Dual-frequency ferromagnetic resonance

We describe a new experimental technique to investigate coupling effects between different layers or modes in ferromagnetic resonance (FMR). Dual FMR frequencies are excited (2-8 GHz) simultaneously and detected selectively in a broadband RF circuit, using lock-in amplifier detection at separate modulation frequencies.Comment: 4 pages, 4 figures, accepted by "Review of Scientific Instruments", 200

A discrete-time performance model for congestion control mechanism using queue thresholds with QOS constraints

This paper presents a new analytical framework for the congestion control of Internet traffic using a queue threshold scheme. This framework includes two discrete-time analytical models for the performance evaluation of a threshold based congestion control mechanism and compares performance measurements through typical numerical results. To satisfy the low delay along with high throughput, model-I incorporates one threshold to make the arrival process step reduce from arrival rate ¿1 directly to ¿2 once the number of packets in the system has reached the threshold value L1. The source operates normally, otherwise. Model-II incorporates two thresholds to make the arrival rate linearly reduce from ¿1 to ¿2 with system contents when the number of packets in the system is between two thresholds L1 and L2. The source operates normally with arrival rate ¿1 before threshold L1, and with arrival rate ¿2 after the threshold L2. In both performance models, the mean packet delay W, probability of packet loss PL and throughput S have been found as functions of the thresholds and maximum drop probability. The performance comparison results for the two models have also been made through typical numerical results. The results clearly demonstrate how different load settings can provide different tradeoffs between throughput, loss probability and delay to suit different service requirements

Who Said What: Modeling Individual Labelers Improves Classification

Data are often labeled by many different experts with each expert only labeling a small fraction of the data and each data point being labeled by several experts. This reduces the workload on individual experts and also gives a better estimate of the unobserved ground truth. When experts disagree, the standard approaches are to treat the majority opinion as the correct label or to model the correct label as a distribution. These approaches, however, do not make any use of potentially valuable information about which expert produced which label. To make use of this extra information, we propose modeling the experts individually and then learning averaging weights for combining them, possibly in sample-specific ways. This allows us to give more weight to more reliable experts and take advantage of the unique strengths of individual experts at classifying certain types of data. Here we show that our approach leads to improvements in computer-aided diagnosis of diabetic retinopathy. We also show that our method performs better than competing algorithms by Welinder and Perona (2010), and by Mnih and Hinton (2012). Our work offers an innovative approach for dealing with the myriad real-world settings that use expert opinions to define labels for training.Comment: AAAI 201

Assessing the Impact of Retreat Mechanisms in a Simple Antarctic Ice Sheet Model Using Bayesian Calibration

The response of the Antarctic ice sheet (AIS) to changing climate forcings is an important driver of sea-level changes. Anthropogenic climate change may drive a sizeable AIS tipping point response with subsequent increases in coastal flooding risks. Many studies analyzing flood risks use simple models to project the future responses of AIS and its sea-level contributions. These analyses have provided important new insights, but they are often silent on the effects of potentially important processes such as Marine Ice Sheet Instability (MISI) or Marine Ice Cliff Instability (MICI). These approximations can be well justified and result in more parsimonious and transparent model structures. This raises the question of how this approximation impacts hindcasts and projections. Here, we calibrate a previously published and relatively simple AIS model, which neglects the effects of MICI and regional characteristics, using a combination of observational constraints and a Bayesian inversion method. Specifically, we approximate the effects of missing MICI by comparing our results to those from expert assessments with more realistic models and quantify the bias during the last interglacial when MICI may have been triggered. Our results suggest that the model can approximate the process of MISI and reproduce the projected median melt from some previous expert assessments in the year 2100. Yet, our mean hindcast is roughly 3/4 of the observed data during the last interglacial period and our mean projection is roughly 1/6 and 1/10 of the mean from a model accounting for MICI in the year 2100. These results suggest that missing MICI and/or regional characteristics can lead to a low-bias during warming period AIS melting and hence a potential low-bias in projected sea levels and flood risks.Comment: v1: 16 pages, 4 figures, 7 supplementary files; v2: 15 pages, 4 figures, 7 supplementary files, corrected typos, revised title, updated according to revisions made through publication proces

