A new method for month-ahead wind power deterministic prediction based on combination method is proposed. Mathematical and statistical methods are applied to reduce the dimensionality of a large amount of historical weather data and wind power data. Then, the fitting relationship between these two variables is obtained by cubic spline interpolation function method. By combining the fitting relationship with future weather forecast data, future wind power forecast results can be obtained finally. The accuracy and effectiveness of the month-ahead wind power forecasting model proposed in this paper have been verified by comparing the actual wind power data and forecast data of a wind farm in Shenyang City, Liaoning Province for 4 months.
As the main interface device between distributed generation and public grid, grid connected inverter is responsible for the stable operation of distributed generation system. In order to solve the problem of interaction among inverters in the parallel system of inverters, based on the double closed-loop PR control system of LCL filter, a multiple three-phase inverter grid system which is close to the reality with relatively complex control structure based on droop control is established. For the current control loop with additional active damping control in the system, a transfer function is established at αβcoordinate system. According to the principle of relative gain array, a method is proposed to analyze the interaction among multiple parallel three-phase inverters. It can quantitatively analyze the relationship between the system control parameters, operation frequency, number of parallel inverters, filter capacitor and the interaction among inverters. Finally, a grid connected model of three-phase inverter is built in MATLAB / Simulink simulation platform to verify the correctness of theoretical analysis and the effectiveness of interaction analysis method.
Artificial neural networks (ANNs) have been an important approach for predicting the value of flow stress, which is dependent on temperature, strain, and strain rate. However, there is still a lack of sufficient knowledge regarding what structure of ANN should be used for predicting metal flow stress. In this paper, we train an ANN for predicting flow stress of In718 alloys at high temperatures using our experimental data, and the structure of the ANN is optimized by comparing the performance of four ANNs in predicting the flow stress of In718 alloy. It is found that, as the size of the ANN increases, the ability of the ANN to retrieve the flow stress results from a training dataset is significantly enhanced; however, the ability to predict the flow stress results absent from the training does not monotonically increase with the size of the ANN. It is concluded that the ANN with one hidden layer and four nodes possesses optimized performance for predicting the flow stress of In718 alloys in this study. The reason why there exists an optimized ANN size is discussed. When the ANN size is less than the optimized size, the prediction, especially the strain dependency, falls into underfitting and fails to predict the curve. When the ANN size is less than the optimized size, the predicted flow stress curves with the temperature, strain, and strain rate will contain non-physical fluctuations, thus reducing their prediction accuracy of extrapolation. For metals similar to the In718 alloy, ANNs with very few nodes in the hidden layer are preferred rather than the large ANNs with tens or hundreds of nodes in the hidden layers.
To investigate the effect of burn on the fat metabolism by observing the effect of burn serum on the proliferation and adipose differentiation of 3T3-L1 preadipocytes.Forty-eight male Sprague Dawley rats were randomly divided into sham burn group and burn at 1, 4, 7, 14, and 21 days groups, 8 rats in each group. The rats in burn groups were made the full-thickness thermal burns comprising 30% total body surface area. At 1, 4, 7, 14, and 21 days after burn, the serum of burn rats was collected. The rats in sham burn group were not treated as normal control. The proliferation activity of 3T3-L1 cells was detected using MTT method after treated by normal and burn serum. The burn serum having the highest proliferation inhibitory effect was chosen for subsequent study. The growth of 3T3-L1 cells in normal serum group (group A), burn serum group (group B), normal serum and adipogenic induction group (group C), burn serum and adipogenic induction group (group D) was observed using inverted microscope. After 7 days of treatment, the adipocytes was stained by oil red O and the absorbance (A) value was measured. The mRNA and protein levels of preoxisome proliferator-activated receptor γ (PPAR-γ) and lipoprotein lipase (LPL) were detected by real-time quantitative PCR and Western blot.The proliferation ability of 3T3-L1 cells was significantly reduced in the group treated by 4- or 7-day burn serum (P < 0.05), especially 7-day burn serum treatment group (P < 0.05). Under inverted microscope, the cell morphology in group A and group B had no obvious change, but a large number of fat cells were observed in group C and a few were observed in group D. The positive or weak positive oil red O staining was observed in group C or group D, respectively. The cell counting and A value were significantly higher in group A than in group B, and in group C than in group D (P < 0.05). The mRNA level of PPAR-γ in group B was significantly reduced when compared with that in group A (P < 0.05). No significant difference was found in LPL mRNA levels and protein levels of PPAR-γ and LPL between group A and group B (P > 0.05). The mRNA and protein levels of PPAR-γ and LPL were significantly attenuated in group D when compared with those in group C (P < 0.05).The adipose differentiation of 3T3-L1 preadipocytes can be significantly reduced after treated by 7-day burn serum of rat.
