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Background The construction of medical alliance is important measure for deepening medical reform. It aims to move the focus and resource to primary health care institutions, and improve service capabilities. Studies have shown that the medical alliance can improve the service capabilities of primary health care institutions, but the exact reason for this is not clear. Objective To analysis the service capabilities of the of primary health care institutions, and explore the impact of service capabilities in the context of medical alliance. Methods In December 2019, we survey on staffing, outpatient and inpatient service and medical alliance construction of 381 primary health care institutions which participated in medical alliance in Chengdu by structured questionnaire. Local administrative departments of public health gave out and recovered questionnaire. With the number of staff, registered generals, beds, outpatient and emergency visits, admission, and the use rate of the beds as the indicator of the service capabilities, we used rank sum ratio to analyze the comprehensive medical service capabilities and divide them to 3 gear. Using orderly Logistic regression to explore the influencing factors of integrated medical services. Results The median number of staff in 381 primary health care institutions was 54 (48), registered generals was 4 (8), beds was 50 (50), outpatient and emergency visits was 49 460 (60 317), admission was 1 440 (2 071), the use rate of beds was 68.43% (45.18%). According to the rank and ratio, there were 61 (16.0%), 260 (68.3%), and 60 (15.7%) institutions with good, medium and poor comprehensive medical service ability, respectively. The analysis of orderly Logistic regression analysis showed that institutional building area, teaching rounds and remote film reading are the influencing factors of the comprehensive medical service capabilities of primary health care institutions (P

The imbalance between the supply and demand of pediatric medical resources and health management services in our country has been a long-standing issue, primary healthcare institutions are particularly prominent in this context. How to achieve integration and optimization of pediatric medical resources at the grassroots medical and health institutions is an urgent problem that needs to be addressed. This article primarily summarizes and analyzes the concept and framework of integrated health management services for children, including children's health assessment, early intervention, long-term follow-up, and case studies and practical experiences. Through a review of domestic and international literature, it concludes feasible models of integrated health services for children. This review suggests that integrated health management services have broad potential and promising applications, providing personalized and efficient health management and intervention for children.

Background: To investigate the effect of percutaneous nephrolithotomy (PCNL) guided by holographic image technology on stress response and renal injury factors in patients with complex renal calculi. Methods: A retrospective analysis was conducted on the clinical data of 70 patients admitted to our hospital between August 2022 and June 2023 who had complex kidney stones. The patients were divided into two groups, namely, group A and group B, based on whether they received guidance from preoperative holographic imaging technology. Group A consisted of forty patients who underwent PCNL after undergoing renal CT examination prior to surgery, while Group B included thirty patients who underwent PCNL guided by holographic imaging technology. Various indexes, including operative factors, stress response, inflammatory response, renal injury factors, renal function, complication rate, and the rate of achieving complete stone clearance in a single procedure, were compared between the two groups. Results: In group B, the puncture time and operation time of the target calyces were shorter compared to group A, additionally, the intraoperative blood loss in group B was lower than that in group A (P 0.05); however, exhibited lower levels of CysC compared to group A (P < 0.05). Additionally, there were no significant differences in postoperative complications between group B and group A (P>0.05). Furthermore, one month after surgery, the one-time stone clearance rate in group B was significantly higher than that in group A (P

Primary health care (PHC) is the bottom of the health care system, and its quality not only relates to the construction of hierarchical medical system, but also affects the health level of residents. Scientific and reasonable evaluation of PHC quality is the cornerstone of quality improvement, however, a unified and standardized quality evaluation system of PHC has not been developed in China. Therefore, the international quality evaluation tools of PHC are classified into four categories based on the evaluation focus: quality evaluation tools based on PHC connotations, quality evaluation tools emphasizing the functional characteristics of PHC, quality evaluation tools based on the perceptions of demand and/or supply side stakeholders, and other disease-specific tools or indicator systems. The content and characteristics of each tool were introduced and compared separately, their applicability and shortcomings were analyzed, and the evolution was reviewed, in order to provide reference for the construction of PHC quality evaluation tools in China.

