Comparison of Vehicle-Based Crash Severity Metrics for Predicting Occupant Injury in Real-World Oblique Crashes

The flail space model (FSM) is currently used in U.S. roadside hardware crash testing as a means of assessing occupant injury risk using observed vehicle kinematics data. European roadside hardware crash tests use an FSM variant along with a variant of the acceleration severity index (ASI). Although the FSM and ASI are currently used in roadside hardware testing, other vehicle-based crash severity metrics exist. Previous research has focused on examining the ability of these metrics to predict injury in frontal crashes. Despite the Manual for Assessing Safety Hardware prescribing a significant number of oblique crash tests, there has been little research on how well these metrics predict real-world oblique crash injury. This study compared the ability of six different vehicle-based metrics to predict occupant injury in oblique crashes: maximum delta-v, occupant impact velocity, ridedown acceleration, ASI, occupant load criterion, and vehicle pulse index. The crash severity metrics were calculated from real-world crash pulse data recorded by event data recorders. Oblique crashes from the National Automotive Sampling System Crashworthiness Data System were used to train logistic regression models that predict moderate to fatal injuries. The models were then compared on a dataset of oblique crashes from the Crash Investigation Sampling System. The results of this study confirmed that vehicle-based metrics provide a reasonable means of predicting real-world occupant injury risk in oblique crashes and suggest little difference between the investigated metrics. In addition to the vehicle-based metrics, belt use and vehicle damage location were found to influence injury risk

O/IR Polarimetry for the 2010 Decade (GAN): Science at the Edge, Sharp Tools for All

Science opportunities and recommendations concerning optical/infrared polarimetry for the upcoming decade in the field of Galactic science. Community-based White Paper to Astro2010 in response to the call for such papers.Comment: White Paper to the Galactic Neighborhood (GAN) Science Frontiers Panel of the Astro2010 Decadal Surve

Dynamics of the Globular Cluster System Associated with M87 (NGC 4486). II. Analysis

We present a dynamical analysis of the globular cluster system associated with M87 (= NGC 4486), the cD galaxy near the dynamical center of the Virgo cluster. The analysis utilizes a new spectroscopic and photometric database which is described in a companion paper (Hanes et al. 2001). Using a sample of 278 globular clusters with measured radial velocities and metallicities, and new surface density profiles based on wide-field Washington photometry, we study the dynamics of the M87 globular cluster system both globally --- for the entire cluster sample --- and separately --- for the metal-rich and metal-poor globular cluster samples. This constitutes the largest sample of radial velocities for pure Population II tracers yet assembled for any galaxy. We discuss the implications of our findings for models for the formation of giant elliptical galaxies, globular cluster systems, and the Virgo cluster. (ABRIDGED)Comment: 28 pages, 19 postscript figures, 1 jpeg image. See http://www.physics.rutgers.edu/ast/ast-rap.html to download the manuscript with higher quality figures. Accepted for publication in the Astrophysical Journa

Choosing the target difference ('effect size') for a randomised controlled trial - DELTA(2) guidance protocol

BACKGROUND: A key step in the design of a randomised controlled trial (RCT) is the estimation of the number of participants needed. By far the most common approach is to specify a target difference and then estimate the corresponding sample size; this sample size is chosen to provide reassurance that the trial will have high statistical power to detect such a difference between the randomised groups (at the planned statistical significance level). The sample size has many implications for the conduct of the study, as well as carrying scientific and ethical aspects to its choice. Despite the critical role of the target difference for the primary outcome in the design of an RCT, the manner in which it is determined has received little attention. This article reports the protocol of the Difference ELicitation in TriAls (DELTA(2)) project, which will produce guidance on the specification and reporting of the target difference for the primary outcome in a sample size calculation for RCTs. METHODS/DESIGN: The DELTA(2) project has five components: systematic literature reviews of recent methodological developments (stage 1) and existing funder guidance (stage 2); a Delphi study (stage 3); a 2-day consensus meeting bringing together researchers, funders and patient representatives, as well as one-off engagement sessions at relevant stakeholder meetings (stage 4); and the preparation and dissemination of a guidance document (stage 5). DISCUSSION: Specification of the target difference for the primary outcome is a key component of the design of an RCT. There is a need for better guidance for researchers and funders regarding specification and reporting of this aspect of trial design. The aim of this project is to produce consensus based guidance for researchers and funders

Understanding Polarized Foreground from Dust: Towards Reliable Measurements of CMB Polarization

Science opportunities and recommendations concerning optical/infrared polarimetry for the upcoming decade in the field of cosmology. Community-based White Paper to Astro2010 in response to the call for such papers.Comment: White Paper to the Cosmology and Fundamental Physics (GCT) Science Frontiers Panel of the Astro2010 Decadal Surve

O/IR Polarimetry for the 2010 Decade (PSF): Science at the Edge, Sharp Tools for All

Science opportunities and recommendations concerning optical/infrared polarimetry for the upcoming decade in the fields of planetary systems and star formation. Community-based White Paper to Astro2010 in response to the call for such papers.Comment: White Paper to the Planetary Systems and Star Formation (PSF) Science Frontiers Panel of the Astro2010 Decadal Surve

DELTA2 guidance on choosing the target difference and undertaking and reporting the sample size calculation for a randomised controlled trial.

