Cross-correlation Weak Lensing of SDSS galaxy Clusters II: Cluster Density Profiles and the Mass--Richness Relation

We interpret and model the statistical weak lensing measurements around 130,000 groups and clusters of galaxies in the Sloan Digital Sky Survey presented by Sheldon et al. 2007 (Paper I). We present non-parametric inversions of the 2D shear profiles to the mean 3D cluster density and mass profiles in bins of both optical richness and cluster i-band luminosity. We correct the inferred 3D profiles for systematic effects, including non-linear shear and the fact that cluster halos are not all precisely centered on their brightest galaxies. We also model the measured cluster shear profile as a sum of contributions from the brightest central galaxy, the cluster dark matter halo, and neighboring halos. We infer the relations between mean cluster virial mass and optical richness and luminosity over two orders of magnitude in cluster mass; the virial mass at fixed richness or luminosity is determined with a precision of 13% including both statistical and systematic errors. We also constrain the halo concentration parameter and halo bias as a function of cluster mass; both are in good agreement with predictions of LCDM models. The methods employed here will be applicable to deeper, wide-area optical surveys that aim to constrain the nature of the dark energy, such as the Dark Energy Survey, the Large Synoptic Survey Telescope and space-based surveys

Prioritizing Tasks in Code Repair: A Psychological Exploration of Computer Code

The current study explored the influence of task prioritization on how computer programmers reviewed and edited code. Forty-five programmers recruited from Amazon Mechanical Turk downloaded and edited a computer program in C#. Programmers were given instructions to review the code and told to prioritize either the reputation, transparency, or performance aspects of the code, or were given no prioritization instruction. Code changes and remarks about their changes to the code were analyzed with a between-within multivariate analysis of variance. Results indicate prioritizing an aspect of the code leads to increased performance on that aspect, but with deficits to other aspects of the code. Managers may want programmers to prioritize certain aspects of code depending on the stage of development of the software (i.e., testing, rollout, etc.). However, managers should also be cognizant of the effects task prioritization has on programmer perceptions of the code as a whole

PudgyTurtle: variable-length, keystream-dependent encoding to resist time-memory tradeoff attacks

PudgyTurtle is a way to use keystream to encode plaintext before XOR-based (stream cipher-like) encryption. It makes stream ciphers less efficient -- a typical implementation requiring about five times as much keystream and producing about twice as much ciphertext -- but also more robust against time-memory-data tradeoff attacks. PudgyTurtle can operate alongside any keystream generator, and thus functions somewhat like an encryption mode for stream ciphers. Here, we introduce the mechanics or PudgyTurtle and discuss its design motivations

Recent trends in UK insects that inhabit early successional stages of ecosystems

Improved recording of less popular groups, combined with new statistical approaches that compensate for datasets that were hitherto too patchy for quantitative analysis, now make it possible to compare recent trends in the status of UK invertebrates other than butterflies. Using BRC datasets, we analysed changes in status between 1992 and 2012 for those invertebrates whose young stages exploit early seral stages within woodland, lowland heath and semi-natural grassland ecosystems, a habitat type that had declined during the 3 decades previous to 1990 alongside a disproportionally high number of Red Data Book species that were dependent on it. Two clear patterns emerged from a meta-analysis involving 299 classifiable species belonging to ten invertebrate taxa: (i) during the past 2 decades, most early seral species that are living near their northern climatic limits in the UK have increased relative to the more widespread members of these guilds whose distributions were not governed by a need for a warm micro-climate; and (ii) independent of climatic constraints, species that are restricted to the early stages of woodland regeneration have fared considerably less well than those breeding in the early seral stages of grasslands or, especially, heathland. The first trend is consistent with predicted benefits for northern edge-of-range species as a result of climate warming in recent decades. The second is consistent with our new assessment of the availability of early successional stages in these three ecosystems since c. 1990. Whereas the proportion and continuity of early seral patches has greatly increased within most semi-natural grasslands and lowland heaths, thanks respectively to agri-environmental schemes and conservation management, the representation of fresh clearings has continued to dwindle within UK woodlands, whose floors are increasingly shaded and ill-suited for this important guild of invertebrates

