Adaptability of water resources development and utilization to social-economy system in Hunan province, China.

The interplay of water resources with social-economy spheres involves a reciprocal feedback mechanism. With the acceleration of the construction process of modernized water networks in Hunan Province, investigating the adaptation status of the "Water-Social-Economy " composite system (WSE) is crucial for promoting sustainability. This study clarifies the connotation of the adaptability of WSE, and the quantitative analyses were conducted through coupling coordinative degree, harmonious development capacity, and the evolution of development lag types among the 14 cities of Hunan Province from 2005 to 2020. The results show that: (1) The development index of the water resources subsystem (WRS) showed a "downward-fluctuation-upward" trend, while the development index of the social-economy subsystem (SES) showed signs of great improvement, the former didn't catch up with the latter. (2) The coupling coordination degree of WSE developed well, and reached the coordinative development stage by 2020, but the unbalanced spatial pattern between north to south and east to west still exists and is further intensified. (3) The development ability of WSE improved while the harmony ability reduced, and the development rate of WRS and SES hasn't achieved dynamic synchronization. Finally, the policies and suggestions to improve the adaptability are put forward, which is of instructive significance for the sustainable development of water suitability.

Emission accounting and drivers in Central Asian countries.

Emerging countries are at the frontier of climate change actions, and carbon emissions accounting provides a quantifiable measure of the environmental impact of economic activities, which allows for comparisons of emissions across different entities. However, currently there is no study covering detailed emissions inventories for emerging countries in Central Asian. This paper compiles detailed and accurate carbon emissions inventories in several Central Asian countries (i.e., Kazakhstan, Kyrgyzstan, Pakistan, Palestine, Tajikistan, and Uzbekistan) during the period 2010-2020. Using the IPCC administrative territorial approach, we for the first time compile their emissions inventories in 47 economic sectors and five energy categories. Moreover, we also investigate decoupling status based on Tapio decoupling model and examine emissions driving factors based on the index decomposition analysis method. The primary results illustrate that carbon emissions in Central Asian countries are increasing with huge differences. Decoupling results highlight that most of the sample countries still need more effort to decouple the economy and emissions except that Pakistan achieves an ideal strong decoupling state. The results of the decomposition indicate that the economy and population both raise emissions, while energy intensity and carbon intensity are negative drivers in some countries. We propose practical policy implications for decarbonization and energy transition roadmap in Central Asian countries.

The heterogeneous driving forces behind carbon emissions change in 30 selective emerging economies.

Emerging economies are predicted to be future emission hotspots due to expected levels of urbanization and industrialization, and their CO2 emissions are receiving more scrutiny. However, the driving forces underlying dynamic change in emissions are poorly understood, despite their crucial role in developing targeted mitigating pathways. We firstly compile energy-related emissions of 30 selective emerging economies from 2010 to 2018. Then, three growth patterns of emissions in these economies have been identified through emission data, which imply different low-carbon pathways. Most emerging economies saw an increase of varying degrees in emissions, driven by economic growth and partly offset by better energy efficiency and improvements in energy mixes. Furthermore, the industrial structure was another factor that slowed emissions, especially in Latin America and the Caribbean. Our research contributes to the heterogeneous exploration of CO2 emissions produced by energy among sectors and the creation of low-carbon development pathways in emerging economies.

Emission growth and drivers in Mainland Southeast Asian countries.