The prediction of rainstorms and floods in small and medium-sized watersheds, as well as the synthesis of related parameters, plays a pivotal role in preventing flood disasters. Environmental changes have led to an increase in hydrological extremes such as rainstorms and floods, presenting unprecedented challenges for small and medium-sized river basins. In this review, we systematically categorize, and summarize the processes involved in predicting rainstorms and floods in these watersheds, along with advancements in correlated parameter synthesis research. Furthermore, we analyze and discuss the most commonly employed runoff and confluence estimation methods and their associated parameters in practical applications, as well as their limitations. First, we establish the concept of small- and medium-sized watersheds across various academic disciplines. From a hydrological perspective, these watersheds typically exhibit slope confluence and have relatively small catchment areas. In terms of eco-hydrology, the ecological water demand of the basin must be calculated based on the different communities occupying the river basin and divided by area according to the ecological samples from each district after the investigation. Thereafter, we summarized the methods and types of runoff calculation and parameter synthesis in small- and medium-sized basins, and the methods and principles of runoff analysis, such as rainfall–runoff correlation diagram, infiltration curve method, deduction method, runoff coefficient method, and hydrological model method as well as the methods of parameter synthesis, such as rainfall-runoff correlation diagrams and loss methods are introduced. Second, we summarize and discuss the assessment of confluence and its associated parameters in small- and medium-sized river basins. This encompasses background information and various calculation methods, such as the instantaneous unit line, comprehensive unit line, inference formula method, and empirical formula method. We also examine how the three major elements of parameter synthesis convergence influence confluence parameters. We emphasize that combining radar rainfall measurements, high-resolution remote sensing, high-performance computing, and deep learning can facilitate research on simulating and forecasting rainstorms and flood processes in small- and medium-sized basins. However, a significant portion of these basins lacks data, limiting the application of simulation and flood forecasting. To address this, integration with geographical parameters specific to small- and medium-sized basins is necessary to enhance regional reliability and forecasting accuracy. Additionally, when applying deep learning to simulate basins with limited or no data, the significance of parameter synthesis becomes even more pronounced. Finally, we discuss the problems and challenges associated with storm flood calculations and parameter synthesis methods in small- and medium-sized basins and offer predictions regarding future research and technical developments. We recommend strengthening the use of emerging technologies for watershed runoff and runoff parameter calculations and advocate for their application in storm flood design.

The mechanical properties of large 2219 Al–Cu alloy rings need to be further improved with the diameter of the launch vehicle being more than 10 m. In this study, the effects of cold rolling (CR) and cold compression on microstructure evolution and the comprehensive mechanical properties of such rings were compared. The evolution of dislocation characteristics, grain structure, second phase, and the mechanical properties of the T8-aged samples were examined. Results show that compared with CR, because of deformation characteristics, cold compression deformation induces less increase in dislocation densities; however, the increase in dislocation densities on the core was higher than at other positions, resulting in a more uniform grain structure and elongation in the axial and radial direction. The cold compression deformation contributes to the uniform dissolution of the secondary phase, resulting in denser precipitates, and thus improved strength. Brittle fractures occur in fewer CR samples because of the longer moving distance of the Al matrix. In summary, both CR and cold compression can improve the mechanical properties. However, the cold-compressed sample exhibits more uniform microstructure and higher comprehensive mechanical properties (the radial elongation increased from 7.1 to 11.2%; the in-plane anisotropy decreased from 36.6 to 8.9%), without any brittle fractures, because of more uniform metal flow.

