Controller design for synchronization of an array of delayed neural networks using a controllable

This is the post-print version of the Article - Copyright @ 2011 ElsevierIn this paper, a controllable probabilistic particle swarm optimization (CPPSO) algorithm is introduced based on Bernoulli stochastic variables and a competitive penalized method. The CPPSO algorithm is proposed to solve optimization problems and is then applied to design the memoryless feedback controller, which is used in the synchronization of an array of delayed neural networks (DNNs). The learning strategies occur in a random way governed by Bernoulli stochastic variables. The expectations of Bernoulli stochastic variables are automatically updated by the search environment. The proposed method not only keeps the diversity of the swarm, but also maintains the rapid convergence of the CPPSO algorithm according to the competitive penalized mechanism. In addition, the convergence rate is improved because the inertia weight of each particle is automatically computed according to the feedback of fitness value. The efficiency of the proposed CPPSO algorithm is demonstrated by comparing it with some well-known PSO algorithms on benchmark test functions with and without rotations. In the end, the proposed CPPSO algorithm is used to design the controller for the synchronization of an array of continuous-time delayed neural networks.This research was partially supported by the National Natural Science Foundation of PR China (Grant No 60874113), the Research Fund for the Doctoral Program of Higher Education (Grant No 200802550007), the Key Creative Project of Shanghai Education Community (Grant No 09ZZ66), the Key Foundation Project of Shanghai(Grant No 09JC1400700), the Engineering and Physical Sciences Research Council EPSRC of the U.K. under Grant No. GR/S27658/01, an International Joint Project sponsored by the Royal Society of the U.K., and the Alexander von Humboldt Foundation of Germany

Using canopy greenness index to identify leaf ecophysiological traits during the foliar senescence in an oak forest

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ecosphere 9 (2018): e02337, doi:10.1002/ecs2.2337.Camera‐based observation of forest canopies allows for low‐cost, continuous, high temporal‐spatial resolutions of plant phenology and seasonality of functional traits. In this study, we extracted canopy color index (green chromatic coordinate, Gcc) from the time‐series canopy images provided by a digital camera in a deciduous forest in Massachusetts, USA. We also measured leaf‐level photosynthetic activities and leaf area index (LAI) development in the field during the growing season, and corresponding leaf chlorophyll concentrations in the laboratory. We used the Bayesian change point (BCP) approach to analyze Gcc. Our results showed that (1) the date of starting decline of LAI (DOY 263), defined as the start of senescence, could be mathematically identified from the autumn Gcc pattern by analyzing change points of the Gcc curve, and Gcc is highly correlated with LAI after the first change point when LAI was decreasing (R2 = 0.88, LAI < 2.5 m2/m2); (2) the second change point of Gcc (DOY 289) started a more rapid decline of Gcc when chlorophyll concentration and photosynthesis rates were relatively low (13.4 ± 10.0% and 23.7 ± 13.4% of their maximum values, respectively) and continuously reducing; and (3) the third change point of Gcc (DOY 295) marked the end of growing season, defined by the termination of photosynthetic activities, two weeks earlier than the end of Gcc curve decline. Our results suggested that with the change point analysis, camera‐based phenology observation can effectively quantify the dynamic pattern of the start of senescence (with declining LAI) and the end of senescence (when photosynthetic activities terminated) in the deciduous forest.Priority Academic Program Development of Jiangsu Higher Education Institutions in Discipline of Environmental Science and Engineer in Nanjing Forest University; China Scholarship Council Grant Number: 201506190095; Brown University Seed Funds for International Research Projects on the Environmen

Comparison of phenology estimated from reflectance-based indices and solar-induced chlorophyll fluorescence (SIF) observations in a temperate forest using GPP-based phenology as the standard

