Aerodynamic design of a cooled cooling air system for an aero gas turbine

This paper examines the aerodynamic design requirements of a cooled cooling air system for a large, high by-pass ratio, high overall pressure ratio aero-engine. This can be broken into aerodynamic sub-systems each with their own set of requirements and challenges. A low pressure system is required to deliver air bled from the bypass duct to a heat exchanger for use as a heat sink. Similarly, a high pressure system removes a portion of the hot core engine air from a location downstream of the compressor and ducts this to-and-from the HX for cooling. This cooled air must then be returned, across the main gas path, for use in component cooling. The challenge is to design these sub-systems such that satisfactorily perform their own function whilst integrating into the existing engine architecture. This paper presents an overview of a number of studies which use CFD to explore the design space and develop appropriate designs which were subsequently experimentally validated on several isothermal test facilities. Ultimately the feasibility of designing the aerodynamic sub-systems was demonstrated and a future design strategy established

On the solvency of firms: Can government's intervention reduce external financing of firms' workingcapital in Nigeria?

This chapter intends to examine the relationship between government incentives and the mode of firms' finance oftheir operation in Nigeria. Specifically, it does relate the solvency of the firm with the quality of their financing decisions andobserved if government incentives such as creation of export processing zones and industrial parks will affect the firm'sdecision of depending on external versus internal financing. Methodology/approach - The results presented in this chapterare based on analysis of a firm-level data taken from the 2014 firm-level survey of the World Bank's Enterprise Surveyproject for Nigeria. Different estimation techniques are applied for robustness and sensitivity. They include both theparametric and nonparametric regression approach. Findings - The robust estimations show that firms that benefit from thegovernment incentives tend to use more of internal funding to finance their operation unlike firms that are non-beneficiaries.In addition smaller firms are going to benefit more from the incentives than older firms, and less profitable firms are alsogoing to use more of internal financing if they benefit from government incentives. Practical implications - This chapter willbe helpful for both research and teaching for undergraduate and post-graduate students. Importantly, its analysis and resultwill be useful for policy makers and their allies. Originality/value - This chapter discusses solvency issues by considering thefinancing decision of firms, which is an important aspect in the going concern of firms. Copyright © 2016 by Emerald GroupPublishing Limited

3D printing of weft knitted textile based structures by selective laser sintering of nylon powder

3D printing is a form of additive manufacturing whereby the building up of layers of material creates objects. The selective laser sintering process (SLS) uses a laser beam to sinter powdered material to create objects. This paper builds upon previous research into 3D printed textile based material exploring the use of SLS using nylon powder to create flexible weft knitted structures. The results show the potential to print flexible textile based structures that exhibit the properties of traditional knitted textile structures along with the mechanical properties of the material used, whilst describing the challenges regarding fineness of printing resolution. The conclusion highlights the potential future development and application of such pieces

Transport poverty meets the digital divide : accessibility and connectivity in rural communities

Peer reviewedPublisher PD

Adaptively monitoring streamflow using a stereo computer vision system

The gauging of free surface flows in waterways provides the foundation for monitoring and managing the water resources of built and natural environments. A significant body of literature exists around the techniques and benefits of optical surface velocimetry methods to estimate flows in waterways without intrusive instruments or structures. However, to date, the operational application of these surface velocimetry methods has been limited by site configuration and inherent challenging optical variability across different natural and constructed waterway environments. This work demonstrates a significant advancement in the operationalisation of non-contact stream discharge gauging applied in the computer vision stream gauging (CVSG) system through the use of methods for remotely estimating water levels and adaptively learning discharge ratings over time. A cost-effective stereo camera-based stream gauging device (CVSG device) has been developed for streamlined site deployments and automated data collection. Evaluations between reference state-of-the-art discharge measurement technologies using DischargeLab (using surface structure image velocimetry), Hydro-STIV (using space–time image velocimetry), acoustic Doppler current profilers (ADCPs), and gauging station discharge ratings demonstrated that the optical surface velocimetry methods were capable of estimating discharge within a 5 %–15 % range between these best available measurement approaches. Furthermore, results indicated model machine learning approaches leveraging data to improve performance over a period of months at the study sites produced a marked 5 %–10 % improvement in discharge estimates, despite underlying noise in stereophotogrammetry water level or optical flow measurements. The operationalisation of optical surface velocimetry technology, such as CVSG, offers substantial advantages towards not only improving the overall density and availability of data used in stream gauging, but also providing a safe and non-contact approach for effectively measuring high-flow rates while providing an adaptive solution for gauging streams with non-stationary characteristics.</p