Previous reports on Selective Androgen Receptor Modulators (SARMs) have described their activity primarily by their tissue selectivity in animal models. A few SARMs have been described with tissue selectivity ascribed to their diminished activity in promoting the intramolecular interaction between the androgen receptor (AR) carboxyl and amino termini. In the current study we characterized an AR ligand PF-05314882 that has an unusual in vitro selectivity profile in AR cell based assays. This SARM was previously reported to have tissue selective AR activity in rats. In the current study PF-05314882 bound to the AR ligand binding domain with good affinity and activated AR-mediated transcription in vitro. However, unlike naturally occurring androgens and other SARMs, PF-05314882 does not stimulate interaction between AR and β-catenin. Consistent with this observation, PF-05314882 had only weak activity on androgen-AR dependent inhibition of Wnt reporter activity. In castrated rats, the daily administration of PF-05314882 had anabolic activity on increasing levator ani muscle weight and elevating RNA expression of androgen regulated metabolic genes in the liver. Similar to previously described tissue selective SARMs, PF-05314882 has very little activity in the prostate, seminal vesicles and in repressing circulating luteinizing hormone (LH) levels. More importantly, since AR and β-catenin have been shown to play important roles in overlapping tissues including adipose, bone, hair and in diseases such as prostate cancer, PF-05314882 may be an important pharmacologic tool to elucidate the role and extent of cross-talk between AR and β-catenin.
The technology of distributed cooperative consensus has been widely used in inverter-based microgrids. However, the traditional information interaction will lead to the problem of data disclosure. Although privacy issues have been widely researched in the tertiary control layer of microgrids, the issues of secondary control layer have not been properly addressed. To fill this gap, taking voltage restoration as the object, the privacy preserving consensus problem for secondary control layer of nDGs islanded microgrids is considered in this paper. Output mask approach, the basic idea of which is to insert a dynamic mask to the transmitted information, is adopted to achieve an accurate consensus rather than a pre-specified convergence accuracy level by differential private method. After that, a newly state decomposition mechanism is proposed, the DG agent is decomposed into two subagents, called $x^{\alpha} _{i}$ and $x^{\beta} _{i}$ . Among the agent pairs $(x^{\alpha} _{i}, x^{\beta} _{i})$ , choose only one subagent of pair $i$ arbitrarily connected to one subagent of its neighbor agent pair. Furthermore, only the communication lines among the agent pairs are masked. Compared with the existing literature, the constraint on the communication topology can be first removed without additional computational burden. Moreover, the consensus and privacy analysis of the controlled system are carried out. In the end, the simulation results verify the effectiveness of the proposed privacy preserving mechanism in the MATLAB/Simulink environment. Note to Practitioners—With the rapid development of information and intelligent technology, the information system and the physical system of MGs have been deeply integrated to get a higher efficiency of energy utilization. However, the traditional information interaction will lead to the problem of data disclosure. Although privacy issues have been widely researched in the tertiary control layer of microgrids, the issues of secondary control layer have not been properly addressed. Motivated by this, an improved privacy-preserving consensus strategy is proposed for secondary voltage control of islanded microgrids based on a newly node decomposition mechanism and the output mask method in this paper. And the theoretical results of this paper can be easily extended to other multi-agent systems.
Osteoarthritis (OA), the most common arthritic condition in humans, is characterized by the progressive degeneration of articular cartilage accompanied by chronic joint pain. Inflammatory mediators, such as cytokines and prostaglandin E 2 (PGE 2 ) that are elevated in OA joints, play important roles in the progression of cartilage degradation and pain-associated nociceptor sensitivity. We have found that the nuclear receptor family transcription factors L iver X R eceptors (LXRα and -β) are expressed in cartilage, with LXRβ being the predominant isoform. Here we show that genetic disruption of Lxrβ gene expression in mice results in significantly increased proteoglycan (aggrecan) degradation and PGE 2 production in articular cartilage treated with IL-1β, indicating a protective role of LXRβ in cartilage. Using human cartilage explants, we found that activation of LXRs by the synthetic ligand GW3965 significantly reduced cytokine-induced degradation and loss of aggrecan from the tissue. Furthermore, LXR activation dramatically inhibited cytokine-induced PGE 2 production by human osteoarthritic cartilage as well as by a synovial sarcoma cell line. These effects were achieved at least partly by repression of the expression of ADAMTS4, a physiological cartilage aggrecanase, and of cyclooxygenase-2 and microsomal prostaglandin E synthase-1, key enzymes in the PGE 2 synthesis pathway. Consistent with our in vitro observations, oral administration of GW3965 potently alleviated joint pain in a rat meniscal tear model of osteoarthritis.
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