Does a ‘notched’ nuchal translucency indicate Down syndrome fetuses or other adverse pregnancy outcome?

The aim of the present study was to assess the sonographic contour of the increased nuchal translucency (NT) and to correlate this with pregnancy outcome. Fifty sonographic images of fetuses with increased NT [>95th centile thickness of the normal range for crown–rump length (CRL) between 38 and 84 mm] were retrospectively assessed. In all the cases a complete pregnancy and even infancy follow-up (<36 months) was available. The NT appearances were subdivided into two forms: a ‘notched’ or ‘uniform’ appearance. The images were correlated with karyotype results [trisomy 21 (DS) vs euploid cases] and pregnancy outcome. Complicated outcomes were classified as being either DS fetuses, miscarriage or termination of pregnancy because of structural anomaly. Thus 30/35 (86%) of the euploid fetuses had a ‘uniformly’ increased NT, whereas 8/13 DS cases (62%) had a ‘notched’ appearance (Fisher's exact test, p=0.004). Additionally, 27/29 fetuses (93%) which had an uneventful pregnancy outcome had a ‘uniform’ increased NT, whereas 12/26 (57%) of the fetuses which had adverse pregnancy outcome had a ‘notched’ appearance of their NT (Fisher's exact test, p<0.001). Although it was not possible to correlate the sonographic data with post-evacuation microdissection findings, it is possible that a uniformly shaped, increased NT may be more representative of a developmental delay in a normal fetus. Conversely, a ‘notched’ nuchal surface may represent abnormal lymphatic or cardiovascular development more commonly seen in DS fetuses. Copyright © 2001 John Wiley & Sons, Ltd.     

Integration of Solid Oxide Fuel Cell in a sugar-ethanol factory: analysis of the efficiency and the environmental profile of the products

The effect of the integration of Solid Oxide Fuel Cell (SOFC) technology in a sugar-ethanol factory on the environmental profile/footprint of the products (sugar, ethanol, electricity) is evaluated. The sugarcane is the primary feedstock and sugar, ethanol and electricity are the main products of the system, where the functional unit is defined as 9.86 ton/h of sugar, 2.195 ton/h of hydrated ethanol (96% w/w) and 847 kWh of electricity. A detailed set of material and energy inputs and outputs was obtained from a local factory and was completed using simulation data by Aspen Plus^®.The environmental impacts (greenhouse gases and air pollution), exergy efficiency and a renewability parameter have been considered as indicators for the comparative assessment with conventional sugar, ethanol and electricity production technologies. The results show that the use of a SOFC technology involves a reduction of greenhouse gas emissions (52-55%) and non-renewable resources (60-64%) when compared with the conventional integrated sugar and ethanol plant. The higher renewability index (0.93) and exergy efficiency (38%) are noticed for the Solid Oxide Fuel Cell technology integrated in the sugar-ethanol factory than conventional sugar-ethanol plant.     

Changes in diatom patch-size distribution and degradation in a spatially self-organized intertidal mudflat ecosystem

Self-organized spatial patterns have been proposed as possible indicators for regime shifts in ecosystems. Until now, this hypothesis has only been tested in drylands. Here, we focus on intertidal mudflats where regular spatial patterns develop in early spring from the interaction between diatom growth and sedimentation but disappear when benthic herbivore abundance increases in early summer, accompanied by a dramatic shift to a bare mudflat. We followed the patch-size distributions of diatom biofilms during this degradation process. As time progressed, we found a temporal change in the spatial configuration occurring simultaneously with the loss of the diatom-sediment feedback. This indicates a gradual failure in time of the self-organization process that underlies regular patterning in this ecosystem. The path to degradation co-occurred with the loss of the larger patches in the ecosystem, which resulted in a decrease of the truncation in the patch-size distribution. Hence, our study in mudflat ecosystems confirms the general hypothesis that spatial patterns can provide important clues about the level of degradation. Nevertheless, our study highlights the need for thorough study about the type of spatial patterns and the nature of the underlying feedbacks before a reliable assessment of ecosystem status can be made, as changes in patch-size distribution differed markedly with those observed in other ecosystems.     

Large-scale diversity and biogeography of benthic copepods in European waters

A large-scale database concerning benthic copepods from the Arctic, Baltic Sea, North Sea, British Isles, Adriatic Sea and Crete was compiled to assess species richness, biodiversity, communities, ecological range size and biogeographical patterns. The Adriatic showed the highest evenness and the most species-rich communities. Assemblages from the North Sea, British Isles, Baltic and Crete had a lower evenness. The British Isles were characterised by impoverished communities. The ecological specificity of copepod species showed two diverging trends: higher specificity of species in more diverse assemblages was observed in the Adriatic, North Sea and Baltic. A uniformly high species specificity disregarding sample diversity was found on Crete and in the British Isles. Benthic copepod communities showed distinct patterns that clearly fit the predefined geographical regions. Communities were distinguishable and β-diversity was found to be high around Europe, indicating a high species turnover on the scale of this investigation. The British Isles and the North Sea were found to be faunistic links to the Baltic and the Arctic.     

