Context-Patch Face Hallucination Based on Thresholding Locality-Constrained Representation and Reproducing Learning

Face hallucination is a technique that reconstruct high-resolution (HR) faces from low-resolution (LR) faces, by using the prior knowledge learned from HR/LR face pairs. Most state-of-the-arts leverage position-patch prior knowledge of human face to estimate the optimal representation coefficients for each image patch. However, they focus only the position information and usually ignore the context information of image patch. In addition, when they are confronted with misalignment or the Small Sample Size (SSS) problem, the hallucination performance is very poor. To this end, this study incorporates the contextual information of image patch and proposes a powerful and efficient context-patch based face hallucination approach, namely Thresholding Locality-constrained Representation and Reproducing learning (TLcR-RL). Under the context-patch based framework, we advance a thresholding based representation method to enhance the reconstruction accuracy and reduce the computational complexity. To further improve the performance of the proposed algorithm, we propose a promotion strategy called reproducing learning. By adding the estimated HR face to the training set, which can simulates the case that the HR version of the input LR face is present in the training set, thus iteratively enhancing the final hallucination result. Experiments demonstrate that the proposed TLcR-RL method achieves a substantial increase in the hallucinated results, both subjectively and objectively. Additionally, the proposed framework is more robust to face misalignment and the SSS problem, and its hallucinated HR face is still very good when the LR test face is from the real-world. The MATLAB source code is available at https://github.com/junjun-jiang/TLcR-RL

Polymorphisms of CYP1A1 I462V and GSTM1 genotypes and lung cancer susceptibility in Mongolian

Aim: To study the genotype of cytochrome P450 1A1(CYP1A1) I462V and glutathions S-transferase M1( GSTM1) and the relationship of the genetic polymorphism of them with the susceptibility of lung cancer in Mongolia of China. 

Methods: Allele-specific PCR and a multiplex PCR were employed to identify the genotypes of I462V of CYP1A1 and GSTM1 in a case-control study of 210 lung cancer patients with bronchoscopy diagnosis and 210 matched controls free of malignancy.

Results: The frequencies of the variant CYP1A1(Val/Val) genotypes and GSTM1(-) in lung cancer groups were higher than that in control groups (15.24% vs 7.4% and 56.67% vs 40.95% ). The individuals who carried with CYP1A1(Val/Val) or GSTM1(-) genotype had a significantly higher risk of lung cancer, the OR is 2.56 and 1.89 respectively. Stratified histologically the relative risk increased to 2.6 - fold when the patients carried with two valine alleles than the ones carried one valine allele in cases of SCC. GSTM1(-) genotype is the risk factor of SCC (OR=2.39) and AC(OR=2.16). The presence of at least one Val allele of CYP1A1 and GSTM1(-), the risk of lung cancer was increased, the OR was 4.15 for one Val allele and GSTM1(-) and 2.67 for two Val alleles and GSTM1 Considering ages and smoking status, the risk of lung cancer increased when the age less than 50 who carried with CYP1A1 valine (one or two) alleles or the age during the 51 to 65 who carried with GSTM1(-) genotype. The light smokers with CYP1A1 valine alleles and GSTM1(-) have a high risk for lung cancer. No association was found between the light and heavy drinkers with the susceptibility of lung cancer and the genetic polymorphisms of CYP1A1 I462V and GSTM1(-). 

Conclusion: The valine allele of CYP1A1 was the risk factors of lung cancer especially for SCC and GSTM1(-) also was the risk factor of lung cancer and especially for SCC and AC of Mongolian, China. Light smoking has a influence each other with genotype of CYP1A1 I462V and GSTM1(-) and susceptibility of lung cancer. No relationship was found between the susceptibility of lung cancer and drinkers with genetic polymorphisms of CYP1A1 I462V and GSTM1(-). The influence of genotypes on the susceptibility of lung cancer may depend on the ages. There may be a synergetic interaction between CYP1A1 valine allele and GSTM1(-) genotypes on the elevated susceptibility of lung cancer. So do those genotypes with light smokers. Key words polymorphism; genotype; lung cancer; cytochrome P450；glutathione S-transferase Abbreviations: SCC, squamous cell carcinoma; AC, adenocarcinoma; SCLC, small cell lung cancer; LCLC, large cell lung cance

On Mean Absolute Error for Deep Neural Network Based Vector-to-Vector Regression

In this paper, we exploit the properties of mean absolute error (MAE) as a loss function for the deep neural network (DNN) based vector-to-vector regression. The goal of this work is two-fold: (i) presenting performance bounds of MAE, and (ii) demonstrating new properties of MAE that make it more appropriate than mean squared error (MSE) as a loss function for DNN based vector-to-vector regression. First, we show that a generalized upper-bound for DNN-based vector-to-vector regression can be ensured by leveraging the known Lipschitz continuity property of MAE. Next, we derive a new generalized upper bound in the presence of additive noise. Finally, in contrast to conventional MSE commonly adopted to approximate Gaussian errors for regression, we show that MAE can be interpreted as an error modeled by Laplacian distribution. Speech enhancement experiments are conducted to corroborate our proposed theorems and validate the performance advantages of MAE over MSE for DNN based regression

Phase transition and entropy force between two horizons in (n+2)-dimensional de Sitter space

In this paper, the effect of the space-time dimension on effective thermodynamic quantities in (n+2)-dimensional Reissoner-Nordstrom-de Sitter space has been stud ied. Based on derived effective thermodynamic quantities, conditions for the phase transition are obtained. The result shows that the accelerating cosmic expansion can be attained by the entropy force arisen from the interaction between horizons of black holes and our universe, which provides a possible way to explain the physical mechanism for the accelerating cosmic expansion.Comment: Accepted by Advances in High Energy Physic

Huber Kalman Filter for Wi-Fi based Vehicle Driver\u27s Respiration Detection

The use of breath detection in vehicles can reduce the number of vehicular accidents caused by drivers in poor physical condition. Prior studies of contactless respiration detection mainly targeted a static person. However, there are emerging applications to sense a driver, with emphasis on contactless methods. For example, being able to detect a driver\u27s respiration while driving by using a vehicular Wi-Fi system can significantly enhance driving safety. The sensing system can be mounted on the back of the driver\u27s seat, and it can sense the tiny chest displacement of the driver via Wi-Fi signals. The body displacement and car vibrations could introduce significant noise in the sensed signal. The noise then needs to be filtered to obtain the driver\u27s respiration. In this work, the noise in the sensed signal is proposed to be reduced using a Huber Kalman filter to restore the original respiration curve. Through several experiments in terms of different drivers, different car models, multiple passengers, and abnormal breathing, we demonstrate the accuracy and robustness of the Huber Kalman filter in driver\u27s respiration