ALBERT

Description: 〈p〉Novel technological applications significantly favor alternatives to electrons toward constructing low power–consuming, high-speed all-optical integrated optoelectronic devices. Polariton condensates, exhibiting high-speed coherent propagation and spin-based behavior, attract considerable interest for implementing the basic elements of integrated optoelectronic devices: switching, transport, and logic. However, the implementation of this coherent polariton condensate flow is typically limited to cryogenic temperatures, constrained by small exciton binding energy in most semiconductor microcavities. Here, we demonstrate the capability of long-range nonresonantly excited polariton condensate flow at room temperature in a one-dimensional all-inorganic cesium lead bromide (CsPbBr〈sub〉3〈/sub〉) perovskite microwire microcavity. The polariton condensate exhibits high-speed propagation over macroscopic distances of 60 μm while still preserving the long-range off-diagonal order. Our findings pave the way for using coherent polariton condensate flow for all-optical integrated logic circuits and polaritonic devices operating at room temperature.〈/p〉

Description: Novel technological applications significantly favor alternatives to electrons toward constructing low power–consuming, high-speed all-optical integrated optoelectronic devices. Polariton condensates, exhibiting high-speed coherent propagation and spin-based behavior, attract considerable interest for implementing the basic elements of integrated optoelectronic devices: switching, transport, and logic. However, the implementation of this coherent polariton condensate flow is typically limited to cryogenic temperatures, constrained by small exciton binding energy in most semiconductor microcavities. Here, we demonstrate the capability of long-range nonresonantly excited polariton condensate flow at room temperature in a one-dimensional all-inorganic cesium lead bromide (CsPbBr 3 ) perovskite microwire microcavity. The polariton condensate exhibits high-speed propagation over macroscopic distances of 60 μm while still preserving the long-range off-diagonal order. Our findings pave the way for using coherent polariton condensate flow for all-optical integrated logic circuits and polaritonic devices operating at room temperature.

Description: With the energy and power costs increasing alongside the growth of the IT infrastructures, achieving workload concentration and high availability in cloud computing environments is becoming more and more complex. Virtual machine (VM) migration has become an important approach to address this issue, particularly; live migration of the VMs across the physical servers facilitates dynamic workload scheduling of the cloud services as per the energy management requirements, and also reduces the downtime by allowing the migration of the running instances. However, migration is a complex process affected by several factors such as bandwidth availability, application workload and operating system configurations, which in turn increases the complications in predicting the migration time in order to negotiate the service-level agreements in a real datacenter. In this paper, we propose an adaptive approach named improved MIGration (iMIG), in which we characterize some of the key metrics of the live migration performance, and conduct several experiments to study the impacts of the investigated metrics on the Kernel-based VM (KVM) functionalities, as well as the energy consumed by both the destination and the source hosts. Our results reveal the importance of the configured parameters: speed limit , TCP buffer size and max downtime , along with the VM properties and also their corresponding impacts on the migration process. Improper setting of these parameters may either incur migration failures or causes excess energy consumption. We witness a few bugs in the existing Quick EMUlator (QEMU)/KVM parameter computation framework, which is one of most widely used KVM frameworks based on QEMU. Based on our observations, we develop an analytical model aimed at better predictions of both the migration time and the downtime, during the process of VM deployment. Finally, we implement a suite of profiling tools in the adaptive mechanism based on the qemu-kvm-0.12.5 version, and our experiment results prove the efficiency of our approach in improving the live migration performance. In comparison with the default migration approach, our approach achieves a 40% reduction in the migration latency and a 45% reduction in the energy consumption.

Description: In this article, ground-motion prediction equations (GMPEs) based on the horizontal components of the strong-motion records from shallow crustal and upper-mantle earthquakes in Japan are presented. We assembled a large dataset from earthquakes with a moment magnitude ( M w ) over 4.9 and a reliable earthquake category (the tectonic location of earthquakes) up to the end of 2012. The GMPEs were based on a set of simple geometric attenuation functions. A bilinear magnitude-scaling function hinged at M w  7.1 was adopted, with the scaling rates for large events being much smaller than those for the smaller events. Site classes based on site period were used as site terms, and nonlinear site terms were included. We modeled the effect of volcanic zones using an anelastic attenuation coefficient applied to a horizontal portion of the seismic-wave travel distance within volcanic zones. Most strong-motion records in our dataset are from stations with a measured shear-wave velocity profile down to engineering bedrock. A small number of records are from stations with inferred site classes using the response spectral ratio of the horizontal-to-vertical components or geologic description of the surface soil layers. We tested the effect of site information quality by comparing the goodness-of-fit parameters from the model with and without the sites with inferred site classes. Our results suggest that the site information quality made a significant difference for spectral periods over 0.7 s, that is, the exclusion of sites with inferred site classes improves the model fit significantly. The within-event residuals were approximately separated into within-site and between-site components, and the corresponding standard deviations were calculated. The approximate separation allows for the possibility of adopting different standard deviations for different site classes in a probabilistic seismic-hazard analysis if desired. Online Material: References for fault rupture plane models, earthquake records and volcanic zones information, illustration of site information quality effect, standard deviations for between-event, within-event, between-site and within-site residual, and the distribution of between-event and within-event residuals.

