Convolutional Deblurring for Natural Imaging

In this paper, we propose a novel design of image deblurring in the form of one-shot convolution filtering that can directly convolve with naturally blurred images for restoration. The problem of optical blurring is a common disadvantage to many imaging applications that suffer from optical imperfections. Despite numerous deconvolution methods that blindly estimate blurring in either inclusive or exclusive forms, they are practically challenging due to high computational cost and low image reconstruction quality. Both conditions of high accuracy and high speed are prerequisites for high-throughput imaging platforms in digital archiving. In such platforms, deblurring is required after image acquisition before being stored, previewed, or processed for high-level interpretation. Therefore, on-the-fly correction of such images is important to avoid possible time delays, mitigate computational expenses, and increase image perception quality. We bridge this gap by synthesizing a deconvolution kernel as a linear combination of Finite Impulse Response (FIR) even-derivative filters that can be directly convolved with blurry input images to boost the frequency fall-off of the Point Spread Function (PSF) associated with the optical blur. We employ a Gaussian low-pass filter to decouple the image denoising problem for image edge deblurring. Furthermore, we propose a blind approach to estimate the PSF statistics for two Gaussian and Laplacian models that are common in many imaging pipelines. Thorough experiments are designed to test and validate the efficiency of the proposed method using 2054 naturally blurred images across six imaging applications and seven state-of-the-art deconvolution methods.Comment: 15 pages, for publication in IEEE Transaction Image Processin

The similarity of astrocytes number in dentate gyrus and CA3 subfield of rats hippocampus

The dentate gyrus is a part of hippocampal formation that it contains granule cells, which project to the pyramidal cells and interneurons of the CA3 subfield of the hippocampus. Astrocytes play a more active role in neuronal activity, including regulating ion flux currents, energy production, neurotransmitter release and synaptogenesis. Astrocytes are the only cells in the brain that contain the energy molecule glycogen. The close relationship between dentate gyrus and CA3 area can cause the similarity of the number of astrocytes in these areas. In this study 5 male albino wistar rats were used. Rats were housed in large plastic cage in animal house and were maintained under standard conditions, after histological processing, The 7 μm slides of the brains were stained with PTAH staining for showing the astrocytes. This staining is specialized for astrocytes. We showed that the number of astrocytes in different (ant., mid., post) parts of dentate gyrus and CA3 of hippocampus is the same. For example, the anterior parts of two area have the most number of astrocytes and the middle parts of two area have the least number of astrocytes. We concluded that dentate gyrus and CA3 area of hippocampus have the same group of astrocytes. © 2007 Asian Network For Scientific Information

The effect of spatial learning on the number of astrocytes in rat dentate gyrus

In this study, we evaluated the effect of spatial learning on the number of astrocytes in the rat dentate gyrus with Morris water maze. Fifteen male albino Wistar rats were divided into three groups as control, reference memory and working memory groups. Each group was consisted of 5 rats. After spatial learning, the brains were histologically examined; the slides were stained with phosphotungstic acid hematoxylin (PTAH) staining to show the astrocytes. We found significant difference in the number of astrocytes in dentate gyrus between control and reference memory groups, and between control and working memory groups as well. When compared two learning groups there was a significant difference in the number of astrocytes between them, being higher in the working memory group. We concluded that the number of astrocytes increased due to spatial learning and this increase can be affected to the period of learning. Our studies of spatial learning and effect of learning techniques (reference and working memory) showed that the technique that has longer period of learning has more effect on the number of astrocytes

TyG index and insulin resistance in beta-thalassemia

Insulin resistance (IR) underlies some glucose metabolism abnormalities in thalassemia major. Recently, triglyceride glucose index (TyG) has been proposed for evaluating insulin resistance as a simple, low cost, and accessible tool. In this study, the TyG index were studied for IR monitoring in beta-thalassemia major (βTM) patients. The participants were 90 βTM patients on chronic regular transfusion therapy. The TyG index was computed based on fasting plasma glucose (FPG) and triglyceride (TG). The time gap between the first and the second TyG index survey (TyG.1 and TyG.2) was 2 years. The agreement between TyG and HOMA-IR were studied with the extension of limit of agreement (LOA). We included 90 patients 53.3 % men (n = 48). Among them, 14.4 % (14.6 % male, 14.3 % female) had impaired fasting glucose level (e.g., 100–125 mg/dl) at first test. It rose to 37.8 % (27.1 % male, 50 % female) during 2 years. Based on TyG.1, the 34.4 % of patients was detected as IR cases. After 2 years, the percent of IR based on TyG.2 was 82.2 %. The mean differences between TyG.1 and TyG.2 and their differences from the considered cutoff values were significant (P < 0.001). The prediction limits between TyG and HOMA-IR had good agreement. These data may suggest the use of TyG index for detection/monitoring of IR in βTM patients. © 2015, Research Society for Study of Diabetes in India

Pigment Melanin: Pattern for Iris Recognition

Recognition of iris based on Visible Light (VL) imaging is a difficult problem because of the light reflection from the cornea. Nonetheless, pigment melanin provides a rich feature source in VL, unavailable in Near-Infrared (NIR) imaging. This is due to biological spectroscopy of eumelanin, a chemical not stimulated in NIR. In this case, a plausible solution to observe such patterns may be provided by an adaptive procedure using a variational technique on the image histogram. To describe the patterns, a shape analysis method is used to derive feature-code for each subject. An important question is how much the melanin patterns, extracted from VL, are independent of iris texture in NIR. With this question in mind, the present investigation proposes fusion of features extracted from NIR and VL to boost the recognition performance. We have collected our own database (UTIRIS) consisting of both NIR and VL images of 158 eyes of 79 individuals. This investigation demonstrates that the proposed algorithm is highly sensitive to the patterns of cromophores and improves the iris recognition rate.Comment: To be Published on Special Issue on Biometrics, IEEE Transaction on Instruments and Measurements, Volume 59, Issue number 4, April 201

Vietnam Inbound M&A Activity: the Role of Government Policy and Regulatory Environment

With a robust recent history of reform and opening, joining of the World Trade&nbsp;Organization, and negotiating a myriad of regional and global trade agreements,&nbsp;Vietnam has emerged as a promising destination for foreign direct investment(FDI) and cross-border mergers and acquisitions (M&amp;A). In this paper, we providean overview of Vietnam&rsquo;s inbound mergers and acquisitions and review the twomain driving forces of inbound M&amp;A, which are the legal framework reformprocess and the equitization of State-owned enterprises. We close by providingdirections for future research in the area of cross-border M&amp;As