The Relationship Between Stroke Patients Characteristics and Family Support with Compliance Rehabilitation

Stroke is a cerebrovascular disease, it is brain function disorders associated with the disease of the blood vessels that supply the brain. The impact of stroke is paralysis. Family support is things that are needed to be considered in the treatment of stroke patients. It is very involved in the compliance rehabilitation of patients to prevent the re-occurrence of stroke. Characteristics of stroke patients may also affect the compliance rehabilitation. The purpose of this research is to determine the relationship between stroke patients characteristics and family support to compliance rehabilitation at the Medical Rehabilitation Unit RSU Haji Surabaya. This research was an analytic observational research with cross sectional design. The subjects of this research are taken using total population technique. The independent variables in this research is family support. The dependent variable is compliance rehabilitation. The results of this research are presented in the form of frequency distributions and calculate the strength of the relationship with Phi coefficient. The result of this research shows that there is a strong relationship between family support and compliance rehabilitation (r=0.582). There are weak relationship between ages (r=-0,027), gender (r=0,092), level of education (r= -0,295), work (r=0,098), and marital status (r=0,319). The conclusion is family support may affect compliance rehabilitation of stroke patients. It is recommended for health workers to provide counseling to improve family support in curing stroke patients

Opportunities and Challenges for the Construction of a Smart City Geo-Spatial Framework in a Small Urban Area in Central China

In 2006, China lunched its first Digital City initiative to build a national geo-spatial framework. Over the past ten years, 511 county-cities benefited from the national initiative with funding and technical resources channeled from the central government. Has the initiative achieved its goals? How has the geo-spatial framework affected local governmental administration, public services, business operation, and the daily life of citizens? What lessons can be learned from the ten-year experience of digital city development? Answering these questions is of important policy, scholarly, and practical interest. The Digital City initiative set the foundation for building smart cities that China’s central government agencies and many local municipalities are currently pursuing. A review in retrospect of China’s digital city development helps inform future Smart City investment decisions and related policy making in the nation. Lessons learned from the Chinese experience are also valuable to cities in other countries

Research on Traffic Design of Urban Vital Streets

As an important part of urban public spaces, the urban street is an important place for people’s lives, communication, and activities. Its vitality directly affects the vitality of the whole city. It is of great practical significance to examine the current situation and theoretical development of urban streets in China and reconstruct the vitality of streets from the perspective of the traffic users. Based on the “people-oriented” design concept of street traffic, this study took street sections and intersections as the main research object, proposed an overall layout of traffic, space, and facilities. A complete set of humanized and green traffic design methods was constructed to enhance the street vitality. First, through the analysis of the concept of road and street, the traffic connotations of the vital street was determined, the characteristics of the vital street was investigated, and the constituent elements of the vital street was summarized. Then, with a focus on people’s needs, the vital street traffic design methods were mainly divided into two parts: vital street section traffic design and vital street intersection design. Finally, Zhongshan Avenue in Wuhan City was chosen for empirical analysis. Through a field questionnaire survey, the traffic characteristics and traffic demands of residents on Zhongshan Avenue were analyzed, and the traffic design of Zhongshan Avenue was carried out in combination with the traffic design method proposed in this study. The results showed that people’s satisfaction with the renovated Zhongshan Avenue reached 90%. Buses, subways, bicycles, and walkways have become the four major green transportation modes for people to arrive at and leave Zhongshan Avenue, and the renovated Zhongshan Avenue has become a vibrant living street

Influence of nano-SiO2 on the bonding strength and wear resistance properties of polyurethane coating

To improve the wear resistance of polyurethane (PU) coating and its adhesion to the steel substrate, a series of simple and practicable techniques were designed to mix nano-SiO2 with PU powder to cast a coating layer onto the steel. When the addition of nano-SiO2 was small, a network structure of PU-SiO2 was produced. It improved the wear resistance of the composite coating and its adhesion to the steel substrate. When the addition of nano-SiO2 was excessive, agglomerated nano-SiO2 particles not only affected the bond between the PU resin and the steel substrate but also became abrasive materials, intensifying the abrasion of the composite coating during friction. It resulted in lower bonding strength and poorer wear resistance of the composite coating. The wear rate and friction coefficient of 2 wt.% SiO2/PU composite coating were 1.52×10−6 cm3/min N and 0.31, respectively. Its wear resistance was about 10 times as high as that of the pure PU coating. Furthermore, a simple and practicable installation was designed to test the bonding strength between the coating and the steel substrate. The bonding strength between 2 wt.% SiO2/PU composite coating and the steel substrate was 7.33 MPa, which was 39% higher than that of the pure PU coating

Eco-geological environment quality assessment in a mining city: a case study of Jiangxia District, Wuhan City

