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This study examines hydrophobic surface coatings for stimulation electrodes to mitigate foreign body reactions and encapsulation. Electrospinning of polydimethylsiloxane (PDMS) resin is explored to create fiber structures for electrode coatings. PDMS resin is succesfully processed into fiber mats. Electrospun PDMS fiber structures showed an increased water contact angle (124 °/125 °) in comparison to a cast flat film (102 °). To further increase hydrophobicity, the fabrication process of Slippery Liquid-Infused Porous Surface (SLIPS) systems with a polyurethane substrate and different natural lubricants is assessed with promising results in an increase in water contact angles up to 11°. The findings suggest the potential of these surface coatings to enhance the performance and safety of stimulation electrodes. [ABSTRACT FROM AUTHOR]

Community-scale power infrastructure may be the only electrification option for tens of millions households that remain out of reach from centralized power grids. The responsiveness of household electricity demand to price is a crucial design input for off-grid systems. While the price elasticity of electricity demand of grid-connected consumers has been abundantly studied, few studies focus on off-grid communities where substantial econometric challenges arise, including the absence of metered consumption data and electricity prices that are simultaneously determined by cost and demand considerations. This study attempts to address these challenges for the case of off-grid micro hydropower consumers. It makes two core contributions: First, we propose the surface area of the contributing hydrologic catchment as a new instrumental variable to estimate elasticity using a cross sectional dataset of existing micro hydropower infrastructure. Second, we provide a first price-elasticity estimate (−0.15) for off-grid electricity demand in Nepal. We surmise that the small (in absolute value) elasticity value found in this study arises from the low levels of consumption observed off-the-grid. We use a Monte Carlo analysis to show that failing to account for this disparity can lead to substantial financial losses caused by suboptimal power infrastructure design.

Rural electrification in developing countries is often hampered by major information gaps between local communities and urban centers, where technical expertise and funding are concentrated. The tool presented in this paper addresses these gaps to support the implementation of off-grid micro hydropower infrastructure. Specifically, we present a method to site, size and evaluate the potential for micro hydropower based on remote sensing data. The method improves on previous approaches by (i) incorporating the effect of hillslope topography on the optimal layout of the infrastructure, and (ii) accounting for the constraints imposed by streamflow variability and local electricity demand on the optimal size of the plants. An assessment of the method's performance against 148 existing schemes indicates that it correctly identifies the most promising locations for hydropower in Nepal, but does not generally reproduce the specific design features of constructed plants, which are affected by site-specific constraints. We develop a proof-of-concept computer tool to explore the potential of webGIS technology to account for these constraints by collecting site-specific information from local users.

Flow duration curves (FDC) display streamflow values against their relative exceedance time. They provide critical information for watershed management by representing the variation in the availability and reliability of surface water to supply ecosystem services and satisfy anthropogenic needs. FDCs are particularly revealing in seasonally dry climates, where surface water supplies are highly variable. While useful, the empirical computation of FDCs is data intensive and challenging in sparsely gauged regions, meaning that there is a need for robust, predictive models to evaluate FDCs with simple parameterization. Here, we derive a process-based analytical expression for FDCs in seasonally dry climates. During the wet season, streamflow is modeled as a stochastic variable driven by rainfall, following the stochastic analytical model of Botter et al. (2007a). During the dry season, streamflow is modeled as a deterministic recession with a stochastic initial condition that accounts for the carryover of catchment storage across seasons. The resulting FDC model is applied to 38 catchments in Nepal, coastal California, and Western Australia, where FDCs are successfully modeled using five physically meaningful parameters with minimal calibration. A Monte Carlo analysis revealed that the model is robust to deviations from its assumptions of Poissonian rainfall, exponentially distributed response times and constant seasonal timing. The approach successfully models period-of-record FDCs and allows interannual and intra-annual sources of variations in dry season streamflow to be separated. The resulting median annual FDCs and confidence intervals allow the simulation of the consequences of interannual flow variations for infrastructure projects. We present an example using run-of-river hydropower in Nepal as a case study. Key Points Probabilistic derivation of flow distribution in seasonally dry climate Successfully applied in Nepal, California, and Western Australia Disentangles inter- and intra-annual streamflow variations © 2014. American Geophysical Union. All Rights Reserved.