Mainland Southeast Asian (MSEA) countries (Cambodia, Laos, Thailand, Myanmar, and Vietnam) are likely to become one of the next hotspots for emission reduction, since CO2 emissions in this area will have a two-thirds increase by 2040 due to rapid economy growth and associated energy consumption. As one of the most vulnerable areas to climate change, MSEA countries need to develop low-carbon roadmaps based on accurate emission data. This study provides emission inventories for MSEA countries for 2010-2019, based on the IPCC territorial emission accounting approach , including emissions from five types of fuels (i.e., coal, crude oil, oil products, natural gas, and biofuels & waste) used in 47 economic sectors. The results show that the emissions in MSEA countries are on the rise, with average annual growth rates ranging from 2.5% in Thailand to 19.3% in Laos. Biomass is one of the most important sources of carbon emissions, contributing between 11.8% and 76.7% of total carbon emissions, but its share has been declining in most countries, whereas the share of emissions from coal has risen sharply in Laos, Vietnam, and Cambodia. We further examine the drivers behind the changes in emissions using index decomposition analysis. Economic growth was the strongest driver of growth in emissions, while population growth has only had a small effect on emission growth. Energy intensity varies widely across nations, but only significantly reduced CO2 emission growth in Thailand. The secondary sector considerable contributed to an increase in CO2 emissions in Laos and Vietnam, while the tertiary sector only moderately contributed to emissions in Thailand. Our study provides a better understanding of the composition and underlying factors of emission growth in MSEA countries, this could shape their low-carbon development pathway. Our results could also inform other emerging economies, which may become emission hotspots in the next decades, to develop low-carbon roadmaps, thereby contributing to the achievement of global climate change targets.

Exploring the environmental properties and resource utilization of construction waste in Beijing-Tianjin-Hebei region.

Beijing-Tianjin-Hebei region is a capital economic circle for the future. Promoting the coordinated development of its population, economy, resources and environment is a major national strategy. And as towns and cities continue to expand, the volume of construction waste is gradually expanding, posing a major challenge to the sustainable development of the construction industry. In order to solve this problem, this paper used portable X-ray fluorescence spectrometry to realize the on-site rapid monitoring of heavy metals in construction waste, and the correlation analysis result was R2 = 0.9908. The visualization of enrichment factor evaluation results was realized through ArcGIS. The Beijing-Tianjin-Hebei region is mainly polluted by heavy metal elements Cr, Zn, Pb and Hg, showing regional pollution characteristics, and the results of mercury morphology analysis show that all are inorganic mercury pollution, and methylmercury is not detected, and the cause can be traced to heavy industrial production in Tangshan City, which is consistent with industrial ecology. The results of leaching toxicity and cation anion analysis showed that the construction waste in Beijing-Tianjin-Hebei region had environmental risks to the surrounding surface water and groundwater. The resource treatment and disposal path were determined by means of XRD, ternary phase diagram and oxide composition analysis to avoid secondary pollution. This study explores the environmental properties and resource utilization pathways of construction waste in the Beijing-Tianjin-Hebei region, laying the foundation for research work on construction waste in the development of national urban agglomerations, effectively solving regional environmental pollution problems and promoting the sustainable development of the construction industry.

Research on Innovation Ecosystem of Dairy Industry Cluster Based on Machine Learning and Improved Neural Network.

With the rapid development of global economy, the industrial cluster has become the new trend of world economic development. So far, the industrial cluster mode with space as the main division has been formed. The cooperation of industrial clusters is dynamic. The industries in the cluster cooperate with each other for mutual benefit and win-win, occupying a place in the fierce market competition. In addition, the industrial cluster is also conducive to strengthen the international economic division of labor and points out the direction of regional industrial transfer. China is now in a critical period of economic development; the industrial cluster plays an important role in China's industrial transformation and economic development. At present, the most common regional development mode in China is industrial cluster. The emergence of industrial cluster accelerates the development of industrial regional economy and the balance of industrial layout. Industrial clusters occupy a key position in China's economic industry chain, and the development and change in industrial clusters will directly affect the development of the entire industrial chain. This study first simulates the evolution path of industrial cluster and then establishes the relevant data model. Finally, through repast simulation, it puts forward conclusions and suggestions according to the verification results. The construction of dynamic model can realize the simulation of industrial cluster theory. According to the simulation results, we can find that the ecosystem in different stages will produce different characteristics; the formation and evolution of industrial clusters are actually the epitome of market development. In this process, the government guidance and market regulation are needed to accelerate the formation of industrial cluster ecosystem and increase the scale of industrial cluster.

Facile, Atom-Economic, Chemical Thinning Strategy for Ultrathin Lithium Foils.

