Communication systems using LabVIEW

LabVIEW enables engineers to simulate various communication and control systems. LabVIEW helps to create Virtual Instruments (VIs) which are the files with which the user interacts to accomplish the required task. In this paper, the AM system implementation in LabVIEW is explained in detail along with the observed waveforms. The AM system is implemented using two separate VIs i.e. Transmitter_AM.vi and Receiver_AM.vi. Each VI has two parts: Front Panel and the Block Diagram. The Front Panel is usually the interface the user interacts with and observes results. The block diagram contains the blocks used to implement the functionality required for the operation of the VI. The individual blocks in the block diagram are called the sub VIs. The user may or may not need to make changes in the block diagram of the VI during the execution of the LabVIEW program

Gestational diabetes mellitus in Cameroon: prevalence, risk factors and screening strategies

Copyright \ua9 2024 Sobngwi, Sobngwi-Tambekou, Katte, Echouffo-Tcheugui, Balti, Kengne, Fezeu, Ditah, Tchatchoua, Dehayem, Unwin, Rankin, Mbanya and Bell.Background: The burden of gestational diabetes (GDM) and the optimal screening strategies in African populations are yet to be determined. We assessed the prevalence of GDM and the performance of various screening tests in a Cameroonian population. Methods: We carried out a cross-sectional study involving the screening of 983 women at 24-28 weeks of pregnancy for GDM using serial tests, including fasting plasma (FPG), random blood glucose (RBG), a 1-hour 50g glucose challenge test (GCT), and standard 2-hour oral glucose tolerance test (OGTT). GDM was defined using the World Health Organization (WHO 1999), International Association of Diabetes and Pregnancy Special Group (IADPSG 2010), and National Institute for Health Care Excellence (NICE 2015) criteria. GDM correlates were assessed using logistic regressions, and c-statistics were used to assess the performance of screening strategies. Findings: GDM prevalence was 5\ub79%, 17\ub77%, and 11\ub70% using WHO, IADPSG, and NICE criteria, respectively. Previous stillbirth [odds ratio: 3\ub714, 95%CI: 1\ub727-7\ub776)] was the main correlate of GDM. The optimal cut-points to diagnose WHO-defined GDM were 5\ub79 mmol/L for RPG (c-statistic 0\ub762) and 7\ub71 mmol/L for 1-hour 50g GCT (c-statistic 0\ub776). The same cut-off value for RPG was applicable for IADPSG-diagnosed GDM while the threshold was 6\ub75 mmol/L (c-statistic 0\ub761) for NICE-diagnosed GDM. The optimal cut-off of 1-hour 50g GCT was similar for IADPSG and NICE-diagnosed GDM. WHO-defined GDM was always confirmed by another diagnosis strategy while IADPSG and GCT independently identified at least 66\ub79 and 41\ub70% of the cases. Interpretation: GDM is common among Cameroonian women. Effective detection of GDM in under-resourced settings may require simpler algorithms including the initial use of FPG, which could substantially increase screening yield

Giant Cell Myocarditis in Children: Elusive Giant Cells Might Not Be the Only Clue

Giant cell myocarditis (GCM) is a form of fulminant myocarditis that is rapidly progressive and frequently lethal even in children. Over the course of 20 years, a definitive histopathologic diagnosis of GCM has been made at our institution in only two pediatric patients, and in neither instance was the diagnosis of GCM rendered on initial cardiac biopsy. We present the two patients and highlight the similarities in their clinical presentation and their challenging and inconclusive- albeit histologically similar- initial cardiac biopsy findings. </jats:p