A case of non-resolving cough and weight loss.

Sarcoidosis is a chronic granulomatous multi-system disease with a clinical picture often mimicking tuberculosis. We present a case of a patient who presented with a clinical picture akin to both of these granulomatous disorders and was started on anti-tuberculous regimen despite the lack of any solid evidence pointing towards tuberculosis. As a result her clinical condition continued to deteriorate for months until finally a bronchoscopic biopsy established her disease process as sarcoidosis. She was then started on systemic corticosteroid therapy for sarcoidosis and during the ensuing period has shown marked improvement in her clinical picture with near normalization of the biochemical and radiographic parameters of her pathology. This case illustrates the need for vigilant interpretation of the clinical scenario in patients such as these where a misdiagnosis may lead to significant patient distress as well as weighing down on the economic and health resources

Experimental investigation of wing tip vortex

Particle image velocimetery was used in a low-speed wind tunnel to investigate and characterize wing tip vortex structures. A rectangular wing of a SWIM model was used as a vortex generator in two different configurations, (i) plain wing and (ii) flapped wing with trailing edge flap extended at 20 degrees. Vortex flow quantities and their dependence on angle of attack at a chord base Reynolds Number of 32.8x103 and 43.8x103 were evaluated. Assessment of measured data reveals that the peak values of tangential velocities, vortex strength and vorticities are directly proportional to the angle of attack. The vortex core radius value grows slowly as the angle of attack is increased. Both plain and flapped configurations showed similar trends. The peak tangential velocities and circulation distribution doubled when the flapped configuration was used instead of the plain wing

Experimental investigation of plain- and flapped-wing tip vortices

Particle image velocimetry was used in a low-speed wind tunnel to investigate and characterize wing tip vortex structures. A rectangular wing of a subsonic wall interference model was used as a vortex generator in two different configurations: 1) plain wing and 2) flapped wing with the trailing-edge flap extended at 20 degrees. Vortex flow quantities and their dependence on angle of attack at Reynolds numbers of 32:8 � 103 and 43:8 � 103 were evaluated. Assessment of measured data reveals that the peak values of tangential velocities, vortex strength, and vorticities are directly proportional to the angle of attack. The vortex core radius value grows slowly as the angle of attack is increased. Both plain and flapped configurations showed similar trends. The peak tangential velocities and circulation almost doubled when the flapped configuration was used instead of the plain wing

Low Reynolds number effect on CFD prediction of bio inspired aerodynamics

This work is motivated by the need for the implementation of the best numerical modelsfor low Reynolds flows and presents the state–of–the–art of the implemented models for thetransition of the laminar-turbulent predictions. The numerical models are applied to investigatethe aerodynamic characteristics and flow behavior around bird–like airfoils. Two DimensionalReynolds Averaged Navier Stokes (2D RANS) and Three-Dimensional Unsteady (3D U-RANS)methods are applied at a Reynolds number of105, whereas two-dimensional laminar simulationsand three-dimensional Large Eddy Simulation are employed for the known Owl-like airfoil atReynolds number of2.3×104. The numerical results of flow fields around Owl-like airfoil atthe latter Reynolds number using two-dimensional laminar and 3DLES predict correctly theunsteadiness of the aerodynamic coefficients. The 2D and 3D RANS methods are predicting wellthe aerodynamics characteristics for the man-made-bird-like airfoil at Reynolds number of105

Experimental optimization of composite collapsible tubular energy absorber device

A four-phase program to improve the specific energy absorbed by axially crushed composite collapsible tubular energy absorber devices was undertaken. In the first phase, examining of the crushing behaviour of non-triggered tubes was carried out. The second phase is aimed at obtaining the best position for the triggered wall. The third phase focuses on the effects of material sizing in order to understand the influence of triggered wall length on the responses of composite circular tubes to the axial crushing load. The results of these three phases of the study contribute to the fourth whose objective is to optimize the shape geometry of the cross-section area to further improving in tube energy absorption capability. The experimental results demonstrated the strong potential benefits of optimizing the material distribution. The sizing and shape optimization of composite collapsible tubes exhibited a pronounced effect on their capability to absorb high specific energy under axial compressive load

