Deep Spatio-temporal Learning Model for Air Quality Forecasting

In recent years, air pollution has seriously affected people’s production and life, so the air prediction has become a research hotspot in recent years. When analyzing air data, it is found that this type of data has not only temporal correlation, but also spatial correlation. For these temporal and spatial characteristics, this paper studies deep spatio-temporal learning method to global prediction. The purpose is to learn the evolution rule behind the spatio-temporal sequence, and give an estimation for future state. To be specific, we propose two novel forecasting models based on video processing technology: Spatio-temporal Orthogonal Cube model (STOR-cube) and Spatio-temporal Dynamic Advection model (ST-DA), which effectively capture the spatio-temporal correlation and accurately predict the long-term air quality. STOR-cube contains three branches, i.e., a spatial branch for capturing moving objects, a temporal branch for processing motion, and an output branch for coupling the first two mutually orthogonal branches to generate a prediction frame. ST-DA constructs a spatio-temporal reasoning network to learn the characteristics of the spatio-temporal domain, and its impact on the future is explicitly modeled by pixel motion. Experiments results on the real-world datasets demonstrate our proposed approach significantly outperforms the state-of-the-art ones. Moreover, our model can be extended to other spatio-temporal data prediction tasks

Fixed frequency finite-state model predictive control for indirect matrix converters with optimal switching pattern

Finite States Model Predictive Control (MPC) has been recently applied to several converters topologies for the many advantages it can provide such as fast dynamics, multi-target control capabilities, easy implementation on digital control board and capability of including constraints in the control law. However, its variable switching frequency and lower steady state waveform quality, with respect to standard control plus modulator systems, represents a limitation to its applicability. Modulated Model Predictive Control (M²PC) combines all the advantages of the simple concept of MPC together with the fixed switching frequency characteristic of PWM algorithms. In particular this work focuses on the Indirect Matrix Converter (IMC), where the tight coupling between rectifier stage and inverter stage has to be taken into account in the M²PC design. This paper proposes an M²PC solution, suitable for IMC, with an optimal switching pattern to emulate the desired waveform quality features of Space Vector Modulation (SVM). In the optimal pattern, the switching sequences of the rectifier stage and inverter stage are rearranged in order to always achieve zero-current switching on the rectifier stage, thus simplifying its commutation strategy. In addition, the optimal pattern enables M²PC to produce sinusoidal source current, sinusoidal output current and maintain all desirable characteristics of MPC

Impacts of model resolution on simulation of meso-scale eddies in the Northeast Pacific Ocean

The model simulated meso-scale eddies in the Northeast Pacific Ocean, using two models with nominal horizontal resolutions of 1/12° and 1/36° in latitude/longitude (grid spacing of 7.5 km and 2.5 km), respectively, are presented. Compared with the 1/12° model, the 1/36° model obtains (1) similar variance and wavenumber spectra of  the sea level anomaly and water temperature anomaly, and (2) increases in the level of the domain-averaged total kinetic energy, eddy kinetic energy (EKE), and variance of horizontal gradient of water temperature. In the interior basin of the southern region, both models show stronger eddy frontal activities, represented by EKE, temperature and its horizontal gradient, in summer and fall than in winter and spring. The challenge of evaluating the realism of high-resolution ocean models with conventional satellite remote sensing observations is discussed

First Characterization of Sphingomyeline Phosphodiesterase Expression in the Bumblebee, Bombus lantschouensis

  The bumblebee (Bombus lantschouensis Vogt) is an important pollinator of wild plants. Sphingomyelin phosphodiesterase (SMPD) is a hydrolase that plays a major role in sphingolipid metabolism reactions. We report the preparation and characterization of a polyclonal antibody for bumblebee SMPD. We then use the polyclonal antiserum to detect the SMPD protein at different development stages and in different tissues. Our results showed that a 1228bp fragment homologous with the B. terrestris SMPD gene was successfully amplified. The molecular weight of the fusion protein was about 70 kDa by SDS-PAGE. An effective polyclonal antibody against SMPD was also obtained from mice and found to have a higher specificity for bumblebee SMPD. Western blotting detection showed that SMPD was expressed at a high level in queen ovaries, although expression was lower in the midgut and venom gland. SMPD expression decreased from the egg stage until the pdd stage. We interpret our results as showing that the development of an effective polyclonal antiserum for the SMPD protein of a bumblebee, which provides a tool for exploring the function of the SMPD gene. In addition, the work has confirmed that SMPD should be considered as an important enzyme during bumblebee egg and larval stages

