34 research outputs found
Advancing the application of systems thinking in health: managing rural China health system development in complex and dynamic contexts
Background: This paper explores the evolution of schemes for rural finance in China as a case study of the long and complex process of health system development. It argues that the evolution of these schemes has been the outcome of the response of a large number of agents to a rapidly changing context and of efforts by the government to influence this adaptation process and achieve public health goals.
Methods:The study draws on several sources of data including a review of official policy documents and academic papers and in-depth interviews with key policy actors at national level and at a sample of localities.
Results: The study identifies three major transition points associated with changes in broad development strategy and demonstrates how the adaptation of large numbers of actors to these contextual changes had a major impact on the performance of the health system. Further, it documents how the Ministry of Health viewed its role as both an advocate for the interests of health facilities and health workers and as the agency responsible for ensuring that government health system objectives were met. It is argued that a major reason for the resilience of the health system and its ability to adapt to rapid economic and institutional change was the ability of the Ministry to provide overall strategy leadership. Additionally, it postulates that a number of interest groups have emerged, which now also seek to influence the pathway of health system development.
Conclusions: This history illustrates the complex and political nature of the management of health system development and reform. The paper concludes that governments will need to increase their capacity to analyze the health sector as a complex system and to manage change processes.UKaid: DFI
Deep sliding instability mechanism and remediation measures: The subgrade soil slope along the Jingguang Railway at K1219
To explore the deep sliding instability mechanism of a soil slope, taking the subgrade slope instability at K1219+000 of the downward line of the Beijing-Guangzhou railway as an example, the deformation and failure characteristics, geomechanical process and instability causes of the soil slope are detailedly studied. The results show that the width and depth of cracks on the surface of the subgrade slope gradually become shallow and narrow from the top of the slope to the toe of the slope, and the deformation has a certain rotation, with obvious traction characteristics, which belongs to deep sliding and splitting instability. The soil slope has experienced three geomechanical processes: the redistribution of the stress field and seepage field caused by slope toe excavation and pumping, the increasing sliding force caused by rainwater infiltration softening and the deepening of the sliding surface, and the failure of retaining structure resistance. The mechanism of slope instability includes the stage of shallow sliding, the stage of shallow sliding surface moving to the deep layer, and the stage of deep sliding instability triggered by the dynamic load.On this basis, the position of the sliding surface is comprehensively determined and the mechanical parameters of the slip surface are determined by the inversion method. The regulation scheme of rigid frame double row anti-slide piles is adopted. Through theoretical calculation and numerical analysis, the deformation of slope and anti-slide piles are consistent with the deformation monitoring results, which indicates that the theoretical analysis of deep instability of soil slope is accurate and the calculation of mechanical parameters is scientific, and the measures are proven stable and reliable
A note on stability of the split-step backward Euler method for linear stochastic delay integro-differential equations
Flower-like Heterogeneous Phosphorus-Doped Co<sub>3</sub>S<sub>4</sub>@Ni<sub>3</sub>S<sub>4</sub> Nanoparticles as a Binder-free Electrode for Asymmetric All-Solid-State Supercapacitors
Through the hydrothermal method and the gas-phase phosphating
method,
the flower-like heterogeneous phosphorus-doped Co3S4@Ni3S4 was synthesized in situ on a
nickel foam substrate as the binder-free electrode material for supercapacitors.