Performance evaluation of convolutional neural network for hand gesture recognition using EMG

peer reviewedElectromyography (EMG) is a measure of electrical activity generated by the contraction of muscles. Non-invasive surface EMG (sEMG)-based pattern recognition methods have shown the potential for upper limb prosthesis control. However, it is still insufficient for natural control. Recent advancements in deep learning have shown tremendous progress in biosignal processing. Multiple architectures have been proposed yielding high accuracies (>95%) for offline analysis, yet the delay caused due to optimization of the system remains a challenge for its real-time application. From this arises a need for optimized deep learning architecture based on fine-tuned hyper-parameters. Although the chance of achieving convergence is random, however, it is important to observe that the performance gain made is significant enough to justify extra computation. In this study, the convolutional neural network (CNN) was implemented to decode hand gestures from the sEMG data recorded from 18 subjects to investigate the effect of hyper-parameters on each hand gesture. Results showed that the learning rate set to either 0.0001 or 0.001 with 80-100 epochs significantly outperformed (p < 0.05) other considerations. In addition, it was observed that regardless of network configuration some motions (close hand, flex hand, extend the hand and fine grip) performed better (83.7% ± 13.5%, 71.2% ± 20.2%, 82.6% ± 13.9% and 74.6% ± 15%, respectively) throughout the course of study. So, a robust and stable myoelectric control can be designed on the basis of the best performing hand motions. With improved recognition and uniform gain in performance, the deep learning-based approach has the potential to be a more robust alternative to traditional machine learning algorithms

Barriers to using cloud computing in sustainable construction in Nigeria : A fuzzy synthetic evaluation

This study aims to assess the barriers impeding cloud computing (CC) applicability in sustainable construction. A total of 11 barriers in the use of CC were identified for the literature review. A questionnaire survey was used to collect the data from construction stakeholders. In total, 101 valid responses were obtained and analyzed using mean ranking, normalized value (NV), overlapping analysis, Kruskal–Wallis H test, exploratory factor analysis (EFA), and fuzzy synthetic evaluation (FSE). The EFA extracted four interrelated components: social, economic, expertise, and connectivity. These components were exported for mathematical analyzing using the FSE technique. As a result, the FSE indicated that connectivity is the highest-impacted component, while the overall impact level of barriers is inclined to high regarding CC applicability in sustainable construction. This is due to other components having an average to high impact level. In this regard, the findings reflect the actual current status of developing countries in using CC in sustainable construction. These research findings will allow construction stakeholders to take proactive steps toward increasing the use of CC in their current and future sustainable construction. Decision-makers could also make accurate decisions that are well-informed in managing CC barriers. This paper provides stakeholders, researchers, and decision-makers with a list of CC barriers that hinder developing countries

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

COVID-19 vaccine acceptance and hesitancy in low- and middle-income countries

Widespread acceptance of COVID-19 vaccines is crucial for achieving sufficient immunization coverage to end the global pandemic, yet few studies have investigated COVID-19 vaccination attitudes in lower-income countries, where large-scale vaccination is just beginning. We analyze COVID-19 vaccine acceptance across 15 survey samples covering 10 low- and middle-income countries (LMICs) in Asia, Africa and South America, Russia (an upper-middle-income country) and the United States, including a total of 44,260 individuals. We find considerably higher willingness to take a COVID-19 vaccine in our LMIC samples (mean 80.3%; median 78%; range 30.1 percentage points) compared with the United States (mean 64.6%) and Russia (mean 30.4%). Vaccine acceptance in LMICs is primarily explained by an interest in personal protection against COVID-19, while concern about side effects is the most common reason for hesitancy. Health workers are the most trusted sources of guidance about COVID-19 vaccines. Evidence from this sample of LMICs suggests that prioritizing vaccine distribution to the Global South should yield high returns in advancing global immunization coverage. Vaccination campaigns should focus on translating the high levels of stated acceptance into actual uptake. Messages highlighting vaccine efficacy and safety, delivered by healthcare workers, could be effective for addressing any remaining hesitancy in the analyzed LMICs.Publisher PDFPeer reviewe