Modulated predictive control for indirect matrix converter

Finite State Model Predictive Control (MPC) has been recently applied to several converter topologies as it can provide many advantages over other MPC techniques. The advantages of MPC include fast dynamics, multi-target control capability and relatively easy implementation on digital control platforms. However, its inherent variable switching frequency and lower steady state waveform quality, with respect to standard control which includes an appropriate modulation technique, represent a limitation to its applicability. Modulated Model Predictive Control (M2PC) combines all the advantages of MPC with the fixed switching frequency characteristic of PWM algorithms. The work presented in this paper focuses on the Indirect Matrix Converter (IMC), where the tight coupling between rectifier stage and inverter stage has to be taken into account in the M2PC design. This paper proposes an M2PC solution, suitable for IMC, with a switching pattern which emulates the desired waveform quality features of Space Vector Modulation (SVM) for matrix converters. The switching sequences of the rectifier stage and inverter stage are rearranged in order to always achieve zero-current switching on the rectifier stage, thus simplifying the current commutation strategy

Steady-state error elimination and simplified implementation of direct source current control for matrix converter with model predictive control

A matrix converter (MC) with model predictive control (MPC) based on the source reactive power control usually fails to show sinusoidal source currents. The analysis presented in this paper shows that this common combination of converter and control has the inherent inability to eliminate some harmonics in the source currents, even with additional passive or active damping control. Direct source current control can be implemented to give sinusoidal source currents and intrinsic active damping. However, the issue of steady-state error in output currents then arises, as the MC topology does not allow of the independent control of source and output currents. Therefore, feedback control of load active power is proposed to address this issue without degrading the fast dynamic performance. Benefiting from the direct source current control, a simplified implementation is also proposed to decrease the number of candidate switching states from 27 to 5, which significantly reduces the computational burden. Experimental results have verified the theoretical analysis and the effectiveness of the proposed control scheme

An Improved Three-Phase Buck Rectifier Topology with Reduced Voltage Stress on Transistors

The three-phase buck rectifier (3ph-BR) is suitable for applications where a voltage step down function is required. In this paper, an improved 3ph-BR topology is proposed to reduce the voltage stress on the transistors. The freewheeling diode in the conventional topology is split into two diodes in series and the input neutral point is connected to the common point of the two diodes. With the proposed topology and the correspondingly modified modulation scheme, the transistors only need to withstand the input phase voltage instead of the line-to-line voltage, bringing about the significant reduction of voltage stress. The proposed topology enables a more cost-efficient and flexible selection of the transistors. Experimental results have verified the validity of the modified topology and associated modulation scheme

Matrix Converter Based on Trapezoidal Current Injection

The Matrix Converter (MC) is a direct AC-AC power converter featuring high power density and high efficiency. However, the conventional MC (CMC) topologies require high control complexity and high transistor capacity, hindering the wide applications. An emerging MC topology (3CI-MC) based on the third-harmonic current injection (3CI) reduces the control complexity, but require more transistors and complex clamping circuit. This paper proposes the trapezoidal current injection (TCI) technique to form a novel MC topology (TCI-MC), which consists of a line-commutated converter (LCC), a TCI circuit and a voltage source converter (VSC). Compared with the 3CI-MC, the proposed TCI-MC not only maintains the advantages of simple modulation and independent voltage control, but also achieves lower current stress on the LCC part of the circuit. The total transistor capacity of the proposed TCI-MC is the lowest among all the considered MC topologies. The clamping circuit is also simplified and the bidirectional switches are eliminated, reducing the implementation cost. Simulation and experimental results have verified the validity of the proposed topology