Runtime asynchronous fault tolerance via speculation

Transient faults are emerging as a critical reliability concern in modern microprocessors. Redundant hardware solutions are commonly deployed to detect transient faults, but they are less flexible and cost-effective than software solutions. However, software solutions are rendered impractical because of high performance overheads. To address this problem, this paper presents Runtime Asynchronous Fault Tolerance via Speculation (RAFT), the fastest transient fault detection technique known to date. Serving as a layer between the application and the underlying platform, RAFT automatically generates two symmetric program instances from a program binary. It detects transient faults in a non-invasive way and exploits high-confidence value speculation to achieve low runtime overhead. Evaluation on a commodity multicore system demonstrates that RAFT delivers a geomean performance overhead of 2.83% on a set of 30 SPEC CPU benchmarks and STAMP benchmarks. Compared with existing transient fault detection techniques, RAFT exhibits the best performance and fault coverage, without requiring any change to the hardware or the software applications

Statistics for citizen science: extracting signals of change from noisy ecological data

1. Policy-makers increasingly demand robust measures of biodiversity change over short time periods. Long-term monitoring schemes provide high-quality data, often on an annual basis, but are taxonomically and geographically restricted. By contrast, opportunistic biological records are relatively unstructured but vast in quantity. Recently, these data have been applied to increasingly elaborate science and policy questions, using a range of methods. At present we lack a firm understanding of which methods, if any, are capable of delivering unbiased trend estimates on policy-relevant timescales. 2. We identified a set of candidate methods that employ data filtering criteria and/or correction factors to deal with variation in recorder activity. We designed a computer simulation to compare the statistical properties of these methods under a suite of realistic data collection scenarios. We measured the Type I error rates of each method-scenario combination, as well as the power to detect genuine trends. 3. We found that simple methods produce biased trend estimates, and/or had low power. Most methods are robust to variation in sampling effort, but biases in spatial coverage, sampling effort per visit, and detectability, as well as turnover in community composition all induced some methods to fail. No method was wholly unaffected by all forms of variation in recorder activity, although some performed well enough to be useful. 4. We warn against the use of simple methods. Sophisticated methods that model the data collection process offer the greatest potential to estimate timely trends, notably Frescalo and Occupancy-Detection models. 5. The potential of these methods and the value of opportunistic data would be further enhanced by assessing the validity of model assumptions and by capturing small amounts of information about sampling intensity at the point of data collection

Autosomal Resequence Data Reveal Late Stone Age Signals of Population Expansion in Sub-Saharan African Foraging and Farming Populations

BACKGROUND:A major unanswered question in the evolution of Homo sapiens is when anatomically modern human populations began to expand: was demographic growth associated with the invention of particular technologies or behavioral innovations by hunter-gatherers in the Late Pleistocene, or with the acquisition of farming in the Neolithic? METHODOLOGY/PRINCIPAL FINDINGS:We investigate the timing of human population expansion by performing a multilocus analysis of > or = 20 unlinked autosomal noncoding regions, each consisting of approximately 6 kilobases, resequenced in approximately 184 individuals from 7 human populations. We test the hypothesis that the autosomal polymorphism data fit a simple two-phase growth model, and when the hypothesis is not rejected, we fit parameters of this model to our data using approximate Bayesian computation. CONCLUSIONS/SIGNIFICANCE:The data from the three surveyed non-African populations (French Basque, Chinese Han, and Melanesians) are inconsistent with the simple growth model, presumably because they reflect more complex demographic histories. In contrast, data from all four sub-Saharan African populations fit the two-phase growth model, and a range of onset times and growth rates is inferred for each population. Interestingly, both hunter-gatherers (San and Biaka) and food-producers (Mandenka and Yorubans) best fit models with population growth beginning in the Late Pleistocene. Moreover, our hunter-gatherer populations show a tendency towards slightly older and stronger growth (approximately 41 thousand years ago, approximately 13-fold) than our food-producing populations (approximately 31 thousand years ago, approximately 7-fold). These dates are concurrent with the appearance of the Late Stone Age in Africa, supporting the hypothesis that population growth played a significant role in the evolution of Late Pleistocene human cultures