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"Boa"
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Boa constrictor
Describes boa constrictors including their physical characteristics, life cycle, habitat, and predatory behavior.
Book
Preliminary Genetic Analysis Supports Cave Populations as Targets for Conservation in the Endemic Endangered Puerto Rican Boa (Boidae: Epicrates inornatus). e63899
The endemic Puerto Rican boa (Epicrates inornatus) has spent 42 years on the Endangered Species List with little evidence for recovery. One significant impediment to effective conservation planning has been a lack of knowledge of the distribution of genetic variability in the species. It has previously been suggested that boas might best be protected around caves that harbor large populations of bats. Prior study has found Puerto Rican boas at relatively high densities in and around bat caves, which they use both to feed and seek shelter. However, it is unknown whether these behaviorally distinctive populations represent a distinct evolutionary lineage, or (conversely) whether caves harbor representative genetic diversity for the species across the island. We provide the first genetic study of the Puerto Rican boa, and we examine and compare genetic diversity and divergence among two cave populations and two surface populations of boas. We find three haplogroups and an apparent lack of phylogeographic structure across the island. In addition, we find that the two cave populations appear no less diverse than the two surface populations, and harbor multiple mtDNA lineages. We discuss the conservation implications of these findings, including a call for the immediate protection of the remaining cave-associated populations of boas.
Journal Article
Boa constrictors : prey-crushing reptiles
\"Boa constrictors are known as huge meat-eating reptiles. But how are they similar to and different from other reptiles, such as turtles or lizards? Read this book to find out\"-- Provided by publisher.
Book
Optimum Synthesis of a BOA Optimized Novel Dual-Stage PI − (1 + ID) Controller for Frequency Response of a Microgrid
A renewable and distributed generation (DG)-enabled modern electrified power network with/without energy storage (ES) helps the progress of microgrid development. Frequency regulation is a significant scheme to improve the dynamic response quality of the microgrid under unknown disturbances. This paper established a maiden load frequency regulation of a wind-driven generator (WG), solar tower (ST), bio-diesel power generator (BDPG) and thermostatically controllable load (heat pump and refrigerator)-based, isolated, single-area microgrid system. Hence, intelligent control strategies are important for this issue. A newly developed butterfly algorithmic technique (BOA) is leveraged to tune the controllers’ parameters. However, to attain a proper balance between net power generation and load power, a dual stage proportional-integral- one plus integral-derivative PI − (1 + ID) controller is developed. Comparative system responses (in MATLAB/SIMULINK software) for different scenarios under several controllers, such as a proportional-integral (PI), proportional-integral-derivative (PID) and PI − (1 + ID) controller tuned by particle swarm optimization (PSO), grasshopper algorithmic technique (GOA) and BOA, show the superiority of BOA in terms of minimizing the peak deviations and better frequency regulation of the system. Real recorded wind data are considered to authenticate the control approach.
Journal Article
It's a boa constrictor!
Introduces boa constrictors, describing their physical features, habitat, life cycle, and predatory behavior.
Book
Molecular characterization of a reptarenavirus detected in a Colombian Red-Tailed Boa (Boa constrictor imperator)
The global decline in biodiversity is a matter of great concern for members of the class
Reptili
a. Reptarenaviruses infect snakes, and have been linked to various clinical conditions, such as Boid Inclusion Body Disease (BIBD) in snakes belonging to the families
Boidae
and
Pythonidae
. However, there is a scarcity of information regarding reptarenaviruses found in snakes in both the United States and globally. This study aimed to contribute to the understanding of reptarenavirus diversity by molecularly characterizing a reptarenavirus detected in a Colombian Red-Tailed Boa (
Boa constrictor imperator
). Using a metagenomics approach, we successfully identified, and
de novo
assembled the whole genomic sequences of a reptarenavirus in a Colombian Red-Tailed Boa manifesting clinically relevant symptoms consistent with BIBD. The analysis showed that the Colombian Red-Tailed Boa in this study carried the University of Giessen virus (UGV-1) S or S6 (UGV/S6) segment and L genotype 7. The prevalence of the UGV/S6 genotype, in line with prior research findings, implies that this genotype may possess specific advantageous characteristics or adaptations that give it a competitive edge over other genotypes in the host population. This research underscores the importance of monitoring and characterizing viral pathogens in captive and wild snake populations. Knowledge of such viruses is crucial for the development of effective diagnostic methods, potential intervention strategies, and the conservation of vulnerable reptilian species. Additionally, our study provides valuable insights for future studies focusing on the evolutionary history, molecular epidemiology, and biological properties of reptarenaviruses in boas and other snake species.
Journal Article
Jimmy's boa and the big splash birthday bash
Jimmy's birthday party at SeaLand turns out to be a big splash when everyone ends up in the big tank.
Book
Solar photovoltaic converter controller using opposition-based reinforcement learning with butterfly optimization algorithm under partial shading conditions
The major use of a power point tracking controller is to maximize or enhance the power generation in photovoltaic systems. These systems are steered to operate and maximize the power point. Under partial shading conditions, the power points may vary or fluctuate between global maxima and local maxima. This fluctuation leads to a decrease in energy or energy loss. Hence, to address the fluctuation issue and its variations, a new hybridized maximum power point tracking technique based on an opposition-based reinforcement learning approach with a butterfly optimization algorithm has been proposed. The proposed methodology has been tested on 6S, 3S2P and 2S3P photo-voltaic configurations under different shading conditions. Performance comparison and analysis have been presented with a butterfly optimization algorithm, grey wolf optimization algorithm, whale optimization algorithm, and particle swarm optimization-based maximum power point tracking techniques. Experimental results show that the proposed method performs better adaptation than the conventional approaches and mitigates the load variation convergence and frequent exploration and exploitation patterns.
Journal Article
Wally wants to hug
Wally is a young boa constrictor who loves hugs, but his classmates at school are scared of getting hugs from him, so Wally shows them his friendly hugs are nothing to be afraid of.
Book
A Chaotic Hybrid Butterfly Optimization Algorithm with Particle Swarm Optimization for High-Dimensional Optimization Problems
In order to solve the problem that the butterfly optimization algorithm (BOA) is prone to low accuracy and slow convergence, the trend of study is to hybridize two or more algorithms to obtain a superior solution in the field of optimization problems. A novel hybrid algorithm is proposed, namely HPSOBOA, and three methods are introduced to improve the basic BOA. Therefore, the initialization of BOA using a cubic one-dimensional map is introduced, and a nonlinear parameter control strategy is also performed. In addition, the particle swarm optimization (PSO) algorithm is hybridized with BOA in order to improve the basic BOA for global optimization. There are two experiments (including 26 well-known benchmark functions) that were conducted to verify the effectiveness of the proposed algorithm. The comparison results of experiments show that the hybrid HPSOBOA converges quickly and has better stability in numerical optimization problems with a high dimension compared with the PSO, BOA, and other kinds of well-known swarm optimization algorithms.
Journal Article