399 research outputs found
An Energy-Efficient MAC Protocol Using Dynamic Queue Management for Delay-Tolerant Mobile Sensor Networks
Conventional MAC protocols for wireless sensor network perform poorly when faced with a delay-tolerant mobile network environment. Characterized by a highly dynamic and sparse topology, poor network connectivity as well as data delay-tolerance, delay-tolerant mobile sensor networks exacerbate the severe power constraints and memory limitations of nodes. This paper proposes an energy-efficient MAC protocol using dynamic queue management (EQ-MAC) for power saving and data queue management. Via data transfers initiated by the target sink and the use of a dynamic queue management strategy based on priority, EQ-MAC effectively avoids untargeted transfers, increases the chance of successful data transmission, and makes useful data reach the target terminal in a timely manner. Experimental results show that EQ-MAC has high energy efficiency in comparison with a conventional MAC protocol. It also achieves a 46% decrease in packet drop probability, 79% increase in system throughput, and 25% decrease in mean packet delay
Methylmercury uptake and degradation by methanotrophs
Methylmercury (CH3Hg+) is a potent neurotoxin produced by certain anaerobic microorganisms in natural environments. Although numerous studies have characterized the basis of mercury (Hg) methylation, no studies have examined CH3Hg+ degradation by methanotrophs, despite their ubiquitous presence in the environment. We report that some methanotrophs, such as Methylosinus trichosporium OB3b, can take up and degrade CH3Hg+ rapidly, whereas others, such as Methylococcus capsulatus Bath, can take up but not degrade CH3Hg+. Demethylation by M. trichosporium OB3b increases with increasing CH3Hg+ concentrations but was abolished in mutants deficient in the synthesis of methanobactin, a metal-binding compound used by some methanotrophs, such as M. trichosporium OB3b. Furthermore, addition of methanol (>5 mM) as a competing one-carbon (C1) substrate inhibits demethylation, suggesting that CH3Hg+ degradation by methanotrophs may involve an initial bonding of CH3Hg+ by methanobactin followed by cleavage of the CâHg bond in CH3Hg+ by the methanol dehydrogenase. This new demethylation pathway by methanotrophs indicates possible broader involvement of C1-metabolizing aerobes in the degradation and cycling of toxic CH3Hg+ in the environment
Population genetics of foxtail millet and its wild ancestor
<p>Abstract</p> <p>Background</p> <p>Foxtail millet (<it>Setaria italica </it>(L.) P. Beauv.), one of the most ancient domesticated crops, is becoming a model system for studying biofuel crops and comparative genomics in the grasses. However, knowledge on the level of genetic diversity and linkage disequilibrium (LD) is very limited in this crop and its wild ancestor, green foxtail (<it>Setaria viridis </it>(L.) P. Beauv.). Such information would help us to understand the domestication process of cultivated species and will allow further research in these species, including association mapping and identification of agricultural significant genes involved in domestication.</p> <p>Results</p> <p>In this study, we surveyed DNA sequence for nine loci across 50 accessions of cultivated foxtail millet and 34 of its wild progenitor. We found a low level of genetic diversity in wild green foxtail (θ = 0.0059), θ means Watterson's estimator of θ. Despite of a 55% loss of its wild diversity, foxtail millet still harbored a considerable level of diversity (θ = 0.0027) when compared to rice and sorghum (θ = 0.0024 and 0.0034, respectively). The level of LD in the domesticated foxtail millet extends to 1 kb, while it decayed rapidly to a negligible level within 150 bp in wild green foxtail. Using coalescent simulation, we estimated the bottleneck severity at k = 0.6095 when Ď/θ = 1. These results indicated that the domestication bottleneck of foxtail millet was more severe than that of maize but slightly less pronounced than that of rice.</p> <p>Conclusions</p> <p>The results in this study establish a general framework for the domestication history of foxtail millet. The low level of genetic diversity and the increased level of LD in foxtail millet are mainly caused by a population bottleneck, although gene flow from foxtail millet to green foxtail is another factor that may have shaped the pattern of genetic diversity of these two related gene pools. The knowledge provided in this study will benefit future population based studies in foxtail millet.</p
Environmental Stress Responses of DnaJA1, DnaJB12 and DnaJC8 in Apis cerana cerana
DnaJ, also known as Hsp40, plays important roles in maintaining the normal physiological state of an organism under stress conditions by mediating essential processes, such as protein synthesis, degradation, folding and metabolism. However, the exact functions of most DnaJ members are not fully understood in insects. Here, we identified three genes, AccDnaJA1, AccDnaJB12, and AccDnaJC8, in Apis cerana cerana and explored their connection with the environmental stress response. Quantitative real-time PCR results showed that the mRNA levels of AccDnaJA1, AccDnaJB12, and AccDnaJC8 were all induced under cold, UV, H2O2 and different pesticides treatment. The expression patterns of AccDnaJB12 and AccDnaJC8 were upregulated by CdCl2 and HgCl2 stress, while the transcriptional levels of AccDnaJA1 were downregulated by CdCl2 and HgCl2 stress. Western blot findings further indicated that AccDnaJB12 protein levels were increased by some stress conditions. Knockdown of each of these three genes downregulated the transcriptional patterns of several stress response-related genes at different levels. Functional analysis further demonstrated that the resistance of A. cerana cerana to lambda-cyhalothrin stress was reduced with knockdown of AccDnaJA1, AccDnaJB12, or AccDnaJC8, indicating that these three genes may be involved in the tolerance to this pesticide. Taken together, these findings indicate that AccDnaJA1, AccDnaJB12, and AccDnaJC8 may play pivotal roles in the stress response by facilitating honeybee survival under some adverse circumstances. To our knowledge, this is the first report that reveals the roles of DnaJ family proteins under different adverse circumstances in A. cerana cerana
Purification, Characterization and Inhibition of Alanine Racemase from a Pathogenic Strain of Streptococcus iniae
Prediction of the shear wave speed of seafloor sediments in the northern South China Sea based on an XGBoost algorithm
Based on data on the shear wave speed and physical properties of the shallow sediment samples collected in the northwest South China Sea, the hyperparameter selection and contribution of the characteristic factors of the machine learning model for predicting the shear wave speed of seafloor sediments were studied using the eXtreme Gradient Boosting (XGBoost) algorithm. An XGBoost model for predicting the shear wave speed of seafloor sediments was established based on four physical parameters of the sediments: porosity (n), water content (w), density (Ď), and average grain size (MZ). The result reveals that: (1) The shear wave speed has a good correlation with n, w, Ď, and MZ, and their Pearson correlation coefficients are all above 0.75, indicating that they can be used as the suitable characteristic parameters for predicting the shear wave speed based on the XGBoost model; (2) When the number of weak learners (n_estimators) is 115 and the maximum depth of the tree (max_depth) is 6, the XGBoost model has a very high goodness of fit (R2) of the validation data of 0.914, the very low mean absolute error (MAE) and mean absolute percentage error (MAPE) of the predicted shear wave speed are 3.366 m/s and 9.90%, respectively; (3) Compared with grain-shearing (GS) model and single- and dual-parameter regression equation prediction models, the XGBoost model for the shear wave speed of seafloor sediments has higher fitting goodness and lower prediction error
Generation of sheep with defined FecBB and TBXT mutations and porcine blastocysts with KCNJ5G151R/+ mutation using prime editing
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