It has been shown that a nearly extremal black hole can be overcharged or overspun by a test particle if radiative and self-force effects are neglected, indicating that the cosmic censorship might fail. In contrast, the existing evidence in literature suggests that an extremal black hole cannot be overcharged or overspun in a similar process. In this paper, we show explicitly that even an exactly extremal black hole can be destroyed by a test particle, leading to a possible violation of the cosmic censorship. By considering higher order terms, which were neglected in previous analysis, we show that the violation is generic for any extremal Kerr-Newman black hole with nonvanishing charge and angular momentum. We also find that the allowed parameter range for the particle is very narrow, indicating that radiative and self-force effects should be considered and may prevent violation of the cosmic censorship.Comment: 9 pages, 2 figur

Day-ahead scheduling of generation units and storage devices is essential for the economic and efficient operation of a power system. Conventionally, a control center calculates the dispatch schedule by gathering information from all of the devices. However, this centralized control structure makes the system vulnerable to single point of failure and communication failures, and raises privacy concerns. In this paper, a fully distributed algorithm is proposed to find the optimal dispatch schedule for a smart grid with renewable and energy storage integration. The algorithm considers modified DC power flow constraints, branch energy losses, and energy storage charging and discharging efficiencies. In this algorithm, each bus of the system is modeled as an agent. By solely exchanging information with its neighbors, the optimal dispatch schedule of the conventional generators and energy storage can be achieved in an iterative manner. The effectiveness of the algorithm is demonstrated through several representative case studies.

Recent evidence shows that option volatility skews and volatility spreads between call and put options predict equity returns. This study investigates whether such predictive ability is driven by option traders' information advantage. We examine the predictive ability of volatility skews and volatility spreads around significant information events including earnings announcements, other firm-specific information events, and events that trigger significant market reactions. Consistent with option traders having an information advantage relative to equity traders before information events, we find that the option measures immediately before these events have higher predictive ability for short-term event returns than they do in a more dated window or before a randomly selected pseudo-event. We also find that option measures have predictive ability after information events. However, this predictive * Quantitative Management Associates; † Stern School of Business Administration, NYU; ‡ Columbia Business School. ability holds only for unscheduled corporate announcements, which suggests that, relative to equity traders, option traders have superior ability to process less anticipated information.

New sulfonium salts with diphenylamino asymmetrically substituted stilbene as a D-π-A conjugated system have been synthesized. The resulting photoacid generators exhibit a highly efficient acid photogeneration process by either one-photon 405 nm or two-photon 800 nm excitation.

Land surface evapotranspiration (ET) is an important component of the surface energy budget and water cycle. To solve the problem of the spatial-scale mismatch between in situ observations and remotely sensed ET, it is necessary to find the most appropriate upscaling approach for acquiring ground truth ET data at the satellite pixel scale. Based on a data set from two flux observation matrices in the middle stream and downstream of the Heihe River Basin, six upscaling methods were intercompared via direct validation and cross validation. The results showed that the area-weighted method performed better than the other five upscaling methods introducing auxiliary variables (the integrated Priestley-Taylor equation, weighted area-to-area regression kriging [WATARK], artificial neural network, random forest [RF], and deep belief network methods) over homogeneous underlying surfaces. Over moderately heterogeneous underlying surfaces, the WATARK method performed better. However, the RF method performed better over highly heterogeneous underlying surfaces. A combined method (using the area-weighted and WATARK methods for homogeneous and moderately heterogeneous underlying surfaces, respectively, and using the RF method for highly heterogeneous underlying surfaces) was proposed to acquire the daily ground truth ET data at the satellite pixel scale, and the errors in the ground truth ET data were evaluated. The Dual Temperature Difference (DTD) and ETMonitor were validated using ground truth ET data, which solve the problem of the spatial-scale mismatch and quantify uncertainties in the validation process.