Hybrid machine learning architecture for automated detection and grading of retinal images for diabetic retinopathy

Purpose: Diabetic retinopathy is the leading cause of blindness, affecting over 93 million people. An automated clinical retinal screening process would be highly beneficial and provide a valuable second opinion for doctors worldwide. A computer-aided system to detect and grade the retinal images would enhance the workflow of endocrinologists. Approach: For this research, we make use of a publicly available dataset comprised of 3662 images. We present a hybrid machine learning architecture to detect and grade the level of diabetic retinopathy (DR) severity. We also present and compare simple transfer learning-based approaches using established networks such as AlexNet, VGG16, ResNet, Inception-v3, NASNet, DenseNet, and GoogLeNet for DR detection. For the grading stage (mild, moderate, proliferative, or severe), we present an approach of combining various convolutional neural networks with principal component analysis for dimensionality reduction and a support vector machine classifier. We study the performance of these networks under different preprocessing conditions. Results: We compare these results with various existing state-of-the-art approaches, which include single-stage architectures.We demonstrate that this architecture is more robust to limited training data and class imbalance. We achieve an accuracy of 98.4% for DR detection and an accuracy of 96.3% for distinguishing severity of DR, thereby setting a benchmark for future research efforts using a limited set of training images. Conclusions: Results obtained using the proposed approach serve as a benchmark for future research efforts. We demonstrate as a proof-of-concept that an automated detection and grading system could be developed with a limited set of images and labels. This type of independent architecture for detection and grading could be used in areas with a scarcity of trained clinicians based on the necessity

Techniques to Enhance the Quality of Service of Multi Hop Relay Networks

AbstractBroadband internet access through the user equipment has become the hot research topic. The shadowing and multipath issues restrict the high performance nature of 4G cells. In Multi hop Relay (MHR) networks, Relay Stations (RS) are introduced to improve coverage and capacity of the system. There exist some issues like path selection and RSs deployment, which severely affects the Quality of Service (QoS) of the system. In this paper, to improve the QoS of MHR networks, Load Aware Routing Metric (LARM) based path selection and a low complex Burst Profile (BP) based RS deployment schemes are discussed

Stability indicating RP-HPLC method for the estimation of flucloxacillin sodium in a tablet dosage form

A Simple, accurate and precise method was developed and validated for the determination of flucloxacillin sodium in its tablet dosage form. The separation was eluted on xterra c18 column (4.6x150mm, 5micron) using a mixture of octane buffer and methanol as mobile phase in a ratio of (30:70) which was pumped through column at a flow rate of  1ml/min. Optimised wavelength for flucloxacillin was 237nm, the retention time was 2.305minutes and the percentage purity was found to be 98.14%. System suitability parameters such as theoretical plate and tailing factor for flucloxacillin sodium was found to be 2991.64 and 1.90 respectively, the proposed method was validated as per ICH guidelines (ICH, Q2 AND (R1)) the method was found to be linear at the concentration range of 20-100µg/ml and the correlation coefficient (r2) value was found to be 0.9994 percentage RSD for precision was 0.9% and percentage RSD for ruggedness was 0.5%. The precision study was precise, robust and repeatable. The LOD and LOQ values are 2.98 and 9.98 respectively. Hence the suggested RP-HPLC method can be used for routine analysis for flucloxacillin sodium in tablet dosage form

Relative Pose from Deep Learned Depth and a Single Affine Correspondence

We propose a new approach for combining deep-learned non-metric monocular depth with affine correspondences (ACs) to estimate the relative pose of two calibrated cameras from a single correspondence. Considering the depth information and affine features, two new constraints on the camera pose are derived. The proposed solver is usable within 1-point RANSAC approaches. Thus, the processing time of the robust estimation is linear in the number of correspondences and, therefore, orders of magnitude faster than by using traditional approaches. The proposed 1AC+D solver is tested both on synthetic data and on 110395 publicly available real image pairs where we used an off-the-shelf monocular depth network to provide up-to-scale depth per pixel. The proposed 1AC+D leads to similar accuracy as traditional approaches while being significantly faster. When solving large-scale problems, e.g., pose-graph initialization for Structure-from-Motion (SfM) pipelines, the overhead of obtaining ACs and monocular depth is negligible compared to the speed-up gained in the pairwise geometric verification, i.e., relative pose estimation. This is demonstrated on scenes from the 1DSfM dataset using a state-of-the-art global SfM algorithm. Source code: https://github.com/eivan/one-ac-pos

Radio Astronomy

Contains reports on four research projects.Joint Services Electronics Program (Contract DAAB07-71-C-0300)California Institute of Technology (Contract 952568)National Aeronautics and Space Administration (Contract NAS1-10693)National Science Foundation (Grant GP-21348A#2

The relationship of air pollution and surrogate markers of endothelial dysfunction in a population-based sample of children

