Improving InSAR geodesy using global atmospheric models

Spatial and temporal variations of pressure, temperature and water vapor content in the atmosphere introduce significant confounding delays in Interferometric Synthetic Aperture Radar (InSAR) observations of ground deformation and bias estimatesof regional strain rates. Producing robust estimates of tropospheric delays remains one of the key challenges in increasing the accuracy of ground deformation measurements using InSAR. Recent studies revealed the efficiency of global atmospheric reanalysis to mitigate the impact of tropospheric delays, motivating further exploration of their potential. Here, we explore the effectiveness of these models in several geographic and tectonic settings on both single interferograms and time series analysis products. Both hydrostatic and wet contributions to the phase delay are important to account for. We validate these path delay corrections by comparing with estimates of vertically integrated atmospheric water vapor content derived from the passive multi-spectral imager MERIS, onboard the ENVISAT satellite. Generally, the performance of the prediction depends on the vigor of atmospheric turbulence. We discuss (1) how separating atmospheric and orbital contributions allows one to better measure long wavelength deformation, (2) how atmospheric delays affect measurements of surface deformation following earthquakes and (3) we show that such a method allows us to reduce biases in multi-year strain rate estimates by reducing the influence of unevenly sampled seasonal oscillations of the tropospheric delay

Semi-Parametric Empirical Best Prediction for small area estimation of unemployment indicators

The Italian National Institute for Statistics regularly provides estimates of unemployment indicators using data from the Labor Force Survey. However, direct estimates of unemployment incidence cannot be released for Local Labor Market Areas. These are unplanned domains defined as clusters of municipalities; many are out-of-sample areas and the majority is characterized by a small sample size, which render direct estimates inadequate. The Empirical Best Predictor represents an appropriate, model-based, alternative. However, for non-Gaussian responses, its computation and the computation of the analytic approximation to its Mean Squared Error require the solution of (possibly) multiple integrals that, generally, have not a closed form. To solve the issue, Monte Carlo methods and parametric bootstrap are common choices, even though the computational burden is a non trivial task. In this paper, we propose a Semi-Parametric Empirical Best Predictor for a (possibly) non-linear mixed effect model by leaving the distribution of the area-specific random effects unspecified and estimating it from the observed data. This approach is known to lead to a discrete mixing distribution which helps avoid unverifiable parametric assumptions and heavy integral approximations. We also derive a second-order, bias-corrected, analytic approximation to the corresponding Mean Squared Error. Finite sample properties of the proposed approach are tested via a large scale simulation study. Furthermore, the proposal is applied to unit-level data from the 2012 Italian Labor Force Survey to estimate unemployment incidence for 611 Local Labor Market Areas using auxiliary information from administrative registers and the 2011 Census

Evidence for DNA-mediated nuclear compartmentalization distinct from phase separation.

RNA Polymerase II (Pol II) and transcription factors form concentrated hubs in cells via multivalent protein-protein interactions, often mediated by proteins with intrinsically disordered regions. During Herpes Simplex Virus infection, viral replication compartments (RCs) efficiently enrich host Pol II into membraneless domains, reminiscent of liquid-liquid phase separation. Despite sharing several properties with phase-separated condensates, we show that RCs operate via a distinct mechanism wherein unrestricted nonspecific protein-DNA interactions efficiently outcompete host chromatin, profoundly influencing the way DNA-binding proteins explore RCs. We find that the viral genome remains largely nucleosome-free, and this increase in accessibility allows Pol II and other DNA-binding proteins to repeatedly visit nearby DNA binding sites. This anisotropic behavior creates local accumulations of protein factors despite their unrestricted diffusion across RC boundaries. Our results reveal underappreciated consequences of nonspecific DNA binding in shaping gene activity, and suggest additional roles for chromatin in modulating nuclear function and organization

Feasibility studies of a converter-free grid-connected offshore hydrostatic wind turbine

Owing to the increasing penetration of renewable power generation, the modern power system faces great challenges in frequency regulations and reduced system inertia. Hence, renewable energy is expected to take over part of the frequency regulation responsibilities from the gas or hydro plants and contribute to the system inertia. In this article, we investigate the feasibility of frequency regulation by the offshore hydrostatic wind turbine (HWT). The simulation model is transformed from NREL (National Renewable Energy Laboratory) 5-MW gearbox-equipped wind turbine model within FAST (fatigue, aerodynamics, structures, and turbulence) code. With proposed coordinated control scheme and the hydrostatic transmission configuration of the HWT, the `continuously variable gearbox ratio' in turbulent wind conditions can be realised to maintain the constant generator speed, so that the HWT can be connected to the grid without power converters in-between. To test the performances of the control scheme, the HWT is connected to a 5-bus grid model and operates with different frequency events. The simulation results indicate that the proposed control scheme is a promising solution for offshore HWT to participated in frequency response in the modern power system

Effect of frequent hemodialysis on residual kidney function.

