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China’s North-South regional differences have been widening since the new century, with obvious differences in the roles of various growth factors. Using the decomposition framework of regional differences based on development accounting and China’s provincial-level data from 1978–2022, this study investigates the impacts of total factor productivity, physical capital, and labor inputs on the economic differences between the North and South, and finds that: (1) the difference in total output between the North and the South has continuously expanded, but the gap of output per worker has not changed much in the last decade or so; (2) total factor productivity differences have been an important factor influencing the North-South differences, and will likely dominate the future trend of regional differences; (3) physical capital differences are more prominently affected by regional policies, but the policy effects need to be coordinated and considered in many ways.

Since the reform and opening-up, under the new economic situation and policy, the rapid growth of power demand in Beijing is threatening the sustainable development of China’s economy and environment. To recognize the driving factors of electricity consumption growth and offer policy implications, based on the data of electricity consumption, the Gross Domestic Product (GDP) and the resident population in Beijing from 1990 to 2021, this research used the Kaya-equation and logarithmic mean divisia index (LMDI) model to decompose the growth of power demand in Beijing into the quantitative contribution of each driving factor from the perspective of industrial electricity consumption and residential electricity consumption. The results of the decomposition analysis show that, as far as industrial electricity consumption is concerned, the contribution rates of economic growth, electricity consumption intensity and output value structure to industrial electricity growth are 234.26%, −109.01% and −25.25%, respectively, which shows that economic growth is the primary driving force promoting the growth of industrial electricity demand. Power consumption intensity is the main reason for restraining the growth of industrial power demand, the growth rate is sliding and the contribution of the industrial structure is relatively small; as far as residential power consumption is concerned, the contribution rates of per capita power consumption and population size to residential power growth are 68.13% and 31.87%, respectively, which indicates that per capita power consumption is the main factor promoting the growth of residential power demand, followed by the total population. The study results show that the consumption of electric power would increase if Beijing’s economy and urbanization keep developing, and optimizing the industry structure, improving the efficiency of electric energy utilization and adopting clean power energy are the main approaches to making Beijing’s consumption of electric power decrease.

The aim of this study was to explore the most updated changing trends of non-rheumatic calcific aortic valve disease (nrCAVD) and reveal possible improvements. We analyzed the age-standardized rates (ASRs) of prevalence, incidence, disability-adjusted life-years (DALYs), and mortality trends of nrCAVD from 1990 to 2019 using data from the Global Burden of Disease (GBD) study 2019. The relations between ASRs and socio-demographic index (SDI) were analyzed with Pearson’s correlation coefficients. Decomposition and frontier analysis were employed to reveal the contribution proportion of influence factors and regions where improvement can be achieved. In 2019, there were 9.40 million (95% uncertainty interval (UI): 8.07 to 10.89 million) individuals with nrCAVD globally. From 1990 to 2019, the prevalence rate of nrCAVD increased by 155.47% (95% IU: 141.66% to 171.7%), with the largest increase observed in the middle SDI region (821.11%, 95% UI: 709.87% to 944.23%). Globally, there were no significant changes in the mortality rate of nrCAVD (0.37%, 95% UI: −8.85% to 7.99%). The global DALYs decreased by 10.97% (95% UI: −17.94% to −3.46%). The population attributable fraction (PAF) of high systolic blood pressure increased in the population aged 15–49 years, while it declined slightly in population aged 50+ years. Population growth was the main contributing factor to the increased DALYs across the globe (74.73%), while aging was the driving force in the high-SDI region (80.27%). The Netherlands, Finland, Luxembourg, Germany, and Norway could reduce DALY rates of nrCAVD using their socio-demographic resources. According to these results, we revealed that the burden of nrCAVD increased markedly from 1990 to 2019 in high-SDI and high-middle-SDI regions. There was a downward trend in the mortality due to nrCAVD since 2013, which is possibly owing to profound advances in transcatheter aortic valve replacement. Some countries may reduce burdens of nrCAVD using their socio-demographic resources.

