Last generation video encoding standards increase computing demands in order to reach the limits on compression efficiency. This is particularly the case of H.264/AVC specification that is gaining interest in industry. We are interested in applying parallel processing to H.264 encoders in order to fulfill the computation requirements imposed by stressing applications like video on demand, videoconference, live broadcast, etc. Given a delivered video quality and bit rate, the main complexity parameters are image resolution, frame rate and latency. These parameters can still be pushed forward in such a way that special purpose hardware solutions are not available. Parallel processing based on off-the-shelf components is a more flexible general purpose alternative. In this work we propose a hierarchical parallelization of H.264 encoders very well suited to low cost clusters. Our proposal uses MPI message passing parallelization at two levels: GOP and frame. The GOP level encodes simultaneously several groups of consecutive frames and the frame level encodes in parallel several slices of one frame. In previous work we found that GOP parallelism alone gives good speed-up but imposes very high latency, on the other side frame parallelism gets less efficiency but low latency. Combining both approaches we obtain a compromise between speed-up and latency and then a broader spectrum of applications can be covered

This study reports for the first time the isolation, identification and characterization of lipase-producing thermophilic strain from the geothermal water of the El Chichón volcano crater lake. Two strains were identified by 16S rRNA sequencing as Geobacillus jurassicus CHI₂ and Geobacillus stearothermophilus CHI₁. Results showed that G. jurassicus CHI₂ is Gram-positive, able to ferment maltose, fructose and sucrose and to hydrolyze starch and casein; while G. stearothermophilus CHI₁ showed to be Gram-variable, able to ferment maltose and fructose and to hydrolyze starch. Colonies of both strains presented irregular shape, umbilicated elevation of gummy texture and cells presented flagellar movement to survive in fluids with high temperature and mass gradients due to complex phenomena of heat and mass transfer present in the geothermal fluids. Lipase production for G. stearothermophilus CHI₁ was also evaluated. It was found that this strain possesses a growth associated with extracellular lipase production with a high activity of 143 U/mL at 8.3 h of incubation time, superior to the activities reported for other microorganisms of genus Geobacillus; for this reason, it can be said that the thermal flow of the El Chichón volcano crater lake can be a useful source of lipase-producing thermophilic bacteria.

Due to the current COVID-19 pandemic, guaranteeing thermal comfort and low CO₂ levels in classrooms through efficient ventilation has become vitally important. This study presents three-dimensional simulations based on computational fluid dynamics of airflow inside an air-conditioned classroom located in Veracruz, Mexico. The analysis included various positions of an air extractor, Reynolds numbers up to 3.5 × 10⁴, four different concentrations of pollutant sources, and three different times of the day. The simulations produced velocity, air temperature, and CO₂ concentrations fields, and we calculated average air temperatures, average CO₂ concentrations, and overall ventilation effectiveness. Our results revealed an optimal extractor position and Reynolds number conducive to thermal comfort and low CO₂ levels due to an adequate ventilation configuration. At high pollutant concentrations, it is necessary to reduce the number of students in the classroom to achieve safe CO₂ levels.

This paper presents a hybrid genetic algorithm with collective communication (HGACC) using distributed processing for the job shop scheduling problem. The genetic algorithm starts with a set of elite micro-populations created randomly, where the fitness of these individuals does not exceed a tuned upper bound in the makespan value. The computational processes distribute the micro-populations collectively. In the micro-populations, each individual's search for good solutions is directed toward the solution space of the fittest individual, identified by an approximation of genetic traits. In each generation of the genetic algorithm, the best individual from each micro-population migrates to another micro-population to maintain diversity in populations. Changes in the genetic sequence are applied to each individual by the simulated annealing algorithm (iterative mutation). In this paper, the results obtained show that the genetic algorithm achieves excellent results, as compared to other genetic algorithms. It is also better than other non-genetic meta heuristics or competes with them.

Indoor air conditioning is currently a topic of much interest, not only to save energy but also due to public health issues such as pandemics. This study focuses on the thermal comfort and air quality of a closed, air-conditioned space located in an extremely hot climate. Due to noise and weather conditions, the door and window of the space are kept closed at all times. The study uses computational fluid dynamics techniques and the finite element method. Average temperatures and CO₂ concentrations, as well as effectiveness for temperature and concentration distribution, are calculated for the analysis. Results indicate that supplying air away from hot walls improves air quality and thermal comfort. Furthermore, there is an optimal Reynolds number that depends on the number of people inside the space. Due to the above, it is possible to find an ideal configuration that simultaneously allows for efficient energy use, helps to avoid the adverse effects of CO₂ on daily activities such as working or studying, and supports people’s health and comfort.

Heat exchangers play an important role in different industrial processes; therefore, it is important to characterize these devices to improve their efficiency by guaranteeing the efficient use of energy. In this study, we carry out a numerical analysis of flow dynamics, heat transfer, and entropy generation inside a heat exchanger; an aqueous medium used for oil extraction flows through the exchanger. Hot water flows on the shell side; nanoparticles have been added to the water in order to improve heat transfer toward the cold aqueous medium flowing on the tube side. The aqueous medium must reach a certain temperature in order to obtain its oil extraction properties. The analysis is performed for different Richardson numbers (Ri = 0.1–10), nanofluid volume fractions (φ = 0.00–0.06), and heat exchanger heights (H = 0.6–1.0). Results are presented in terms of Nusselt number, total entropy generation, Bejan number, and performance evaluation criterion. Results showed that heat exchanger performance increases with the increase in Ri when Ri > 1 and when reducing H.