Noninvasive fetal genome sequencing: a primer

We recently demonstrated whole genome sequencing of a human fetus using only parental DNA samples and plasma from the pregnant mother. This proof-of-concept study demonstrated how samples obtained noninvasively in the first or second trimester can be analyzed to yield a highly accurate and substantially complete genetic profile of the fetus, including both inherited and de novo variation. Here, we revisit our original study from a clinical standpoint, provide an overview of the scientific approach, and describe opportunities and challenges along the path toward clinical adoption of noninvasive fetal whole genome sequencing. © 2013 John Wiley & Sons, Ltd.     

Nitrogen removal and nitrate leaching for forage systems receiving dairy effluent

Florida dairies need year-round forage systems that prevent loss of N to ground water from waste effluent sprayfields. Our purpose was to quantify forage N removal and monitor nitrate N (NO3(-)-N) concentrations in soil water below the rooting zone for two forage systems during four 12-mo cycles (1996-2000). Soil in the sprayfield is an excessively drained Kershaw sand (thermic, uncoated Typic Quartzipsamment). Over four cycles, average loading rates of effluent N were 500, 690, and 910 kg ha(-1) per cycle. Nitrogen removed by the bermudagrass (Cynodon spp.)-rye (Secale cereale L.) system (BR) during the first three cycles was 465 kg ha(-1) per cycle for the low loading rate, 528 kg ha(-1) for the medium rate, and 585 kg ha(-1) for the high. For the corn (Zea mays L.)-forage sorghum [Sorghum bicolor (L.) Moench]-rye system (CSR), N removals were 320 kg ha(-1) per cycle for the low rate, 327 kg ha(-1) for the medium, and 378 kg ha(-1) for the high. The higher N removals for BR were attributed to higher N concentration in bermudagrass (18.1-24.2 g kg(-1)) than in corn and forage sorghum (10.3-14.7 g kg(-1)). Dry matter yield declined in the fourth cycle for bermudagrass but N removal continued to be higher for BR than CSR. The BR system was much more effective at preventing NO3(-)-N leaching. For CSR, NO3(-)-N levels in soil water (1.5 m below surface) increased steeply during the period between the harvest of one forage and canopy dosure of the next. Overall, the BR system was better than CSR at removing N from the soil and maintaining low NO3(-)-N concentrations below the rooting zone.     

California households' willingness to pay for ‘green’ electronics

Concerns about rapid increases in the volume of electronic waste (e-waste) and its potential toxicity have sharpened policy makers' interest for extended producer responsibility to encourage manufacturers of consumer electronic devices (CEDs) to ‘design for the environment’. This paper examines consumer willingness to pay for ‘green’ electronics based on a 2004 mail survey of California households. Using ordered logit models, it was found that significant predictors of willingness to pay for ‘greener’ computers and cell phones include age, income, education, beliefs about the role of government for improving environmental quality, as well as environmental attitudes and behaviors, but neither gender nor political affiliation. Although most respondents are willing to pay only a 1% premium for ‘greener’ CEDs, innovation and EU directives may soon make them competitive with conventional CEDs.     

Secchi Disc Relationships1

ABSTRACT: The problem of estimating bulk light extinction coefficients in surface water impoundments is examined. It is shown that the bulk extinction coefficient can be accurately estimated from the Secchi disc depth. In addition, the equation derived is significantly different from that derived by Poole and Atkins in 1929. This empirical expression for the extinction coefficient is then used to develop a semiempirical expression for the euphotic depth as a function of the Secchi disc depth.     

RUNOFF MODELING OF A MOUNTAINOUS CATCHMENT USING TOPMODEL: A CASE STUDY1

ABSTRACT: The rainfall‐runoff response of the Tygarts Creek Catchment in eastern Kentucky is studied using TOPMODEL, a hydrologic model that simulates runoff at the catchment outlet based on the concepts of saturation excess overland flow and subsurface flow. Unlike the traditional application of this model to continuous rainfall‐runoff data, the use of TOPMOEL in single event runoff modeling, specifically floods, is explored here. TOPMODEL utilizes a topographic index as an indicator of the likely spatial distribution of rainfall excess generation in the catchment. The topographic index values within the catchment are determined using the digital terrain analysis procedures in conjunction with digital elevation model (DEM) data. Select parameters in TOPMODEL are calibrated using an iterative procedure to obtain the best‐fit runoff hydrograph. The calibrated parameters are the surface transmissivity, T_O, the transmissivity decay parameter, m, and the initial moisture deficit in the root zone, S_r0. These parameters are calibrated using three storm events and verified using three additional storm events. Overall, the calibration results obtained in this study are in general agreement with the results documented from previous studies using TOPMODEL. However, the parameter values did not perform well during the verification phase of this study.     