Frequent hemodialysis can alter volume status, blood pressure, and the concentration of osmotically active solutes, each of which might affect residual kidney function (RKF). In the Frequent Hemodialysis Network Daily and Nocturnal Trials, we examined the effects of assignment to six compared with three-times-per-week hemodialysis on follow-up RKF. In both trials, baseline RKF was inversely correlated with number of years since onset of ESRD. In the Nocturnal Trial, 63 participants had non-zero RKF at baseline (mean urine volume 0.76 liter/day, urea clearance 2.3 ml/min, and creatinine clearance 4.7 ml/min). In those assigned to frequent nocturnal dialysis, these indices were all significantly lower at month 4 and were mostly so at month 12 compared with controls. In the frequent dialysis group, urine volume had declined to zero in 52% and 67% of patients at months 4 and 12, respectively, compared with 18% and 36% in controls. In the Daily Trial, 83 patients had non-zero RKF at baseline (mean urine volume 0.43 liter/day, urea clearance 1.2 ml/min, and creatinine clearance 2.7 ml/min). Here, treatment assignment did not significantly influence follow-up levels of the measured indices, although the range in baseline RKF was narrower, potentially limiting power to detect differences. Thus, frequent nocturnal hemodialysis appears to promote a more rapid loss of RKF, the mechanism of which remains to be determined. Whether RKF also declines with frequent daily treatment could not be determined

Climate Change and Farm Use of Weather Information

More rapid than normal global climate change as represented by rising temperatures and more erratic and severe weather events have heightened the interest in how farmers use weather information. The greenhouse influence through driving climate change will likely be affecting agricultural efforts for some years to come. It behooves us to pay attention to this phenomenon, and especially put effort into understanding how farmers will respond to information about climate generally and forecasts in particular. This research is being funded by the U.S. Department of Commerce, National Oceanic and Atmospheric Administration. To address this issue farmers were surveyed in three major agroecological zones representing 1) a western Corn Belt, rainfed corn-soybean regime, 2) a central Great Plains irrigated corn-soybean regime, and 3) a central Great Plains irrigated continuous corn regime. Each of these zones is represented in three counties in eastern Nebraska. To better reflect farmers' weather related needs and issues, focus groups were held in each county to engage farmers in helping the researchers to design the survey instrument. The fact we used focus groups added an intriguing flavor to the study. Between 15-20 farmers in each zone were involved. These farmers were paid $25 for a 2-hour session that culminated in a provided lunch. Each session was also videotaped, providing the opportunity for all members of the research team to see the results of the event (in that only 3-4 members of the larger multidisciplinary research team were allowed to attend an event, due to concerns over affecting farmer responses). The focus was on the farmers' reactions to a series of questions prepared beforehand by the research team, all of which stirred lively dialogue on how farmers actually use weather information. The result was a substantially improved questionnaire. We also sent drafts back to farmer participants for final reviews, and subsequent adjustments were then made reflecting the way they used the words and understood the survey questions. The qualitative data from the focus group events ultimately influenced not only the way questions were asked but also how the modeling is done, and, especially, how the model results are interpreted. A total of 2211 questionnaires were sent, in two separate mailings. There was also a follow-up reminder card. Farmers were offered a payment of$25 to return the questionnaire. A total of 28% took the offer and the overall return rate was 33%, with 698 usable questionnaires in the econometric analysis. A distinctive aspect of this study is the fact that the research team involves active participation not only by agricultural economists but also by a psychologist and a social psychologist, as well as two meteorologists, and an agronomist (who is also a GIS specialist). The result is a nontraditional behavioral economics approach that is sensitive to the climate and agronomic realities faced by farmers in these zones. This approach has a unique two-fold feature; first, it puts special attention on underlying motives, and second, asks whether there may be a complex expression of both private (self) and public (other, community) interest in how forecasts influence farm level decisions. Yet, the modeling still reflects standard derived demand theory and the general expectancy-value or subjective utility perspective, i.e. that farmers have beliefs about fact events and values relating to the outcomes from those events, and that the demand for weather information is derived from the value (profit, sense of well-being, risk-reducing value) it produces for them. The beliefs represent probability statements about outcomes and the values represent the utility or profit related transformations of meaning about the farmer perceptions of the outcomes. The econometric analysis uses proxy measures of the expectancy-value as independent measures, along with such variables as financial capability of the farmer as represented in farm sales, to explain in a Tobit kind of framework 1) the probability of applying weather forecast information since it influences farm level decision(s), and 2) the extent to which this forecast information is influencing these decision(s). The set of four Tobit models in Table 1 test the influence of recent past and current experience (RPE), short (STF) and long-term forecasts (LTF) on 1) agronomic (e.g. selecting the crop type, spraying), 2) insurance, and 3) marketing decisions, within recent past experience/short-term and long-term forecasts. To test the models, we created four indices represented in balance (joint and nonseparable ratio of public (other) to private (self) interests); attitude as a construct of personal belief and value system, influence of social norms, household and community members, county extension, etc; farmers' need for internal control over crop production; and farm sales representing financial limitations. Preliminary analyses suggest that all the farm decisions are influenced by weather forecast information at a different intensity (Table 1). The probability of that influence increases with balance, as the farmer puts more effort into pursuing the self over the community interests. Influence of others and social norms intensify the use of weather information in the decisions as well. Those who want more control over the farm are likely to be more influenced by weather forecasts. Finally, influence of weather forecasts becomes greater as gross farm income (sales) increases. Other intriguing interpretations are suggested by the changes in the size of the parameter elasticities and marginal effects3, e.g. the control parameter is substantively smaller in the insurance decision, which suggests farmers see insurance as offsetting the need for more control over their decisions. As another example, the balance in private and public interests is less significant and less a factor in the very personal, private marketing decision in contrast to "how one farms" (which is likely more sensitive to community scrutiny) in the agronomic decisions. The larger paper explores these refinements in greater detail. Table 1. Intensity of Weather Forecast Influence on Farm Decisions. Variables Agronomy (Cur. Rec. Past Exp. & Short term forecasts) decisions Agronomy (Long Term Forecasts) decisions E1 E 2 ME 1 ME 2 E 1 E 2 ME 1 ME 2 Balance -.37b -.37b -1.109b -.012b -.23a -.24a -.637a -.0202a Attitude .62c .62c .495c .0052c .71c .72c .560c .0178c Norms .12c .12c .153c .0016c .09b .09b .102b .0032b PBC .15c .15c .157c .0017c .19c .19c .178c .0056c Farm Sale .07b .07b .086b .0009b .02 .02 .024 .0008 Easting .06b .06b -2.2E-6b -2.3E-8b -.01 -.01 3.7E-7 1.2E-8 Insurance decisions Marketing decisions Balance -.12 -.13 -.247 -.033 -.29a -.29a -.779a -.040a Attitude .93c .98c .674c .089c .58c .59c .486c .025c PBC .07 .07 .048 .006 .13b .13b .119b .006b Farm Sale .18c .19c .164c .022c .20c .20c .238c .012c Notes: Dependent variable is the degree of influence of climate and weather information and forecasts. a p<0.10, b p<0.05, c p<0.001. 3 E1 is the elasticity at the mean that represents the percentage change in the probability that the weather and climate forecast and information influences decisions at all, and; E2 is the elasticity at the mean for those who are being influenced, the percentage change in the degree of influence. ME1 is the effect of the expected value for the weather and climate already influenced farmers; ME2 is the effect of the probability of being influenced by climate and weather information (elasticity of influence).Farm Management,

