The main objective of this paper is to investigate the effects of routing protocols on wireless sensor and actuator networks (WSANs), focusing on the control system response and the energy consumption of nodes in a network. We demonstrate that routing algorithms designed without considering the relationship between communication and control cannot be appropriately used in wireless networked control applications. For this purpose, an ad-hoc on-demand distance vector (AODV) routing, an IEEE 802.15.4, and a building-temperature control system are employed for this exploration. The findings from our scenarios show that the AODV routing can select a path with a high traffic load for data transmission. It takes a long time before deciding to change a new route although it experiences the unsuccessful transmission of packets. As a result, the desirable control target cannot be achieved in time, and nodes consume more energy due to frequent packet collisions and retransmissions. Consequently, we propose a simple routing solution to alleviate these research problems by modifying the original AODV routing protocol. The delay-threshold is considered to avoid any congested connection during routing procedures. The simulation results demonstrate that our solution can be appropriately applied in WSANs. Both the energy consumption and the control system response are improved.
The development of outgrowths from plant shoots depends on formation of epidermal sites of cell polarity convergence with high intracellular auxin at their centre. A parsimonious model for generation of convergence sites is that cell polarity for the auxin transporter PIN1 orients up auxin gradients, as this spontaneously generates convergent alignments. Here we test predictions of this and other models for the patterns of auxin biosynthesis and import. Live imaging of outgrowths from kanadi1 kanadi2 Arabidopsis mutant leaves shows that they arise by formation of PIN1 convergence sites within a proximodistal polarity field. PIN1 polarities are oriented away from regions of high auxin biosynthesis enzyme expression, and towards regions of high auxin importer expression. Both expression patterns are required for normal outgrowth emergence, and may form part of a common module underlying shoot outgrowths. These findings are more consistent with models that spontaneously generate tandem rather than convergent alignments.
The problems of the neural network-based nonuniformity correction algorithm for infrared focal plane arrays mainly concern slow convergence speed and ghosting artifacts. In general, the more stringent the inhibition of ghosting, the slower the convergence speed. The factors that affect these two problems are the estimated desired image and the learning rate. In this paper, we propose a learning rate rule that combines adaptive threshold edge detection and a temporal gate. Through the noise estimation algorithm, the adaptive spatial threshold is related to the residual nonuniformity noise in the corrected image. The proposed learning rate is used to effectively and stably suppress ghosting artifacts without slowing down the convergence speed. The performance of the proposed technique was thoroughly studied with infrared image sequences with both simulated nonuniformity and real nonuniformity. The results show that the deghosting performance of the proposed method is superior to that of other neural network-based nonuniformity correction algorithms and that the convergence speed is equivalent to the tested deghosting methods.
- Proceedings of the National Academy of Sciences of the United States of America
- Published about 6 years ago
There is a rising concern regarding the accumulation of floating plastic debris in the open ocean. However, the magnitude and the fate of this pollution are still open questions. Using data from the Malaspina 2010 circumnavigation, regional surveys, and previously published reports, we show a worldwide distribution of plastic on the surface of the open ocean, mostly accumulating in the convergence zones of each of the five subtropical gyres with comparable density. However, the global load of plastic on the open ocean surface was estimated to be on the order of tens of thousands of tons, far less than expected. Our observations of the size distribution of floating plastic debris point at important size-selective sinks removing millimeter-sized fragments of floating plastic on a large scale. This sink may involve a combination of fast nano-fragmentation of the microplastic into particles of microns or smaller, their transference to the ocean interior by food webs and ballasting processes, and processes yet to be discovered. Resolving the fate of the missing plastic debris is of fundamental importance to determine the nature and significance of the impacts of plastic pollution in the ocean.
- Proceedings of the National Academy of Sciences of the United States of America
- Published over 2 years ago
Floating oil, plastics, and marine organisms are continually redistributed by ocean surface currents. Prediction of their resulting distribution on the surface is a fundamental, long-standing, and practically important problem. The dominant paradigm is dispersion within the dynamical context of a nondivergent flow: objects initially close together will on average spread apart but the area of surface patches of material does not change. Although this paradigm is likely valid at mesoscales, larger than 100 km in horizontal scale, recent theoretical studies of submesoscales (less than ∼10 km) predict strong surface convergences and downwelling associated with horizontal density fronts and cyclonic vortices. Here we show that such structures can dramatically concentrate floating material. More than half of an array of ∼200 surface drifters covering ∼20 × 20 km2 converged into a 60 × 60 m region within a week, a factor of more than 105 decrease in area, before slowly dispersing. As predicted, the convergence occurred at density fronts and with cyclonic vorticity. A zipperlike structure may play an important role. Cyclonic vorticity and vertical velocity reached 0.001 s-1 and 0.01 ms-1, respectively, which is much larger than usually inferred. This suggests a paradigm in which nearby objects form submesoscale clusters, and these clusters then spread apart. Together, these effects set both the overall extent and the finescale texture of a patch of floating material. Material concentrated at submesoscale convergences can create unique communities of organisms, amplify impacts of toxic material, and create opportunities to more efficiently recover such material.