Description: Cancer is often driven by the accumulation of genetic alterations, including single nucleotide variants, small insertions or deletions, gene fusions, copy-number variations, and large chromosomal rearrangements. Recent advances in next-generation sequencing technologies have helped investigators generate massive amounts of cancer genomic data and catalog somatic mutations in both common and rare cancer types. So far, the somatic mutation landscapes and signatures of 〉10 major cancer types have been reported; however, pinpointing driver mutations and cancer genes from millions of available cancer somatic mutations remains a monumental challenge. To tackle this important task, many methods and computational tools have been developed during the past several years and, thus, a review of its advances is urgently needed. Here, we first summarize the main features of these methods and tools for whole-exome, whole-genome and whole-transcriptome sequencing data. Then, we discuss major challenges like tumor intra-heterogeneity, tumor sample saturation and functionality of synonymous mutations in cancer, all of which may result in false-positive discoveries. Finally, we highlight new directions in studying regulatory roles of noncoding somatic mutations and quantitatively measuring circulating tumor DNA in cancer. This review may help investigators find an appropriate tool for detecting potential driver or actionable mutations in rapidly emerging precision cancer medicine.

Description: Tumor suppressor genes (TSGs) are a major type of gatekeeper genes in the cell growth. A knowledgebase with the systematic collection and curation of TSGs in multiple cancer types is critically important for further studying their biological functions as well as for developing therapeutic strategies. Since its development in 2012, the Tumor Suppressor Gene database (TSGene), has become a popular resource in the cancer research community. Here, we reported the TSGene version 2.0, which has substantial updates of contents (e.g. up-to-date literature and pan-cancer genomic data collection and curation), data types (noncoding RNAs and protein-coding genes) and content accessibility. Specifically, the current TSGene 2.0 contains 1217 human TSGs (1018 protein-coding and 199 non-coding genes) curated from over 9000 articles. Additionally, TSGene 2.0 provides thousands of expression and mutation patterns derived from pan-cancer data of The Cancer Genome Atlas. A new web interface is available at http://bioinfo.mc.vanderbilt.edu/TSGene/ . Systematic analyses of 199 non-coding TSGs provide numerous cancer-specific non-coding mutational events for further screening and clinical use. Intriguingly, we identified 49 protein-coding TSGs that were consistently down-regulated in 11 cancer types. In summary, TSGene 2.0, which is the only available database for TSGs, provides the most updated TSGs and their features in pan-cancer.

Description: Compiling for distributed-memory architectures comprise two main phases. The first phase is to determine computation and data composition. In the 1990s, a great deal of work addressed this problem. The second phase is code generation. However, there is still no effective solution to this problem. Existing methods try to generate codes on the basis of computation and data composition. To enhance the performance of generated codes, various communication optimizations are introduced since communication is one of the main factors degrading the performance. These approaches would bring redundant communication data, as they did not optimize communications jointly with code generation. In this paper, we propose a novel code generation technique for distributed-memory architectures. First, we determine the communication sender and receiver by traversing a loop-based tree structure. To support message aggregation, we find the most appropriate point to insert a message. Secondly, we construct the communication set by proposing some code generation rules, and prove their correctness and accuracy. Redundant communication is thus eliminated. Also, we have evaluated some programs ranging from micro-kernels to applications in NAS parallel benchmarks, and have compared the performance with their message passing interface (MPI), High Performance Fortran (HPF) and Unified Parallel C (UPC) versions. Compared with these versions, our compiler can generate fewer communication points. The generated codes of outperform the HPF and UPC versions and the state-of-the-art, and the average performance can reach 70% of the hand-coded MPI programs.

Description: 〈p〉Protein nuclear translocation is highly regulated and crucial for diverse biological processes. However, our understanding concerning protein nuclear import is incomplete. Here we report that a cellular purine synthesis enzyme inhibits protein nuclear import via deamidation. Employing human Kaposi’s sarcoma-associated herpesvirus (KSHV) to probe the role of protein deamidation, we identified a purine synthesis enzyme, phosphoribosylformylglycinamidine synthetase (PFAS) that inhibits KSHV transcriptional activation. PFAS deamidates the replication transactivator (RTA), a transcription factor crucial for KSHV lytic replication. Mechanistically, deamidation of two asparagines flanking a positively charged nuclear localization signal impaired the binding of RTA to an importin β subunit, thus diminishing RTA nuclear localization and transcriptional activation. Finally, RTA proteins of all gamma herpesviruses appear to be regulated by PFAS-mediated deamidation. These findings uncover an unexpected function of a metabolic enzyme in restricting viral replication and a key role of deamidation in regulating protein nuclear import.〈/p〉

Description: Here we present a catalogue of 1056 spectroscopically identified hydrogen-dominated white dwarfs (DAWDs), 34 helium-dominated white dwarfs (DBWDs) and 276 white dwarf main sequence (WDMS) binaries from the Large sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) survey data release 2 (DR2). 383 DAWDs, 4 DBWDs and 138 WDMSs are new identifications after cross-match with literature. There are ~4100 k spectra in total from DR 2. The low ratio of white dwarfs found in LAMOST is attributed to biased selection of LAMOST input catalogue and much brighter targets relative to stars observed in Sloan Digital Sky Survey. In this paper, a new DAWD selection method is adopted as a new attempt and supplement to the traditional methods. The effective temperature, surface gravity, mass, cooling age and distance of high signal-to-noise DAWDs are estimated. The peak of the mass distribution is found to be ~0.6 M , which is consistent with previous work. The parameters of WDMS binaries are also provided in this paper. As the foundation of our future work, which is to identify more WDs with debris disc, WDs found in LAMOST showed a lot of potential. Interesting infrared-excess WDs will be reported in our forthcoming paper.

Description: F-box protein Fbxl18 mediates polyubiquitylation and proteasomal degradation of the pro-apoptotic SCF subunit Fbxl7 Cell Death and Disease 6, e1630 (February 2015). doi:10.1038/cddis.2014.585 Authors: Y Liu, T Lear, Y Zhao, J Zhao, C Zou, B B Chen & R K Mallampalli