Adherence rates to ferric citrate as compared to active control in patients with end stage kidney disease on dialysis

Introduction: Oral phosphate binders are the main stay of treatment of hyperphosphatemia. Adherence rates to ferric citrate, a recently approved phosphate binder, are unknown. Methods: We conducted a post‐hoc analysis to evaluate whether adherence rates were different for ferric citrate vs. active control in 412 subjects with end stage kidney disease (ESKD) who were randomized to ferric citrate vs. active control (sevelamer carbonate and/or calcium acetate). Adherence was defined as percent of actual number of pills taken to total number of pills prescribed. Findings: There were no significant differences in baseline characteristics including gender, race/ethnicity, and age between the ferric citrate and active control groups. Baseline phosphorus, calcium, and parathyroid hormone levels were similar. Mean (SD) adherence was 81.4% (17.4) and 81.7% (15.9) in the ferric citrate and active control groups, respectively (P = 0.88). Adherence remained similar between both groups after adjusting for gender, race/ethnicity, age, cardiovascular disease (CVD), and diabetic nephropathy (mean [95% CI]: 81.4% [78.2, 84.6] and 81.5% [77.7, 85.2] for ferric citrate and active control, respectively). Gender, race/ethnicity, age, and diagnosis of diabetic nephropathy did not influence adherence to the prescribed phosphate binder. Subjects with CVD had lower adherence rates to phosphate binder; this was significant only in the active control group. Discussion: Adherence rates to the phosphate binder, ferric citrate, were similar to adherence rates to active control. Similar adherence rates to ferric citrate are notable since tolerance to active control was an entry criteria and the study was open label. Gender, race/ethnicity, nor age influenced adherence.     

Partitioning large networks without breaking communities

The identification of cohesive communities is a key process in social network analysis. However, the algorithms that are effective for finding communities do not scale well to very large problems, as their time complexity is worse than linear in the number of edges in the graph. This is an important issue for those interested in applying social network analysis techniques to very large networks, such as networks of mobile phone subscribers. In this respect, the contributions of this paper are twofold. First, we demonstrate these scaling issues using a prominent community-finding algorithm as a case study. Then, we show that a two-stage process, whereby the network is first decomposed into manageable subnetworks using a multilevel graph partitioning procedure, is effective in finding communities in networks with more than 10⁶ nodes.     

Development of a Position Sensitive Neutron Detector with High Efficiency and Energy Resolution for Use at High-Flux Beam Sources

We are developing a high-efficiency neutron detector with 1 cm position resolution and coarse energy resolution for use at high-flux neutron source facilities currently proposed or under construction. The detector concept integrates a segmented ³He ionization chamber with the position sensitive, charged particle collection methods of a MicroMegas detector. Neutron absorption on the helium produces protons and tritons that ionize the fill gas. The charge is amplified in the field region around a wire mesh and subsequently detected in current mode by wire strips mounted on a substrate. One module consisting of a high-voltage plate, a field-shaping high-voltage plate, a grid and wire strips defines a detection region. For 100 % efficiency, detector modules are consecutively placed along the beam axis. Analysis over several regions with alternating wire strip orientation provides a two-dimensional beam profile. By using ³He, a 1/v absorption gas, each axial region captures neutrons of a different energy range, providing an energy-sensitive detection scheme especially useful at continuous beam sources.     

Fuel cells for non-automotive uses: Status and prospects

Fuel cells are in varying stages of commercialization for both automotive and non-automotive applications. The fuel cell industry has made substantial progress but still needs to reduce costs and improve performance to compete successfully with established technologies. In just 5 years, costs have been reduced by a factor of two while improving efficiency and durability. Based on interviews with fuel cell manufacturers in the U.S., Japan and the EU and information from published sources, a model of non-automotive fuel cell markets is constructed and used to estimate the impacts of government policies and to project the potential evolution of the industry to 2025. The model includes the effects of learning-by-doing, scale economies and exogenous technological progress on component and system costs, estimates customer choices between fuel cell and competing established technologies, and attempts to measure the impacts of government policies. With continued policy support it appears likely that the industry can become self-sustaining within the next decade.     

Fractality of tics as a quantitative assessment tool for Tourette syndrome

Tics manifest as brief, purposeless and unintentional movements or noises that, for many individuals, can be suppressed temporarily with effort. Previous work has hypothesized that the chaotic temporal nature of tics could possess an inherent fractality, that is, have neighbour-to-neighbour correlation at all levels of timescale. However, demonstrating this phenomenon has eluded researchers for more than two decades, primarily because of the challenges associated with estimating the scale-invariant, power law exponent—called the fractal dimension D_f—from fractional Brownian noise. Here, we confirm this hypothesis and establish the fractality of tics by examining two tic time series datasets collected 6–12 months apart in children with tics, using random walk models and directional statistics. We find that D_f is correlated with tic severity as measured by the YGTTS total tic score, and that D_f is a sensitive parameter in examining the effect of several tic suppression conditions on the tic time series. Our findings pave the way for using the fractal nature of tics as a robust quantitative tool for estimating tic severity and treatment effectiveness, as well as a possible marker for differentiating typical from functional tics.     

RESTORING SALMON HABITAT FOR A CHANGING CLIMATE

An important question for salmon restoration efforts in the western USA is ‘How should habitat restoration plans be altered to accommodate climate change effects on stream flow and temperature?’ We developed a decision support process for adapting salmon recovery plans that incorporates (1) local habitat factors limiting salmon recovery, (2) scenarios of climate change effects on stream flow and temperature, (3) the ability of restoration actions to ameliorate climate change effects, and (4) the ability of restoration actions to increase habitat diversity and salmon population resilience. To facilitate the use of this decision support framework, we mapped scenarios of future stream flow and temperature in the Pacific Northwest region and reviewed literature on habitat restoration actions to determine whether they ameliorate a climate change effect or increase life history diversity and salmon resilience. Under the climate change scenarios considered here, summer low flows decrease by 35–75% west of the Cascade Mountains, maximum monthly flows increase by 10–60% across most of the region, and stream temperatures increase between 2 and 6°C by 2070–2099. On the basis of our literature review, we found that restoring floodplain connectivity, restoring stream flow regimes, and re‐aggrading incised channels are most likely to ameliorate stream flow and temperature changes and increase habitat diversity and population resilience. By contrast, most restoration actions focused on in‐stream rehabilitation are unlikely to ameliorate climate change effects. Finally, we illustrate how the decision support process can be used to evaluate whether climate change should alter the types or priority of restoration actions in a salmon habitat restoration plan. Copyright © 2012 John Wiley & Sons, Ltd.     

Measuring energy security: Can the United States achieve oil independence?

Stochastic simulation of the direct economic costs of oil dependence in an uncertain future is proposed as a useful metric of oil dependence. The market failure from which these costs arise is imperfect competition in the world oil market, chiefly as a consequence of the use of market power by the Organization of the Petroleum Exporting Countries (OPEC) cartel. Oil dependence costs can be substantial. It is estimated that oil dependence costs to the US economy in 2008 will exceed $500 billion. Other costs, such as military expenditures or foreign policy constraints are deemed to be largely derivative of the actual or potential economic costs of oil dependence. The use of quantifiable economic costs as a security metric leads to a measurable definition of oil independence, or oil security, which can be used to test the ability of specific policies to achieve oil independence in an uncertain future.     

Nonlinear modeling of transformers

The performance of classical transformer models under nonsinusoidal excitation is investigated and two novel models for such analysis, both of which account for the transformer core magnetic nonlinearities, are presented. All analytical results are compared with experimental data