© The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Remote Sensing 10 (2018): 932, doi:10.3390/rs10060932.We assessed the performance of reflectance-based vegetation indices and solar-induced chlorophyll fluorescence (SIF) datasets with various spatial and temporal resolutions in monitoring the Gross Primary Production (GPP)-based phenology in a temperate deciduous forest. The reflectance-based indices include the green chromatic coordinate (GCC), field measured and satellite remotely sensed Normalized Difference Vegetation Index (NDVI); and the SIF datasets include ground-based measurement and satellite-based products. We found that, if negative impacts due to coarse spatial and temporal resolutions are effectively reduced, all these data can serve as good indicators of phenological metrics for spring. However, the autumn phenological metrics derived from all reflectance-based datasets are later than the those derived from ground-based GPP estimates (flux sites). This is because the reflectance-based observations estimate phenology by tracking physiological properties including leaf area index (LAI) and leaf chlorophyll content (Chl), which does not reflect instantaneous changes in phenophase transitions, and thus the estimated fall phenological events may be later than GPP-based phenology. In contrast, we found that SIF has a good potential to track seasonal transition of photosynthetic activities in both spring and fall seasons. The advantage of SIF in estimating the GPP-based phenology lies in its inherent link to photosynthesis activities such that SIF can respond quickly to all factors regulating phenological events. Despite uncertainties in phenological metrics estimated from current spaceborne SIF observations due to their coarse spatial and temporal resolutions, dates in middle spring and autumn—the two most important metrics—can still be reasonably estimated from satellite SIF. Our study reveals that SIF provides a better way to monitor GPP-based phenological metrics.This research was supported by U. S. Department of Energy Office of Biological and Environmental Research Grant DE-SC0006951, National Science Foundation Grants DBI 959333 and AGS-1005663, and the University of Chicago and the MBL Lillie Research Innovation Award to Jianwu Tang and China Scholarship Council No. 201506190095 to Z. Liu. Xiaoliang Lu was also supported by the open project grant (LBKF201701) of Key Laboratory of Land Surface Pattern and Simulation, Chinese Academy of Sciences

On the group theoretic structure of a class of quantum dialogue protocols

Intrinsic symmetry of the existing protocols of quantum dialogue are explored. It is shown that if we have a set of mutually orthogonal $n$-qubit states {\normalsize $\{|\phi_{0}>,|\phi_{1}>,....,|\phi_{i}\}$ and a set of $m-qubit$ ($m\leq n$) unitary operators $\{U_{0},U_{2},...,U_{2^{n}-1}\}:U_{i}|\phi_{0}>=|\phi_{i}>$ and $\{U_{0},U_{2},...,U_{2^{n}-1}\}$ forms a group under multiplication then it would be sufficient to construct a quantum dialogue protocol using this set of quantum states and this group of unitary operators}. The sufficiency condition is used to provide a generalized protocol of quantum dialogue. Further the basic concepts of group theory and quantum mechanics are used here to systematically generate several examples of possible groups of unitary operators that may be used for implementation of quantum dialogue. A large number of examples of quantum states that may be used to implement the generalized quantum dialogue protocol using these groups of unitary operators are also obtained. For example, it is shown that GHZ state, GHZ-like state, W state, 4 and 5 qubit Cluster states, Omega state, Brown state, $Q_{4}$ state and $Q_{5}$ state can be used for implementation of quantum dialogue protocol. The security and efficiency of the proposed protocol is appropriately analyzed. It is also shown that if a group of unitary operators and a set of mutually orthogonal states are found to be suitable for quantum dialogue then they can be used to provide solutions of socialist millionaire problem.Comment: 15 page

(3S,4S)-1-Benzyl­pyrrolidine-3,4-diol

In the title compound, C11H15NO2, the pyrrolidine ring adapts a twisted envelope conformation and the two hydroxyl groups are arranged in a trans conformation. The crystal packing is stabilized by inter­molecular O—H⋯N and O—H⋯O hydrogen bonds. A weak C—H⋯π inter­action also occurs

Atomic force microscopy measurement of the Young’s modulus and hardness of single LaB6 nanowires

