Dancing With Care: Promoting Social Inclusion Among Older Women in China Through a Novel Preventative Care Model

This article examines how a new form of preventative care provision - dancing with care (DWC) - promotes social inclusion among older women in China and explores whether DWC can be regarded as an effective way to address the challenges these older women face in improving their social inclusion and achieving a healthy lifestyle. Our study demonstrates that various dimensions of DWC play a vital role in addressing the difficulties these older women encounter in their struggle to end their own social exclusion: These dimensions include levels of happiness, social network involvement, access to social support in "preventative care terms", and the role of own's grandchildren as a means to social bonding. Various dimensions of DWC align with the concept of preventative care for older women in urban communities. Using semi-structured interviews in selected "DWC communities" located in southern China, this article demonstrates that DWC contributes to addressing older women's social inclusion by providing preventative care. In addition, we also performed an empirical data analysis that included institutional regulations for DWC design and implementation, publications by DWC communities, and academic research focused on DWC communities. DWC proposes an appealing path for older women to actively engage with and within their community. Furthermore, it offers valuable insights into the potential of a new model of preventative care and our conclusions will serve as a reference for enhancing social involvement among older individuals globally

The block mutual coherence property condition for signal recovery

Compressed sensing shows that a sparse signal can stably be recovered from incomplete linear measurements. But, in practical applications, some signals have additional structure, where the nonzero elements arise in some blocks. We call such signals as block-sparse signals. In this paper, the $\ell_2/\ell_1-\alpha\ell_2$ minimization method for the stable recovery of block-sparse signals is investigated. Sufficient conditions based on block mutual coherence property and associating upper bound estimations of error are established to ensure that block-sparse signals can be stably recovered in the presence of noise via the $\ell_2/\ell_1-\alpha\ell_2$ minimization method. For all we know, it is the first block mutual coherence property condition of stably reconstructing block-sparse signals by the $\ell_2/\ell_1-\alpha\ell_2$ minimization method. Additionally, the numerical experiments implemented verify the performance of the $\ell_2/\ell_1-\alpha\ell_2$ minimization.Comment: 14 pages, 8 figure

Analysis of an SEIR Epidemic Model with Saturated Incidence and Saturated Treatment Function

The dynamics of SEIR epidemic model with saturated incidence rate and saturated treatment function are explored in this paper. The basic reproduction number that determines disease extinction and disease survival is given. The existing threshold conditions of all kinds of the equilibrium points are obtained. Sufficient conditions are established for the existence of backward bifurcation. The local asymptotical stability of equilibrium is verified by analyzing the eigenvalues and using the Routh-Hurwitz criterion. We also discuss the global asymptotical stability of the endemic equilibrium by autonomous convergence theorem. The study indicates that we should improve the efficiency and enlarge the capacity of the treatment to control the spread of disease. Numerical simulations are presented to support and complement the theoretical findings

NUMERICAL ANALYSIS OF VALVE STRUCTURE OF HIGH POWER MARINE ENGINE

Valve as an important part of the gas distribution mechanism, is an crucial part of the engine. When the engine works, the valve is subjected to high temperature, high impact, frictional wear and corrosion and other harsh working conditions, and the reliable and durable valve has an important impact on the safety and reliability of the engine. In this paper, a model of four-stroke marine diesel engine valve is used as the research object, and the intake valve set and exhaust valve set models are established respectively. Heat transfer simulation and failure analysis of inlet and exhaust valves of different structures and materials under different operating conditions were carried out using finite element analysis. The results show that the different valve structures and manufacturing materials have different effects on the reliability of the valves; Changing the valve structures and choosing different valve manufacturing materials have a greater impact on the heat transfer and deformation, thus affecting the overall reliability of the valves

Clinical outcome and prognostic factors of patients with non-traumatic angiography-negative subarachnoid hemorrhage

PurposeThe cause of spontaneous subarachnoid hemorrhage (SAH) is unknown in 10% of cases. The aim of this study was to demonstrate the characteristics of patients with angiography-negative subarachnoid hemorrhage (anSAH) and to analyze factors influencing the clinical outcome in patients suffering from anSAH.MethodsA retrospective cohort of 75 patients with anSAH [26 perimesencephalic (pmSAH) and 49 non-perimesencephalic SAH (npmSAH)] admitted between January 2016 and June 2022 was included. We analyzed demographic, clinical data and 6-month functional outcomes. Enter regression analysis was performed to identify factors associated with outcomes.ResultsUnfavorable outcome was achieved in 10 of 75 patients (13.3%). Unfavorable outcome was associated with senior adults (p = 0.008), Hijdra cistern score (HCS) elevation (p = 0.015), long-time lumbar cistern continuous drainage (LCFD; p = 0.029) and hydrocephalus (p = 0.046). The only significant risk factor for unfavorable outcome after npmSAH was the HCS (OR 1.213 (95%CI 1.007–1.462), p = 0.042).ConclusionOur study provides valuable information on both SAH patterns and functional outcome in patients suffering from anSAH and should be taken into consideration during management of these patients

Hybrid Optimization Algorithm of Particle Swarm Optimization and Cuckoo Search for Preventive Maintenance Period Optimization

All equipment must be maintained during its lifetime to ensure normal operation. Maintenance is one of the critical roles in the success of manufacturing enterprises. This paper proposed a preventive maintenance period optimization model (PMPOM) to find an optimal preventive maintenance period. By making use of the advantages of particle swarm optimization (PSO) and cuckoo search (CS) algorithm, a hybrid optimization algorithm of PSO and CS is proposed to solve the PMPOM problem. The test functions show that the proposed algorithm exhibits more outstanding performance than particle swarm optimization and cuckoo search. Experiment results show that the proposed algorithm has advantages of strong optimization ability and fast convergence speed to solve the PMPOM problem