Fast Dual-LiDAR Reconstruction for Dynamic Wind Field Retrieval

With the advantages of high accuracy, high spatial resolution, and long measurement range, LiDAR is considered as the most suitable measurement technique to deliver quantitative imaging of wind fields. However, for complex wind fields, such as monitoring wind turbine wakes where both the temporal resolution and reconstruction speed are of great significance, the conventional LiDAR system lacks the temporal resolution to capture the fast changes of wind turbine wake fields. In this paper, a novel dynamic wind retrieval method is developed to improve temporal resolution using the unsynchronised dual-LiDAR scanning scheme. By exploiting the temporal redundancy information of the LiDAR Line-of-Sight (LoS) data in successive frames, a reduced number of LiDAR scanning points is required for the 2D horizontal wind field retrieval with the help of unsynchronised dual-LiDAR wind scanning scheme, low-rank data up-sampling and a divergence-free regularised wind retrieval algorithm. Numerical simulation is performed to validate the proposed method. Results show that the temporal resolution of LiDAR wind retrieval can be improved by a factor of 2 to 8 and provide acceptable results with good spatial resolution

Relationship between occupational stress, job burnout, and depressive symptoms among workers in an automobile manufacturing enterprise in Guangzhou

BackgroundThe operation mode of automobile manufacturing industry (AMI) makes workers have different degrees of occupational stress and burnout, which may lead to negative emotions and depressive symptoms. ObjectiveTo study the relationship between occupational stress, job burnout, and depressive symptoms in AMI workers. MethodsIn this study, 1300 workers from a Guangzhou AMI company were selected as subjects by cluster random sampling method. Occupational stress, job burnout, and depressive symptoms of the workers were assessed by using the Effort-Reward Imbalance (ERI) questionnaire, the Maslach Burnout Inventory general survey questionnaire, and the Patient Health Questionnaire-9, respectively. Hierarchical regression was used to analyze the effects of occupational stress and job burnout on depressive symptoms in AMI workers. Mediating effect model was used to analyze the mediating effect of job burnout on the relationship between occupational stress and depressive symptoms. ResultsThere were 1300 questionnaires distributed, 1228 valid questionnaires collected, with a 94.5% recovery rate. The ERI ratio of 1228 AMI workers was 1.06±0.72, and the positive rate of occupational stress was 37.3% (458/1228). The score of job burnout was 2.18±1.37, and the positive rate of job burnout was 62.6% (769/1228). The score of depressive symptoms was 10.27±6.42, and the positive rate of depressive symptoms was 47.1% (578/1228). The dimensional scores of effort and over-commitment in occupational stress as well as emotional exhaustion and depersonalization in job burnout of AMI workers were positively correlated with the depressive symptom scores (rs=0.415, 0.571, 0.573, 0.593, P＜0.05). The dimensional scores of reward and personal achievement were negatively correlated (rs=−0.454, −0.339, P＜0.05). The percentages of variance in depressive symptoms score explained by occupational stress and job burnout were 26.7% and 16.6%, respectively. Job burnout had a partial mediating effect between the three dimensions of occupational stress and depressive symptoms, and the mediating effect values were −0.2832 (95%CI: −0.3250– −0.2434), 0.3553 (95%CI: 0.3071–0.4041), and 0.4193 (95%CI: 0.3681–0.4725), respectively. ConclusionAMI workers' occupational stress affects job burnout, but also indirectly affects depressive symptoms. Job burnout partially mediates the association between occupational stress and depressive symptoms. Reducing occupational stress and burnout levels of AMI workers may alleviate depressive symptoms

Measurement of vertical oil-in-water two-phase flow using dual-modality ERT EMF system

Oil-in-water two-phase flows are often encountered in the upstream petroleum industry. The measurement of phase flow rates is of particular importance for managing oil production and water disposal and/or water reinjection. The complexity of oil-in-water flow structures creates a challenge to flow measurement. This paper proposes a new method of two-phase flow metering, which is based on the use of dual-modality system and multidimensional data fusion. The Electrical Resistance Tomography system (ERT) is used in combination with a commercial off-the-shelf Electromagnetic Flow meter (EMF) to measure the volumetric flow rate of each constituent phase. The water flow rate is determined from the EMF with an input of the mean oil-fraction measured by the ERT. The dispersed oil-phase flow rate is determined from the mean oil-fraction and the mean oil velocity measured by the ERT cross-correlation velocity profiling. Experiments were carried out on a vertical upward oil-in-water pipe flow, 50 mm inner-diameter test section, at different total liquid flow rates covering the range of 8–16 m3/hr. The oil and water flow rate measurements obtained from the ERT and the EMF are compared to their respective references. The accuracy of these measurements is discussed and the capability of the measurement system is assessed

Imaging of gas-liquid annular flows for underbalanced drilling using electrical resistance tomography

The underbalanced drilling technique, which is also known as managed-pressure drilling, is playing an important role in oil and gas sector, as it reduces common conventional drilling problems such as minimal drilling rates and formation damage, differential sticking and lost circulation. Flow regime monitoring is one of the key topics in annular multiphase flow research, particularly for underbalanced drilling technique. Prediction of the prevailing flow regime in an annulus is of particular importance in the design and installation of underbalanced drilling facilities. Especially, for establishing a suitable pressure-drop model based on the characteristics of the active flow regime. The methods of flow regime prediction (or visualisation) in an annulus that are currently in use are very limited, this is evidently due to poor accuracy or they are simply not applicable to underbalanced drilling operation in practice. Therefore, this paper presents a monitoring method, in which Electrical Resistance Tomography (ERT) is used to rapidly image the prevailing flow regime in an annulus with a metallic inner pipe. Experiments were carried out using an air–water flow loop with a test section 50 mm diameter flow pipe. The two-phase air–water flow regimes are visualised in the upward vertical annulus with a radius ratio (r/R) 0.4. This paper highlights the visualisation results of only three flow regimes, namely bubble flow, transitional bubble-slug flow and slug flow. The flow regimes are visualised through axial images stacked from 50 mm diameter-pixels of 2D tomograms reconstructed with the Conjugate Gradient Method (SCG). Gas volume fraction profiles within the annular flow channel are also illustrated. The profiles are extracted using the Modified Sensitivity coefficient Back-Projection (MSBP) method with a sensitivity matrix generated from a realstic phantom in the finite element method software. The results are compared with visual observations (e.g. photographs) of the active flow regime at the time of ERT measurements

Multiplatform Analysis of 12 Cancer Types Reveals Molecular Classification within and across Tissues of Origin

Recent genomic analyses of pathologically-defined tumor types identify “within-a-tissue” disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head & neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multi-platform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All datasets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies

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