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

Analytical and experimental study of vibrations in a gear transmission

An analytical simulation of the dynamics of a gear transmission system is presented and compared to experimental results from a gear noise test rig at the NASA Lewis Research Center. The analytical procedure developed couples the dynamic behaviors of the rotor-bearing-gear system with the response of the gearbox structure. The modal synthesis method is used in solving the overall dynamics of the system. Locally each rotor-gear stage is modeled as an individual rotor-bearing system using the matrix transfer technique. The dynamics of each individual rotor are coupled with other rotor stages through the nonlinear gear mesh forces and with the gearbox structure through bearing support systems. The modal characteristics of the gearbox structure are evaluated using the finite element procedure. A variable time steping integration routine is used to calculate the overall time transient behavior of the system in modal coordinates. The global dynamic behavior of the system is expressed in a generalized coordinate system. Transient and steady state vibrations of the gearbox system are presented in the time and frequency domains. The vibration characteristics of a simple single mesh gear noise test rig is modeled. The numerical simulations are compared to experimental data measured under typical operating conditions. The comparison of system natural frequencies, peak vibration amplitudes, and gear mesh frequencies are generally in good agreement

Site Index Prediction for Willow and Cherrybark Oaks in East Texas Bottomland Forests

Estimating site quality for a specific tree species is an important tool in forest management. While intensively managed pine species are often the focus of site quality studies using site index, hardwood species found in bottomland hardwood sites are often lacking in quality growth prediction equations. Two valuable hardwood species, willow oak (Quercus phellos) and cherrybark oak (Q. pagoda), are of interest for forest managers of east Texas bottomland sites. The objective of this study was to develop site index prediction equations and curves for these two species. Using height and age data from 267 cherrybark oaks and 460 willow oaks collected from sites across east Texas, remarkably similar equations were developed, with coefficient of determination (R2 ) of 0.63 for cherrybark oak and 0.52 for willow oak

Relational Prior Knowledge Graphs for Detection and Instance Segmentation

Humans have a remarkable ability to perceive and reason about the world around them by understanding the relationships between objects. In this paper, we investigate the effectiveness of using such relationships for object detection and instance segmentation. To this end, we propose a Relational Prior-based Feature Enhancement Model (RP-FEM), a graph transformer that enhances object proposal features using relational priors. The proposed architecture operates on top of scene graphs obtained from initial proposals and aims to concurrently learn relational context modeling for object detection and instance segmentation.Experimental evaluations on COCO show that the utilization of scene graphs, augmented with relational priors, offer benefits for object detection and instance segmentation. RP-FEM demonstrates its capacity to suppress improbable class predictions within the image while also preventing the model from generating duplicate predictions, leading to improvements over the baseline model on which it is built.</p

Time-dependent Hamiltonian estimation for Doppler velocimetry of trapped ions

The time evolution of a closed quantum system is connected to its Hamiltonian through Schroedinger's equation. The ability to estimate the Hamiltonian is critical to our understanding of quantum systems, and allows optimization of control. Though spectroscopic methods allow time-independent Hamiltonians to be recovered, for time-dependent Hamiltonians this task is more challenging. Here, using a single trapped ion, we experimentally demonstrate a method for estimating a time-dependent Hamiltonian of a single qubit. The method involves measuring the time evolution of the qubit in a fixed basis as a function of a time-independent offset term added to the Hamiltonian. In our system the initially unknown Hamiltonian arises from transporting an ion through a static, near-resonant laser beam. Hamiltonian estimation allows us to estimate the spatial dependence of the laser beam intensity and the ion's velocity as a function of time. This work is of direct value in optimizing transport operations and transport-based gates in scalable trapped ion quantum information processing, while the estimation technique is general enough that it can be applied to other quantum systems, aiding the pursuit of high operational fidelities in quantum control.Comment: 10 pages, 8 figure

Detecting Objects with Context-Likelihood Graphs and Graph Refinement

The goal of this paper is to detect objects by exploiting their interrelationships. Contrary to existing methods, which learn objects and relations separately, our key idea is to learn the object-relation distribution jointly. We first propose a novel way of creating a graphical representation of an image from inter-object relation priors and initial class predictions, we call a context-likelihood graph. We then learn the joint distribution with an energy-based modeling technique which allows to sample and refine the context-likelihood graph iteratively for a given image. Our formulation of jointly learning the distribution enables us to generate a more accurate graph representation of an image which leads to a better object detection performance. We demonstrate the benefits of our context-likelihood graph formulation and the energy-based graph refinement via experiments on the Visual Genome and MS-COCO datasets where we achieve a consistent improvement over object detectors like DETR and Faster-RCNN, as well as alternative methods modeling object interrelationships separately. Our method is detector agnostic, end-to-end trainable, and especially beneficial for rare object classes

