Learning to Optimize LSM-trees: Towards A Reinforcement Learning based Key-Value Store for Dynamic Workloads

LSM-trees are widely adopted as the storage backend of key-value stores. However, optimizing the system performance under dynamic workloads has not been sufficiently studied or evaluated in previous work. To fill the gap, we present RusKey, a key-value store with the following new features: (1) RusKey is a first attempt to orchestrate LSM-tree structures online to enable robust performance under the context of dynamic workloads; (2) RusKey is the first study to use Reinforcement Learning (RL) to guide LSM-tree transformations; (3) RusKey includes a new LSM-tree design, named FLSM-tree, for an efficient transition between different compaction policies -- the bottleneck of dynamic key-value stores. We justify the superiority of the new design with theoretical analysis; (4) RusKey requires no prior workload knowledge for system adjustment, in contrast to state-of-the-art techniques. Experiments show that RusKey exhibits strong performance robustness in diverse workloads, achieving up to 4x better end-to-end performance than the RocksDB system under various settings.Comment: 25 pages, 13 figure

Effects of Graphite Additions on Microstructures and Wear Resistance of Fe-Cr-C-Nb Hardfacing Alloys

Hardfacing alloys with different carbon contents by changing graphite additions in flux-cored wires were prepared on a surface of steel C45E4 (ISO 683) using open-arc overlaying. Testing was conducted using scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), a Rockwell hardness tester and an abrasion tester to study the effect of variation of graphite additions on the microstructures, hardness and abrasive resistance of the hardfacing alloys. The results show that the microstructures of the hardfacing alloys consisted of ferrite, martensite, retained austenite, independent austenite and NbC particles. Firstly, as graphite additions increased, the carbon contents gradually increased and the microstructures of the hardfacing alloys changed from ferrite plus NbC particles to martensite with retained austenite and larger NbC particles, which was accompanied by hardness increasing and better abrasive resistance. And then the hardfacing layer alloy best performance was obtained as graphite addition was 60 g. The highest hardness was 61.8 HRC and the wear resistance was nearly four times as high as that of the base metal. But excessive graphite additions resulted in some independent austenite present in the microstructures of the hardfacing alloys together with martensite plus retained austenite and NbC particles, which deteriorated the performance of the hardfacing alloys

Genetic Diversity of Carbapenem-Resistant Enterobacteriaceae (CRE) Clinical Isolates From a Tertiary Hospital in Eastern China

The prevalence of carbapenem-resistant Enterobacteriaceae (CRE) is increasing globally, with different molecular mechanisms described. Here we studied the molecular mechanisms of carbapenem resistance, including clonal and plasmid dissemination, of 67 CRE isolates collected between 2012 and 2016 from a tertiary hospital in Eastern China, an CRE endemic region. Species identification and susceptibility testing were performed using the BD Phoenix Automated Microbiology System. Isolates were characterized by PCR (for carbapenemases, ESBLs, AmpC and porin genes), multilocus sequence typing (MLST), pulsed-field gel electrophoresis (PFGE), and conjugation transfer experiments. Selected blaKPC-2 -harboring plasmids were subjected to next-generation sequencing using the Illumina Miseq platform. Among the 67 CRE isolates, 42 Klebsiella pneumoniae, 10 Serratia marcescens, 6 Enterobacter cloacae, 2 Raoultella ornithinolytica, 2 K. oxytoca, 1 K. aerogenes, and 4 Escherichia coli isolates were identified. Six different carbapenemases were detected, including blaKPC-2 (n = 45), blaKPC-3 (n = 1), blaNDM-1 (n = 6), blaNDM-5 (n = 1), blaIMP-4 (n = 2), and blaVIM-1 (n = 2); blaOXA-48-like genes were not detected. One E. cloacae strain possessed both blaNDM-1 and blaKPC-3, while two E. cloacae isolates harbored blaNDM-1 and blaVIM-1. ESBLs (CTX-M, SHV, and TEM) and/or AmpC (CMY, DHA, and ACT/MIR) genes were also identified in 59 isolates, including 13 strains that lacked carbapenemases. Several insertions or stop codon mutations were found within porin genes of K. pneumoniae, E. coli and S. marcescens isolates, both with and without carbapenemases. The 42 K. pneumoniae isolates belonged to 12 different sequence types (ST), with ST11 being the most common, while the 6 E. cloacae isolates comprised 4 different STs. The 10 S. marcescens all shared the same PFGE pulsotype, suggestive of clonal spread. Complete plasmid sequencing and PCR screening revealed both intra-strain and inter-species spread of a common blaKPC-2-harboring plasmid in our hospital. Taken together, our study revealed extensive genetic diversity among CRE isolates form a single Chinese hospital. CRE isolates circulating in the hospital differ significantly in their species, STs, porin genes, carbapenemase genes, and their plasmid content, highlighting the complex dissemination of CRE in this endemic region

Tribological Properties of Carbon Fabric/Epoxy Composites Filled with FGr@MoS2 Hybrids under Dry Sliding Conditions

Hybrids of fluorinated graphite/MoS2 (FGr@MoS2) were prepared via a hydrothermal method and used as lubricating additives to take full advantage of the synergy between FGr and MoS2 in carbon-fiber-reinforced polymer (CFRP). The results show a 21.6% reduction in the friction coefficient compared to the neat sample when the CFRP was filled with 1.2 wt.% FGr@MoS2 hybrids. The addition of 1.5 wt.% FGr@MoS2 resulted in a 60.9% reduction in the wear rate compared to neat CFRP. For the 1.2 wt.% FGr@MoS2-reinforced CFRP, the friction coefficient maintained a relatively steady value of approximately 0.46 at various temperatures, indicating frictional stability. However, the wear rate increased by 13.95% at 60 °C compared to that at room temperature. The interfacial bonding force between the FGr@MoS2 hybrid and the matrix, as well as the adhesive force with the surface of the counterpart ball, is improved, caused by the heterostructure of FGr@MoS2, resulting in enhanced mechanical properties and formation efficiency as well as the transfer film on the surface of the counterpart ball. The results suggest that an FGr@MoS2 micro-nano structure is a promising additive to be applied in polymer tribology

