Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

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

CFD studies of the effect of holes and angles of upstream duct of horizontal axis wind turbines

This work presents an approach to the analysis of duct-augmented wind turbines using Computational Fluid Dynamics (CFD). The main objective is to find the optimum duct shape and design that gives maximum boost to the performance of wind turbines. A duct surrounding the rotor is able to increase the power coefficient above the Betz limit, so it has attracted great attention for many years. In this work, an extensive analysis of the performance of duct augmented wind turbines is presented, considering the influence of various duct angles and axial holes in the diffuser on the efficiency, in which a new formulation for the far-wake velocity is proposed. This study consists of two main parts. The first part compares the experimental performance of a conventional wind turbine with the identical turbine modeled and solved using CFD. Once the CFD results are validated, the second part presents an extensive parametric study by integrating a convergent duct with different parametric designs into the wind turbine model. The study reveals that the CFD results are in close agreement with the experimental results. It is found that the presence of holes in the duct has a detrimental effect on performance. However, the increase in the angle of the duct enhanced the performance, and there was an average increase in power output by 96% with a duct angle of 20°

Prediction of Discharge Coefficient of Circular Side Orifice Through Machine Learning Technique

A sharp-crested circular side orifice is a crucial element when it comes to diverting flow from primary source to its subordinate source. Such a flow measurement instrument technique is of immense value in conservation and evaluation of drainage and irrigation networks. Usually, it is placed towards the side of a channel in order to regulate the flow of the fluid. Traditionally, coefficient of discharge was predicted through regression methods which are time-consuming and lack accuracy. Artificial Intelligence (AI) and its applications in this domain have bridged this gap by providing novel alternative methods which prove much more efficient. Repeated studies have pointed out that AI techniques generally give better results when it comes to a myriad of water variables such as rainfall-runoff, evaporation and evapotranspiration, streamflow, and dam water level changes. Total 261 dataset has been collected from the literature review comprising of the fully submerged orifice and for partially-submerged orifice with varying orifice diameter (D) of 5 cm, 10 cm and 15 cm. This study aims to provide a better estimate of prediction of discharge through circular sharp-crested orifice using Artificial Neural Network (ANN). The ANN model has been deployed to randomly select 80% of the data for training, 15% for validation and remaining 5% for testing. In the ANN model, Lavenberg-Marquardt algorithm was used as back-propagation step to assign weights in order to predict the output. The correlation coefficient (R), mean absolute error (MAE) and root mean squared error (RMSE) for complete data of fully and partially submerged circular side orifice are observed to be 0.9765, 0.0228 and 0.0172 respectively

Concentrated solar power integration with refinery process heaters

Crude oil heating is considered an energy-intensive process in the oil industry that requires a huge amount of heat to process the crude oil. There is scarcity of a thorough research that deals with the techno-economic viability of introducing renewable energy solutions to the refinery industry including its environmental benefits. Therefore, a renewable energy solution i.e. a parabolic trough system is reviewed and examined to support minimizing the burning of natural gas in crude heaters and relying on thermal heat from sun radiation to increase crude oil temperature prior to going into the fractionation column. The system is designed to support refinery operation during day time whereas system design and analysis were done from thermal and financial points of view. Furthermore, benefits such as natural gas savings, reduction in CO2 emissions, and total payback period are presented in the paper to reflect the feasibility of constructing such a solution. Moreover, a MATLAB simulation was carried out to define the design points for the solar field and related heat exchanger components. This is to assure that the system can operate during winter and summer seasons given that the direct normal irradiance (DNI) is typically variant throughout the year. It has been concluded that integrating a parabolic trough collector into the operation of an oil refinery, i.e. crude oil heater, can potentially result in natural gas savings of 555,515 MMBtu and can prevent 30,020 tons of CO2 emissions annually. Moreover, the system is anticipated to result in cost savings of approximately 1.65 M $ per year

Enhancing Solar Still Performance Using Vacuum Pump and Geothermal Energy

Improvement in the performance of a solar still is investigated with the integration of a geothermal cooling system and a vacuum pump. Geothermal cooling is simulated to provide a cold, effective underground water temperature, which could reach 15⁻25 °C below ambient. Cooling is achieved by circulating water underground. As a result of this circulation, the cold fluid from the ground flows into a counter flow shell and tube heat exchanger. A vacuum pump is used to keep the solar still at a certain vacuum pressure. The sizes of the geothermal system and solar still are designed in such a way that the water outlet temperature from the ground and its flow rate are capable of condensing the entire vapor produced by the still. An analytical model was developed and then solved using the Newton⁻Raphson method for solving non-linear equations. A prototype was built to validate the analytical model. The results were in close agreement. A 305% increase in daily water productivity resulted from the proposed enhancements. After experimental validation, the effects of various parameters such as vacuum pressure, ambient temperature, and wind speed on the yield of geothermal solar still were examined. It was found that the increase in vacuum pressure enhanced performance, whereas the increase in wind speed had a detrimental effect on the yield of the solar still. A higher ambient temperature increased the yield of the solar still. Finally, the design of the heat exchanger for condensing the distilled water using geothermal cooling water was also investigated in terms of the increase in UA (the product of overall heat transfer coefficient and the area of heat exchanger) with inlet cooling geothermal water temperature