A Controlled Increase in Dietary Phosphate Elevates BP in Healthy Human Subjects.

Background Despite epidemiologic evidence for increased cardiovascular morbidity and mortality associated with both high dietary and serum phosphate in humans with normal renal function, no controlled phosphate intervention studies of systemic hemodynamics have been reported. Higher serum 25(OH) vitamin D levels are associated with better cardiovascular outcomes, but vitamin D increases intestinal phosphate absorption.Methods We conducted a prospective outpatient study with blinded assessment in 20 young adults with normal renal function randomized to high phosphate (regular diet plus 1 mmol/kg body wt per day of Na as neutral sodium phosphate) or low phosphate (regular diet plus lanthanum, 750 mg thrice/day, plus 0.7 mmol/kg body wt per day of Na as NaCl) for 11 weeks. After 6 weeks, all subjects received vitamin D3 (600,000 U) by intramuscular injection. Outcome parameters were 24-hour ambulatory systolic and diastolic BP (SBP and DBP), pulse rate (PR), biomarkers, and measures of endothelial and arterial function.Results Compared with the low-phosphate diet group, the high-phosphate diet group had a significant increase in mean±SEM fasting plasma phosphate concentration (0.23±0.11 mmol/L); 24-hour SBP and DBP (+4.1; 95% confidence interval [95% CI], 2.1 to 6.1; and +3.2; 95% CI, 1.2 to 5.2 mm Hg, respectively); mean 24-hour PR (+4.0; 95% CI, 2.0 to 6.0 beats/min); and urinary metanephrine and normetanephrine excretion (54; 95% CI, 50 to 70; and 122; 95% CI, 85 to 159 µg/24 hr, respectively). Vitamin D had no effect on any of these parameters. Neither high- nor low-phosphate diet nor vitamin D affected endothelial function or arterial elasticity.Conclusions Increased phosphate intake (controlled for sodium) significantly increases SBP, DBP, and PR in humans with normal renal function, in part, by increasing sympathoadrenergic activity

Navigation input to level C OFT navigation functional subsystem software requirements (rendezvous onorbit-2)

Navigation software design requirements are presented for the orbital flight test phase of space shuttle. Computer loads for the entire onorbit-2 operation are documented