The swarming behaviour of natural populations of Anopheles gambiae and An. coluzzii (formerly known as An. gambiae S and M forms, respectively) were investigated through longitudinal surveys conducted between July 2006 and October 2009 in two rural areas of south-western Burkina Faso where these forms are sympatric. In both sites, the majority of swarms were recorded above visual markers localised among houses. In Soumousso, a wooded area of savannah, 108 pairs caught in copula from 205 swarms were sampled; in VK7, a rice growing area, 491 couples from 250 swarms were sampled. If segregated swarms were the norm in both sites, many visual markers were shared by the two forms of An. gambiae. Furthermore, mixed swarms were collected annually in frequencies varying from one site to another, though no mixed inseminations were recorded, corroborating the low hybrid rate previously reported in the field. The occurrence of inter-specific mate-recognition mechanisms, which allow individuals to avoid hybridisation, is discussed.
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http://dx.doi.org/10.1016/j.actatropica.2013.12.011 | DOI Listing |
Sci Rep
December 2024
Computer Science Department, Faculty of Computers and Information, South Valley University, Qena, 83523, Egypt.
Enhanced technologies of the future are gradually improving the digital landscape. Internet of Things (IoT) technology is an advanced technique that is quickly increasing owing to the development of a network of organized online devices. In today's digital era, the IoT is considered one of the most robust technologies.
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December 2024
Department of Power Electrical Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran.
With increasing worldwide attention on environmental sustainability, microgrids that harness renewable sources have become more prominent. The changing characteristics of renewable energy sources and energy demand's unpredictable patterns might cause disruptions in the sustainable working of microgrids. Moreover, EVs (electric vehicles), being dynamic loads, might significantly affect the security administration of the microgrid.
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December 2024
Department of Computer Science, College of Computer and Information Sciences, King Saud University, 11543, Riyadh, Saudi Arabia.
The traditional optimization approaches suffer from certain problems like getting stuck in local optima, low speed, susceptibility to local optima, and searching unknown search spaces, thus requiring reliance on single-based solutions. Herein, an Improved Aquila Optimizer (IAO) is proposed, which is a unique meta-heuristic optimization method motivated by the hunting behavior of Aquila. An improved version of Aquila optimizer seeks to increase effectiveness and productivity.
View Article and Find Full Text PDFBiomimetics (Basel)
December 2024
Institute of Knowledge Technology, University Complutense of Madrid, 28040 Madrid, Spain.
The COVID-19 pandemic highlighted the urgent need for effective surface disinfection solutions, which has led to the use of mobile robots equipped with ultraviolet (UVC) lamps as a promising technology. This study aims to optimize the navigation of differential mobile robots equipped with UVC lamps to ensure maximum efficiency in disinfecting complex environments. Bio-inspired metaheuristic algorithms such as the gazelle optimization algorithm, whale optimization algorithm, bat optimization algorithm, and particle swarm optimization are applied.
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December 2024
School of Electrical and Photoelectronic Engineering, West Anhui University, Lu'an 237012, China.
This work presents a rat optimization algorithm (ROA), which simulates the social behavior of rats and is a new nature-inspired optimization technique. The ROA consists of three operators that simulate rats searching for prey, chasing and fighting prey, and jumping and hunting prey to deal with optimization issues. The Levy flight strategy is introduced into the ROA to keep the algorithm from running into issues with slow convergence and local optimums.
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