Energy-efficient Compressive Data Gathering Utilizing Virtual Multi-input Multi-output

Data gathering is an attractive operation for obtaining information in wireless sensor networks (WSNs). But one of important challenges is to minimize energy consumption of networks. In this paper, an integration of distributed compressive sensing (CS) and virtual multi-input multi-output (vMIMO) in WSNs is proposed to significantly decrease the data gathering cost. The scheme first constructs a distributed data compression model based on low density parity check-like (LDPC-like) codes. Then a cluster-based dynamic virtual MIMO transmission protocol is proposed. The number of clusters, number of cooperative nodes and the constellation size are determined by a new established optimization model under the restrictions of compression model. Finally, simulation results show that the scheme can reduce the data gathering cost and prolong the sensor network’s lifetime in a reliable guarantee of sensory data recovery quality

NARROW BAND PEROVSKITE SINGLE CRYSTAL PHOTODETECTORS WITH TUNABLE SPECTRAL RESPONSE

Photoelectronic devices using perovskite single-crystal materials having a narrow spectral response, e.g., with a full-width-at-half-maximum response of less than about 20 nm, are provided. The response spectra are continuously (in frequency band) settable or tunable, e.g., from blue to red, by changing the halide composition and thus the band gap of the single crystals. The narrow-band response can be explained by the strong surface charge recombination of the excess carriers lose to the crystal surfaces generated by short wavelength light. The excess carriers generated by below-band gap excitation locate away from the surfaces and can be much more efficiently collect by the electrodes to produce a photocurrent

Classical Keggin intercalated into layered double hydroxides: facile preparation and catalytic efficiency in Knoevenagel condensation reaction

The family of polyoxometalate (POM) intercalated layered double hydroxides (LDHs) composite materials has shown great promise for the design of functional materials with numerous applications. It is known that intercalation of the classical Keggin polyoxometalate (POM) of [PW12O40]3- (PW12) into layered double hydroxides (LDHs) is very unlikely to take place by conventional ion exchange methods due to spatial and geometrical restrictions. In this paper, such intercalated compound of Mg0.73Al0.22(OH)2 [PW12O40]0.04•0.98H2O (Mg3Al-PW12) has been successfully obtained by adopting a spontaneous flocculation method. The Mg3Al-PW12 has been fully characterized using a wide range of methods (XRD, SEM, TEM, XPS, EDX, XPS, FT-IR, NMR, BET). XRD patterns of Mg3Al-PW12 exhibit no impurity phase usually observed next to the (003) diffraction peak. Subsequent application of the Mg3Al-PW12 as catalyst in Knoevenagel condensation reactions of various aldehydes and ketones with Z–CH2-Z‘ type substrates (ethyl-cyanoacetate and malononitrile) at 60 oC in mixed solvents (Vi-propanol:Vwater = 2 : 1) demonstrated highly efficient catalytic activity. The synergistic effect between the acidic and basic sites of the Mg3Al-PW12 composite proved to be crucial for the efficiency of the condensation reactions. Additionally, the Mg3Al-PW12 catalysed Knoevenagel condensation of benzaldehyde with ethyl cyanoacetate demonstrated the highest turnover number (TON) of 47980 reported so far

Leader-following consensus for lower-triangular nonlinear multi-agent systems with unknown controller and measurement sensitivities

summary:In this paper, a novel consensus algorithm is presented to handle with the leader-following consensus problem for lower-triangular nonlinear MASs (multi-agent systems) with unknown controller and measurement sensitivities under a given undirected topology. As distinguished from the existing results, the proposed consensus algorithm can tolerate to a relative wide range of controller and measurement sensitivities. We present some important matrix inequalities, especially a class of matrix inequalities with multiplicative noises. Based on these results and a dual-domination gain method, the output consensus error with unknown measurement noises can be used to construct the compensator for each follower directly. Then, a new distributed output feedback control is designed to enable the MASs to reach consensus in the presence of large controller perturbations. In view of a Lyapunov function, sufficient conditions are presented to guarantee that the states of the leader and followers can achieve consensus asymptotically. In the end, the proposed consensus algorithm is tested and verified by an illustrative example

Rising grain prices in response to phased climatic change during 1736-1850 in the North China Plain

