Out-Of-Band Management on UEFI System Firmware

The modern Redfish is a specification that utilize RESTful interface semantics to access data defined in model format to perform out-of-band (OOB) management through specific OOB software or hardware (such as Baseboard Management Controller, BMC). The OOB management allow users to configure system remotely when the system is in either power-off or power-on state. Industry can expect there are more and more pre-boot firmware drivers (like UEFI drivers) and system peripherals (such as PCI devices, PCI add-on-card and so on) support Redfish Schema/Configuration data model in the near future. This article describes the method to abstract the data communication/synchronization between UEFI drivers and OOB management on UEFI firmware environment. Furthermore, this article is not only restricted to single OOB management on system, the abstracts method described in this article is flexible and extensible to support multiple OOB management instances on one system simultaneously. Not only Redfish OOB management data model is supported, this article fulfills the requirements of any other data model of OOB managements such as OData XML/JSON data model, CIM-XML data model, 3rd party data model and etc

Regioselective One-pot Protection and Protection-glycosylation of Carbohydrates

Deciphering the roles and structure–activity relationships of carbohydrates in biological processes requires access to sugar molecules of confirmed structure and high purity. Chemical synthesis is one of the best ways to obtain such access. However, the synthesis of carbohydrates has long been impeded by two major challenges – the regioselective protection of the polyol moiety of each monosaccharide building block and the stereoselective glycosylation to produce oligosaccharides of desired length. Here, we review the development of the first regioselective protection-glycosylation and a revolutionary regioselective combinatorial one-pot protection of monosaccharides that can be used to differentiate the various hydroxy groups of monosaccharides with a vast array of orthogonal protective groups in one-pot procedures

Effects of Hydrogen Plasma on the Electrical Properties of F-Doped ZnO Thin Films and p-i-n -Si:H Thin Film Solar Cells

1.5 wt% zinc fluoride (ZnF2) was mixed with zinc oxide powder to form the F-doped ZnO (FZO) composition. At first, the FZO thin films were deposited at room temperature and 5×10-3 Torr in pure Ar under different deposition power. Hall measurements of the as-deposited FZO thin films were investigated, and then the electrical properties were used to find the deposition power causing the FZO thin films with minimum resistance. The FZO thin films with minimum resistance were further treated by H2 plasma and then found their variations in the electrical properties by Hall measurements. Hydrochloric (HCl) acid solutions with different concentrations (0.1%, 0.2%, and 0.5%) were used to etch the surfaces of the FZO thin films. Finally, the as-deposited, HCl-etched as-deposited, and HCl-etched H2-plasma-treated FZO thin films were used as transparent electrodes to fabricate the p-i-n α-Si:H thin film solar cells and their characteristics were compared in this study. We would show that using H2-plasma-treated and HCl-etched FZO thin films as transparent electrodes would improve the efficiency of the fabricated thin film solar cells

A Reinforcement Learning Approach for the Multichannel Rendezvous Problem

In this paper, we consider the multichannel rendezvous problem in cognitive radio networks (CRNs) where the probability that two users hopping on the same channel have a successful rendezvous is a function of channel states. The channel states are modelled by two-state Markov chains that have a good state and a bad state. These channel states are not observable by the users. For such a multichannel rendezvous problem, we are interested in finding the optimal policy to minimize the expected time-to-rendezvous (ETTR) among the class of {\em dynamic blind rendezvous policies}, i.e., at the $t^{th}$ time slot each user selects channel $i$ independently with probability $p_i(t)$, $i=1,2, \ldots, N$. By formulating such a multichannel rendezvous problem as an adversarial bandit problem, we propose using a reinforcement learning approach to learn the channel selection probabilities $p_i(t)$, $i=1,2, \ldots, N$. Our experimental results show that the reinforcement learning approach is very effective and yields comparable ETTRs when comparing to various approximation policies in the literature.Comment: 5 pages, 9 figures. arXiv admin note: text overlap with arXiv:1906.1042

Molecular typing and profiling of topoisomerase mutations causing resistance to ciprofloxacin and levofloxacin in Elizabethkingia species

Objectives Several Elizabethkingia species often exhibit extensive antibiotic resistance, causing infections associated with severe morbidity and high mortality rates worldwide. In this study, we determined fluoroquinolone susceptibility profiles of clinical Elizabethkingia spp. isolates and investigated the resistance mechanisms. Methods In 2017–2018, 131 Elizabethkingia spp. isolates were recovered from specimens collected at tertiary care centers in northern Taiwan. Initial species identification using the Vitek MS system and subsequent verification by 16S rRNA sequencing confirmed the presence of Elizabethkingia anophelis (n = 111), E. miricola (n = 11), and E. meningoseptica (n = 9). Fluoroquinolone susceptibility was determined using the microbroth dilution method, and fluoroquinolone resistance genes were analyzed by sequencing. Results Among Elizabethkingia spp. isolates, 91% and 77% were resistant to ciprofloxacin and levofloxacin, respectively. The most prevalent alterations were two single mutations in GyrA, Ser83Ile, and Ser83Arg, detected in 76% of the isolates exhibiting fluoroquinolone MIC between 8 and 128 μg/ml. Another GyrA single mutation, Asp87Asn, was identified in two quinolone-resistant E. miricola strains. None of the isolates had alterations in GyrB, ParC, or ParE. We developed a high-resolution melting assay for rapid identification of the prevalent gyrA gene mutations. The genetic relationship between the isolates was evaluated by random amplified polymorphic DNA PCR that yielded diverse pulsotypes, indicating the absence of any temporal or spatial overlap among the patients during hospitalization. Conclusion Our analysis of fluoroquinolone-resistant Elizabethkingia spp. isolates provides information for further research on the variations of the resistance mechanism and potential clinical guidance for infection management