A Variational Bayesian Superresolution Approach Using Adaptive Image Prior Model

The objective of superresolution is to reconstruct a high-resolution image by using the information of a set of low-resolution images. Recently, the variational Bayesian superresolution approach has been widely used. However, these methods cannot preserve edges well while removing noises. For this reason, we propose a new image prior model and establish a Bayesian superresolution reconstruction algorithm. In the proposed prior model, the degree of interaction between pixels is adjusted adaptively by an adaptive norm, which is derived based on the local image features. Moreover, in this paper, a monotonically decreasing function is used to calculate and update the single parameter, which is used to control the severity of penalizing image gradients in the proposed prior model. Thus, the proposed prior model is adaptive to the local image features thoroughly. With the proposed prior model, the edge details are preserved and noises are reduced simultaneously. A variational Bayesian inference is employed in this paper, and the formulas for calculating all the variables including the HR image, motion parameters, and hyperparameters are derived. These variables are refined progressively in an iterative manner. Experimental results show that the proposed SR approach is very efficient when compared to existing approaches

Protein functional module identification method combining topological features and gene expression data

Article conducting an intensive study on the problems of low recognition efficiency and noise in the overlapping structure of protein functional modules, based on topological characteristics of PPI network. Developing a protein function module recognition method ECTG based on Topological Features and Gene expression data for Protein Complex Identification. The experimental results show that the ECTG algorithm can detect protein functional modules better

Interactive Effects of Chemical Composition of Food Waste during Anaerobic Co-Digestion under Thermophilic Temperature

The effects of chemical composition (carbohydrates, lipids, and protein) on the anaerobic co-digestion performance of food wastes (FW) were investigated from the viewpoints of methane production, dynamic parameters, and microbial community structure. The results of this study showed that a notable gasification rate was positively correlated with the proportion of the composition. A T2 reactor, which consisted of 60% carbohydrates, 20% lipids, and 20% protein, held a higher gasification rate of 65.09% compared to other groups, while its process parameters showed some deficiency regarding the stability of digestion, especially for low biochemical methane potential (BMP), which was not beneficial for the actual practice. A T4 reactor, with a highest gasification rate of 70.68%, held the maximum BMP (497.44 mL/g VS). The stable chemical parameters achieved the optimal proportion, consisting of 40% carbohydrates, 40% lipids, and 20% protein. Furthermore, its microbial populations were rich and achieved a balance of the two main dominant communities of acetoclastic methanogens and hydrogenotrophic methanogens, whose relative abundance was close. It was obvious that interactive effects were caused by different proportional composition, which led to constantly changing chemical parameters and microbial community

Multiframe Superresolution of Vehicle License Plates Based on Distribution Estimation Approach

Low-resolution (LR) license plate images or videos are often captured in the practical applications. In this paper, a distribution estimation based superresolution (SR) algorithm is proposed to reconstruct the license plate image. Different from the previous work, here, the high-resolution (HR) image is estimated via the obtained posterior probability distribution by using the variational Bayesian framework. To regularize the estimated HR image, a feature-specific prior model is proposed by considering the most significant characteristic of license plate images; that is, the target has high contrast with the background. In order to assure the success of the SR reconstruction, the models representing smoothness constraints on images are also used to regularize the estimated HR image with the proposed feature-specific prior model. We show by way of experiments, under challenging blur with size 7 × 7 and zero-mean Gaussian white noise with variances 0.2 and 0.5, respectively, that the proposed method could achieve the peak signal-to-noise ratio (PSNR) of 22.69 dB and the structural similarity (SSIM) of 0.9022 under the noise with variance 0.2 and the PSNR of 19.89 dB and the SSIM of 0.8582 even under the noise with variance 0.5, which are 1.84 dB and 0.04 improvements in comparison with other methods

Numerical Study on the Effect of Wall Thickness on the Combustion Characteristics of Non-premixed Hydrogen Micro-jet Flame

