2,998 research outputs found

    Bishop-Phelps-Bolloba's theorem on bounded closed convex sets

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    This paper deals with the \emph{Bishop-Phelps-Bollob\'as property} (\emph{BPBp} for short) on bounded closed convex subsets of a Banach space XX, not just on its closed unit ball BXB_X. We firstly prove that the \emph{BPBp} holds for bounded linear functionals on arbitrary bounded closed convex subsets of a real Banach space. We show that for all finite dimensional Banach spaces XX and YY the pair (X,Y)(X,Y) has the \emph{BPBp} on every bounded closed convex subset DD of XX, and also that for a Banach space YY with property (β)(\beta) the pair (X,Y)(X,Y) has the \emph{BPBp} on every bounded closed absolutely convex subset DD of an arbitrary Banach space XX. For a bounded closed absorbing convex subset DD of XX with positive modulus convexity we get that the pair (X,Y)(X,Y) has the \emph{BPBp} on DD for every Banach space YY. We further obtain that for an Asplund space XX and for a locally compact Hausdorff LL, the pair (X,C0(L))(X, C_0(L)) has the \emph{BPBp} on every bounded closed absolutely convex subset DD of XX. Finally we study the stability of the \emph{BPBp} on a bounded closed convex set for the 1\ell_1-sum or \ell_{\infty}-sum of a family of Banach spaces

    Large Global Volatility Matrix Analysis Based on Structural Information

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    In this paper, we develop a novel large volatility matrix estimation procedure for analyzing global financial markets. Practitioners often use lower-frequency data, such as weekly or monthly returns, to address the issue of different trading hours in the international financial market. However, this approach can lead to inefficiency due to information loss. To mitigate this problem, our proposed method, called Structured Principal Orthogonal complEment Thresholding (Structured-POET), incorporates structural information for both global and national factor models. We establish the asymptotic properties of the Structured-POET estimator, and also demonstrate the drawbacks of conventional covariance matrix estimation procedures when using lower-frequency data. Finally, we apply the Structured-POET estimator to an out-of-sample portfolio allocation study using international stock market data

    Integrating Vehicle-to-Grid Technologies in Autonomous Electric Vehicle Systems

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    Electrochemical Vehicle-to-Grid (V2G) technologies in autonomous electric vehicles (EVs) offer immense potential to revolutionize energy management and optimize the utilization of EVs. By enabling bidirectional energy flow between EVs and the electric grid, V2G allows EVs not only to consume electricity but also to contribute power back to the grid when necessary. When combined with autonomous capabilities, V2G can provide even greater benefits and flexibility. This research abstract highlights key points concerning V2G technologies in autonomous EVs. Firstly, autonomous EVs equipped with V2G technology can function as mobile energy storage units, aiding in grid stabilization and balancing high electricity demand. Secondly, V2G-enabled autonomous EVs can participate in demand response programs, optimizing charging schedules to off-peak hours and reducing strain on the grid during peak demand. Moreover, V2G facilitates the integration of renewable energy sources by allowing autonomous EVs to store and inject excess renewable energy into the grid when needed. Furthermore, V2G-enabled autonomous EVs act as backup power sources during emergencies or power outages, ensuring uninterrupted electricity supply to critical infrastructure. By participating in V2G programs, autonomous EV owners can generate revenue by selling stored energy to the grid and providing grid services, offsetting EV ownership costs. Additionally, autonomous EVs with V2G technology can intelligently manage their charging and discharging based on factors like electricity prices, grid demand, and user preferences, thereby optimizing energy usage and reducing charging costs. While the widespread adoption of V2G technologies in autonomous EVs hinges on infrastructure development, standardization, regulatory frameworks, and user acceptance, their integration is poised to play a significant role in future sustainable energy and transportation systems. As autonomous and electric vehicle technologies continue to evolve, V2G capabilities hold tremendous promise in transforming energy management, promoting grid reliability, and maximizing the benefits of EVs for both consumers and the grid

    A Dog Model of Pancreaticojejunostomy Without Duct-to-Mucosa Anastomosis

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    Context Various anastomosis techniques have been introduced for the safe pancreaticoenterostomy. Objective In the present study, we developed an experimental animal model for simple pancreaticojejunostomy and evaluated the feasibility, safety, and efficacy of this technique. Animals Ten dogs were studied. Intervention The dogs underwent the simple approximation (“docking”) method for pancreaticojejunostomy and were re-explored on the 30th post-operative day. Main outcome measure After excision of the remnant pancreas with the jejunal segment of the pancreaticojejunostomy, the degrees of fibrosis in the remnant pancreas were analyzed according to the patency of the pancreaticojejunostomy. Results There were no mortalities and clinically significant complications. The patency of pancreaticojejunostomy remained in six cases and was obliterated in four cases. It was noted that obliterated pancreaticojejunostomy accompanied cases with more dilated pancreatic ducts (3.1±0.4 mm vs. 5.5±0.6 mm, P=0.008). The grade of pancreatic fibrosis was significantly correlated with the obliterated pancreaticojejunostomy (P=0.038) and the size change of the remnant pancreatic duct (P=0.040). Conclusions The suggested simple pancreaticojejunostomy method is easy and shows no evidence of significant pancreatic fistula. However, the potential risk of dysfunction in the remnant pancreas limits its possible clinical applications. The meticulous duct-to-mucosa pancreaticojejunostomy is highly preferred to manage the remnant pancreas following pancreaticoduodenectomy
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