The dynamic response of a β titanium alloy to high strain rates and elevated temperatures

The stress-strain behaviour and microstructural evolution of the Ti-6Cr-5Mo-5V-4Al (Ti6554) alloy was systematically investigated using Split Hopkinson Pressure Bar (SHPB) tests over a wide range of strain rates from 1000s-1 to 10,000s-1 and initial temperatures from 293K to 1173K. Dislocation slip is the main deformation mechanism for plastic flow of the Ti6554 alloy at high strain rates. The flow stress increases with increasing strain rate and decreasing temperature. Also the flow stress is more sensitive to temperature than to strain rate. For high strain rate deformations, the strain hardening rate is found to be negative at 293K and increases with increasing temperatures. Flow softening observed at 293K is potentially caused by adiabatic heating. The increment in the strain hardening rate with increasing temperatures may be the result of interactions between thermally activated solute Cr atoms and mobile dislocations. When the temperature is raised to 873K, a novel α precipitate morphology consisting of globular α aligned in strings was observed in specimens deformed at strain rates of 4000 and 10,000s-1. It has hardening effects on the β matrix and is purported to nucleate on dislocations introduced by the high strain rate deformation. Adiabatic shear bands were observed in specimens deformed at higher temperatures (873K). The microstructure inside the shear bands is harder than that outside of the shear bands in the Ti6554 alloy

BigDataBench: a Big Data Benchmark Suite from Internet Services

As architecture, systems, and data management communities pay greater attention to innovative big data systems and architectures, the pressure of benchmarking and evaluating these systems rises. Considering the broad use of big data systems, big data benchmarks must include diversity of data and workloads. Most of the state-of-the-art big data benchmarking efforts target evaluating specific types of applications or system software stacks, and hence they are not qualified for serving the purposes mentioned above. This paper presents our joint research efforts on this issue with several industrial partners. Our big data benchmark suite BigDataBench not only covers broad application scenarios, but also includes diverse and representative data sets. BigDataBench is publicly available from http://prof.ict.ac.cn/BigDataBench . Also, we comprehensively characterize 19 big data workloads included in BigDataBench with varying data inputs. On a typical state-of-practice processor, Intel Xeon E5645, we have the following observations: First, in comparison with the traditional benchmarks: including PARSEC, HPCC, and SPECCPU, big data applications have very low operation intensity; Second, the volume of data input has non-negligible impact on micro-architecture characteristics, which may impose challenges for simulation-based big data architecture research; Last but not least, corroborating the observations in CloudSuite and DCBench (which use smaller data inputs), we find that the numbers of L1 instruction cache misses per 1000 instructions of the big data applications are higher than in the traditional benchmarks; also, we find that L3 caches are effective for the big data applications, corroborating the observation in DCBench.Comment: 12 pages, 6 figures, The 20th IEEE International Symposium On High Performance Computer Architecture (HPCA-2014), February 15-19, 2014, Orlando, Florida, US

Constitutive modelling of the flow behaviour of a β titanium alloy at high strain rates and elevated temperatures using the Johnson-Cook and modified Zerilli-Armstrong models

The objectives of this work are to characterize the flow behaviour of the Ti-6Cr-5Mo-5V-4Al (Ti6554) alloy at high strain rates and elevated temperatures using the Johnson-Cook (JC) model and a modified Zerilli-Armstrong (ZA) model, and to make a comparative study on the predictability of these two models. The stress-strain data from Split Hopkinson Pressure Bar (SHPB) tests over a wide range of temperatures (293-1173K) and strain rates (103-104s-1) were employed to fit parameters for the JC and the modified ZA models. It is observed that both the JC and the modified ZA models have good capacities of describing the flow behaviour of the Ti6554 alloy at high strain rates and elevated temperatures in terms of the average absolute error. The modified ZA model is able to capture the strain-hardening behaviour of the Ti6554 alloy better as it incorporates the coupling effects of strain and temperature. However, dynamic recovery or dynamic recrystallization that may happen at elevated temperatures should be taken into consideration when selecting data set for parameters fitting for the modified ZA model. Also the modified ZA model requires more stress-strain data for the parameters fitting than the JC model

SPEDRE: a web server for estimating rate parameters for cell signaling dynamics in data-rich environments

Cell signaling pathways and metabolic networks are often modeled using ordinary differential equations (ODEs) to represent the production/consumption of molecular species over time. Regardless whether a model is built de novo or adapted from previous models, there is a need to estimate kinetic rate constants based on time-series experimental measurements of molecular abundance. For data-rich cases such as proteomic measurements of all species, spline-based parameter estimation algorithms have been developed to avoid solving all the ODEs explicitly. We report the development of a web server for a spline-based method. Systematic Parameter Estimation for Data-Rich Environments (SPEDRE) estimates reaction rates for biochemical networks. As input, it takes the connectivity of the network and the concentrations of the molecular species at discrete time points. SPEDRE is intended for large sparse networks, such as signaling cascades with many proteins but few reactions per protein. If data are available for all species in the network, it provides global coverage of the parameter space, at low resolution and with approximate accuracy. The output is an optimized value for each reaction rate parameter, accompanied by a range and bin plot. SPEDRE uses tools from COPASI for pre-processing and post-processing. SPEDRE is a free service at http://LTKLab.org/SPEDRE.Singapore-MIT Alliance (IUP R-154-001-348-646