Management of primary hepatic malignancies during the COVID-19 pandemic: recommendations for risk mitigation from a multidisciplinary perspective

Around the world, recommendations for cancer treatment are being adapted in real time in response to the pandemic of COVID-19. We, as a multidisciplinary team, reviewed the standard management options, according to the Barcelona Clinic Liver Cancer classification system, for hepatocellular carcinoma. We propose treatment recommendations related to COVID-19 for the different stages of hepatocellular carcinoma (ie, 0, A, B, and C), specifically in relation to surgery, locoregional therapies, and systemic therapy. We suggest potential strategies to modify risk during the pandemic and aid multidisciplinary treatment decision making. We also review the multidisciplinary management of intrahepatic cholangiocarcinoma as a potentially curable and incurable diagnosis in the setting of COVID-19

Micrometastasis Detection Guidance by Whole-Slide Image Texture Analysis in Colorectal Lymph Nodes

Introduction/ Background Cancer is a disease that affects millions worldwide and accurate determination of whether lymph nodes (LNs) near the primary tumor contain metastatic foci is of critical importance for proper patient management. Histopathological evaluation is the only accepted method to make that determination. However, the current standard of care only examines a single central histological section per LN and yields an unacceptable false-negative rate. Aims To help pathologists in their examination we propose a method that extracts textural features from histopathological LN whole slide images (WSI) and then applies support vector machines (SVMs) to automatically identify regions suspicious for metastatic foci. Methods The database consisted of WSI from 44 LNs. Sections were stained with hematoxylin-eosin and examined at 20x (0.45μm resolution). Twenty-eight of the LNs were identified by an expert pathologist as positive for cancer (P), and the remaining sixteen were negative (N). This database was divided into two groups. Group 1 (15P and 5N) was used for training and Group 2 (13P and 11N) was used for testing the classification technique. For all analysis each WSI was divided into non-overlapping 1000 x 1000 pixel sub-images that will be referred to as high-power fields (HPFs). For each LN in Group 1, at least one WSI was annotated by a pathologist to identify rectangular, HPF-scale regions as locally cancerous or locally non-cancerous. From these annotated slides, 924 HPFs (462 P and 462 N) were obtained. For each of these HPFs, statistical features based on gray-level co-occurrence matrices [1] and Law’s texture energy measures [2, 3] were extracted from 9 derived images [4]. The extracted features were submitted to a sequential forward selection (SFS) method [5] to select few non-redundant features providing best class separation (cancerous vs. non-cancerous region). Combinations of the selected features were tested on the 924 HPFs using k-fold cross-validation to find those that produced the best results and consequently to train our SVM-based classifier. In Group 2, WSI were not annotated for cancerous and non-cancerous zones on a HPF scale. Each LN, however, had been labeled by a pathologist as positive or negative for cancer. For each WSI, each section was divided into contiguous HPFs, and those which mainly contain fatty tissue, background, and tears were automatically excluded. Each selected HPFs was classified as cancerous or non-cancerous using the previously trained classifier to obtain the total number of cancer-classified per LN. A receiver operating characteristics (ROC) curve was traced by changing the discriminator threshold (T) used to label the LN as P for cancer as a function of the total number of cancer-classified HPFs. Results During training, 5 Laws features were selected by SFS. Highly satisfactory k-fold cross-validation with a F-score of 0.996 ± 0.005 was obtained using only 2 statistical features computed at different scales. The ROC curve obtained by applying the SVM-classifier to the test set is shown in the next figure. Two valuable operating points can be identified which both guaranteed no false-negative. At T=11 we got 2 false-positives and an optimal F-score of 0.917, and with a more conservative approach, T=1, we got 7 false-positives and a F-score of 0.759. The top-left part of the slide displayed in next figure would have been proposed to the pathologist as the most suspicious region of the cancerous LN