Analyzing the Variability of Remote Sensing and Hydrologic Model Evapotranspiration Products in a Watershed in Michigan

The goal of this paper was to statistically explore the spatiotemporal performance of remotely sensed actual evapotranspiration (ETa) datasets and a remotely sensed ensemble in a region that lacks observed data. The remotely sensed datasets were further compared with ETa results from a physically based hydrologic model (Soil and Water Assessment Tool) to examine the differences and determine the level of agreement between the ETa datasets and the model outputs. ETa datasets were compared on temporal (i.e., monthly and seasonal basis) and spatial (i.e., landuse) scales at both watershed and subbasin levels. The results showed a lack of consistent similarities and differences among the datasets when evaluating the monthly ETa variations; however, the seasonal aggregated data presented more consistent similarities and differences during the spring and summer compared to the fall and winter. Meanwhile, spatial analysis of the datasets showed the MOD16A2 500 m ETa product was the most versatile of the tested datasets, being able to differentiate between landuses during all seasons. Furthermore, the use of an averaging ensemble was able to improve overall ETa performance in the study area. This study showed that the remotely sensed ETa products are not similar throughout the year, but the appropriate application periods for different ETa products were identified. Finally, spatial variabilities of the ETa products are more in tune with landuse and climate characteristics.     

Estimating Long-Term Ground Level Concentrations of SO2 from Short-Term Peak Data

Maximum concentrations of sulfur dioxide vary approximately inversely as the square root of the averaging time for periods up to a year, a much longer time period than those reported in previously published studies. This finding is based on analyses of SO₂ and tracer gas concentrations measured in the vicinities of a test stack, a petrochemical complex, and eight power plants. Therefore, for a given set of emission conditions, long-term concentrations of SO₂ and other conservative pollutants emitted by well-defined sources can be rapidly estimated from maximum short-term concentrations, and vice versa. The scatter in the data corresponds to an estimation error of about a factor of three for averaging time conversions of one day to one year. This is approximately the same error associated with conventional calculations. Therefore, the use of averaging time conversions is justified as a rapid screening technique to estimate compliance with ambient air quality standards.     

From Global to Local: Providing Actionable Flood Forecast Information in a Cloud‐Based Computing Environment

Global and continental scale flood forecast provide coarse resolution flood forecast, but from the perspective of emergency management, flood warnings should be detailed and specific to local conditions. The desired refinement can be provided by the use of downscaling global scale models and through the use of distributed hydrologic models to produce a high‐resolution flood forecast. Three major challenges associated with transforming global flood forecasting to a local scale are addressed in this work. The first is using open‐source software tools to provide access to multiple data sources and lowering the barriers for users in management agencies at local level. This can be done through the Tethys Platform that enables web water resources modeling applications. The second is finding a practical solution for the computational requirements associated with running complex models and performing multiple simulations. This is done using Tethys Cluster that manages distributed and cloud computing resources as a companion to the Tethys Platform for web app development. The third challenge is discovering ways to downscale the forecasts from the global extent to the local context. Three modeling strategies have been tested to address this, including downscaling of coarse resolution global runoff models to high‐resolution stream networks and routing with Routing Application for Parallel computatIon of Discharge (RAPID), the use of hierarchical Gridded Surface and Subsurface Hydrologic Analysis (GSSHA) distributed models, and pre‐computed distributed GSSHA models.     

AERCOARE: An overwater meteorological preprocessor for AERMOD

AERCOARE is a meteorological data preprocessor for the American Meteorological Society and U.S Environmental Protection Agency (EPA) Regulatory Model (AERMOD). AERCOARE includes algorithms developed during the Coupled-Ocean Atmosphere Response Experiment (COARE) to predict surface energy fluxes and stability from routine overwater measurements. The COARE algorithm is described and the implementation in AERCOARE is presented. Model performance for the combined AERCOARE-AERMOD modeling approach was evaluated against tracer measurements from four overwater field studies. Relatively better model performance was found when lateral turbulence measurements were available and when several key input variables to AERMOD were constrained. Namely, requiring the mixed layer height to be greater than 25 m and not allowing the Monin Obukhov length to be less than 5 m improved model performance in low wind speed stable conditions. Several options for low wind speed dispersion in AERMOD also affected the model performance results. Model performance for the combined AERCOARE-AERMOD modeling approach was found to be comparable to the current EPA regulatory Offshore Coastal Model (OCD) for the same tracer studies. AERCOARE-AERMOD predictions were also compared to simulations using the California Puff-Advection Model (CALPUFF) that also includes the COARE algorithm. Many model performance measures were found to be similar, but CALPUFF had significantly less scatter and better performance for one of the four field studies. For many offshore regulatory applications, the combined AERCOARE-AERMOD modeling approach was found to be a viable alternative to OCD the currently recommended model.

Implications: A new meteorological preprocessor called AERCOARE was developed for offshore source dispersion modeling using the U.S. Environmental Protection Agency (EPA) regulatory model AERMOD. The combined AERCOARE-AERMOD modeling approach allows stakeholders to use the same dispersion model for both offshore and onshore applications. This approach could replace current regulatory practices involving two completely different modeling systems. As improvements and features are added to the dispersion model component, AERMOD, such techniques can now also be applied to offshore air quality permitting.