The Spatial Effect of Accessibility to Public Service Facilities on Housing Prices: Highlighting the Housing Equity

Understanding how public service accessibility is related to housing prices is crucial to housing equity, yet the heterogeneous capitalisation effect remains unknown. This study aims to investigate the spatial effect of public service accessibility on housing prices in rapidly urbanising regions. Here, we propose a novel methodological framework that integrates the hedonic price model, geographical detector model and the spatial association detector model to understand housing equity issues. The rapidly rising housing prices, vastly transformed urban planning and heterogeneous land use patterns make the urban centre of Wuhan a typical case study. High-value units of public service accessibility are concentrated in built-up areas, while low-value units are located at the urban fringe. The results indicate that larger public services have more significant clustering effects than smaller ones. Recreational, medical, educational and financial facilities all have capitalisation effects on housing prices. Both the geographical detector model and the spatial association detector model could identify the drivers of housing prices, but the explanatory power of the latter is greater and could enhance the validity and reliability of the findings. We further find that the explanatory power of the driving factors on housing prices obtained from the spatial association detector model is greater than that of the geographical detector model. Based on the spatial association detector model, the main drivers of public service facilities are accessibility to restaurants and bars and accessibility to ATMs. In addition, there are bivariate or nonlinear enhancement effects between each pair of driving factors. This approach provides significant insights for urban environmental development planning and local real estate planning

Rhamnose-Containing Compounds: Biosynthesis and Applications

Rhamnose-associated molecules are attracting attention because they are present in bacteria but not mammals, making them potentially useful as antibacterial agents. Additionally, they are also valuable for tumor immunotherapy. Thus, studies on the functions and biosynthetic pathways of rhamnose-containing compounds are in progress. In this paper, studies on the biosynthetic pathways of three rhamnose donors, i.e., deoxythymidinediphosphate-L-rhamnose (dTDP-Rha), uridine diphosphate-rhamnose (UDP-Rha), and guanosine diphosphate rhamnose (GDP-Rha), are firstly reviewed, together with the functions and crystal structures of those associated enzymes. Among them, dTDP-Rha is the most common rhamnose donor, and four enzymes, including glucose-1-phosphate thymidylyltransferase RmlA, dTDP-Glc-4,6-dehydratase RmlB, dTDP-4-keto-6-deoxy-Glc-3,5-epimerase RmlC, and dTDP-4-keto-Rha reductase RmlD, are involved in its biosynthesis. Secondly, several known rhamnosyltransferases from Geobacillus stearothermophilus, Saccharopolyspora spinosa, Mycobacterium tuberculosis, Pseudomonas aeruginosa, and Streptococcus pneumoniae are discussed. In these studies, however, the functions of rhamnosyltransferases were verified by employing gene knockout and radiolabeled substrates, which were almost impossible to obtain and characterize the products of enzymatic reactions. Finally, the application of rhamnose-containing compounds in disease treatments is briefly described

Dynamic Behavior Investigation of a Novel Epidemic Model Based on COVID-19 Risk Area Categorization

This study establishes a compartment model for the categorized COVID-19 risk area. In this model, the compartments represent administrative regions at different transmission risk levels instead of individuals in traditional epidemic models. The county-level regions are partitioned into High-risk (H), Medium-risk (M), and Low-risk (L) areas dynamically according to the current number of confirmed cases. These risk areas are communicable by the movement of individuals. An LMH model is established with ordinary differential equations (ODEs). The basic reproduction number R0 is derived for the transmission of risk areas to determine whether the pandemic is controlled. The stability of this LHM model is investigated by a Lyapunov function and Poincare–Bendixson theorem. We prove that the disease-free equilibrium (R0 < 1) is globally asymptotically stable and the disease will die out. The endemic equilibrium (R0 > 1) is locally and globally asymptotically stable, and the disease will become endemic. The numerical simulation and data analysis support the previous theoretical proofs. For the first time, the compartment model is applied to investigate the dynamics of the transmission of the COVID-19 risk area. This work should be of great value in the development of precision region-specific containment strategies

Dynamic Behavior Investigation of a Novel Epidemic Model Based on COVID-19 Risk Area Categorization

This study establishes a compartment model for the categorized COVID-19 risk area. In this model, the compartments represent administrative regions at different transmission risk levels instead of individuals in traditional epidemic models. The county-level regions are partitioned into High-risk (H), Medium-risk (M), and Low-risk (L) areas dynamically according to the current number of confirmed cases. These risk areas are communicable by the movement of individuals. An LMH model is established with ordinary differential equations (ODEs). The basic reproduction number R0 is derived for the transmission of risk areas to determine whether the pandemic is controlled. The stability of this LHM model is investigated by a Lyapunov function and Poincare–Bendixson theorem. We prove that the disease-free equilibrium (R0 R0 > 1) is locally and globally asymptotically stable, and the disease will become endemic. The numerical simulation and data analysis support the previous theoretical proofs. For the first time, the compartment model is applied to investigate the dynamics of the transmission of the COVID-19 risk area. This work should be of great value in the development of precision region-specific containment strategies