This study investigates the eco-geological environmental challenges faced by Jiangxia District, a mining region in Wuhan City. By combining field surveys, literature analysis and multi-source data such as remote sensing images and on-site monitoring data, an eco-geological environment quality (EGEQ) assessment system was developed. The system consists of six indicators representing biological abundance, vegetation cover, land erosion, water abundance, surface deformation and socio-economic characteristics of the assessed area. The grey relational analysis method was utilized to calculate the weights of each indicator, and the eco-geological environment quality index (EGQI) value was obtained through the linear weighted method. The assessment results indicated a moderate grade of overall eco-geological condition in Jiangxia District between 2017 and 2021, with an 8.56% increase in the EGQI during that period. This suggests a stable and favorable eco-geo logical environment situation in the district during the specified timeframe

Automatic Identification of Thaw Slumps Based on Neural Network Methods and Thaw Slumping Susceptibility

Abstract Thaw slumping is a periglacial process that occurs on slopes in cold environments, where the ground becomes unstable and the surface slides downhill due to saturation with water during thawing. In this study, GaoFen-1 remote sensing and fused multi-source feature data were used to automatically map thaw slumping landforms in the Beilu River Basin of the Qinghai–Tibet Plateau. The bi-directional cascade network structure was used to extract edges at different scales, where an individual layer was supervised by labeled edges at its specific scale, rather than directly applying the same supervision to all convolutional neural network outputs. Additionally, we conducted a 5-year multi-scale feature analysis of small baseline subset interferometric synthetic aperture radar deformation, normalized difference vegetation index, and slope, among other features. Our study analyzed the performance and accuracy of three methods based on edge object supervised learning and three preconfigured neural networks, ResNet101, VGG16, and ResNet152. Through verification using site surveys and multi-data fusion results, we obtained the best ResNet101 model score of intersection over union of 0.85 (overall accuracy of 84.59%).The value of intersection over union of the VGG and ResNet152 are 0.569 and 0.773, respectively. This work provides a new insight for the potential feasibility of applying the designed edge detection method to map diverse thaw slumping landforms in larger areas with high-resolution images

Comparative analysis of visit and home blood pressure in a pilot trial on the effect of 18% sodium substitute salt on blood pressure

Abstract Aim to compare the home blood pressure monitoring (HBPM) and visit blood pressure monitoring in a clinical phase I single-arm pilot trial. The 18% sodium substitute salt was used in 43 hypertensives for 8 weeks, and visited once a week, while weekly visit blood (VBP) pressure, daily home blood pressure (HBP) and urine test results before and after intervention were collected. 43 hypertensive patients were recruited, 4 were lost. And enrolled 39 patients for analysis. The VBP were lower than morning HBP and night HBP (P < 0.05). And VBP was good correlated with morning BP (SBP: r = 0.692, P < 0.001, DBP: r = 0.789, P < 0.001) and night BP (SBP: r = 0.571, P < 0.001, DBP: r = 0.738, P < 0.001). The results of mixed linear model analysis showed that patients' visit SBP (− 11.4 mmHg, 95% CI: − 17.0 to − 5.7, P < 0.001), morning home SBP (− 10.0 mmHg, 95% CI: − 16.4 to − 3.6, P = 0.003) and night home SBP (− 10.2 mmHg, 95% CI: − 15.8 to − 4.6, P = 0.001) decreased significantly, after intervention. Both HBP and VBP showed that 18% substitute salt intervention could decrease the blood pressure of hypertensives. Medication led to VBP lower than HBP, but the two still had a good correlation. Trial registration: NCT03226327. Registered 21 July 2017—Retrospectively registered, http://www.clinicaltrials.gov

Monitoring and Analysis of Ground Surface Settlement in Mining Clusters by SBAS-InSAR Technology

In this paper, we use the small baseline set technology and the early geological hazard identification method based on the selection of Permanent Scatter (PS) and Distributed Scatter (DS) points to carry out the research on surface deformation monitoring caused by underground activities in mining cluster areas. We adopted the Small Baseline Subset InSAR (SBAS-InSAR) technique to process Sentinel-1A SAR images over the research area from March 2017 to May 2021. The deformation estimation technology based on the robustness of PS points and DS points can be used for early identification of high-density surface subsidence in a large area of mines. The surface subsidence information can be obtained quickly and accurately, and the advantages of using InSAR technology to monitor long-time surface subsidence in complex mining cluster areas was explored in this study. By comparing the monitoring data of the Global Navigation Satellite System (GNSS) ground monitoring equipment, the accuracy error of large-scale surface settlement information is controlled within 8 mm, which has high accuracy. Meanwhile, according to the spatial characteristics of cluster mining areas, it is analyzed that the relationship between adjacent mining areas through groundwater easily leads to regional associated large-area settlement changes. Compared with the D-InSAR (Differential InSAR) technology applied in mine monitoring at the early stage, this proposed method can monitor a large range of long time series and optimize the problem of decoherence to some extent in mining cluster areas. It has important reference significance for early monitoring and early warning of subsidence disaster evolution in mining intensive areas