(E)-N′-[4-(Dimethyl­amino)­benzyl­idene]-4-methyl­benzohydrazide methanol monosolvate

In the title compound, C17H19N3O·CH3OH, the hydrazone mol­ecule exists in a trans geometry with respect to the methyl­idene unit and the dihedral angle between the two substituted benzene rings is 42.6 (2)°. In the crystal, the components are linked through N—H⋯O and O—H⋯O hydrogen bonds, forming [100] chains of alternating hydrazone and methanol mol­ecules

When Distributed Consensus Meets Wireless Connected Autonomous Systems: A Review and A DAG-based Approach

The connected and autonomous systems (CAS) and auto-driving era is coming into our life. To support CAS applications such as AI-driven decision-making and blockchain-based smart data management platform, data and message exchange/dissemination is a fundamental element. The distributed message broadcast and forward protocols in CAS, such as vehicular ad hoc networks (VANET), can suffer from significant message loss and uncertain transmission delay, and faulty nodes might disseminate fake messages to confuse the network. Therefore, the consensus mechanism is essential in CAS with distributed structure to guaranteed correct nodes agree on the same parameter and reach consistency. However, due to the wireless nature of CAS, traditional consensus cannot be directly deployed. This article reviews several existing consensus mechanisms, including average/maximum/minimum estimation consensus mechanisms that apply on quantity, Byzantine fault tolerance consensus for request, state machine replication (SMR) and blockchain, as well as their implementations in CAS. To deploy wireless-adapted consensus, we propose a Directed Acyclic Graph (DAG)-based message structure to build a non-equivocation data dissemination protocol for CAS, which has resilience against message loss and unpredictable forwarding latency. Finally, we enhance this protocol by developing a two-dimension DAG-based strategy to achieve partial order for blockchain and total order for the distributed service model SMR

Study on a High-Accuracy Real-Time Algorithm to Estimate SOC of Multiple Battery Cells Simultaneously

In traditional battery equalization strategy, open-circuit voltage (OCV) of battery cells was used to judge the difference of SOC between them. However, OCV is not only determined by SOC but also influenced by internal resistance, polarization voltage, capacity, and other nonlinear factors. As a result, OCV is not an ideal indicator of SOC differences, especially in transient conditions. In order to control battery consistency accurately, it is best to use SOC directly as standard for battery consistency judgment and control. To achieve this, an algorithm that can estimate SOC of multiple battery cells simultaneously with low computational complexity and high accuracy is needed. Limited by computing speed of Battery Control Unit (BCU), existing SOC estimation method is hard to estimate SOC of each battery cell simultaneously with high accuracy. In this research, a new SOC estimation strategy was proposed to estimate SOC of multiple battery cells simultaneously for battery equalization control. Battery model is established based on experimental data, and a processor-in-the-loop test system was established to verify the actual performance of the proposed algorithm. Results of simulation and test indicate that the proposed algorithm can estimate SOC of multiple battery cells simultaneously and achieved good real-time performance and high accuracy

Stability and genetic insights of the co-existence of blaCTX-M-65, blaOXA-1, and mcr-1.1 harboring conjugative IncI2 plasmid isolated from a clinical extensively-drug resistant Escherichia coli ST744 in Shanghai

BackgroundCo-existence of colistin, β-lactam and carbapenem in multidrug-resistant Enterobacteriaceae isolates poses a serious threat to public health. In this study, we investigated and characterized the co-occurrence of blaCTX-M-65, blaOXA-1, and mcr-1.1 strain isolated from a clinical extensively-drug-resistant Escherichia coli ST744 in Shanghai.MethodsAntimicrobial susceptibility test was carried out by agar dilution methods. Whole genome sequencing was conducted, and resistance genes, and sequence types of colistin in E. coli isolates were analyzed. Plasmid stability and amino acid mutations were assessed in E. coli isolates.ResultsA colistin resistant E. coli ST744, named ECPX221, was identified out of 145 fecal samples collected. The strain carries a 60,168 IncI2 plasmid with the mcr-1.1 gene. The strain also has blaCTX-M-65, blaOXA-1, dfrA14, qnrS1, cmlA5, arr2, ampC, aph(4)-Ia, sul1, and aadA5 resistance genes. The plasmid pECPX221 was capable of conjugation with an efficiency of 2.6 × 10−2. Notably, 45% of the transconjugants were determined as mcr-1.1-harboring in the colistin-free environment after 60 generation of passage. No mutations occurred in pmrB, mgrB, and phoPQ gene in the mcr-1.1-harboring transconjugants. Bioinformatic analysis indicated pECPX221 shared highly similar backbone with the previously reported mcr-1.1-harboring pAH62-1, pMFDS1339.1, pSCZE4, and p2018-10-2CC. Furthermore, sequencing and phylogenetic analyses revealed a similarity between other MCR-1-homolog proteins, indicating that ECPX221 was colistin resistant.ConclusionThe stable transferable mcr-1.1-harboring plasmid found in the E. coli ST744 strain indicated the high risk to disseminate the extensively-drug-resistance phenotype among Enterobacteriaceae