SCAMP:standardised, concentrated, additional macronutrients, parenteral nutrition in very preterm infants: a phase IV randomised, controlled exploratory study of macronutrient intake, growth and other aspects of neonatal care

<p>Abstract</p> <p>Background</p> <p>Infants born <29 weeks gestation are at high risk of neurocognitive disability. Early postnatal growth failure, particularly head growth, is an important and potentially reversible risk factor for impaired neurodevelopmental outcome. Inadequate nutrition is a major factor in this postnatal growth failure, optimal protein and calorie (macronutrient) intakes are rarely achieved, especially in the first week. Infants <29 weeks are dependent on parenteral nutrition for the bulk of their nutrient needs for the first 2-3 weeks of life to allow gut adaptation to milk digestion. The prescription, formulation and administration of neonatal parenteral nutrition is critical to achieving optimal protein and calorie intake but has received little scientific evaluation. Current neonatal parenteral nutrition regimens often rely on individualised prescription to manage the labile, unpredictable biochemical and metabolic control characteristic of the early neonatal period. Individualised prescription frequently fails to translate into optimal macronutrient delivery. We have previously shown that a standardised, concentrated neonatal parenteral nutrition regimen can optimise macronutrient intake.</p> <p>Methods</p> <p>We propose a single centre, randomised controlled exploratory trial of two standardised, concentrated neonatal parenteral nutrition regimens comparing a standard macronutrient content (maximum protein 2.8 g/kg/day; lipid 2.8 g/kg/day, dextrose 10%) with a higher macronutrient content (maximum protein 3.8 g/kg/day; lipid 3.8 g/kg/day, dextrose 12%) over the first 28 days of life. 150 infants 24-28 completed weeks gestation and birthweight <1200 g will be recruited. The primary outcome will be head growth velocity in the first 28 days of life. Secondary outcomes will include a) auxological data between birth and 36 weeks corrected gestational age b) actual macronutrient intake in first 28 days c) biomarkers of biochemical and metabolic tolerance d) infection biomarkers and other intravascular line complications e) incidence of major complications of prematurity including mortality f) neurodevelopmental outcome at 2 years corrected gestational age</p> <p>Trial registration</p> <p>Current controlled trials: <a href="http://www.controlled-trials.com/ISRCTN76597892">ISRCTN76597892</a>; EudraCT Number: 2008-008899-14</p

A novel RFC1 repeat motif (ACAGG) in two Asia-Pacific CANVAS families

Cerebellar ataxia, neuropathy and vestibular areflexia syndrome (CANVAS) is a progressive late-onset, neurological disease. Recently, a pentanucleotide expansion in intron 2 of RFC1 was identified as the genetic cause of CANVAS. We screened an Asian-Pacific cohort for CANVAS and identified a novel RFC1 repeat expansion motif, (ACAGG)exp, in three affected individuals. This motif was associated with additional clinical features including fasciculations and elevated serum creatine kinase. These features have not previously been described in individuals with genetically-confirmed CANVAS. Haplotype analysis showed our patients shared the same core haplotype as previously published, supporting the possibility of a single origin of the RFC1 disease allele. We analysed data from >26 000 genetically diverse individuals in gnomAD to show enrichment of (ACAGG) in non-European populations