The effect of wall thickness on the combustion characteristics of nonpremixed hydrogen micro-jet flames was studied by two-dimensional numerical computation with a detailed reaction kinetics for the development of hydrogen micro-burner. The hydrogen jet diffusion flames achieved by micro-tubes with the same inner diameter and length but different wall thicknesses were investigated. The heat exchange between solid tube and gases were included in the numerical computation. The distributions of flame temperature, OH radicals, details of thermal interaction, and combustion efficiency were analyzed for comparison. It was found that the temperature distribution, flame shape, and heat recirculation are changed with the fuel flow velocity, and they are affected by wall thickness. The mechanism of wall thickness on the combustion characteristics of hydrogen jet diffusion flame was clarified. Finally, an interesting numerical experiment was conducted to give a further explanation of the effect of heat recirculation and to provide guidance of the thermal management of the micro-burner

Enhanced production of polysaccharides and triterpenoids in Ganoderma lucidum fruit bodies on induction with signal transduction during the fruiting stage.

Ganoderma lucidum is a medicinal mushroom that has been widely used in East Asia for the treatment of various diseases. The pharmacological activity of this fungus is primarily attributable to the polysaccharides and triterpenoids. In this study, to obtain the fruit bodies with improved content of active constituents, we examined the effect of salicylic acid (SA) and calcium ion on the biosynthesis of polysaccharides and triterpenoids by spraying the chemicals during the fruiting. To explore the underlying mechanisms for the variation, the transcripts of related genes involved in the polysaccharide and triterpenoid biosynthesis were measured. Results showed that Ca2+ had no effect on production of polysaccharides and triterpenoids, whereas SA increased triterpenoid content by 23.32%, compared to the control, but it had little influence on polysaccharide production. Interestingly, the combined induction increased polysaccharide and triterpenoid content by 9.02% and 13.61%, respectively, compared to the control. Under Ca2+ induction, the transcript of ugp gene in the polysaccharide biosynthetic pathway up-regulated in all three stages (mycelium, primordium, and fruit body), while pgm and gls gave no response in the mycelium and primordium stages, and up-regulated in the fruit body stage. Differently, six key triterpenoid biosynthetic genes including hmgr, hmgs, mvd, fps, sqs, and ls did not respond to the induction. In the case of SA and combined induction, pgm and ugp were up-regulated in all three stages, while gls showed an increased expression in the primordium stage and no response in other stages. The six triterpenoid biosynthetic genes were up-regulated in all three stages. The present study provides a useful approach to producing G. lucidum fruit bodies with high polysaccharide and triterpenoid content. This is important to the G. lucidum industry

Extended State Observer-Based Sliding-Mode Control for Floating Interleaved Boost Converters

International audienceA novel control scheme for two phases floating interleaved boost DC-DC converter (FIBC) is presented in this paper. The proposed controller is based on second order sliding mode method combined with an extend state observer (ESO), which comprises two loops: the outer loop is a voltage regulation loop whereas the inner loop is an instantaneous current regulation loop. The outer loop is accomplished by SOSM and ESO, which aims to regulate the output voltage of the converter and reject the disturbance of the load variations. The SOSM strategy is also applied to inner loop to make the current track its reference accurately. Through the proposed approach, the system can obtain a stronger robustness, and the chattering problem is also suppressed. Both theoretical analysis and simulation results are demonstrated. Moreover, in order to verify the effectiveness of the proposed control scheme, comparisons with dual loops super-twisting control scheme (ST + ST) and outer active disturbance reject control plus inner super-twisting control scheme (ADRC + ST) in case of parameter uncertainties and loads disturbances have been made in this paper

Robust Voltage Control of Floating Interleaved Boost Converter for Fuel Cell Systems

International audienceIn this paper, a robust voltage control is designed for a floating interleaved boost converter with high voltage gain. The proposed controller has an inner loop based on super-twisting sliding mode algorithm, which has continuous control signal and the sliding surface is defined for the inductor current. The reference current value is generated by active disturbance rejection control (ADRC) algorithm in the outer loop, based on the output voltage error. The stability of the sliding mode inner loop and the ADRC outer loop are proven using Lyapunov stability theorem and Routh-Hurwitz criteria, respectively. The robustness of the proposed controller is analyzed in depth, and validated by the simulations and experimental results obtained with a 100 W prototype converter