How Does the Low-Rank Matrix Decomposition Help Internal and External Learnings for Super-Resolution

Wisely utilizing the internal and external learning methods is a new challenge in super-resolution problem. To address this issue, we analyze the attributes of two methodologies and find two observations of their recovered details: 1) they are complementary in both feature space and image plane, 2) they distribute sparsely in the spatial space. These inspire us to propose a low-rank solution which effectively integrates two learning methods and then achieves a superior result. To fit this solution, the internal learning method and the external learning method are tailored to produce multiple preliminary results. Our theoretical analysis and experiment prove that the proposed low-rank solution does not require massive inputs to guarantee the performance, and thereby simplifying the design of two learning methods for the solution. Intensive experiments show the proposed solution improves the single learning method in both qualitative and quantitative assessments. Surprisingly, it shows more superior capability on noisy images and outperforms state-of-the-art methods

Age and Gender Differences in the Association between Serious Psychological Distress and Cancer: Findings from the 2003, 2005, and 2007 Health Information National Trends Surveys (HINTS)

Background: Little is known about the association of serious psychological distress (SPD) with cancer.Aims: This study examined the association between SPD and cancer, and tested whether such association differed by age and gender.Methods: Data came from the 2003, 2005, and 2007 Health Information National Trends Surveys (HINTS) (2,637 cancer cases and 16,581 controls). Weighted univariate and multiple logistic regression analyses were used to estimate the odds ratios (ORs) with 95% confidence intervals (CIs).Results: The overall prevalence of SPD was 6.7% (5.4% for males and 7.9 % for females; 7.1% for cancers and 6.4% for controls). The prevalence of SPD decreased with age (7.8%, 5.8% and 3.9% for age groups 18-49, 50-64 and 65+ years, respectively). After adjusting for other factors, being female, elder (65+ years), SPD, and poor general health were positively associated with cancer (p0.05). Gender-stratified analyses showed that SPD was associated with cancer only in women. Stratified by age groups, SPD and obesity were associated with cancer only in elderly.Conclusions: Older age, being female, SPD and poor general health were associated with increased likelihood of cancer. Stratified by age groups and gender, SPD was significantly associated with cancer in women and elder group. It is important to develop effective strategies to manage SPD among patients with cancer, especially in women and elder adults

Associations of Anxiety and Psychological Distress with Cancer in US Adults: Results from the 2012 National Health Interview Survey

Background: Little is known about age differences in the associations of anxiety, depression, and psychological distress (PD) with cancer.Objectives: We estimated the prevalence of cancer in the United States (US) adults and examined the associations between mental health problems and cancer, and tested the related age differences.Materials and Methods: This was a cross-sectional study (n=34,505, 3,118 had cancer) from the 2012 National Health Interview Survey (NHIS) data. Weighted univariate and multiple logistic regression analyses were used to estimate the odds ratios (ORs) with 95% confidence intervals (CIs).Results: The overall prevalence of cancer is 8.6% (7.6% for males and 9.4 % for females). The prevalence increased with age (2.0%, 9.3% and 24.3% for age groups 18-49, 50-64 and 65+ years, respectively). The prevalence of anxiety, depression, and PD was significantly higher in cancer patients than in non-cancers (26% vs. 18%, 20% vs.13%, and 13% vs. 9%, respectively). Multiple logistic regression analyses showed that being female, aging, anxiety, and PD were positively associated with cancer (p0.05). Age group revealed significant interactions with anxiety and PD, in relation to cancer. Stratified by age groups, PD was positively associated with cancer just in young adults (18-49 years) while anxiety showed a stronger association with cancer in young adults and elderly (65+ years).Conclusions: The prevalence of mental health problems was higher among US adults who had cancer. The associations between mental health problems and cancer varied across ages. Effective strategies may be needed to manage these mental health conditions among patients with cancer at each age

