Assise: Performance and Availability via NVM Colocation in a Distributed File System

The adoption of very low latency persistent memory modules (PMMs) upends the long-established model of disaggregated file system access. Instead, by colocating computation and PMM storage, we can provide applications much higher I/O performance, sub-second application failover, and strong consistency. To demonstrate this, we built the Assise distributed file system, based on a persistent, replicated coherence protocol for managing a set of server-colocated PMMs as a fast, crash-recoverable cache between applications and slower disaggregated storage, such as SSDs. Unlike disaggregated file systems, Assise maximizes locality for all file IO by carrying out IO on colocated PMM whenever possible and minimizes coherence overhead by maintaining consistency at IO operation granularity, rather than at fixed block sizes. We compare Assise to Ceph/Bluestore, NFS, and Octopus on a cluster with Intel Optane DC PMMs and SSDs for common cloud applications and benchmarks, such as LevelDB, Postfix, and FileBench. We find that Assise improves write latency up to 22x, throughput up to 56x, fail-over time up to 103x, and scales up to 6x better than its counterparts, while providing stronger consistency semantics. Assise promises to beat the MinuteSort world record by 1.5x

Effect of a graphene oxide coating layer on critical heat flux enhancement under pool boiling

We report an investigation of the boiling heat transfer characteristics of graphene-based materials. Pool boiling experiments were carried out to investigate the critical heat flux (CHF) enhancement in a graphene oxide (GO) colloidal suspension with various concentrations as the working fluid with a Nichrome wire heat source. We found that nucleate boiling resulted in deposition of the GO colloids onto the heated wire, whereby the GO flakes formed a smooth laminated film, and that the thickness of this layer was approximately proportional to the observed increase in the CHF. The surface wettability could not explain the enhancement in the CHF. Instead, we focused on thermal activity analysis based on heat dissipation effects of the GO layer with extraordinary thermal properties. The large thermal conductivity of the GO layer inhibited the formation of local hot spots, thus preventing the formation of dryout regions and delaying the CHF. Furthermore, a thermal reduction of the GO colloids led to further increase of its thermal conductivity, also thermal activity, and hence additional enhancement of the CHF. (C) 2014 Elsevier Ltd. All rights reserved.X111715sciescopu

Crawling Magnetic Robot to Perform a Biopsy in Tubular Environments by Controlling a Magnetic Field

We developed a crawling magnetic robot (CMR), which can stably navigate and perform biopsies remotely in tubular environments by controlling a magnetic field. The CMR is composed of a crawling part and a biopsy part. The crawling part allows the CMR to crawl forward and backward via an asymmetric friction force generated by an external precessional magnetic field. The biopsy part closes or opens the cover of a needle to use the biopsy needle selectively with the control of the external precessional magnetic field. The cover of the biopsy part prevents damage to the tubular environments because the biopsy needle is inside the cover while the CMR is navigating. We developed the design of the proposed CMR using magnetic torque constraints and a magnetic force constraint, and then we fabricated the CMR with three-dimensional printing technology. Finally, we conducted an experiment to measure the CMR’s puncturing force with a load cell and conducted an experiment in a Y-shaped watery glass tube with pseudo-tissue to verify the crawling motion, the uncovering and covering motion of the biopsy needle, and the CMR’s ability to extract tissue with the biopsy needle

Digital Twin for Operation of Microgrid: Optimal Scheduling in Virtual Space of Digital Twin

Due to the recent development of information and communication technology (ICT), various studies using real-time data are now being conducted. The microgrid research field is also evolving to enable intelligent operation of energy management through digitalization. Problems occur when operating the actual microgrid, causing issues such as difficulty in decision making and system abnormalities. Using digital twin technology, which is one of the technologies representing the fourth industrial revolution, it is possible to overcome these problems by changing the microgrid configuration and operating algorithms of virtual space in various ways and testing them in real time. In this study, we proposed an energy storage system (ESS) operation scheduling model to be applied to virtual space when constructing a microgrid using digital twin technology. An ESS optimal charging/discharging scheduling was established to minimize electricity bills and was implemented using supervised learning techniques such as the decision tree, NARX, and MARS models instead of existing optimization techniques. NARX and decision trees are machine learning techniques. MARS is a nonparametric regression model, and its application has been increasing. Its performance was analyzed by deriving performance evaluation indicators for each model. Using the proposed model, it was found in a case study that the amount of electricity bill savings when operating the ESS is greater than that incurred in the actual ESS operation. The suitability of the model was evaluated by a comparative analysis with the optimization-based ESS charging/discharging scheduling pattern