Phosphorus-doped Co3S4@Ni3S4 electrode material combines the merits of transition metal sulfides
and 3D porous network heterostructure, showing the excellent theoretical
specific capacitance and the high specific surface area. The introduction
of phosphorus atoms with an atomic radius larger than sulfur atoms
can optimize the internal electronic structure and cause structural
distortion. Therefore, the specific capacitance/specific capacity
of this electrode can reach 3614 F gā1 (451 mAh
gā1) at 1 A gā1 and still maintain
the initial specific capacitance of 73% after 3000 cycles. The assembled
PāCo3S4@Ni3S4-175//AC
ASC device exhibits an ultra-high energy density of 72 Wh kgā1 at a power density of 800 W kgā1. Meanwhile, it
can show extraordinary cyclic stability, with a retention rate of
91% after 5000 cycles. This work provides a feasible synthesis method
to prepare the composite electrode materials for supercapacitors
Polythiophene solar cells processed from non-halogenated solvent with 15.68% efficiency
Polythiophenes (PTs) are prospective polymer donors for large-scale manufacturing and industrialization owing to their simple structures and low synthetic cost. However, the fabrication of PT solar cells depends on highly toxic chlorinated solvents, and less research has been done on the use of more environmentally friendly non-halogenated solvents. Herein, highly efficient PT solar cells based on top-performance polythiophene, P5TCN-F25, processed from a non-halogenated solvent are reported by delicate aggregation control. A power conversion efficiency of up to 15.68% was achieved by depositing the active layer from a hot o-xylene solution, which is the record efficiency of non-halogenated processed PT solar cells up to date. The appropriate solution temperature is beneficial to the formation of ordered polymer stacking and desirable phase separation size, which thereby contributes to enhanced charge transfer efficiency, more balanced hole electron mobility, and reduced trap-assisted recombination. These results provide valuable implications for improving the efficiency of PT solar cells via environmentally-friendly processing
Clinical Data based XGBoost Algorithm for infection risk prediction of patients with decompensated cirrhosis: a 10-year (2012ā2021) Multicenter Retrospective Case-control study
Abstract Objectives To appraise effective predictors for infection in patients with decompensated cirrhosis (DC) by using XGBoost algorithm in a retrospective case-control study. Methods Clinical data were retrospectively collected from 6,648 patients with DC admitted to five tertiary hospitals. Indicators with significant differences were determined by univariate analysis and least absolute contraction and selection operator (LASSO) regression. Further multi-tree extreme gradient boosting (XGBoost) machine learning-based model was used to rank importance of features selected from LASSO and subsequently constructed infection risk prediction model with simple-tree XGBoost model. Finally, the simple-tree XGBoost model is compared with the traditional logical regression (LR) model. Performances of models were evaluated by area under the receiver operating characteristic curve (AUROC), sensitivity, and specificity. Results Six features, including total bilirubin, blood sodium, albumin, prothrombin activity, white blood cell count, and neutrophils to lymphocytes ratio were selected as predictors for infection in patients with DC. Simple-tree XGBoost model conducted by these features can predict infection risk accurately with an AUROC of 0.971, sensitivity of 0.915, and specificity of 0.900 in training set. The performance of simple-tree XGBoost model is better than that of traditional LR model in training set, internal verification set, and external feature set (Pā<ā0.001). Conclusions The simple-tree XGBoost predictive model developed based on a minimal amount of clinical data available to DC patients with restricted medical resources could help primary healthcare practitioners promptly identify potential infection
Understanding the synergistic effects of cobalt single atoms and small nanoparticles: enhancing oxygen reduction reaction catalytic activity and stability for zinc-air batteries
The development of earth-abundant oxygen reduction reaction (ORR) catalysts with high catalytic activity and good stability for practical metal-air batteries remains an enormous challenge. Herein, a highly efficient and durable ORR catalyst is reported, which consists of atomically dispersed Co single atoms (Co-SAs) in the form of Co-N4 moieties and small Co nanoparticles (Co-SNPs) co-anchored on nitrogen-doped porous carbon nanocage (Co-SAs/SNPs@NC). Benefiting from the synergistic effect of Co-SAs and Co-SNPs as well as the enhanced anticorrosion capability of the carbon matrix brought by its improved graphitization degree, the resultant Co-SAs/SNPs@NC catalyst exhibits outstanding ORR activity and remarkable stability in alkaline media, outperforming Co-SAs-based catalyst (Co-SAs@NC), and benchmark Pt/C catalyst. Density functional theory calculations reveal that the strong interaction between Co-SNPs and Co-N4 sites can increase the valence state of the active Co atoms in Co-SAs/SNPs@NC and moderate the adsorption free energy of ORR intermediates, thus facilitating the reduction of O2. Moreover, the practical zinc-air battery assembled with Co-SAs/SNPs@NC catalyst demonstrates a maximum power density of 223.5 mW cmā2, a high specific capacity of 742 W h kgā1 at 50 mA cmā2 and a superior cycling stability.Ministry of Education (MOE)Nanyang Technological UniversityNational Research Foundation (NRF)The authors thank Nanyang Technological University, Singapore, for providing financial support. This work was also supported by National Research FoundationāCompetitive Research Programs (NRF-CRP22-2019-0007, and NRF-CRP21-2018-0007), and the Singapore Ministry of Education AcRF Tier 2 (MOE2019-T2-2-105) and AcRF Tier 1 (RG7/18 and RG161/19). X.Z. acknowledges the financial supports from the National Natural Science Foundation of China (NSFC): Grant No. 21922507 and 21771079, the Jilin Province Science and Technology Development Plan (No. YDZJ202101ZYTS126), and the Fundamental Research Funds for the Central Universities. Y.L. acknowledges the financial supports from the NSFC (Grant No. 22005116), the International Postdoctoral Exchange Fellowship Program (20190054)