Rising atmospheric CO2 is anticipated to influence global runoff through its radiative effect and physiological effect, thereby resulting in profound impacts on water availability and security. While existing literature has explored the two effects on global total runoff, there is still a lack of attention to changes in runoff components (surface and subsurface runoff). Here, based on idealized 1% yr−1 CO2 increase experiments and 14 Earth system models, we decouple the two effects on changes in runoff components and disentangle the contributions of three influencing factors, namely water supply, atmospheric water demand, and vegetation regulation, which are closely intertwined with the two effects. Global total runoff is expected to increase with rising CO2, and this increase mainly comes from subsurface runoff, leading to an elevated subsurface runoff ratio. Vegetation regulation emerges as the most important factor for the increase in subsurface runoff ratio, with the contribution of 49.3%, followed by water supply (41.7%) and atmospheric water demand (8.9%). Increased total runoff implies potentially more flood risk, while the increase in subsurface runoff ratio could decrease some of the risk. The results indicate the necessity of emphasizing changes in subsurface runoff under climate change. Plain Language Summary: Runoff components comprise surface runoff and subsurface runoff. Surface runoff reaches the stream quickly, and efficiently carries soil and nutrients. Subsurface runoff represents the watershed's slow response to precipitation events and is crucial for maintaining continuous river flow and water supply. Here, based on idealized 1% yr−1 CO2 increase experiments and 14 Earth system models, we explore the trend and influencing factors of runoff components with rising atmospheric CO2. Global surface and subsurface runoff are expected to increase, with subsurface runoff increasing faster than surface runoff. Vegetation regulation plays a crucial role in the increase of subsurface runoff ratio, which is of great significance in reducing the potential flood risk caused by the increase in global total runoff. Key Points: Subsurface runoff ratio is expected to increase with rising CO2Vegetation regulation is the most critical factor, contributing about half of the increaseWater supply contributes 41.7%, and atmospheric water demand contributes 8.9% to the increase in subsurface runoff ratio [ABSTRACT FROM AUTHOR]

On the Tibetan Plateau, the limited ground-based rainfall information owing to a harsh environment has brought great challenges to hydrological studies. Satellite-based rainfall products, which allow for a better coverage than both radar network and rain gauges on the Tibetan Plateau, can be suitable alternatives for studies on investigating the hydrological processes and climate change. In this study, a newly developed daily satellite-based precipitation product, termed Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR), is used as input for a hydrologic model to simulate streamflow in the upper Yellow and Yangtze River basins on the Tibetan Plateau. The results show that the simulated streamflows using PERSIANN-CDR precipitation and the Global Land Data Assimilation System (GLDAS) precipitation are closer to observation than that using limited gauge-based precipitation interpolation in the upper Yangtze River basin. The simulated streamflow using gauge-based precipitation are higher than the streamflow observation during the wet season. In the upper Yellow River basin, gauge-based precipitation, GLDAS precipitation, and PERSIANN-CDR precipitation have similar good performance in simulating streamflow. The evaluation of streamflow simulation capability in this study partly indicates that the PERSIANN-CDR rainfall product has good potential to be a reliable dataset and an alternative information source of a limited gauge network for conducting long-term hydrological and climate studies on the Tibetan Plateau.

In prostate cancer, castration resistance is a factor that frequently leads to death in individuals with this disease. Recent studies have suggested that prostate cancer stem cells (PCSCs) are pivotal regulators in the establishment of castration resistance. The nanog homeobox (NANOG) and the transforming growth factor (TGF)-β1/drosophila mothers against decapentaplegic protein (SMAD) signaling pathways are involved in several cancer stem cells but are not involved in PCSCs. The purpose of this study is to investigate the effect of NANOG on the proliferation of PCSCs regulated by the TGF-β1/SMAD signaling pathway.

This article explores the technology of recognizing non-cooperative communication behavior, with a specific emphasis on analyzing communication station signals. Conventional techniques for analyzing signal data frames to determine their identity, while precise, do not have the ability to operate in real-time. In order to tackle this issue, we developed a pragmatic architecture for recognizing communication behavior and a system based on polling. The method utilizes a one-dimensional convolutional neural network (CNN) to segment data, hence improving its ability to recognize various communication activities. The study assesses the reliability of CNN in several real-world scenarios, examining its accuracy in the presence of noise interference, varying lengths of interception signals, interferences at different frequency points, and dynamic changes in outpost locations. The experimental results confirm the efficacy and dependability of the convolutional neural network in recognizing communication behavior in various contexts. [ABSTRACT FROM AUTHOR]