A New Method for Superresolution Image Reconstruction Based on Surveying Adjustment

A new method for superresolution image reconstruction based on surveying adjustment method is described in this paper. The main idea of such new method is that a sequence of low-resolution images are taken firstly as observations, and then observation equations are established for the superresolution image reconstruction. The gray function of the object surface can be found by using surveying adjustment method from the observation equations. High-resolution pixel value of the corresponding area can be calculated by using the gray function. The results show that the proposed algorithm converges much faster than that of conventional superresolution image reconstruction method. By using the new method, the visual feeling of reconstructed image can be greatly improved compared to that of iterative back projection algorithm, and its peak signal-to-noise ratio can also be improved by nearly 1 dB higher than the projection onto convex sets algorithm. Furthermore, this method can successfully avoid the ill-posed problems in reconstruction process

Uncontrolled Hypertension Increases Risk of All-Cause and Cardiovascular Disease Mortality in Us Adults: The NHANES III Linked Mortality Study

Clinical trials had provided evidence for the benefit effect of antihypertensive treatments in preventing future cardiovascular disease (CVD) events; however, the association between hypertension, whether treated/untreated or controlled/uncontrolled and risk of mortality in US population has been poorly understood. A total of 13,947 US adults aged ≥18 years enrolled in the Third National Health and Nutrition Examination Survey (1988-1994) were used to conduct this study. Mortality outcome events included all-cause, CVD-specific, heart disease-specific and cerebrovascular disease-specific deaths, which were obtained from linked 2011 National Death Index (NDI) files. During a median follow-up of 19.1 years, there were 3,550 all-cause deaths, including 1,027 CVD deaths. Compared with normotensives, treated but uncontrolled hypertensive patients were at higher risk of all-cause (HR = 1.62, 95%CI = 1.35-1.95), CVD-specific (HR = 2.23, 95%CI = 1.66-2.99), heart disease-specific (HR = 2.19, 95%CI = 1.57-3.05) and cerebrovascular disease-specific (HR = 3.01, 95%CI = 1.91-4.73) mortality. Additionally, untreated hypertensive patients had increased risk of all-cause (HR = 1.40, 95%CI = 1.21-1.62), CVD-specific (HR = 1.77, 95%CI = 1.34-2.35), heart disease-specific (HR = 1.69, 95%CI = 1.23-2.32) and cerebrovascular disease-specific death (HR = 2.53, 95%CI = 1.52-4.23). No significant differences were identified between normotensives, and treated and controlled hypertensives (all p \u3e 0.05). Our study findings emphasize the benefit of secondary prevention in hypertensive patients and primary prevention in general population to prevent risk of mortality later in life

Coating titania nanoparticles with epoxy-containing catechol polymers via Cu(0)-living radical polymerization as intelligent enzyme carriers

Immobilization of enzyme could offer the biocatalyst with increased stability and important recoverability, which plays a vital role in the enzyme’s industrial applications. In this study, we present a new strategy to build an intelligent enzyme carrier by coating titania nanoparticles with thermoresponsive epoxy-functionalized polymers. Zero-valent copper-mediated living radical polymerization (Cu(0)-LRP) was utilized herein to copolymerize N-isopropylacrylamide (NIPAM) and glycidyl acrylate (GA) directly from an unprotected dopamine-functionalized initiator to obtain an epoxy-containing polymer with terminal anchor for the “grafting to” or “one-pot” modification of titania nanoparticles. A rhodamine B-labeled laccase has been subsequently used as a model enzyme for successful immobilization to yield an intelligent titania/laccase hybrid bifunctional catalyst. The immobilized laccase has shown excellent thermal stability under ambient or even relatively high temperature above the lower critical solution temperature (LCST) at which temperature the hybrid particles could be facilely recovered for reuse. The enzyme activity could be maintained during the repeated use after recovery and enzymatic degradation of bisphenol A was proven to be efficient. The photocatalytic ability of titania was also investigated by fast degradation of rhodamine B under the excitation of simulated sunlight. Therefore, this study has provided a facile strategy for the immobilization of metal oxide catalysts with enzymes, which constructs a novel bifunctional catalyst that will be promising for the “one-pot” degradation of different organic pollutants

DPPMask: Masked Image Modeling with Determinantal Point Processes

Masked Image Modeling (MIM) has achieved impressive representative performance with the aim of reconstructing randomly masked images. Despite the empirical success, most previous works have neglected the important fact that it is unreasonable to force the model to reconstruct something beyond recovery, such as those masked objects. In this work, we show that uniformly random masking widely used in previous works unavoidably loses some key objects and changes original semantic information, resulting in a misalignment problem and hurting the representative learning eventually. To address this issue, we augment MIM with a new masking strategy namely the DPPMask by substituting the random process with Determinantal Point Process (DPPs) to reduce the semantic change of the image after masking. Our method is simple yet effective and requires no extra learnable parameters when implemented within various frameworks. In particular, we evaluate our method on two representative MIM frameworks, MAE and iBOT. We show that DPPMask surpassed random sampling under both lower and higher masking ratios, indicating that DPPMask makes the reconstruction task more reasonable. We further test our method on the background challenge and multi-class classification tasks, showing that our method is more robust at various tasks