Eucrite‐type achondrites: Petrology and oxygen isotope compositions

We report petrologic studies and oxygen isotope analyses of normal and anomalous eucrites, termed eucrite-type achondrites. Petrologically anomalous eucrite-type achondrites can have normal oxygen isotope compositions, and vice versa. Two basaltic eucrites with normal oxygen isotope compositions contain pyroxenes with anomalous Fe/Mn engendered by parent body processes acting on normal eucrites: solid-state reduction by S gas in EET 87542, and reduction during crystallization by magmatic S in QUE 94484. Cataclastic basaltic breccias PCA 82502 and PCA 91007 are paired (petrology, anomalous oxygen). Although isotopically like Pasamonte, they are petrologically distinct. We confirm the petrological and isotopic anomalies of cumulate gabbro EET 92023; likely formed by impact melting of mixed cumulate and basaltic materials. Many main group eucrites include plagioclases that retain near-liquidus compositions despite metamorphic overprinting. Stannern group eucrites contain more sodic plagioclase, which is consistent with the melt hybridization hypothesis for Stannern group magma formation. The lack of more calcic plagioclase suggests reactive exchange of the anorthite component of the primary melt with the albitic component of the crust. Asteroids that are modestly different in composition can produce virtually indistinguishable basalts, providing a ready explanation for the eucrite-type achondrite suite. Small stochastic variations in petrologic evolution can cause substantial differences in rocks produced on an asteroid

Multi-level evidence of an allelic hierarchy of USH2A variants in hearing, auditory processing and speech/language outcomes.

Language development builds upon a complex network of interacting subservient systems. It therefore follows that variations in, and subclinical disruptions of, these systems may have secondary effects on emergent language. In this paper, we consider the relationship between genetic variants, hearing, auditory processing and language development. We employ whole genome sequencing in a discovery family to target association and gene x environment interaction analyses in two large population cohorts; the Avon Longitudinal Study of Parents and Children (ALSPAC) and UK10K. These investigations indicate that USH2A variants are associated with altered low-frequency sound perception which, in turn, increases the risk of developmental language disorder. We further show that Ush2a heterozygote mice have low-level hearing impairments, persistent higher-order acoustic processing deficits and altered vocalizations. These findings provide new insights into the complexity of genetic mechanisms serving language development and disorders and the relationships between developmental auditory and neural systems

Contrasting patterns of evolutionary constraint and novelty revealed by comparative sperm proteomic analysis in Lepidoptera

Background: Rapid evolution is a hallmark of reproductive genetic systems and arises through the combined processes of sequence divergence, gene gain and loss, and changes in gene and protein expression. While studies aiming to disentangle the molecular ramifications of these processes are progressing, we still know little about the genetic basis of evolutionary transitions in reproductive systems. Here we conduct the first comparative analysis of sperm proteomes in Lepidoptera, a group that exhibits dichotomous spermatogenesis, in which males produce a functional fertilization-competent sperm (eupyrene) and an incompetent sperm morph lacking nuclear DNA (apyrene). Through the integrated application of evolutionary proteomics and genomics, we characterize the genomic patterns potentially associated with the origination and evolution of this unique spermatogenic process and assess the importance of genetic novelty in Lepidopteran sperm biology. Results: Comparison of the newly characterized Monarch butterfly (Danaus plexippus) sperm proteome to those of the Carolina sphinx moth (Manduca sexta) and the fruit fly (Drosophila melanogaster) demonstrated conservation at the level of protein abundance and post-translational modification within Lepidoptera. In contrast, comparative genomic analyses across insects reveals significant divergence at two levels that differentiate the genetic architecture of sperm in Lepidoptera from other insects. First, a significant reduction in orthology among Monarch sperm genes relative to the remainder of the genome in non-Lepidopteran insect species was observed. Second, a substantial number of sperm proteins were found to be specific to Lepidoptera, in that they lack detectable homology to the genomes of more distantly related insects. Lastly, the functional importance of Lepidoptera specific sperm proteins is broadly supported by their increased abundance relative to proteins conserved across insects. Conclusions: Our results identify a burst of genetic novelty amongst sperm proteins that may be associated with the origin of heteromorphic spermatogenesis in ancestral Lepidoptera and/or the subsequent evolution of this system. This pattern of genomic diversification is distinct from the remainder of the genome and thus suggests that this transition has had a marked impact on lepidopteran genome evolution. The identification of abundant sperm proteins unique to Lepidoptera, including proteins distinct between specific lineages, will accelerate future functional studies aiming to understand the developmental origin of dichotomous spermatogenesis and the functional diversification of the fertilization incompetent apyrene sperm morph

A heterozygous moth genome provides insights into herbivory and detoxification

How an insect evolves to become a successful herbivore is of profound biological and practical importance. Herbivores are often adapted to feed on a specific group of evolutionarily and biochemically related host plants1, but the genetic and molecular bases for adaptation to plant defense compounds remain poorly understood2. We report the first whole-genome sequence of a basal lepidopteran species, Plutella xylostella, which contains 18,071 protein-coding and 1,412 unique genes with an expansion of gene families associated with perception and the detoxification of plant defense compounds. A recent expansion of retrotransposons near detoxification-related genes and a wider system used in the metabolism of plant defense compounds are shown to also be involved in the development of insecticide resistance. This work shows the genetic and molecular bases for the evolutionary success of this worldwide herbivore and offers wider insights into insect adaptation to plant feeding, as well as opening avenues for more sustainable pest management.Minsheng You … Simon W Baxter … et al