Video compression with 1-D directional transforms in H.264/AVC

Typically the same transforms, such as the 2-D Discrete Cosine Transform (DCT), are used to compress both images in image compression and prediction residuals in video compression. However, these two signals have different spatial characteristics. In, we analyzed the difference between these two signals and proposed 1-D directional transforms for prediction residuals. In this paper, we provide further experimental results using these transforms in the H.264/AVC codec and present other related information which can provide insights in understanding the use of these transforms in video coding applications

Transforms for the Motion Compensation Residual

The Discrete-Cosine-Transform (DCT) is the most widely used transform in image and video compression. Its use in image compression is often justified by the notion that it is the statistically optimal transform for first-order Markov signals, which have been used to model images. In standard video codecs, the motion-compensation residual (MC-residual) is also compressed with the DCT. The MC-residual may, however, possess different characteristics from an image. Hence, the question that arises is if other transforms can be developed that can perform better on the MC-residual than the DCT. Inspired by recent research on direction-adaptive image transforms, we provide an adaptive auto-covariance characterization for the MC-residual that shows some statistical differences between the MC-residual and the image. Based on this characterization, we propose a set of block transforms. Experimental results indicate that these transforms can improve the compression efficiency of the MC-residual

Directional wavelet transforms for prediction residuals in video coding

Various directional transforms have been developed recently to improve image compression. In video compression, however, prediction residuals of image intensities, such as the motion compensation residual or the resolution enhancement residual, are transformed. The applicability of the directional transforms on prediction residuals have not been carefully investigated. In this paper, we briefly discuss differing characteristics of prediction residuals and images, and propose directional transforms specifically designed for prediction residuals. We compare these transforms with the directional transforms proposed for images using prediction residuals. The results of the comparison indicate that our proposed directional transforms can provide better compression of prediction residuals than the directional transforms proposed for images

Cancer Patients and Oncology Nursing: Perspectives of Oncology Nurses in Turkey

Background and Aim: Burnout and exhaustion is a frequent problem in oncology nursing. The aim of this study is to evaluate the aspects of oncology nurses about their profession in order to enhance the standards of oncology nursing. Materials and Methods: This survey was conducted with 70 oncology nurses working at Hacettepe University Oncology Hospital. Data were collected between January–April 2012. Each participant provided a study form comprising questions about sociodemographic information; about difficulties, positive aspects and required skills for oncology nursing; and questions evaluating level of participation and clinical perception of oncology nursing. Results: Mean age of nurses was 29.9 ± 5.7 years. More than half of the participants were married (51.4%) and 30% had at least one child. Percent of nurses working in oncology for their entire work life was 75.8%. Most frequently expressed difficulties were exhaustion (58.6%), coping with the psychological problems of the patients (25.7%), and frequent deaths (24.3%); positive aspects were satisfaction (37.1%), changing the perceptions about life (30%), and empathy (14.3%); and required skills were patience (60%), empathy (57.1%), and experience (50%). For difficulties of oncology nursing, 28.3% of difficulties could be attributed to job-related factors, 30.3% to patient-related factors, and 77% of difficulties to individual factors. The independent predictors of participation level of the nurses were self-thoughts of skills and positive aspects of oncology nursing. Conclusion: According to the findings of this study, nurses declared that working with cancer patients increase burnout, they are insufficient in managing work stress and giving psychological care to patients, but their job satisfaction, clinical skills and awareness regarding priorities of life has increased.Keywords: Cancer patient, oncology nursing, participation, perceptio

experimental autoimmune encephalomyelitis (EAE) in C57BL/6 mouse model

Aim: The aim of this study was to investigate the beneficial effects of 18 beta-glycyrrhetinic acid (GA) on the experimental allergic encephalomyelitis (EAE) in C57BL/6 mice. GA is a natural substance found in the root of licorice and is used in traditional Chinese medicine. It has many pharmacological activities such as antioxidant, anti-inflammatory, and anti-cancer effects.Materials and methods: A total of 40 C57BL/6 mice were divided equally into four groups: (1) Control, (2) EAE, (3) GA and (4) GAthornEAE. 14 days after induction of EAE with MOG35-55 and pertussis toxin, mice were treated with GA at doses of 100 mg/kg/day for 7 days intraperitoneally.Results: To our results, oxidative stress and lipid peroxidations (elevated TBARS levels, decreased GPx, SOD, CAT, and GSH levels) were significantly (p<. 01) increased, causing EAE in brain tissue. Also, histopathological damage (Caspase-3 and IL-17 activity, p <=.01) and cytokine levels (TNF-alpha and IL-1 beta, p<. 01) were induced with EAE in mice brain tissue. On the other hand, GA treatment significantly (p<. 01) reversed oxidative histological and immunological alterations caused by EAE.Conclusions: In conclusion, the GA treatment can protect the brain tissue against EAE in mice with its antioxidant and anti-inflammatory properties