379 research outputs found
Global synchronization control of general delayed discrete-time networks with stochastic coupling and disturbances
No full textCopyright [2008] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected].
By choosing to view this document, you agree to all provisions of the copyright laws protecting it.In this paper, the synchronization control problem is considered for two coupled discrete-time complex networks with time delays. The network under investigation is quite general to reflect the reality, where the state delays are allowed to be time varying with given lower and upper bounds, and the stochastic disturbances are assumed to be Brownian motions that affect not only the network coupling but also the overall networks. By utilizing the Lyapunov functional method combined with linear matrix inequality (LMI) techniques, we obtain several sufficient delay-dependent conditions that ensure the coupled networks to be globally exponentially synchronized in the mean square. A control law is designed to synchronize the addressed coupled complex networks in terms of certain LMIs that can be readily solved using the Matlab LMI toolbox. Two numerical examples are presented to show the validity of our theoretical analysis results.This work was supported by the Royal Society Sino-British Fellowship Trust Award of the
U.K
Regulation of gene expression and intestinal calcium absorption: Role of CAT1, calbindin D9k, and VDR
No full textTranscellular calcium (Ca) absorption is primarily regulated by genomic action of 1,25(OH)2 D3 through vitamin D receptor (VDR). In an attempt to better understand the molecular mechanisms of transcellular Ca absorption, we investigated the role of CaT1, calbindin D9k and VDR in the process of Ca absorption in mouse. We found that duodenal CaT1 mRNA is very responsive to the changes in serum 1,25(OH)2 D3 caused by diet and 1,25(OH)2 D3 injection. Coordinate regulation of duodenal CaT1, calbindin D9k, and Ca absorption in response to short-term changes of dietary Ca, and rapid induction of CaT1 preceeding Ca absorption after 1,25(OH)2 D3 injection suggest an essential role for 1,25(OH)2 D3-mediated expression of CaT1 in Ca absorption. However, in VDR knockout (KO) mice on a 2.0% Ca diet, Ca absorption was increased by 13% while CaT1 mRNA was \u3c1% of the levels seen in WT fed a 0.5% Ca diet. Our data suggest that it is not likely that CaT1 is a rate-limiting determinant in Ca absorption. Calbindin D9k has been proposed to function as a ferry to facilitate the diffusion of Ca in the cytosol. In KO mice fed a 0.5% Ca diet, we did not see high Ca absorption based on their relative high calbindin D9k protein. Moreover, with 1,25(OH)2 D3 injection, Ca absorption proceeded the induction of calbindin D9k mRNA. Our data does not support the role of calbindin D9k as a rate-limiting determinant in intestinal Ca absorption. However, it does not eliminate the possibility that this protein acts as an intracellular buffer to prevent the cytotoxicity during active Ca absorption. Reduced VDR levels have been proposed to be responsible for intestinal resistance to 1,25(OH)2 D3 in aging. Compared to VDR heterozygous (VDR +/−) mice containing 50% of VDR protein, we found the slope of the relationship between Ca absorption and circulating 1,25(OH)2 D3 was steeper in normal mice, suggesting blunt responsiveness of intestine in VDR +/− mice. Our data support the hypothesis that reduced VDR levels account for the intestinal resistance to 1,25(OH)2 D3
On the clustering extreme precipitation events over the Indo-Pacific rim and its relationship to Rossby waves
No full textClustering extreme weather events are consecutive occurrences of disastrous weather in multiple regions. As the climate continues to warm up, cluster occurrence is becoming a prevailing feature of extreme weather events and leading to cumulative impacts. Understanding the associated atmospheric teleconnection patterns and their underlying mechanisms can help quantify their risk, i.e., the probability of occurrence and severity of cluster extremes in the future. In this study, over 400 clustering extreme precipitation events over South Asia, East Asia, and North America in the past 42 years are identified, and they show a significant increasing trend. This trend can be largely attributable to the increasing frequency of the Rossby wave response, including the circum-Pacific and cross-Pacific patterns due to Rossby wave activity propagation, and the Pacific anticyclone pattern due to Rossby wave breaking. The three patterns show remarkable disparity in seasonality, persistence, and hydrological impacts. They can increase the probability of most severe precipitation by up to 5, 8, and 25 times, respectively. The key driving mechanisms behind these wave patterns are as follows: 1) tropical latent heat anomaly during the Boreal Summer Intraseasonal Oscillation (BSISO) period serves as a first-order driving mechanism for the Rossby wave propagation to higher latitudes. In particular, the "wet India-dry Philippines" dipole heating anomaly can make the Rossby wave train more northeastward compared to the simply wet India condition. 