ObjectiveUsing MAL-ED (Etiology, Risk Factors, and Interactions of Enteric Infections and Malnutrition and the Consequences for Child Health) Bangladesh birth cohort data, we sought to measure the relative contributions of the most predictive correlates of stunting to mean length-for-age z (LAZ) score difference between stunted and non-stunted children at 24 months of age.SettingDhaka, BangladeshParticipants211 slum-dwelling children enrolled within 17 days of their birth.Variables and methodThe explanatory variables were identified from the following groups: maternal characteristics, birth characteristics, macronutrient intake, socioeconomic status, morbidity and serum micronutrient level. At step 1, predictive correlates of stunting were identified longitudinally (from 9 to 24 months of age) using generalized estimating equations (GEE) model. Then, the relative contributions of the most predictive correlates of stunting to mean LAZ score difference between stunted and non-stunted children at 24 months of age was measured using Blinder-Oaxaca decomposition analysisResultsThe GEE multivariable model identified maternal height, birth weight, people per room, gender, having separate room for kitchen and energy intake as the most predictive correlates of stunting. At 24 months, mean LAZ score difference between stunted and non-stunted children was 1.48. The variable by variable decomposition of the LAZ gap identified maternal height (coefficient: −3.04; 95% CI: 0.35 to -6.44), birth weight (coefficient: −0.21; 95% CI: 0.88 to -1.30), people per room (coefficient: 0.31; 95% CI: 0.92 to -0.30) and energy intake (coefficient: −0.12; 95% CI: 0.22 to -0.46) as the top most factors responsible for the mean LAZ score difference between stunted and non-stunted children at 24 months of age.ConclusionsThe relative contributions of maternal height and birth weight to LAZ gap signifies that improvement in nutritional status of a women during her adolescence and pregnancy would have an impact on birth weight of her offspring, and ultimately, on linear growth of the child.

Mechanical structural systems are subject to multiple dynamic disturbances during service. While several possible scenarios can be examined to determine their design loading conditions, only a relatively small set of such scenarios is considered critical. Therefore, only such particular deterministic set of critical load cases is commonly employed for the structural design and optimization. Nevertheless, during the design and optimization stages, the mass and stiffness distributions of such assemblies vary, and, in consequence, their dynamic response also varies. Thus, it is important to consider the variations in the dynamic loading conditions during the design-and-optimization cycles. This paper studies the modal participation factors at length and proposes an alternative to the current point-wise treatment of the dynamic equations of motion of flexible bodies during design optimization. First, the most relevant-to-structural-dynamics definitions available in the literature are reviewed in depth. Second, the analysis of those definitions that have the potential to be adopted as point-wise constraint equations during structural optimization is extended. Finally, a proof of concept is presented to demonstrate the usability of each definition, followed by a case study in which the potential advantages of the proposed extended analysis are shown.

China’s carbon intensity (CI) reduction target in 2030 needs to be allocated to each province in order to be achieved. Thus, it is of great significance to study the vertical linkage of CI change between China and its provinces. The existing research on the vertical linkage focuses more on energy-related economic sectors in China; however, attention has not been paid to China’s animal husbandry (AH) sector, although the role of the China’s AH sector in greenhouse gas (GHG) reduction is increasingly important. This study firstly established a vertical linkage of change in greenhouse gas emission intensity of the animal husbandry sector (AHGI) between China and its 31 provinces based on the logarithmic mean Divisia index (LMDI) decomposing method from the perspective of combining emission reduction with economic development, and quantified the contributions of each province and its three driving factors of environmental efficiency (AHEE), productive efficiency (AHPE), and economic share (AHES) to reducing China’s AHGI during the period of 1997–2016. The main results are: (1) The AHGI of China decreased from 5.49 tCO2eq/104 yuan in 1997 to 2.59 tCO2eq/104 in 2016, showing a 75.25% reduction. The AHGI in 31 provinces also declined and played a positive role in promoting the reduction of national AHGI, but there were significant inter-provincial differences in the extent of the contribution. Overall, the provinces with higher emission levels contributed the most to the reduction of China’s AHGI; (2) The AHPE and AHEE factors in 31 provinces cumulatively contributed to the respective 68.17% and 11.78% reduction of China’s AHGI, while the AHES factors of 31 provinces cumulatively inhibited the 4.70% reduction. Overall, the AHPE factor was the main driving factor contributing to the reduction of China’s AHGI. In the future, improving the level of AHEE through GHG emissions reduction technology and narrowing the inter-provincial gap of the level of AHPE are two important paths for promoting the reduction of China’s AHGI.