Genome/transcriptome analysis of the chigger mite Leptotrombidium pallidum, a major vector for scrub typhus, with a special focus on genes more abundantly expressed in larval stage

Leptotrombidium pallidum is the major vector mite for Orientia tsutsugamushi, the causative agent of scrub typhus, in Asian countries, including Korea. Despite its medical importance, L. pallidum has little genetic information available to date. To analyze the L. pallidum genome, we extracted genomic DNA (gDNA) from a single female of a 7-generation inbred L. pallidum colony and amplified the gDNA by whole genome amplification (WGA). The resulting amplified gDNA was used to construct paired-end and mate-pair libraries that were sequenced using Illumina platforms (HiSeq2000 and MiSeq). More than 45 Gb of sequence reads from both paired-end and mate-pair libraries of the WGA gDNA were trimmed and then de novo assembled using CLC Assembly Cell v.4.0 for contig assembly and SSPACE for scaffolding. The assembly generated approximately 6,545 scaffolds with an N50 value of 92,945 and total size of similar to 193 Mb. For gene predictions, the PASA and GeneWise models were used, and ab initio gene predictions were performed independently, resulting in the prediction of 15,842 genes. RNA-Seq expression profiles revealed constitutive expression of 11,572 unique protein-coding genes in larva, 12,364 in protonymph, 12,872 in male adult, and 12,617 in female adult stages. Of the 15,842 predicted genes, 10,885 were commonly expressed through all L. pallidum stages. Genes selectively over-transcribed in the larval stage, which is when host parasitization and disease transmission occur, were further annotated, and their putative roles were discussed.N

Quantitative Neutron Dark-Field Imaging of Milk: A Feasibility Study

Scattering studies of milk and milk products, which are highly relevant food products on the global market, are often utilized and reported in literature to investigate and understand the subtle microscopic structural differences between dairy samples. These structural features determine the physical properties and ultimately the texture of milk products and, thus, also influence the consumer’s experience. Small-angle neutron scattering is a prominent example, which enables observations of length scales, which convey proteins and fat globules in food-grade milk. In addition, deuteration enables contrast variations between the constituents of dairy products. In this study, we investigate the potential of probing small-angle neutron scattering from milk samples through quantitative neutron dark-field imaging using grating interferometry, to establish the feasibility of studying, in particular, fat globules and milk gel structures with this spatially resolved scattering technique

Quantitative Neutron Dark-Field Imaging of Milk: A Feasibility Study

International audienceScattering studies of milk and milk products, which are highly relevant food products on the global market, are often utilized and reported in literature to investigate and understand the subtle microscopic structural differences between dairy samples. These structural features determine the physical properties and ultimately the texture of milk products and, thus, also influence the consumer’s experience. Small-angle neutron scattering is a prominent example, which enables observations of length scales, which convey proteins and fat globules in food-grade milk. In addition, deuteration enables contrast variations between the constituents of dairy products. In this study, we investigate the potential of probing small-angle neutron scattering from milk samples through quantitative neutron dark-field imaging using grating interferometry, to establish the feasibility of studying, in particular, fat globules and milk gel structures with this spatially resolved scattering technique

Assise: Performance and Availability via Client-local NVM in a Distributed File System

The adoption of low latency persistent memory modules (PMMs) upends the long-established model of remote storage for distributed file systems. Instead, by colocating computation with PMM storage, we can provide applications with much higher IO performance, sub-second application failover, and strong consistency. To demonstrate this, we built the Assise distributed file system, based on a persistent, replicated coherence protocol that manages client-local PMM as a linearizable and crash-recoverable cache between applications and slower (and possibly remote) storage. Assise maximizes locality for all file IO by carrying out IO on process-local, socket-local, and client-local PMM whenever possible. Assise minimizes coherence overhead by maintaining consistency at IO operation granularity, rather than at fixed block sizes. We compare Assise to Ceph/BlueStore, NFS, and Octopus on a cluster with Intel Optane DC PMMs and SSDs for common cloud applications and benchmarks, such as LevelDB, Postfix, and FileBench. We find that Assise improves write latency up to 22x, throughput up to 56x, fail-over time up to 103x, and scales up to 6x better than its counterparts, while providing stronger consistency semantics.QC 20201109</p