The effect of pension accounting on corporate pension asset allocation

We examine the impact of new pension disclosures and subsequent full pension recognition under FRS 17 and IAS 19 in the United Kingdom and SFAS 158 in the United States on pension asset allocation. These standards require recognition of net pension surplus/deficit on the balance sheet and actuarial gains/losses in other comprehensive income. Therefore, these standards introduce volatility into comprehensive income and balance sheets. We identify a disclosure period during which UK companies disclosed all the required data under FRS 17 in the notes without recognition. We also identify a full recognition period starting 1 year before until 1 year after the adoption of FRS 17/IAS 19 (UK) and SFAS 158 (US). We predict and find that UK companies, on average, shifted pension assets from equity to debt securities during both the disclosure and the full recognition periods. We also find that while before the adoption of SFAS 158 US companies maintained a stable allocation to equities and bonds, these companies, on average, shifted funds from equities to bonds around the adoption of SFAS 158. Cross-sectional analysis shows that the shift away from equities is related to changes in funding levels, shorter investment horizons, increased financial leverage, and the expected impact of the new standards on shareholders' equity. © 2009 Springer Science+Business Media, LLC.postprin

Abnormal Fees and Timely Loss Recognition - A Long-Term Perspective

This is the author accepted manuscript. The final version is available from the American Accounting Association via the DOI in this recordWe examine the relation between timely loss recognition and abnormal audit, non-audit, and total fees over a long period (2001–2007 and 2010–2015). We use positive abnormal audit fees as a measure of abnormal audit effort, and positive abnormal non-audit fees as a measure of economic bond between the auditor and the auditee. Using the Ball and Shivakumar (2006) model, we report some evidence suggesting audit effort is associated with slower loss recognition in accruals before the Sarbanes–Oxley Act (SOX) became effective. However, we find stronger evidence that audit effort is associated with slower loss recognition post-SOX when clients raise substantial external funds or when the auditor is not an industry specialist. Using C_Score, we find a negative association between changes in abnormal audit fees and total fees, and changes in C_Score post-SOX, but not pre-SOX. We find no sample-wide evidence that abnormal non-audit fees are associated with the speed of loss recognition. Collectively, the results suggest post-SOX auditors exert more effort when losses are delayed and that non-audit services do not compromise auditor independence

Vertical Structure of Stationary Accretion Disks with a Large-Scale Magnetic Field

In earlier works we pointed out that the disk's surface layers are non-turbulent and thus highly conducting (or non-diffusive) because the hydrodynamic and/or magnetorotational (MRI) instabilities are suppressed high in the disk where the magnetic and radiation pressures are larger than the plasma thermal pressure. Here, we calculate the vertical profiles of the {\it stationary} accretion flows (with radial and azimuthal components), and the profiles of the large-scale, magnetic field taking into account the turbulent viscosity and diffusivity and the fact that the turbulence vanishes at the surface of the disk. Also, here we require that the radial accretion speed be zero at the disk's surface and we assume that the ratio of the turbulent viscosity to the turbulent magnetic diffusivity is of order unity. Thus at the disk's surface there are three boundary conditions. As a result, for a fixed dimensionless viscosity $\alpha$-value, we find that there is a definite relation between the ratio ${\cal R}$ of the accretion power going into magnetic disk winds to the viscous power dissipation and the midplane plasma-$\beta$, which is the ratio of the plasma to magnetic pressure in the disk. For a specific disk model with ${\cal R}$ of order unity we find that the critical value required for a stationary solution is $\beta_c \approx 2.4r/(\alpha h)$, where $h$ the disk's half thickness. For weaker magnetic fields, $\beta > \beta_c$, we argue that the poloidal field will advect outward while for $\beta< \beta_c$ it will advect inward. Alternatively, if the disk wind is negligible (${\cal R} \ll 1$), there are stationary solutions with $\beta \gg \beta_c$.Comment: 5 pages, 3 figure