Insulation Performance of Building Components and Effect on the Cooling Load of Homes in Saudi Arabia

A common practice in the construction of residential and commercial buildings in Saudi Arabia is to insulate the outer walls and windows only. Other building components such as the roof, columns and slabs, and doors are usually neglected. Moreover, vital components such as the roof and windows are especially neglected in commercially built residential and commercial buildings. The aim of this study is to put this common impression and practice to the test by quantifying the contribution of every building component to the overall air-conditioning load of the building. The hypothesis evaluated in this paper is that despite the common practices, there could be an optimum selection of insulators for the building components that yields the lowest energy consumption and maximum savings not only in energy costs but also installation costs. The required air-conditioning load is determined using manual calculations and the HAP software package for 1022 possible configurations. The findings of the analysis point to the importance of the roof, as it is the major contributor to the thermal load, followed closely by columns and slabs, with 44.2% of the overall cooling load. It is found that a single wall consisting of 2 cm of cement plaster, 20 cm of cement–polyurethane brick, and 2 cm of cement plaster is less expensive and has higher thermal resistance than any of the more expensive double walls. The study found one scenario of possible configurations with the optimized selection of building materials and their insulation materials that provides the most effective insulation at the lowest cost

Improved Prediction Model and Utilization of Pump as Turbine for Excess Power Saving from Large Pumping System in Saudi Arabia

The throttling process is frequently encountered in many industrial practices utilizing Pressure Reducing Valves (PRVs). This process is typically used to control pressure and flow in pipeline networks. The practice of utilizing PRVs is considered simple and cheap in terms of installation cost and control. It dissipates the excess fluid energy that can be used for other purposes. This paper studies the feasibility of utilizing the Pump as Turbine (PAT) concept to partially recover the excess power dissipated from PRVs located at the discharge lines of refined product shipping pumps at one of the hydrocarbon distribution facilities in Saudi Arabia. Multiple PAT installation layouts have been studied to achieve this goal, selecting the optimum option to maximize the power recovery. The final selection of PAT was conducted to achieve a reasonable payback period. A new method for predicting the pump performance in reverse mode was developed depending on the manufacturer’s pump performance curves. The comparison of the proposed model with experimental data and previous models for three modes of operation reveals that the proposed model in this paper’s results either have the minimum deviation or the second minimum deviation out of all models. In the case of flow ratio prediction, the predicted deviation is merely 3.83%, −1.14%, and 1.35% in three modes of operation. For power prediction, the proposed model is the best and the only reliable model out of all with the least deviation of −7.48%, 0.07%, and −3.16% in three modes of operation. The economic analysis reveals the Capital Payback Time (CPP) for five optimum PATs is around 5 years. The new method was also validated against previous models showing more precise performance prediction of multistage centrifugal pumps running in turbine mode

Effect of tip clearance and rotor–stator axial gap on the efficiency of a multistage compressor

International audienceMultistage compressor is the most important constituent of gas turbines used in land, naval and aeronautical applications. Overall performance of such machinery depends mainly on the axial compressor performance. Due to the relative motion between rotor and stator blades, the flow field in this machinery is highly unsteady. Furthermore several technological effects like tip clearances, complexity of the blade shapes, variation of axial distance between stator and rotor, seal leakages and cooling holes among others complicate the machine. Therefore the study of a complicated, strongly three-dimensional flow field inside a compressor is considered to be one of the most difficult tasks to be performed by a CFD expert. The present work is the extensive numerical study of the effect of: (1) tip clearance of rotor blades and (2) the axial gap between rotor and stator on the overall performance of a multistage axial compressor. A commercial software package is used for this study. Reynolds-averaged Navier–Stokes equations are solved using Spalart–Allmaras model. A number of steady-state viscous flow simulations were run for both the tip clearance effect and different axial gaps between stator and rotor. All simulations were performed for the first stage, i.e. Stator–Rotor–Stator. Simulations were carried out with coarse, medium and fine meshes to find an optimum, mesh-independent solution. It has been found that larger tip clearance has a detrimental effect on the stage pressure ratio and efficiency of a multistage axial compressor. Similarly there exists a certain distance ratio between the stator1–rotor and rotor–stator2, where stage performance is optimum. Overall performance characteristics obtained through simulation for both the tip clearance and axial gap variation were also compared with the experimental studies and found to be in good agreement