We have employed the atomic force microscopy based (a) three-point bending and (b) nanoindentation methods to obtain the Young’s modulus and hardness of single La B 6 nanowires. The Young’s modulus, E = 467.1 ± 15.8 GPa , is the same as that of the La B 6 single crystals but larger than the sinteredpolycrystalline La B 6 samples. The nanoindentationhardness of the La B 6 nanowire is H = 70.6 ± 2.1 GPa at an indent depth of 4.6 nm , which is higher than that of the La B 6 single crystals, La B 6 polycrystals, and W metals. A superior resistance against thermal vibration, field modification, and ion bombardment is expected for the La B 6 nanowires as a field-emission point electron source

3D Histogram Based Anomaly Detection for Categorical Sensor Data in Internet of Things

The applications of Internet-of-things (IoT) deploy massive number of sensors to monitor the system and environment. Anomaly detection on streaming sensor data is an important task for IoT maintenance and operation. In real IoT applications, many sensors report categorical values rather than numerical readings. Unfortunately, most existing anomaly detection methods are designed only for numerical sensor data. They cannot be used to monitor the categorical sensor data. In this study, we design and develop a 3D Histogram based Categorical Anomaly Detection (HCAD) solution to monitor categorical sensor data in IoT. HCAD constructs the histogram model by three dimensions: categorical value, event duration, and frequency. The histogram models are used to profile normal working states of IoT devices. HCAD automatically determines the range of normal data and anomaly threshold. It only requires very limit parameter setting and can be applied to a wide variety of different IoT devices. We implement HCAD and integrate it into an online monitoring system. We test the proposed solution on real IoT datasets such as telemetry data from satellite sensors, air quality data from chemical sensors, and transportation data from traffic sensors. The results of extensive experiments show that HCAD achieves higher detecting accuracy and efficiency than state-of-the-art methods

Effect of Miao medicine, Jinwujiangu decoction, on IL- 17/IL-23 inflammatory axis of fibroblast-like synoviocytes in rheumatoid arthritis

Purpose: To explore the influence of the Miao medicine, Jinwujiangu decoction, on the interleukin (IL)- 17/IL-23 inflammatory axis of fibroblast-like synoviocytes (FLS) in rheumatoid arthritis (RA).Methods: Synovial tissue samples were randomly divided into a blank control group, high-dose (0.06mg/mL), medium-dose (0.6mg/mL), and low-dose (6.0mg/mL) groups of Jinwujiangu decoction, a leflunomide group, and a tripterygium glycosides group. Proliferation of RA synovial cells was detected by 3-[4,5-dimethylthiazol-2-yl]-2,5 diphenyl tetrazolium bromide (MTT) assay. Enzyme-linked immunosorbent assay (ELISA) was used to determine the secretion of IL-6, transforming growth factor beta (TGF-β), and IL-17. Real-time polymerase chain reaction was used to evaluate the expression of IL-23R, IL-17R, RAR-related orphan receptor alpha (RORα), RORγt, and signal transducer and activator of transcription (STAT3) mRNA. The protein activities of IL-17R, STAT3 and pSTAT3 were assessed by Western blot assay.Results: Jinwujiangu decoction inhibited the proliferation of RA synovial cells. Treatment with different drug concentrations resulted in downregulation of IL-6, TGF-β, and IL-17 secretion. The expression levels of IL-23R, IL-17R, RORα, RORγt, and STAT3 mRNA in RA-FLS were significantly reduced after intervention with different drugs. Protein expression levels of STAT3, pSTAT3, and IL-17 in the different drug treatment groups were significantly decreased.Conclusion: Jinwujiangu decoction inhibits the secretion of IL-6 and TGF-β in RA-FLS, and intervenes to regulate gene expression of IL-23/IL-17 inflammation axis and suppress immune inflammation. The results of this study provide new evidence for the study of anti-inflammatory mechanism of TCM compound prescription.Keywords: Jinwujiangu decoction, IL-17/IL-23, Fibroblast-like synoviocytes, Rheumatoid arthritis, Ethnomedicin