The synthesis of efficient water-oxidation catalysts demands insight into the only known, naturally occurring water-oxidation catalyst, the oxygen-evolving complex (OEC) of photosystem II (PSII). Understanding the water oxidation mechanism requires knowledge of where and when substrate water binds to the OEC. Mn catalase in its Mn(III)-Mn(IV) state is a protein model of the OEC’s S2 state. From 17O-labeled water exchanged into the di-μ-oxo di-Mn(III,IV) coordination sphere of Mn catalase, CW Q-band ENDOR spectroscopy revealed two distinctly different 17O signals incorporated in distinctly different time regimes. First, a signal appearing after two hours of 17O exchange was detected with a 13.0 MHz hyperfine coupling. From similarity in the time scale of isotope incorporation and in the 17O μ-oxo hyperfine coupling of the di-μ-oxo di-Mn(III,IV) bipyridine model (Usov, O. M.; Grigoryants, V. M.; Tagore, R.; Brudvig, G. W.; Scholes, C. P. J. Am. Chem. Soc. 2007, 129, 11886-11887), this signal was assigned to μ-oxo oxygen. EPR line broadening was obvious from this 17O μ-oxo species. Earlier exchange proceeded on the minute or faster time scale into a non-μ-oxo position, from which 17O ENDOR showed a smaller 3.8 MHz hyperfine coupling and possible quadrupole splittings, indicating a terminal water of Mn(III). Exchangeable proton/deuteron hyperfine couplings, consistent with terminal water ligation to Mn(III), also appeared. Q-band CW ENDOR from the S2 state of the OEC was obtained following multi-hour 17O exchange, which showed a 17O hyperfine signal with a 11 MHz hyperfine coupling, tentatively assigned as μ-oxo-17O by resemblance to the μ-oxo signals from Mn catalase and the di-μ-oxo di-Mn(III,IV) bipyridine model.

Our analysis demonstrated that the multidisciplinary care program provided better health care and reduced renal replacement therapy in patients with advanced chronic kidney disease. By decreasing hospitalizations, emergent start, and the need for renal replacement therapy, the multidisciplinary care program was cost-effective.

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An appropriate session management technique is crucial in CPE WAN (customer premises equipment code area method) management protocol (CWMP) to efficiently handle numerous sessions. In addition, with the rapid growth of mobile devices, more clients with wireless links result in an environment with possibly higher connection failure rates (CFRs). To improve the resource utilisation in a server cluster, the feature of predictable numbers of connections in all CWMP sessions is used to design a dynamic distribution (DD) technique. By adaptively choosing an appropriate session management strategy, the proposed DD technique helps to minimise memory and time consumption in different network situations. When the network situation is good or there are only a small number of connections, DD distributes each session to a single cluster node. However, as the CFR increases with a large number of connections, DD replicates a session to a number of cluster nodes, but not to all cluster nodes. Furthermore, as the network situation improves, the replicated sessions are adaptively removed so as to reduce memory usage. Experimental results show that the DD approach generally outperforms previous techniques in terms of both memory and time consumption, especially when the CFR is higher than 2.8%.Introduction: With a large increase of networked devices, operators of telecommunication services have widely used CPE WAN management protocol (CWMP) to manage a massive number of devices. In addition, a well-known computing scheme to improve system performance is the server cluster, which groups several independent nodes in a system and responds to concurrent user requests. Furthermore, given the sheer number of mobile services, more wireless clients connected to server clusters result in overloaded servers and unstable links, and cause environments with high connection failure rates (CFRs) [1]. In view of all this, techniques of session management are usually utilised to prevent unexpected connection crashes. Two basic techniques are sticky session and session replication. For the sticky session technique, all requests in each session are directed to the same cluster node. The major advantage of the sticky session technique is that the memory space is well utilised, but the primary drawback is the single point of failure feature that can stop the system from working if the connection fails. In contrast, the session replication technique avoids the disconnection issue by duplicating sessions to all cluster nodes. However, a large amount of memory resources are needed for storing redundant information. On the other hand, although modern servers are equipped with considerable memory resources, with the increase in the number of clients (especially in the cloud environment), memory resources continue to be insufficient [2]. Early researches focused on enhancements of session management that have been thus introduced [3-5], but memory consumption remains the largest drawback. Hence, some other works have been presented for improving memory consu...