Regularized Fourier ptychography using an online plug-and-play algorithm

The plug-and-play priors (PnP) framework has been recently shown to achieve state-of-the-art results in regularized image reconstruction by leveraging a sophisticated denoiser within an iterative algorithm. In this paper, we propose a new online PnP algorithm for Fourier ptychographic microscopy (FPM) based on the accelerated proximal gradient method (APGM). Specifically, the proposed algorithm uses only a subset of measurements, which makes it scalable to a large set of measurements. We validate the algorithm by showing that it can lead to significant performance gains on both simulated and experimental data.https://arxiv.org/abs/1811.00120Published versio

Regularized Fourier ptychography using an online plug-and-play algorithm

The plug-and-play priors (PnP) framework has been recently shown to achieve state-of-the-art results in regularized image reconstruction by leveraging a sophisticated denoiser within an iterative algorithm. In this paper, we propose a new online PnP algorithm for Fourier ptychographic microscopy (FPM) based on the accelerated proximal gradient method (APGM). Specifically, the proposed algorithm uses only a subset of measurements, which makes it scalable to a large set of measurements. We validate the algorithm by showing that it can lead to significant performance gains on both simulated and experimental data.https://arxiv.org/abs/1811.00120Published versio

The Determinants of Capital Structure of Listed Companies in Developed and Developing Countries: Evidence from Eight Countries

This research will discuss the determinants that contribute to capital structure from both the external and internal perspective. Most empirical capital structure determinants are concluded based on data from developed countries. To test whether these factors are generally suitable for different countries, this dissertation chooses 4 developed countries (Australia, Japan, the UK and the USA) and 4 developing countries (Brazil, Russia, India, China, generally known as BRIC block) as research objects. This dissertation will use the panel model to verify the relationship between capital structure and potential determinants. The results show that profitability has the strongest relationship with leverage ratio as it is significant in 6 out of 8 countries., which also indicates the same trend in both non-BRIC and BRIC countries. Size is believed to be the second related variable to leverage as it also has the 6 countries who show reliable relationship of it as profitability. Though the correlation is not identical in these countries, it still has relatively high consistency in BRIC. Consistency of variables in non-BRIC and BRIC can also be found in tangibility and liquidity, whereas the former shows strong positive relationship with the dependent variable and the latter indicates strong negative correlation to leverage ratio. However, the correlation to leverage for growth opportunity is different for non-BRIC and BRIC, it is highly negative in BRIC and less strong but positive in the UK, which is the only related country in non-BRIC

Noise-to-Norm Reconstruction for Industrial Anomaly Detection and Localization

Anomaly detection has a wide range of applications and is especially important in industrial quality inspection. Currently, many top-performing anomaly-detection models rely on feature-embedding methods. However, these methods do not perform well on datasets with large variations in object locations. Reconstruction-based methods use reconstruction errors to detect anomalies without considering positional differences between samples. In this study, a reconstruction-based method using the noise-to-norm paradigm is proposed, which avoids the invariant reconstruction of anomalous regions. Our reconstruction network is based on M-net and incorporates multiscale fusion and residual attention modules to enable end-to-end anomaly detection and localization. Experiments demonstrate that the method is effective in reconstructing anomalous regions into normal patterns and achieving accurate anomaly detection and localization. On the MPDD and VisA datasets, our proposed method achieved more competitive results than the latest methods, and it set a new state-of-the-art standard on the MPDD dataset

Hypothermia treatment ameliorated cyclin-dependent kinase 5-mediated inflammation in ischemic stroke and improved outcomes in ischemic stroke patients

OBJECTIVES: The inflammatory response is a key mechanism of neuronal damage and loss during acute ischemic stroke. Hypothermia has shown promise as a treatment for ischemic stroke. In this study, we investigated the molecular signaling pathways in ischemic stroke after hypothermia treatment. METHODS: Cyclin-dependent kinase 5 (CDK5) was overexpressed or silenced in cultured cells. Nuclear transcription factor-kB (NF-kB) activity was assessed by measurement of the luciferase reporter gene. An ischemic stroke model was established in Sprague–Dawley (SD) rats using the suture-occluded method. Animals were assigned to three groups: sham operation control, ischemic stroke, and ischemic stroke + hypothermia treatment groups. Interleukin 1b (IL-1b) levels in the culture supernatant and blood samples were assessed by ELISA. Protein expression was measured by Western blotting. RESULTS: In HEK293 cells and primary cortical neuronal cultures exposed to hypothermia, CDK5 overexpression was associated with increased IL-1b, caspase 1, and NF-kB levels. In both a murine model of stroke and in patients, increased IL-1b levels were observed after stroke, and hypothermia treatment was associated with lower IL-1b levels. Furthermore, hypothermia-treated patients showed significant improvement in neurophysiological functional outcome. CONCLUSIONS: Overall, hypothermia offers clinical benefit, most likely through its effects on the inflammatory response