Organic amendments with high proportion of heterocyclic compounds promote soil microbiome shift and microbial use efficiency of straw-C

Soil microbial use efficiency of straw carbon (C), which is the proportion of straw-C microbes assimilate into new biosynthetic material relative to C lost out of the system as CO2, is critical in increasing soil organic C (SOC) content, and hence maintaining soil fertility and productivity. However, the effect of chemical structures of the organic amendments (OAs) on the microbial use efficiency of straw-C remains unclear. The effect of the chemical structure of the OAs on microbial use efficiency of straw-C was elucidated by a combination of 13C-straw labeling with high-throughput sequencing and pyrolysis-GC/MS. We found a strong positive correlation between the microbial use efficiency of straw-C and the proportion of heterocyclic compounds (Hete_C). The microbial use efficiency of straw-C was highest in soil supplemented with Hete_C-dominant OAs, which significantly shifted microbial community structure toward fungal dominance. Specifically, fungal-to-bacterial ratio, fungal richness, and the relative abundance of Ascomycota were higher in soil with a higher proportion of Hete_C-dominant OAs. Together, our study suggests that OAs with high proportion of Hete_C promote the microbial use efficiency of straw-C by increasing the dominance of fungi in the soil microbial community in agroecosystems

Nonlinear Adjustment Model with Integral and Its Application to Super Resolution Image Reconstruction

The process of super resolution image reconstruction is such a process that multiple observations are taken on the same target to obtain low resolution images, then the low resolution images are used to reconstruct the real image of the target, namely high resolution image. This process is similar to that in the field of surveying and mapping, in which the same target is observed repeatedly and the optimal values is calculated with surveying adjustment methods. In this paper, the method of surveying adjustment is applied into super resolution image reconstruction. A integral nonlinear adjustment model for super resolution image reconstruction is proposed at first. And then the model is parameterized with a quadratic function. Finally the model is solved with the least squares adjustment method. Based on the proposed adjustment method, the specific strategy of image reconstruction is presented. This method for super resolution image reconstruction can make quantitative analysis of the results, and avoid successfully ill-condition problem, etc. The results show that, compared to the traditional method of super resolution image reconstruction, this method has greatly improved the visual effects, and the PSNR and SSIM has also greatly improved, so the method is reliable and feasible

Investigation on microstructure and its transformation mechanisms of B2O3-SiO2-Al2O3-CaO brazing flux system

The B2O3-SiO2-Al2O3-CaO brazing fluxes and slags were investigated by using X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscopy (FTIR). The microstructure of the fluxes and slags and its transformation mechanism during the brazing process were investigated, especially the effect of ratio of B2O3to SiO2(B2O3/SiO2) on the microstructural transformation was analyzed. The results show that the structure units of the fluxes and slags are [BO4], [BO3], [SiO4], [AlO4] and [AlO6], and the network structure is a silicon-boron network structure. The O in the slags consist of bridged oxygen, non-bridged oxygen and free oxygen. During the brazing process, part of the [BO4] in slag combined with silica-oxygen network to form Si-O-B structure, which contribute to the network structure of slag, and another part of the [BO4] was transformed to [BO3]. The increase of (B2O3/SiO2) contribute to the transformation of [BO4] to [BO3], and more B2O3 take part in the interface reaction with the increase of (B2O3/SiO2). Therefore, the increase of (B2O3/SiO2) leads to the decrease in the viscosity of the slag, which is beneficial to the spreading behavior during the brazing process

A survey on network data collection

Networks have dramatically changed our daily life and infiltrated all aspects of human society. At the same time when we enjoy the convenience and benefits brought by the networks, we also suffer from a great amount of intelligent attacks and malicious intrusions. As a fundamental procedure of network security measurement, network data collection executes real time network monitoring, supports network performance evaluation, assists network billing, and helps traffic testing and filtering. Thus, it plays a crucial and essential role for dealing with network intrusion detection and unwanted traffic control. But an adaptive and effective data collection mechanism that can be pervasively applied into heterogeneous networks is still lacked. The literature we have hunted rarely comments and compares the performance of existing data collection mechanisms. In this paper, we conduct a survey on existing data collection methods, mechanisms and architectures. According to a number of proposed assessment criteria, we evaluate the performance of existing data collection mechanisms and summarize their characteristics. Furthermore, we figure out some open issues based our investigation and forecast future research directions.Peer reviewe