Effect of Employing Vortex Generator on Curve Diffuser Performance

A diffuser is commonly applied in fluid-flow engineering applications with its simplest form of expanding area in the flow direction. A curve diffuser is one of its kinds often associated with secondary flow separation, thus improvement via installing passive flow control devices such as a vortex generator is to explore. The present work aims to numerically investigate the potential of four (4) types of vortex generators, i.e. triangle, rectangle, tapered, wishbone to improve the 90° curve diffuser performance. The results suggest that using vortex generators on a curve diffuser can improve performance. Triangle vortex generator provides the most optimum pressure recovery and flow uniformity of respectively 0.250 and 2.14.  This promises improvement of approximately 31.3% and 25.4% relative to the benchmark case, without vortex generator

Effect of angle of turn on loss characteristics and flow rectification of curve diffuser

Curve diffuser is often used in HVAC and wind tunnel systems to provide pressure recovery and avoid excessive energy loss to the surrounding environment. Performance of curve diffuser is disturbed mainly by the presences of flow separation and secondary flow vortices occurred due to the effect of turning angle, in which scarce literature found. In this study, the effect of turning angle from 30° to 180° configured with an area ratio of 1.60 to 4.00 and inflow Reynolds number of 5.934x104 – 1.783x105 on loss characteristics and flow rectification of curve diffuser is investigated with optimum configuration is proposed. Performance of curve diffuser is evaluated in terms of pressure recovery and flow uniformity using ANSYS CFD equipped with validated Standard k-ɛ model (ske) and enhanced wall treatment of y+ = 1.2 - 1.7. Results show that performance of pressure recovery and flow uniformity decreases respectively by 85.71% and 45.84% as the angle of turn increases from 30° to 180°. Curve diffuser with minimum angle of turn 30o , optimum area ratio 2.16 and intermediate Rein 8.163x104 turns out to be the best configuration to provide pressure recovery of 0.399 and flow uniformity of 3.630 m/s

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Analysis of antenna selection rate in bi-directional network coded multi-antenna relay

In bi-directional multi-antenna relaying with binary network coding, antenna selection can offer the benefits of full diversity at lower complexity. However, the rate at which the antennas are switched can also contribute to the complexity of the relaying scheme. In this paper, we explore a way of reducing this switching rate and study the implications of a reduced switching compared to the optimal antenna selection scheme

Performance Analysis of Two-Way Multiple-Antenna Relaying with Network Coding

Abstract — Two-way relaying is a way of improving the bandwidth efficiency of a half-duplex relay system. In such scenarios, network coding can also be applied to improve the system if there exist sufficient degrees of freedom to decode the received messages at the relay node. In this paper, we look at two specific transmission schemes employed at the multi-antenna relay node and analyze their performance by deriving both the upper bounds of their symbol error probability and their diversity order. I

Performance analysis of two-step bi-directional relaying with multiple antennas

In this paper we study decode-and-forward multi-antenna relay systems that achieve bi-directional communication in two time slots. We investigate different downlink broadcast schemes which employ binary or analog network coding at the relay. We also analyze and compare their performances in terms of diversity order and symbol error probability. It is shown that if exact downlink channel state information is available at the relay, using analog network coding in the form of multi-antenna maximal-ratio transmit beamforming to precode the information vectors at the relay gives the best performance. Then, we propose a Max-Min antenna selection with binary network coding scheme that can approach this performance with only partial channel state information