in Indonesia, especially its influence on logistics costs, inflation, and economic growth. The policy is not discussed here only as a matter of transport compliance, but also as a structural change in logistics governance that may affect the wider economy. A mixed-methods approach was used, based on primary survey data collected in 2025 from logistics stakeholders in DKI Jakarta and West Java. For the analysis, the Leontief Price Model was applied to estimate price transmission effects, while the dynamic Computable General Equilibrium (CGE) IndoTERM model was used to simulate cost shocks, investment adjustment, and fiscal reallocation. The findings show that the policy increases national logistics costs by 4.58% in the short term, which raises the logistics cost-to-GDP ratio to 14.94%. However, the longer-term results are more positive. The simulation suggests a 0.05% increase in GDP, equivalent to a net output gain of IDR 14.3 trillion. This result is associated with a 6.74% increase in fleet investment, estimated at IDR 42.4 trillion, as well as fiscal savings caused by lower infrastructure damage. These results suggest that stricter logistics regulation may bring broader economic benefits when the analysis goes beyond the immediate rise in transport costs. In practical terms, the policy should be supported by fiscal incentives for fleet modernization and by careful timing of enforcement, especially to limit inflationary pressure in food and construction-related sectors.

This study examines the effects of viscous dissipation, Joule heating, and coupled heat transfer on dissipative ternary nanofluid flow over a permeable surface. The ternary nanofluid is composed of Al$_2$O$_3$, SiO$_2$, and TiO$_2$ nanoparticles dispersed in water as the base fluid. By introducing suitable similarity transformations, the governing partial differential equations are reduced to a coupled system of ordinary differential equations. The thermal field is analyzed for both prescribed surface temperature (PST) and prescribed heat flux (PHF) conditions, while a temperature-dependent heat source/sink term is incorporated to maintain energy balance within the fluid domain. The resulting energy equation is treated analytically with the aid of Kummer’s function and Laguerre polynomial techniques. The effects of the main controlling parameters, including the inverse Darcy number, magnetic parameter, viscosity-ratio parameter, and radiation parameter, are discussed with the support of graphical results. It is found that an increase in the magnetic parameter reduces the velocity by about 12% and raises the temperature by nearly 18%. These findings provide useful guidance for the design and thermal optimization of engineering systems involving complex nanofluids in porous media, including polymer extrusion and automotive cooling applications.