Dielectric polymer materials with high energy density and low dielectric loss are highly desired for applications in advanced electronic devices and electric power systems. Here, we report on flexible dielectric composites using semiconductor nanoparticles as fillers and polyvinylidene fluoride (PVDF) as a matrix. The introduction of a small amount of ZnO filler results in significantly enhanced voltage breakdown strength and energy density in comparison with pure PVDF. Based on the multi-core model, combining the electric double layer theory and the interface contact theory, we investigate mechanisms and come out with that transportation of carriers under applied voltage is regulated by the charged interface, which delays the formation of the conduction path. Besides, the electric field imposed on the composites is alleviated by the internal micro-electric field.

Solar energy is the key to clean energy, which can generate large amounts of electricity for the future smart grid. Unfortunately, the randomness and intermittency of solar energy resources bring difficulties to the stable operation and management of the power systems. To reduce the negative impact of photovoltaic (PV) plants accessing on the power systems, it is great significant to predict PV power accurately. In light of this, we propose a hybrid deep learning approach based on convolutional neural network (CNN) and long-short term memory recurrent neural network (LSTM) for the PV output power forecasting. The CNN model is leveraged to discover the nonlinear features and invariant structures exhibited in the previous output power data, thereby facilitating the prediction of PV power. The LSTM is used to model the temporal changes in the latest PV data, and predict the PV power of next time step. Then, the prediction results in the two models are comprehensively considered to obtain the expected output power. The proposed approach is extensively evaluated on real PV data in Limberg, Belgium, and numerical results demonstrate that the proposed approach can provide good prediction performance in PV systems. INDEX TERMS Solar energy, deep learning, photovoltaic (PV) power forecasting, power systems.

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We estimated the inpatient resource use for a Fontan patient from birth to adulthood and explored factors that might induce cost differences (2014 US dollar). Inpatient costing records from four hospitals with greatest numbers of Fontan patients in Australia and New Zealand were linked with the Fontan registry database. Inpatient records between July 1995 and September 2014 for 420 Fontan patients were linked, and the most frequent primary diagnoses were hypoplastic left heart syndrome (HLHS) (20.7%), tricuspid atresia (19.7%), and double inlet left ventricle (17.1%). The mean hospital cost for a Fontan patient from birth to 18 years of age was estimated to be $390,601 (95% confidence interval [CI] $264,703 to $516,499), corresponding to 164 (95% CI 98 to 231) inpatient days. The cost incurred from birth through to Fontan completion (the staged procedures period) was $219,482 (95% CI $202,410 to $236,553) and the cost thereafter over 15 years was $146,820 (95% CI $44,409 to $249,231), corresponding to 82 (95% CI 72 to 92) and 65 (95% CI 18 to 112) inpatient days respectively. Costs were higher in male and HLHS patients in the staged procedures period (P<0.001). Having fenestration was associated with higher costs in the staged procedures period (P<0.001) and lower cost post Fontan over 15 years (P=0.66). In conclusion, patients with single-ventricle congenital heart disease continue to demand considerable inpatient resources after the staged procedures period. Over 40% of the pediatric hospital costs for Fontan patients were estimated to occur after the last planned surgery.Key Words: Fontan patients, hospital cost, congenital heart disease, health serviceThe Fontan procedure is the final in a series of staged palliations for single-ventricle congenital heart disease, affecting approximately 1 in 2000 live births. 1, 2 As the outcomes of the staged procedures improve, an increasing number of children with complex heart conditions have survived into adulthood. [2][3][4][5] More patients are now undergoing staged procedures 6-8 but the trend in long-term inpatient cost and care needs for this population are unclear. Using hospital billing data associated with encounters, Keren et al. (2012) have shown that the cumulative costs of the 10 most expensive pediatric conditions in the US accounted for approximately one third of the standardized costs for all pediatric visits to hospital, and single-ventricle congenital heart defects such as hypoplastic left heart syndrome (HLHS) ranked 7 th on the list. 9 Previous studies also documented the costs of a single staged procedure 10, 11 , the costs of non-cardiac admissions to pediatric hospitals 12 , and the costs of admissions in adults for this patient group. 13 Nevertheless, the literature is limited by its focus on single encounters and knowledge regarding the long-term trend in hospital costs for single-ventricle patients is lacking. The purpose of this study was to assess the trend in longterm hospital costs for single-ventricle patients surviving the F...

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