BACKGROUND: A key step in the design of a RCT is the estimation of the number of participants needed in the study. The most common approach is to specify a target difference between the treatments for the primary outcome and then calculate the required sample size. The sample size is chosen to ensure that the trial will have a high probability (adequate statistical power) of detecting a target difference between the treatments should one exist. The sample size has many implications for the conduct and interpretation of the study. Despite the critical role that the target difference has in the design of a RCT, the way in which it is determined has received little attention. In this article, we summarise the key considerations and messages from new guidance for researchers and funders on specifying the target difference, and undertaking and reporting a RCT sample size calculation. This article on choosing the target difference for a randomised controlled trial (RCT) and undertaking and reporting the sample size calculation has been dual published in the BMJ and BMC Trials journals METHODS: The DELTA2 (Difference ELicitation in TriAls) project comprised five major components: systematic literature reviews of recent methodological developments (stage 1) and existing funder guidance (stage 2); a Delphi study (stage 3); a two-day consensus meeting bringing together researchers, funders and patient representatives (stage 4); and the preparation and dissemination of a guidance document (stage 5). RESULTS AND DISCUSSION: The key messages from the DELTA2 guidance on determining the target difference and sample size calculation for a randomised caontrolled trial are presented. Recommendations for the subsequent reporting of the sample size calculation are also provided

In-Datacenter Performance Analysis of a Tensor Processing Unit

Many architects believe that major improvements in cost-energy-performance must now come from domain-specific hardware. This paper evaluates a custom ASIC---called a Tensor Processing Unit (TPU)---deployed in datacenters since 2015 that accelerates the inference phase of neural networks (NN). The heart of the TPU is a 65,536 8-bit MAC matrix multiply unit that offers a peak throughput of 92 TeraOps/second (TOPS) and a large (28 MiB) software-managed on-chip memory. The TPU's deterministic execution model is a better match to the 99th-percentile response-time requirement of our NN applications than are the time-varying optimizations of CPUs and GPUs (caches, out-of-order execution, multithreading, multiprocessing, prefetching, ...) that help average throughput more than guaranteed latency. The lack of such features helps explain why, despite having myriad MACs and a big memory, the TPU is relatively small and low power. We compare the TPU to a server-class Intel Haswell CPU and an Nvidia K80 GPU, which are contemporaries deployed in the same datacenters. Our workload, written in the high-level TensorFlow framework, uses production NN applications (MLPs, CNNs, and LSTMs) that represent 95% of our datacenters' NN inference demand. Despite low utilization for some applications, the TPU is on average about 15X - 30X faster than its contemporary GPU or CPU, with TOPS/Watt about 30X - 80X higher. Moreover, using the GPU's GDDR5 memory in the TPU would triple achieved TOPS and raise TOPS/Watt to nearly 70X the GPU and 200X the CPU.Comment: 17 pages, 11 figures, 8 tables. To appear at the 44th International Symposium on Computer Architecture (ISCA), Toronto, Canada, June 24-28, 201

Choosing the target difference and undertaking and reporting the sample size calculation for a randomised controlled trial – the development of the DELTA2 guidance

Background A key step in the design of a randomised controlled trial is the estimation of the number of participants needed. The most common approach is to specify a target difference in the primary outcome between the randomised groups and then estimate the corresponding sample size. The sample size is chosen to provide reassurance that the trial will have high statistical power to detect the target difference at the planned statistical significance level. Alternative approaches are also available, though most still require specification of a target difference. The sample size has many implications for the conduct of the study, as well as incurring scientific and ethical aspects. Despite the critical role of the target difference for the primary outcome in the design of a randomised controlled trial (RCT), the manner in which it is determined has received little attention. This article reports the development of the DELTA2 guidance on the specification and reporting of the target difference for the primary outcome in a sample size calculation for a RCT. Methods The DELTA2 (Difference ELicitation in TriAls) project has five components comprising systematic literature reviews of recent methodological developments (stage 1) and existing funder guidance (stage 2), a Delphi study (stage 3), a 2-day consensus meeting bringing together researchers, funders and patient representatives (stage 4), and the preparation and dissemination of a guidance document (stage 5). Results The project started in April 2016. The literature search identified 28 articles of methodological developments relevant to a method for specifying a target difference. A Delphi study involving 69 participants, along with a 2-day consensus meeting were conducted. In addition, further engagement sessions were held at two international conferences. The main guidance text was finalised on April 18, 2018, after revision informed by feedback gathered from stages 2 and 3 and from funder representatives. Discussion The DELTA2 Delphi study identified a number of areas (such as practical recommendations and examples, greater coverage of different trial designs and statistical approaches) of particular interest amongst stakeholders which new guidance was desired to meet. New relevant references were identified by the review. Such findings influenced the scope, drafting and revision of the guidance. While not all suggestions could be accommodated, it is hoped that the process has led to a more useful and practical document. Keywords Target difference Clinically important difference Sample size Guidance Randomised tria

Erratum to: Methods for evaluating medical tests and biomarkers

[This corrects the article DOI: 10.1186/s41512-016-0001-y.]