Adaptive Grid Refinement for Discrete Tomography

Discrete tomography has proven itself as a powerful approach to image reconstruction from limited data. In recent years, algebraic reconstruction methods have been applied successfully to a range of experimental data sets. However, the computational cost of such reconstruction techniques currently prevents routine application to large data-sets. In this paper we investigate the use of adaptive refinement on QuadTree grids to reduce the number of pixels (or voxels) needed to represent an image. Such locally refined grids match well with the domain of discrete tomography as they are optimally suited for representing images containing large homogeneous regions. Reducing the number of pixels ultimately promises a reduct

Robust artefact reduction in tomography using Student’s t data fitting

Algebraic methods are popular for tomographic image reconstruction from limited data. These methods typically minimize the Euclidean norm of the residual of the corresponding linear equation system. The underlying assumption of this approach is that the noise has a Gaussian distribution. However, in cases where large outliers are present in the projection data, e.g., due to defective camera pixels, photon starvation from metal implants etc., the equation system is not consistent and the reconstruction will be fitted to these outliers, resulting in artefacts in the reconstruction. In this paper we use a penalty function for the residual that is based on the maximum likelihood estimate from the Student’s t distribution, which assigns a smaller penalty to outliers. No preprocessing is required to locate the outliers. We demonstrate the effectiveness of this approach on a 3D cone-beam simulated dataset for a series of perturbations in the projection data. Our results suggest that artefacts due to metal objects, de

Dealing with Time in Health Economic Evaluation: Methodological Issues and Recommendations for Practice

Time is an important aspect of health economic evaluation, as the timing and duration of clinical events, healthcare interventions and their consequences all affect estimated costs and effects. These issues should be reflected in the design of health economic models. This article considers three important aspects of time in modelling: (1) which cohorts to simulate and how far into the future to extend the analysis; (2) the simulation of time, including the difference between discrete-time and continuous-time models, cycle lengths, and converting rates and probabilities; and (3) discounting future costs and effects to their present values. We provide a methodological overview of these issues and make recommendations to help inform both the conduct of cost-effectiveness analyses and the interpretation of their results. For choosing which cohorts to simulate and how many, we suggest analysts carefully assess potential reasons for variation in cost effectiveness between cohorts and the feasibility of subgroup-specific recommendations. For the simulation of time, we recommend using short cycles or continuous-time models to avoid biases and the need for half-cycle corrections, and provide advic

Our Administrative System of Criminal Justice

To commemorate our founding in 1914, the Board of Editors has selected six influential pieces published by the Law Review over the past 100 years and will republish one piece in each issue. The fourth piece selected by the Board is Our Administrative System of Criminal Justice, an article written by Gerard E. Lynch that is among the most cited works in the Law Review’s history. This article illustrates how the practice of plea bargaining blurs the boundaries between adversarial and inquisitorial criminal justice systems. Judge Lynch now sits on the Second Circuit having eventually succeeded the late Judge Joseph M. McLaughlin, who also is honored in the pages of this book for the permanent mark he left on Fordham Law School and the Law Review. We think it is fitting that the Law Review feature two of the many contributions that judges of the Second Circuit have made to legal education and scholarship in this issue

What works where and for whom? Farm Household Strategies for Food Security across Uganda

East Africa's smallholder agriculture is expected to be strongly affected by climate change, which, together with a growing population and pressure on natural resources, will result in an increasing challenge to achieve food security for households and regions. Policy makers need information on what works where for which farmers in order to guide their decision making and prioritise investment for agricultural interventions to increase food security. For this, we must better understand how smallholder farm strategies for achieving food security differ across regions and farm types and what drives these strategies. In this study we present new analyses at country and farm household level that quantify drivers of productivity and food security, and that can be used to prioritise agricultural interventions. Uganda was chosen as a case study because of data availability but the approach can be applied to other countries in sub-Saharan Africa. First, we quantified how food security and farm types varied across Uganda, and which key factors drive this variability. We used household level data from the Living Standard Measurement Study – Integrated Survey on Agriculture (LSMS-ISA) of the World Bank and developed an approach to map and quantitatively explain food security and agricultural land use across Uganda. The resulting maps showed where which crops and livestock activities are important for which types of farm households. Subsequently, the effects of agricultural interventions on food security of different farm types were assessed. Second, we used this information to select contrasting sites and farm households for detailed interviews, which aimed at identifying drivers of farmers' decision making, assessing farmers' vulnerability to climate change and how proposed interventions match with the farmers' socio-ecological niche. The spatial approach we developed is a novel way to use farm household level information to generate country-wide patterns in farming systems and their productivity. It generates useful information for a quantitative assessment of what might happen to the food security of smallholder farmers in Uganda under climate change and for a country-wide targeting of agricultural interventions that aim at mitigating the effects of climate change