- IEEE transactions on pattern analysis and machine intelligence
- Published almost 5 years ago
In recent years, sparse coding has been widely used in many applications ranging from image processing to pattern recognition. Most existing sparse coding based applications require solving a class of challenging non-smooth and non-convex optimization problems. Despite the fact that many numerical methods have been developed for solving these problems, it remains an open problem to find a numerical method which is not only empirically fast, but also has mathematically guaranteed strong convergence. In this paper, we propose an alternating iteration scheme for solving such problems. A rigorous convergence analysis shows that the proposed method satisfies the global convergence property: the whole sequence of iterates is convergent and converges to a critical point. Besides the theoretical soundness, the practical benefit of the proposed method is validated in applications including image restoration and recognition. Experiments show that the proposed method achieves similar results with less computation when compared to widely used methods such as K-SVD.
Existing evidence suggests that in social contexts individuals become coupled in their emotions and behaviors. Furthermore, recent biological studies demonstrate that the physiological signals of interacting individuals become coupled as well, exhibiting temporally synchronized response patterns. However, it is yet unknown whether people can shape each other’s responses without the direct, face-to-face interaction. Here we investigated whether the convergence of physiological and emotional states can occur among “merely co-present” individuals, without direct interactional exchanges. To this end, we measured continuous autonomic signals and collected emotional responses of participants who watched emotional movies together, seated side-by-side. We found that the autonomic signals of co-present participants were idiosyncratically synchronized and that the degree of this synchronization was correlated with the convergence of their emotional responses. These findings suggest that moment-to-moment emotional transmissions, resulting in shared emotional experiences, can occur in the absence of direct communication and are mediated by autonomic synchronization.
Convergent evolution provides insight into the link between phenotype and genotype. Recently, large-scale comparative studies of convergent evolution have become possible, but researchers are still trying to determine the best way to design these types of analyses. One aspect of molecular convergence studies that has not yet been investigated is how taxonomic sample size affects inferences of molecular convergence. Here we show that increased sample size decreases the amount of inferred molecular convergence associated with the three convergent transitions to a marine environment in mammals. The sampling of more taxa-both with and without the convergent phenotype-reveals that alleles associated only with marine mammals in small datasets are actually more widespread, or are not shared by all marine species. The sampling of more taxa also allows finer resolution of ancestral substitutions, revealing that they are not in fact on lineages leading to solely marine species. We revisit a previous study on marine mammals and find that only 7 of the reported 43 genes with convergent substitutions still show signs of convergence with a larger number of background species. However, 4 of those 7 genes also showed signs of positive selection in the original analysis and may still be good candidates for adaptive convergence. Though our study is framed around the convergence of marine mammals, we expect our conclusions on taxonomic sampling are generalizable to any study of molecular convergence.
The lateral habenula (LHb) is a brain structure that participates in cognitive and emotional processing and has been implicated in several mental disorders. Although one of the largest inputs to the LHb originates in the lateral preoptic area (LPO), little is known about how the LPO participates in the regulation of LHb function. Here, we provide evidence that the LPO exerts bivalent control over the LHb through the convergent transmission of LPO glutamate and γ-aminobutyric acid (GABA) onto single LHb neurons. In vivo, both LPO-glutamatergic and LPO-GABAergic inputs to the LHb are activated by aversive stimuli, and their predictive cues yet produce opposing behaviors when stimulated independently. These results support a model wherein the balanced response of converging LPO-glutamate and LPO-GABA are necessary for a normal response to noxious stimuli, and an imbalance in LPO→LHb glutamate or GABA results in the type of aberrant processing that may underlie mental disorders.
Because of the remarkable developments in robotics in recent years, technological convergence has been active in this area. We focused on finding patterns of convergence within robot technology using network analysis of patents in both the USPTO and KIPO. To identify the variables that affect convergence, we used quadratic assignment procedures (QAP). From our analysis, we observed the patent network ecology related to convergence and found technologies that have great potential to converge with other robotics technologies. The results of our study are expected to contribute to setting up convergence based R&D policies for robotics, which can lead new innovation.