Joint prior learning for visual sensor network noisy image super-resolution

The visual sensor network (VSN), a new type of wireless sensor network composed of low-cost wireless camera nodes, is being applied for numerous complex visual analyses in wild environments, such as visual surveillance, object recognition, etc. However, the captured images/videos are often low resolution with noise. Such visual data cannot be directly delivered to the advanced visual analysis. In this paper, we propose a joint-prior image super-resolution (JPISR) method using expectation maximization (EM) algorithm to improve VSN image quality. Unlike conventional methods that only focus on up scaling images, JPISR alternatively solves upscaling mapping and denoising in the E-step and M-step. To meet the requirement of the M-step, we introduce a novel non-local group-sparsity image filtering method to learn the explicit prior and induce the geometric duality between images to learn the implicit prior. The EM algorithm inherently combines the explicit prior and implicit prior by joint learning. Moreover, JPISR does not rely on large external datasets for training, which is much more practical in a VSN. Extensive experiments show that JPISR outperforms five state-of-the-art methods in terms of both PSNR, SSIM and visual perception

Multi-Classifier Interactive Learning for Ambiguous Speech Emotion Recognition

In recent years, speech emotion recognition technology is of great significance in industrial applications such as call centers, social robots and health care. The combination of speech recognition and speech emotion recognition can improve the feedback efficiency and the quality of service. Thus, the speech emotion recognition has been attracted much attention in both industry and academic. Since emotions existing in an entire utterance may have varied probabilities, speech emotion is likely to be ambiguous, which poses great challenges to recognition tasks. However, previous studies commonly assigned a single-label or multi-label to each utterance in certain. Therefore, their algorithms result in low accuracies because of the inappropriate representation. Inspired by the optimally interacting theory, we address the ambiguous speech emotions by proposing a novel multi-classifier interactive learning (MCIL) method. In MCIL, multiple different classifiers first mimic several individuals, who have inconsistent cognitions of ambiguous emotions, and construct new ambiguous labels (the emotion probability distribution). Then, they are retrained with the new labels to interact with their cognitions. This procedure enables each classifier to learn better representations of ambiguous data from others, and further improves the recognition ability. The experiments on three benchmark corpora (MAS, IEMOCAP, and FAU-AIBO) demonstrate that MCIL does not only improve each classifier's performance, but also raises their recognition consistency from moderate to substantial.Comment: 10 pages, 4 figure

Analytic study on the foundation of shaker based on AIR spring

In view of the limitation of the traditional installation method of the shaker placed on the floor structure, a method of foundation isolation based on the AIR spring is proposed. According to the dynamic characteristics of the AIR spring, the relationship between the natural frequency and the parameters, such as the air pressure and the weight of the load, are analyzed. In order to evaluate the coupling properties between the vibration isolation system and the vibration test system, the factors affecting the vibration isolation transfer function of the system and the response of the foundation under vibration excitation were analyzed. Test results revealed that: it is feasible to adjust the natural frequency of system, to obtain the good isolation performance and stationary dynamic response, by reasonably choosing the structural parameters of the AIR spring and adjusting the internal inflation pressure of spring

The human parvovirus B19 non-structural protein 1 N-terminal domain specifically binds to the origin of replication in the viral DNA

The non-structural protein 1 (NS1) of human parvovirus B19 plays a critical role in viral DNA replication. Previous studies identified the origin of replication in the viral DNA, which contains four DNA elements, namely NSBE1 to NSBE4, that are required for optimal viral replication (Guan et al, 2009, J. Virology, 83, 9541-9553). Here we have demonstrated in vitro that the NS1 N-terminal domain (NS1N) binds to the origin of replication in a sequence-specific, length-dependent manner that requires NSBE1 and NSBE2, while NSBE3 and NSBE4 are dispensable. Mutagenesis analysis has identified nucleotides in NSBE1 and NSBE2 that are critical for NS1N binding. These results suggest that NS1 binds to the NSBE1-NSBE2 region in the origin of replication, while NSBE3 and NSBE4 may provide binding sites for potential cellular factors. Such a specialized nucleoprotein complex may enable NS1 to nick the terminal resolution site and separate DNA strands during replication