Information Storage and Retrieval for Probe Storage using Optical Diffraction Patterns

A novel method for fast information retrieval from a probe storage device is considered. It is shown that information can be stored and retrieved using the optical diffraction patterns obtained by the illumination of a large array of cantilevers by a monochromatic light source. In thermo-mechanical probe storage, the information is stored as a sequence of indentations on the polymer medium. To retrieve the information, the array of probes is actuated by applying a bending force to the cantilevers. Probes positioned over indentations experience deflection by the depth of the indentation, probes over the flat media remain un-deflected. Thus the array of actuated probes can be viewed as an irregular optical grating, which creates a data-dependent diffraction pattern when illuminated by laser light. We develop a low complexity modulation scheme, which allows the extraction of information stored in the pattern of indentations on the media from Fourier coefficients of the intensity of the diffraction pattern. We then derive a low-complexity maximum likelihood sequence detection algorithm for retrieving the user information from the Fourier coefficients. The derivation of both the modulation and the detection schemes is based on the Fraunhofer formula for data-dependent diffraction patterns. We show that for as long as the Fresnel number F<0.1, the optimal channel detector derived from Fraunhofer diffraction theory does not suffer any significant performance degradation.Comment: 14 pages, 11 figures. Version 2: minor misprints corrected, experimental section expande

Solving the bank with Rebel: on the design of the Rebel specification language and its application inside a bank

Large organizations like banks suffer from the ever growing complexity of their systems. Evolving the software becomes harder and harder since a single change can affect a much larger part of the system than predicted upfront. A large contributing factor to this problem is that the actual domain knowledge is often implicit, incomplete, or out of date, making it difficult to reason about the correct behavior of the system as a whole. With Rebel we aim to capture and centralize the domain knowledge and relate it to the running systems. Rebel is a formal specification language for controlling the intrinsic complexity of software for financial enterprise systems. In collaboration with ING, a large Dutch bank, we developed the Rebel specification language and an Integrated Specification Environment (ISE), currently offering automated simulation and checking of Rebel specifications using a Satisfiability Modulo Theories (SMT) solver. In this paper we report on our design choices for Rebel, the implementation and features of the ISE, and our initial observations on the application of Rebel inside the bank

Internal phase inversion narrow bandwidth MEMS filter

This paper reports a novel capacitively coupled twin beam resonator internal phase inversion filter fabricated in a SOI MEMS process. A narrow bandwidth of 0.0157% is demonstrated with a low control-voltage of -0.87 V. The bandwidth can be substantially reduced by utilizing an electrical coupling spring as opposed to a mechanical coupling-spring. The bandwidth is tunable with control achieved using a differential DC bias. A summary and comparison with other members of the phase inversion filter family is also included

Assessing the chronic toxicity of nickel to a tropical marine gastropod and two crustaceans

The mining and processing of nickel ores from tropical regions contributes 40% of the global supply. The potential impact of these activities on tropical marine ecosystems is poorly understood. Due to the lack of ecotoxicity data for tropical marine species, there is currently no available water quality guideline value for nickel that is specific to tropical species. In this study, we investigated the toxicity of nickel to three tropical marine invertebrates, the gastropod Nassarius dorsatus, the barnacle Amphibalanus amphitrite, and the copepod Acartia sinjiensis. All toxicity tests used chronic endpoints, namely larval growth, metamorphosis (transition from nauplii to cyprid larvae) and larval development for the snail, barnacle and copepod respectively. Toxicity tests were carried out under environmentally relevant conditions (i.e. 27-30ᵒC, salinity 34-36‰ pH 8.1-8.4). Copper was also tested for quality assurance purposes and to allow for comparisons with previous studies. The copepod was the most sensitive species to nickel, with development inhibited by 10% (EC10) at 5.5 (5.0-6.0) µg Ni/L (95% confidence limits (CL)). Based on EC10 values, the gastropod and barnacle showed similar sensitivities to nickel with growth and metamorphosis inhibited by 10% at 64 (37−91) µg Ni/L and 67 (53−80) µg Ni/L, respectively. Based on existing data available in the literature, the copepod A. sinjiensis is so far the most sensitive tropical marine species to nickel. This study has provided high quality data which will contribute to the development of a water quality guideline value for nickel in tropical marine waters. A species sensitivity distribution of chronic nickel toxicity used the data generated in this paper supplemented by available literature data, comprising 12 species representing 6 taxonomic groups. A 5% hazard concentration (HC5) was determined as 8.2 µg/L Ni