Avoidance of death and injury through mionitoring of dams and flood evacuation in Essex, Connecticut, June 1982

During a period of heavy ranfall in Essex, Connecticut, on 4th and 5th June 1982, dams in the town along the Fall River were monitored for signs of braks. The observation of water spilling over one of teh dams at 10 p.m. in 5th June ld to the decision to evacuate community rsidents. The notification and avacuation process was conducted by the cvolunteer fire department over a two-hour periopd. At 12.30 a.m 6th June, the upper dam on the Fall River gave way, rsulting in a rapidly moving floodwave which sequentially destroyed four additional dams along the river. Although there was extensive property damage, gthere were no serious injuries and no deaths. The responsible actons of the town officials in monitoring the dams during the period of heavy rainfall permitted the evacuation order to be given in sufficient time to evacuate the residnts. The success of the evacuation was the result of good communication, trust, and co-operation between town officials and the community.     

Improving sustainability through effective reuse of product returns: minimizing waste in a batch blending process environment

A case study of a successful reuse program in a batch blending production environment is presented. This program involves not only addressing the company's own potential waste, but also working with distributors and customers to take back and reuse product, thus eliminating the customers' burden of disposal. Implications of the program for downstream supply chain partners are identified and a structured approach for implementation is presented. Modification for use in similar production environments is possible, enhancing sustainability, while providing environmental as well as economic benefits.     

A comparison of nonlinear regression and neural network models for ground-level ozone forecasting

A hybrid nonlinear regression (NLR) model and a neural network (NN) model, each designed to forecast next-day maximum 1-hr average ground-level O3 concentrations in Louisville, KY, were compared for two O3 seasons--1998 and 1999. The model predictions were compared for the forecast mode, using forecasted meteorological data as input, and for the hindcast mode, using observed meteorological data as input. The two models performed nearly the same in the forecast mode. For the two seasons combined, the mean absolute forecast error was 12.5 ppb for the NLR model and 12.3 ppb for the NN model. The detection rate of 120 ppb threshold exceedances was 42% for each model in the forecast mode. In the hindcast mode, the NLR model performed marginally better than the NN model. The mean absolute hindcast error was 11.1 ppb for the NLR model and 12.9 ppb for the NN model. The hindcast detection rate was 92% for the NLR model and 75% for the NN model.     

Transport and dispersion during wintertime particulate matter episodes in the San Joaquin Valley, California

Data analysis and modeling were performed to characterize the spatial and temporal variability of wintertime transport and dispersion processes and the impact of these processes on particulate matter (PM) concentrations in the California San Joaquin Valley (SJV). Radar wind profiler (RWP) and radio acoustic sounding system (RASS) data collected from 18 sites throughout Central California were used to estimate hourly mixing heights for a 3-month period and to create case studies of high-resolution diagnostic wind fields, which were used for trajectory and dispersion analyses. Data analyses show that PM episodes were characterized by an upper-level ridge of high pressure that generally produced light winds through the entire depth of the atmospheric boundary layer and low mixing heights compared with nonepisode days. Peak daytime mixing heights during episodes were -400 m above ground level (agl) compared with -800 m agl during nonepisodes. These episode/nonepisode differences were observed throughout the SJV. Dispersion modeling indicates that the range of influence of primary PM emitted in major population centers within the SJV ranged from -15 to 50 km. Trajectory analyses revealed that little intrabasin pollutant transport occurred among major population centers in the SJV; however, interbasin transport from the northern SJV and Sacramento regions into the San Francisco Bay Area (SFBA) was often observed. In addition, this analysis demonstrates the usefulness of integrating RWP/RASS measurements into data analyses and modeling to improve the understanding of meteorological processes that impact pollution, such as aloft transport and boundary layer evolution.