The multiple input multiple output-orthogonal frequency division multiplexing (m-MIMO-OFDM) is a hot research topic as it provides air interface solution for 5G wireless communications. The transmitted signals typically reflect the high-speed scattered signals which are processed using light emitting diodes (LED). The transmitted signals arrive at the receiver from the multiple paths. From both the receivers, objects are scattered and the channels are changed over time in m-MIMO which gives rise to slower convergence. The proposed FastICA algorithm produces improved performance as it uses for separating components for the selection of better parameters. The components from the source are transmitted, after which they are separated and detected based on the receiver channel’s location. The present research proposes a method to estimate the blind channel approach using fast independent component analysis based on the weight function (FICA-WF) for blind interference cancellation. The existing models such as parallel factor analysis, joint parallel factor analysis, STBC-m-MIMO-OFDM, and MMSE-CMA-DFCE obtained SNR ranging from 10 to 20 dB, whereas the proposed model obtained better SNR of 9.02 dB for the FastICA-WF.

Bully victimization is a common problem among children with neurodevelopmental disorders, including attention deficit/hyperactivity disorder and autism spectrum disorder. Previous research was mostly cross-sectional and seldom accounted for co-morbid psychopathology, which makes it difficult to draw conclusions about causality and specificity of any association. Using a genetically informative prospective design, we investigated the association between various neurodevelopmental problems (NDPs) in childhood and bully victimization in adolescence, and the relative contributions of genetic and environmental factors to this association. We obtained parent-reports of NDPs at age 9/12 years and self-reported bully victimization at age 15 for 3,921 children participating in the The Child and Adolescent Twin Study in Sweden (CATSS). Structural equation modelling was used to control for NDP co-morbidity and bully victimization at baseline. Cholesky decomposition was used to analyse genetic and environmental contributions to observed associations. Because most of the NDPs were associated to later bully victimization, a common effect of all NDPs was summarized into a general NDP factor. Controlling for this general factor, only problems with social interaction and motor control uniquely predicted subsequent bully victimization in girls. General and unique associations were influenced by both genetic and unique environmental factors. NDPs in general and social interaction and motor problems in particular predicted later bully victimization. The longitudinal design and twin analyses indicated that these associations might be causal. Knowledge of these vulnerabilities may be important when designing risk assessment and prevention strategies.

To determine age group‐ and cause‐of‐death‐specific contributions to area socioeconomic status (SES), sex and remoteness life expectancy inequalities. Mortality and estimated residential population data from New South Wales, Australia, over 2010–2012 was used to calculate life expectancy. Inequalities by sociodemographic groups were partitioned into age group‐ and cause‐of‐death‐specific contributions. The largest contributions to SES differentials in life expectancy were observed at 60–84 years of age; for cancer, cardiovascular, endocrine and respiratory causes of death; and additionally external causes of death for males. Sex inequalities ranged from 3.6 to 5.2 years, with common causes of death such as cardiovascular disease and cancer in late adulthood (60+ years) accounting for the bulk of the differences. Smaller differences in life expectancy were observed by remoteness, with the largest contributions observed in ages 85 years and above, and for cardiovascular, mental, cancer and external causes of death. Common causes of death in late adulthood accounted for the bulk of life expectancy inequalities. Development of policy and interventions aimed at addressing social determinants, such as proposed by the WHO's Global Plan of Action, are needed to help reduce sociodemographic inequalities in lifespan.

The paper provides some new decompositions of labour productivity growth and total factor productivity (TFP) growth into sectoral effects. These new decompositions draw on the earlier work of Tang and Wang (Can J Econ 37:421-144, 2004). The economy wide labour productivity growth rate turns out to depend on the sectoral productivity growth rates, real output price changes and changes in sectoral labour input shares. The economy wide TFP growth decomposition into explanatory factors is similar but some extra terms due to real input price change make their appearance in the decomposition.