Universality in the Crossover between Edge Channel and Bulk Transport in the Quantum Hall Regime

We present a new theoretical approach for the integer quantum Hall effect, which is able to describe the inter-plateau transitions as well as the transition to the Hall insulator. We find two regimes (metallic and insulator like) of the top Landau level, in which the dissipative bulk current appears in different directions. The regimes are separated by a temperature invariant point.Comment: 4 page, 2 eps figures included, submitte

Elasticity of smectic liquid crystals with focal conic domains

We study the elastic properties of thermotropic smectic liquid crystals with focal conic domains (FCDs). After the application of the controlled preshear at different temperatures, we independently measured the shear modulus G' and the FCD size L. We find out that these quantities are related by the scaling relation G' ~ \gamma_{eff}/L where \gamma_{eff} is the effective surface tension of the FCDs. The experimentally obtained value of \gamma_{\rm eff} shows the same scaling as the effective surface tension of the layered systems \sqrt{KB} where K and B are the bending modulus and the layer compression modulus, respectively. The similarity of this scaling relation to that of the surfactant onion phase suggests an universal rheological behavior of the layered systems with defects.Comment: 14 pages, 7 figures, accepted for publication in JPC

Microalgae for municipal wastewater nutrient remediation: mechanisms, reactors and outlook for tertiary treatment

This review explores the use of microalgae for nutrient removal in municipal wastewater treatment, considering recent improvements in the understanding of removal mechanisms and developments of both suspended and non-suspended systems. Nutrient removal is associated to both direct and indirect uptake, with the former associated to the biomass concentration and growth environment (reactor). Importantly, direct uptake is influenced by the Nitrogen:Phosphorus content in both the cells and the surrounding wastewater, with opposite trends observed for N and P. Comparison of suspended and non-suspended systems revealed that whilst all were capable of achieving high levels of nutrient removal, only non-suspended immobilized systems could do so with reduced hydraulic retention times of less than 1 day. As microalgae are photosynthetic organisms, the metabolic processes associated with nutrient assimilation are driven by light. Optimization of light delivery remains a key area of development with examples of improved mixing in suspended systems and the use of pulsating lights to enhance light utilization and reduce costs. Recent data provide increased confidence in the use of microalgae for nutrient removal in municipal wastewater treatment, enabling effluent discharges below 1 mg L−1 to be met whilst generating added value in terms of bioproducts for energy production or nutrient recovery. Ultimately, the review suggests that future research should focus on non-suspended systems and the determination of the added value potential. In so doing, it is predicted that microalgae systems will be significant in the delivery of the circular economy

‘Fair’ inequality, consumption and climate mitigation

Economic inequality and climate change are pressing issues that have climbed high up the political agenda, yet action to mitigate both remains slow. As income is a key determinant of ecological impacts, the Global North—and wealthier classes elsewhere—are the primary drivers of global carbon emissions, while the least well off have contributed the least yet are set to be hit hardest by climate impacts. These inequalities are clearly unjust, but the interrelations between economic inequality and ecological impacts are complex, leaving open the question of whether reducing the former would mitigate the latter, in the absence of reductions in total economic output. Here, we contribute to these debates by estimating the carbon-footprint implications of reducing income (and hence expenditure) inequalities within 32 countries of the Global North to the levels people consider to be fair; levels that are substantially smaller than currently exist. We find that realising these levels of economic inequality brings comparable reductions in carbon-footprint inequalities. However, in isolation, implementing fair inequalities has a negligible impact upon total emissions. In contrast, recomposing consumption—by reducing inequalities in household expenditure and the overall levels, then reallocating the reductions to public services—reduces carbon footprint by up to 30% in individual countries and 16% overall and, crucially, still allows the consumption of those at the bottom to rise. Such reductions could be significant on a global level, and they would be additional to the full range of conventional technological and demand-side measures to reduce carbon emissions