Metallic lithium is considered as the ultimate anode material for lithium-based batteries due to its highest energy density. However, as an anode, commercial Li metal foils are too thick, with a large amount of trouble to balance its exorbitant areal capacity with common cathodes in full cells. Here, a new chemical thinning strategy is proposed via a simple surface dissolving reaction between lithium and naphthalene, which enables scalable, continuous, and roll-to-roll preparation of ultrathin Li foil. A Li foil less than 15 µm with a clean surface can be successfully obtained within 20 min. The thinning rate and thickness of the lithium foil can be easily adjusted by changing the concentration, temperature, and operation mode. The produced Li-Naph solution after thinning can also be used as a multifunctional reagent of great value, and the Li ions in the final waste solution can be further extracted in the form of Li2CO3, showing superior lithium atom economy of our strategy.

Cost-effectiveness analysis of dabigatran, rivaroxaban and warfarin in the prevention of stroke in patients with atrial fibrillation in China.

BACKGROUND AND OBJECTIVE: To evaluate the cost-effectiveness of new anticoagulants and warfarin in the prevention of stroke in Chinese patients with atrial fibrillation (AF). METHODS: The Markov model was constructed to compare patients' quality-adjusted life-years (QALYs) using drug cost, the cost of the examination after taking a drug, and the incremental cost of other treatments. Both dabigatran (110 and 150 mg, twice a day) and rivaroxaban (20 mg, once a day) were compared with warfarin (3-6 mg, once a day). Willingness to pay, three times the 2018 China GDP per capita (9481.88 $), was the cost-effect threshold in our study. RESULTS: The total cost were was 5317.31$, 29673.33$, 23615.49$, and 34324.91$ for warfarin, rivaroxaban, dabigatran 110 mg bid, and dabigatran 150 mg bid, respectively. The QALYs for each of the four interventions were 11.07 years, 15.46 years, 12.4 years, and 15 years, respectively. The cost-effectiveness analysis of the three new oral anticoagulants and warfarin showed that the incremental cost-effectiveness ratio (ICER) was 5548.07$/QALY when rivaroxaban was compared with warfarin. Rivaroxaban was the most cost-effective choice and warfarin was the least. CONCLUSIONS: In Chinese patients with AF, although warfarin is cheaper, rivaroxaban has a better cost-effectiveness advantage from an economic point of view.

Low-Cost Nested-MIMO Array for Large-Scale Wireless Sensor Applications.

In modern communication and radar applications, large-scale sensor arrays have increasingly been used to improve the performance of a system. However, the hardware cost and circuit power consumption scale linearly with the number of sensors, which makes the whole system expensive and power-hungry. This paper presents a low-cost nested multiple-input multiple-output (MIMO) array, which is capable of providing O ( 2 N 2 ) degrees of freedom (DOF) with O ( N ) physical sensors. The sensor locations of the proposed array have closed-form expressions. Thus, the aperture size and number of DOF can be predicted as a function of the total number of sensors. Additionally, with the help of time-sequence-phase-weighting (TSPW) technology, only one receiver channel is required for sampling the signals received by all of the sensors, which is conducive to reducing the hardware cost and power consumption. Numerical simulation results demonstrate the effectiveness and superiority of the proposed array.

Early Marketplace Enrollees Were Older And Used More Medication Than Later Enrollees; Marketplaces Pooled Risk.

Little is known about the health status of the 7.3 million Americans who enrolled in insurance plans through the Marketplaces established by the Affordable Care Act in 2014. Medication use may provide an early indicator of the health needs and access to care among Marketplace enrollees. We used data from January-September 2014 on more than one million Marketplace enrollees from Express Scripts, the largest pharmacy benefit management company in the United States. We compared the characteristics and medication use between early and late Marketplace enrollees and between all Marketplace enrollees and enrollees with employer-sponsored insurance. Among Marketplace enrollees, we found that those who enrolled earlier (October 2013-February 2014) were older and used more medication than later enrollees. Marketplace enrollees, as a whole, had lower average drug spending and were less likely to use most medication classes than the employer-sponsored comparison group. However, Marketplace enrollees were more likely to use medicines for hepatitis C and particularly for HIV.