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Increasing antimicrobial resistance to key antibiotics in Helicobacter pylori has become a main cause of treatment failures in many countries, including Vietnam. For this reason it is advisable to perform antimicrobial sensitivity tests to provide more focused regimens for H. pylori eradication. However, this approach is generally unavailable for H. pylori in Vietnam and the selection of treatment regimens is mainly based on the trend of antibiotic use in the population, resistance development in the region, and history of H. pylori eradication of patients. The aim of this review is to examine the current situation of antimicrobial resistance in Vietnam and suggest management strategies for treatment selection.

Fair bandwidth allocation (FBA) has been studied in optical burst switching (OBS) networks, with the main idea being to map the max‐min fairness in traditional IP networks to the fair‐loss probability in OBS networks. This approach has proven to be fair in terms of the bandwidth allocation for differential connections, but the use of the ErlangB formula to calculate the theoretical loss probability has made this approach applicable only to Poisson flows. Furthermore, it is necessary to have a reasonable fairness measure to evaluate FBA models. This article proposes an approach involving throughput‐based‐FBA, called TFBA, and recommends a new fairness measure that is based on the ratio of the actual throughput to the allocated bandwidth. An analytical model for the performance of the output link with TFBA is also proposed.

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Abstract:Burst assembly plays an important role in reducing the end-to-end delay of packets transported through optical burst switching (OBS) networks. Several methods have been proposed to reduce the delay of the packets buffered at ingress OBS nodes. However, these have created significant estimation errors, which result in wasting the reserved bandwidth or increasing the delay of excess packets. In this paper, we propose a model of optimal burst assembly for delay reduction, which minimizes the estimation error, eliminates the excess packets, and decreases the blocking probability of scheduling.