Estimating precipitation over large spatial areas remains a challenging problem for hydrologists. Sparse ground-based gauge networks do not provide a robust basis for interpolation, and the reliability of remote sensing products, although improving, is still imperfect. Current techniques to estimate precipitation rely on combining these different kinds of measurements to correct the bias in the satellite observations. We propose a novel procedure that, unlike existing techniques, (i) allows correcting the possibly confounding effects of different sources of errors in satellite estimates, (ii) explicitly accounts for the spatial heterogeneity of the biases and (iii) allows the use of non overlapping historical observations. The proposed method spatially aggregates and interpolates gauge data at the satellite grid resolution by focusing on parameters that describe the frequency and intensity of the rainfall observed at the gauges. The resulting gridded parameters can then be used to adjust the probability density function of satellite rainfall observations at each grid cell, accounting for spatial heterogeneity. Unlike alternate methods, we explicitly adjust biases on rainfall frequency in addition to its intensity. Adjusted rainfall distributions can then readily be applied as input in stochastic rainfall generators or frequency domain hydrological models. Finally, we also provide a procedure to use them to correct remotely sensed rainfall time series.We apply the method to adjust the distributions of daily rainfall observed by the TRMM satellite in Nepal, which exemplifies the challenges associated with a sparse gauge network and large biases due to complex topography. In a cross-validation analysis on daily rainfall from TRMM 3B42 v6, we find that using a small subset of the available gauges, the proposed method outperforms local rainfall estimations using the complete network of available gauges to directly interpolate local rainfall or correct TRMM by adjusting monthly means. We conclude that the proposed frequency-domain bias correction approach is robust and reliable compared to other bias correction approaches. © 2013 Elsevier Ltd.

The groundbreaking discovery of vitamin E by Evans and Bishop in 1922 was an important milestone in vitamin research, inspiring further investigation into its crucial role in both human and animal nutrition. Supplementing vitamin E has been proved to enhance multiple key physiological systems such as the reproductive, circulatory, nervous and muscular systems. As the main antioxidant in the blood and on a cellular level, vitamin E maintains the integrity of both cellular and vascular membranes and thus modulates the immune system. This overview showcases important and innovative routes for synthesizing vitamin E on a commercial scale, provides cutting‐edge insights into formulation concepts for successful product form development and emphasizes the importance and future of vitamin E in healthy and sustainable animal nutrition. [ABSTRACT FROM AUTHOR]

We establish a general kinetic scheme for the energy transfer and radical-pair dynamics in photosystem I (PSI) of Chlamydomonas reinhardtii, Synechocystis PCC6803, Thermosynechococcus elongatus and Spirulina platensis grown under white-light conditions. With the help of simultaneous target analysis of transient-absorption data sets measured with two selective excitations, we resolved the spectral and kinetic properties of the different species present in PSI. WL-PSI can be described as a Bulk Chl a in equilibrium with a higher-energy Chl a, one or two Red Chl a and a reaction-center compartment (WL-RC). Three radical pairs (RPs) have been resolved with very similar properties in the four model organisms. The charge separation is virtually irreversible with a rate of ≈900 ns−1. The second rate, of RP1 → RP2, ranges from 70–90 ns−1 and the third rate, of RP2 → RP3, is ≈30 ns−1. Since RP1 and the Red Chl a are simultaneously present, resolving the RP1 properties is challenging. In Chlamydomonas reinhardtii, the excited WL-RC and Bulk Chl a compartments equilibrate with a lifetime of ≈0.28 ps, whereas the Red and the Bulk Chl a compartments equilibrate with a lifetime of ≈2.65 ps. We present a description of the thermodynamic properties of the model organisms at room temperature. [ABSTRACT FROM AUTHOR]