Grain price volatility during historical periods is regarded as an important indicator of the impact of climate change on economic system, as well as a key link to adjust food security and social stability. The present study used the wheat prices in Baoding Prefecture, China, during 1736-1850 to explore connections between climatic transition and grain price anomalies in the North China Plain. The main findings were as follows: (1) The grain price change showed an apparent correspondence with climatic transition. The period 1781-1820 was a transition phase, with more extremes and decreased precipitations when the climate shifted from a warm phase to a cold one. Corresponding with the climatic transition, the grain price during 1781-1820 was characterized by that the mean of the original grain price series was significantly higher (lower) than the previous (later) phase, and the variance and anomaly amplitude of the detrended grain price series was the highest during 1736-1850. (2) The correspondence between grain price extremes and drought events occurred in phases. Five grain price extremes occurred following drought events during 1781-1810, while extreme droughts were the direct cause of the grain price spike during 1811-1820. (3) Social stability affected by climate change also played an important role in the grain price spike between 1811 and 1820. Paralleling the pathway of "precipitation-grain production-grain price", climate change could have an impact on grain price via the pathway of "precipitation-grain production-grain price-famine-uprising-grain price", as shown during the Tianli Uprising in 1813. These findings could contribute to an improved understanding of the interaction between climate change and human society during the historical period.Peer reviewe

Dynamic Environmental/Economic Scheduling for Microgrid Using Improved MOEA/D-M2M

The environmental/economic dynamic scheduling for microgrids (MGs) is a complex multiobjective optimization problem, which usually has dynamic system parameters and constraints. In this paper, a biobjective optimization model of MG scheduling is established. And various types of microsources (like the conventional sources, various types of renewable sources, etc.), electricity markets, and dynamic constraints are considered. A recently proposed MOEA/D-M2M framework is improved (I-MOEA/D-M2M) to solve the real-world MG scheduling problems. In order to deal with the constraints, the processes of solutions sorting and selecting in the original MOEA/D-M2M are revised. In addition, a self-adaptive decomposition strategy and a modified allocation method of individuals are introduced to enhance the capability of dealing with uncertainties, as well as reduce unnecessary computational work in practice and meet the time requirements for the dynamic optimization tasks. Thereafter, the proposed I-MOEA/D-M2M is applied to the independent MG scheduling problems, taking into account the load demand variation and the electricity price changes. The simulation results by MATLAB show that the proposed method can achieve better distributed fronts in much less running time than the typical multiobjective evolutionary algorithms (MOEAs) like the improved strength Pareto evolutionary algorithm (SPEA2) and the nondominated sorting genetic algorithm II (NSGAII). Finally, I-MOEA/D-M2M is used to solve a 24-hour MG dynamic operation scheduling problem and obtains satisfactory results

Improving the sensitivity of a near-infrared nanocomposite photodetector by enhancing trap induced hole injection

We report the enhancement of the photoconductive gain of nanocomposite near-infrared photodetectors by a zinc oxide nanoparticles (ZnO NPs) rich surface at the nanocomposite/cathode interface. An argon plasma etching process was used to remove polymer at the surface of nanocomposite films, which resulted in a ZnO NPs rich surface. The other way is to spin-coat a thin layer of ZnO NPs onto the nanocomposite layer. The ZnO NPs rich surface, which acts as electron traps to induce secondary hole injection under reverse bias, increased hole injection, and thus the external quantum efficiency by 2–3 times. The darkcurrent declined one order of magnitude simultaneously as a result of etching the top nanocomposite layer. The specific detectivity at 800 nm was increased by 7.4 times to 1.11x1010 Jones due to the simultaneously suppressed noise and enhanced gain

Improving the sensitivity of a near-infrared nanocomposite photodetector by enhancing trap induced hole injection

We report the enhancement of the photoconductive gain of nanocomposite near-infrared photodetectors by a zinc oxide nanoparticles (ZnO NPs) rich surface at the nanocomposite/cathode interface. An argon plasma etching process was used to remove polymer at the surface of nanocomposite films, which resulted in a ZnO NPs rich surface. The other way is to spin-coat a thin layer of ZnO NPs onto the nanocomposite layer. The ZnO NPs rich surface, which acts as electron traps to induce secondary hole injection under reverse bias, increased hole injection, and thus the external quantum efficiency by 2–3 times. The darkcurrent declined one order of magnitude simultaneously as a result of etching the top nanocomposite layer. The specific detectivity at 800 nm was increased by 7.4 times to 1.11x1010 Jones due to the simultaneously suppressed noise and enhanced gain