<p>Abstract</p> <p>Background</p> <p>This study aimed to assess the relationship of air pollution and plasma surrogate markers of endothelial dysfunction in the pediatric age group.</p> <p>Methods</p> <p>This cross-sectional study was conducted in 2009-2010 among 125 participants aged 10-18 years. They were randomly selected from different areas of Isfahan city, the second large and air-polluted city in Iran. The association of air pollutants' levels with serum thrombomodulin (TM) and tissue factor (TF) was determined after adjustment for age, gender, anthropometric measures, dietary and physical activity habits.</p> <p>Results</p> <p>Data of 118 participants was complete and was analyzed. The mean age was 12.79 (2.35) years. The mean pollution standards index (PSI) value was at moderate level, the mean particular matter measuring up to 10 μm (PM₁₀) was more than twice the normal level. Multiple linear regression analysis showed that TF had significant relationship with all air pollutants except than carbon monoxide, and TM had significant inverse relationship with ozone. The odds ratio of elevated TF was significantly higher in the upper vs. the lowest quartiles of PM₁₀, ozone and PSI. The corresponding figures were in opposite direction for TM.</p> <p>Conclusions</p> <p>The relationship of air pollutants with endothelial dysfunction and pro-coagulant state can be an important factor in the development of atherosclerosis from early life. This finding should be confirmed in future longitudinal studies. Concerns about the harmful effects of air pollution on children's health should be considered a top priority for public health policy; it should be underscored in primordial and primary prevention of chronic diseases.</p

Silicone models as basic training and research aid in endovascular neurointervention-a single-center experience and review of the literature

The rapid development and wider use of neurointerventional procedures have increased the demand for a comprehensive training program for the trainees, in order to safely and efficiently perform these procedures. Artificial vascular models are one of the dynamic ways to train the new generation of neurointerventionists to acquire the basic skills of material handling, tool manipulation through the vasculature, and development of hand-eye coordination. Herein, the authors present their experience regarding a long-established training program and review the available literature on the advantages and disadvantages of vascular silicone model training. Additionally, they present the current research applications of silicone replicas in the neurointerventional arena

Regulatory T cells and their role in rheumatic diseases: a potential target for novel therapeutic development

Regulatory T cells have an important role in limiting immune reactions and are essential regulators of self-tolerance. Among them, CD4+CD25high regulatory T cells are the best-described subset. In this article, we summarize current knowledge on the phenotype, function, and development of CD4+CD25high regulatory T cells. We also review the literature on the role of these T cells in rheumatic diseases and discuss the potential for their use in immunotherapy

The Immune System in Stroke

Stroke represents an unresolved challenge for both developed and developing countries and has a huge socio-economic impact. Although considerable effort has been made to limit stroke incidence and improve outcome, strategies aimed at protecting injured neurons in the brain have all failed. This failure is likely to be due to both the incompleteness of modelling the disease and its causes in experimental research, and also the lack of understanding of how systemic mechanisms lead to an acute cerebrovascular event or contribute to outcome. Inflammation has been implicated in all forms of brain injury and it is now clear that immune mechanisms profoundly influence (and are responsible for the development of) risk and causation of stroke, and the outcome following the onset of cerebral ischemia. Until very recently, systemic inflammatory mechanisms, with respect to common comorbidities in stroke, have largely been ignored in experimental studies. The main aim is therefore to understand interactions between the immune system and brain injury in order to develop novel therapeutic approaches. Recent data from clinical and experimental research clearly show that systemic inflammatory diseases -such as atherosclerosis, obesity, diabetes or infection - similar to stress and advanced age, are associated with dysregulated immune responses which can profoundly contribute to cerebrovascular inflammation and injury in the central nervous system. In this review, we summarize recent advances in the field of inflammation and stroke, focusing on the challenges of translation between pre-clinical and clinical studies, and potential anti-inflammatory/immunomodulatory therapeutic approaches

Ambient air pollution and thrombosis

Abstract Air pollution is a growing public health concern of global significance. Acute and chronic exposure is known to impair cardiovascular function, exacerbate disease and increase cardiovascular mortality. Several plausible biological mechanisms have been proposed for these associations, however, at present, the pathways are incomplete. A seminal review by the American Heart Association (2010) concluded that the thrombotic effects of particulate air pollution likely contributed to their effects on cardiovascular mortality and morbidity. The aim of the current review is to appraise the newly accumulated scientific evidence (2009–2016) on contribution of haemostasis and thrombosis towards cardiovascular disease induced by exposure to both particulate and gaseous pollutants. Seventy four publications were reviewed in-depth. The weight of evidence suggests that acute exposure to fine particulate matter (PM2.5) induces a shift in the haemostatic balance towards a pro-thrombotic/pro-coagulative state. Insufficient data was available to ascertain if a similar relationship exists for gaseous pollutants, and very few studies have addressed long-term exposure to ambient air pollution. Platelet activation, oxidative stress, interplay between interleukin-6 and tissue factor, all appear to be potentially important mechanisms in pollution-mediated thrombosis, together with an emerging role for circulating microvesicles and epigenetic changes. Overall, the recent literature supports, and arguably strengthens, the contention that air pollution contributes to cardiovascular morbidity by promoting haemostasis. The volume and diversity of the evidence highlights the complexity of the pathophysiologic mechanisms by which air pollution promotes thrombosis; multiple pathways are plausible and it is most likely they act in concert. Future research should address the role gaseous pollutants play in the cardiovascular effects of air pollution mixture and direct comparison of potentially susceptible groups to healthy individuals