2) The sea surface temperature (SST) anomaly over the Pacific will affect the atmospheric mean state to influence the Rossby wave pattern. 3) The propagation of the Rossby wave patterns in mid-latitude is modulate by the variation of the jet streams. Our findings suggest that specific Rossby wave patterns may influence the potential evolution of future clustering extrees.</p
Cooperation in the sphere of regional security strengthening – priority task of SCO
No full textThe author insists that cooperation in the sphere of security remains the main task of SCO. The achievements of recent 10 years as well as new threats and challenges for security are considered, the author argues for necessity to provide common for all members of SCO legal basis for further approaches to security issues in the region of Central Asia
Deep learning bird song recognition based on MFF-ScSEnet
No full textBird diversity plays an important role in ecological balance, and bird song identification is of great practical significance. The spectrum generated by feature extraction shows good performance on classification. However, the information extracted by the filter in the process of spectrogram generation can cause information loss, which limits the learning ability of birdsong recognition. This study proposes a feature fusion network (MFF-ScSEnet) to solve this problem. The audios of the birdsong extracted the Mel-spectrogram with low-frequency feature advantage by the Mel-filter, and the Sinc-spectrogram with timbral feature advantage by the Sincnet-filter, respectively, and perform the early fusion strategy. The ScSEnet attention module is introduced into the backbone network ResNet18 to enhance the sound ripple information of the spectrogram, reduce the influence of spectrogram noise information on the recognition and improve the recognition performance of the network. Based on the feature fusion network MFF-ScSEnet in this paper, the accuracy of the experimental results on the self-built birdsong dataset (Huabei_dataset), the public datasets of Urbansound8K and Birdsdata reached 96.28%, 98.34%, and 96.66%, respectively. The results indicated that the method proposed in this paper is superior to the recent and latest birdsong recognition method
Stability and synchronization of discrete-time Markovian jumping neural networks with mixed mode-dependent time delays
No full textCopyright [2009] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.In this paper, we introduce a new class of discrete-time neural networks (DNNs) with Markovian jumping parameters as well as mode-dependent mixed time delays (both discrete and distributed time delays). Specifically, the parameters of the DNNs are subject to the switching from one to another at different times according to a Markov chain, and the mixed time delays consist of both discrete and distributed delays that are dependent on the Markovian jumping mode. We first deal with the stability analysis problem of the addressed neural networks. A special inequality is developed to account for the mixed time delays in the discrete-time setting, and a novel Lyapunov-Krasovskii functional is put forward to reflect the mode-dependent time delays. Sufficient conditions are established in terms of linear matrix inequalities (LMIs) that guarantee the stochastic stability. We then turn to the synchronization problem among an array of identical coupled Markovian jumping neural networks with mixed mode-dependent time delays. By utilizing the Lyapunov stability theory and the Kronecker product, it is shown that the addressed synchronization problem is solvable if several LMIs are feasible. Hence, different from the commonly used matrix norm theories (such as the M-matrix method), a unified LMI approach is developed to solve the stability analysis and synchronization problems of the class of neural networks under investigation, where the LMIs can be easily solved by using the available Matlab LMI toolbox. Two numerical examples are presented to illustrate the usefulness and effectiveness of the main results obtained
The Model of Malware Propagation in Wireless Sensor Networks with Regional Detection Mechanism
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