Social networks and type 2 diabetes: a narrative review

It has been known for decades that social networks are causally related to disease and mortality risk. However, this field of research and its potential for implementation into diabetes care is still in its infancy. In this narrative review, we aim to address the state-of-the-art of social network research in type 2 diabetes prevention and care. Despite the diverse nature and heterogeneity of social network assessments, we can draw valuable lessons from the available studies. First, the structural network variable ‘living alone’ and the functional network variable ‘lack of social support’ have been associated with increased type 2 diabetes risk. The latter association may be modified by lifestyle risk factors, such as obesity, low level of physical activity and unhealthy diet. Second, smaller network size and less social support is associated with increased risk of diabetes complications, particularly chronic kidney disease and CHD. Third, current evidence shows a beneficial impact of social support on diabetes self-management. In addition, social support interventions were found to have a small, favourable effect on HbA1c values in the short-term. However, harmonisation and more detailed assessment of social network measurements are needed to utilise social network characteristics for more effective prevention and disease management in type 2 diabetes. Graphical abstract

Review of Performance Improvement of VSS FLC and NN MPPT Photo Voltaic Power System

In this paper guides in the fuzzy logic and Neural network variable step size Incremental conductance maximum power point tracking controller were analyzed as well suggested on further work. Firstly, the Fuzzy Logic Control (FLC) controller based hardware system derived paper were discussed followed by Neural Network (NN) based VSS Inc-Cond were discussed in the second half. In the first paper derived simple FLC I.e short, medium and long distance were considered to derive the 25 rules. The input of FLC are current and voltage, the output of FLC is duty cycle or D. The duty cycle apply into variable step Inc-conductance method to find the optimal point of the PV system. Further discussed experimental block diagram of FLC-Inc-Cond system. At the end of the paper authors compared various hardware to show tabulations. In the second half, initially discussed conventional Inc-Cond, followed by general Fuzzy logic controller were discussed. Further author derived VSS Inc-Cond based NN MPPT were developed on Matlab simulink. The output of FLC-Inc Cond as well NN based MPPT is great performance when compare to conventional system.

Adaptive Neural Network Variable Structure Control for Liquid-Filled Spacecraft under Unknown Input Saturation

This study addresses the problem of attitude maneuver control for a three-axis stabilized liquid-filled spacecraft using an adaptive neural network variable structure control algorithm in the presence of parametric uncertainty, external disturbances, and control input saturation. The liquid fuel is equivalent to a spherical pendulum model, and the coupled dynamic model of liquid-filled spacecraft is derived using the conservation law of angular momentum moment. Then, adaptive variable structure control technique is designed, which contains hyperbolic tangent function that preserves control smoothness at all times. The proposed control algorithm has the properties that state variables converge to the origin asymptotically under parametric uncertainty and external disturbance. Furthermore, the controller derived here is extended by adding a feed-forward saturation compensation scheme to reduce the influence of unknown control input saturation on the system. Also, the saturation compensation scheme is derived by using a radial basis function neural network to approximate the unknown saturation nonlinearity. The associated stability proof of the resulting closed-loop system is presented based on Lyapunov analysis, and asymptotic convergence of the state variables is guaranteed via the Barbalat lemma. Numerical simulations are presented to illustrate the spacecraft performance obtained by using the proposed controllers.

A combined variable reluctance network-finite element VR machine modeling for stator inter-turn short-circuit diagnosis

<span lang="EN-US">The work presented in this paper, proposes a comparison study between the network variable reluctance (NVR) model and the finite elements (FE) model intended for the diagnosis of stator inter-turn short-circuit (ITSC) of the variable reluctance machine (VRM). In the first place, the model of the VRM by the NRV is presented. To validate this model, the FE model of the VRM has been then studied. The detection of the ITSC is achieved by the use of the stator current spectral analysis technique. The simulation results obtained, illustrate well the interest and efficiency of the proposed model as well as of the merits of the stator current spectral analysis technique for the stator ITSC fault diagnosis of the VRM.</span>

Network Effects in Blau Space: Imputing Social Context from Survey Data

We develop a method of imputing ego network characteristics for respondents in probability samples of individuals. This imputed network uses the homophily principle to estimate certain properties of a respondent’s core discussion network in the absence of actual network data. These properties measure the potential exposure of respondents to the attitudes, values, beliefs, and so on of their (likely) network alters. We use American National Election Study data to demonstrate that the imputed network features show substantial effects on individual-level measures, such as political attitudes and beliefs. In some cases, the imputed network variable substantially reduces the effects of standard sociodemographic variables, like age and education. We argue that the imputed network variable captures many of the aspects of social context that have been at the core of sociological analysis for decades.

Provider Connectedness to Other Providers Reduces Risk of Readmission After Hospitalization for Heart Failure

Provider interactions other than explicit care coordination, which is challenging to measure, may influence practice and outcomes. We performed a network analysis using claims data from a commercial payor. Networks were identified based on provider pairs billing outpatient care for the same patient. We compared network variables among patients who had and did not have a 30-day readmission after hospitalization for heart failure. After adjusting for comorbidities, high median provider connectedness—normalized degree, which for each provider is the number of connections to other providers normalized to the number of providers in the region—was the network variable associated with reduced odds of readmission after heart failure hospitalization (odds ratio = 0.55; 95% confidence interval [0.35, 0.86]). We conclude that heart failure patients with high provider connectedness are less likely to require readmission. The structure and importance of provider relationships using claims data merits further study.

The Impact of Remittances on Child Education in Pakistan

This study examines the impact of remittances on school enrollment and the level of education attained among children aged 4–15 years in Pakistan. It uses a nationally representative survey, the Pakistan Social and Living Standards Measurement Survey for 2010/11. The migrant network variable at the village level interacting with the number of adults at the household level is used as an instrument for remittances. The results of the IV probit model show that children from remittance-receiving households are more likely to enroll in school. The marginal impact of remittances on school enrollment is larger for girls and for rural households. Hence, remittances help reduce regional and gender disparities in child school enrollment in Pakistan. The IV censored ordered probit model is used to investigate the impact of remittances on children’s grade attainment. The estimated impact is negative and significant, except for urban children, lowering the probability that a child will move to a higher grade.

ANALISIS FAKTOR-FAKTOR YANG MEMENGARUHI DAYA SAING PADA SENTRA INDUSTRI MAKANAN KHAS BANGKA DI KOTA PANGKALPINANG

This study aims to determine the effect of capital, packaging, network, business development, and human resource to the competitive ability at central industry of Bangka’s food in Pangkalpinang.It used primary data with census method as the sampling technique. The number of samples were 68 respondents, analyzed by confirmatory factor. The results of study issue two factors. First, financial factor which has capital and business development variable. Second, marketing factor which has packaging and network variable. Keywords: Micro and Medium Enterprise, Capital, Business Development, Financial Factor, Packaging, Network, Marketing Factor