Polyvinylidene fluoride (PVDF) film with high energy storage density has exhibited great potential for applications in modern electronics, particle accelerators, and pulsed lasers. Typically, dielectric/ferroelectric properties of PVDF film have been tailored for energy storage through stretching, annealing, and defect modification. Here, PVDF films were prepared by the solution casting method followed by an ultraviolet (UV) irradiation process, with special emphasis on how such treatment influences their dielectric and energy storage properties. Upon UV irradiation, the dielectric constant and breakdown strength of the PVDF film were enhanced simultaneously. A high energy density of 18.6 J/cm 3 , along with a charge–discharge efficiency of 81% at 600 MV/m, was achieved in PVDF after exposure to UV for 15 min. This work may provide a simple and yet effective route to enhance energy storage density of PVDF-based polymers.

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Lost circulation is one of the frequent challenges encountered in the well drilling and completion process, which can not only increase well construction time and operational cost but also pose great risk to the formation. However, choosing the most useful treatments may still be a problem due to the complexity of the drilling and geological condition. In this paper, machine-learning algorithms and big data technology are employed to mine and analyze drilling data of wells in South China Sea where lost circulation is severe. Geological characteristics, drilling fluids property parameters and operational drilling parameters are both considered. Moreover, an artificial neural network is employed to conduct supervised learning. The four metrics: accuracy, precision, f1 score and recall are used to evaluate the model. The trained artificial neural network model is employed to predict the lost circulation risks. To train and test the proposed model, drilling operation parameters, geological parameters and drilling property parameters are collected for lost circulation events for 50 drilled wells over past two years in South China Sea. The trained model is excellent with the most important evaluation metrics, attaining an accuracy up to 92%, with f1 score, recall and precision up to 89% similarly. This suggests that the model have a good generalization ability and can be applied to other fields. Data analysis through an artificial neural network is carried out to develop a lost circulation prediction system model. This methodology can predict six lost circulation risks, each is defined according to drilling mud loss rate. This is one of the first attempts to predict lost circulation using data-analytics and artificial intelligence. The proposed intelligent lost circulation prediction method can assist the drilling engineer to choose the optimal drilling parameters prior to drilling and avoid lost circulation events.

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To investigate the role of nerve growth factor (NGF) in the development of hypertensive renal vascular remodeling, antiserum against NGF (anti-NGF) or vehicle was injected at 3 weeks of age in spontaneously hypertensive rats (SHR) and Wistar-Kyoto (WKY) rats (n = 9 for each treatment in each strain). Flow-pressure (F-P) and pressure-glomerular filtration rate (P-GFR) relationships at vasodilated perfused kidneys were determined at 10 weeks of age. In the vehicle rats, blood pressure, renal noradrenaline content, the gradient of F-P (minimal vascular resistance at pre- and post-glomerular vasculature) and the X-intercept of P-GFR (preglomerular : postglomerular vascular resistance ratio) were greater in SHR than in WKY rats, although the gradient of P-GFR (glomerular filtration capacity) did not differ significantly between the strains. Blood pressure and renal noradrenaline content were lower in SHR receiving anti-NGF than in SHR receiving vehicle, although such difference was not observed in WKY rats. The gradient of F-P was less but the gradient of P-GFR was greater in SHR receiving anti-NGF compared with SHR receiving vehicle, although the similar differences did not occur in WKY rats. Blood pressure and renal noradrenaline content remained greater in SHR treated with anti-NGF compared with WKY rats treated with vehicle; however, the gradient of F-P did not differ significantly between them. Contrary, anti-NGF did not affect the X-intercept of P-GFR in either strain. In conclusion, NGF could contribute to the genesis of renal vascular remodeling, at least in part, through modification of renal sympathetic activity and blood pressure in SHR.