Adaptive streaming over Hypertext Transport Protocol (HTTP) has been widely used for the transmission of video content. Most of the existing studies about HTTP adaptive streaming (HAS) concentrate on improving resource efficiency, fairness among users, and quality of service for single-source videos. However, there is a growing number of live streaming applications, such as video-casts of courses, where service providers want to transmit video streams of different scenes simultaneously over the bandwidth-constrained network. Since concurrent streams further deteriorate the insufficient bandwidth situation, a systematic solution is highly needed to utilize the resources efficiently and guarantee the quality of multi-view video services. In this paper, we propose a priority-based adaptive scheme for multi-view live streaming based on HTTP streaming. Firstly, we adopt an integrated bandwidth prediction approach to calculate the available bandwidth, solving the low bandwidth utilization problem existing in the benchmark method. Secondly, we design a unified segment request strategy to restrict the interval between each request, and guarantee the synchronization of different live video streams. Finally, an adaptive scheduling algorithm is proposed with respect to priorities, to dynamically adjust the quality level of multiple video streams and improve the quality of multi-view video service. Simulations show that the proposed scheme makes considerable improvements compared to the benchmarks.

Psoriasis is a chronic and inflammatory skin disorder characterized by inflammation and epidermal hyperplasia. Punicalagin (PUN) is a main active ingredient of pomegranate (Punica granatum L.) peel with multiple biological activities, such as antibacterial, antioxidant and anti-tumor effects. However, the potential effect of PUN on psoriasis remains unknown. In this study, we want to investigate the pharmacological effect of PUN on psoriasis by using imiquimod (IMQ)-induced psoriatic mice model in vivo and tumor necrosis factor a (TNF-α) and interleukin-17A (IL-17A)-stimulated HaCaT cells in vitro. Our results showed that PUN can effectively alleviate the severity of psoriasis-like symptoms. Mechanistically, PUN potently suppresses the aberrant upregulation of interleukin-1β (IL-1β) and subsequent IL-1β-mediated inflammatory cascade in keratinocytes by inhibiting the nuclear factor kappa B (NF-κB) activation and cleaved caspase-1 expression in vitro and in vivo. Taken together, our findings indicate that PUN can relieve psoriasis by repressing NF-κB-mediated IL-1β transcription and caspase-1-regulated IL-1β secretion, which provide evidence that PUN might represent a novel and promising candidate for the treatment of psoriasis.

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Temperature and humidity are two important interconnected factors in the performance of PEMFCs (Proton Exchange Membrane Fuel Cells). The fuel and oxidant humidity and stack temperature in a fuel cell were analyzed in this study. There are many factors that affect the temperature and humidity of the stack. We adopt the fuzzy control method of multi-input and multi-output to control the temperature and humidity of the stack. A model including a driver, vehicle, transmission motor, air feeding, electrical network, stack, hydrogen supply and cooling system was established to study the fuel cell performance. A fuzzy controller is proven to be better in improving the output power of fuel cells. The three control objectives are the fan speed control for regulating temperature, the solenoid valve on/off control of the bubble humidifier for humidity variation and the speed of the pump for regulating temperature difference. In addition, the results from the PID controller stack model and the fuzzy controller stack model are compared in this research. The fuel cell bench test has been built to validate the effectiveness of the proposed fuzzy control. The maximum temperature of the stack can be reduced by 5 °C with the fuzzy control in this paper, so the fuel cell output voltage (power) increases by an average of approximately 5.8%.