Prenatal diagnosis of Pierre–Robin sequence as part of Stickler syndrome

Stickler syndrome or hereditary progressive arthro-ophthalmopathy, is an autosomal dominant condition characterized by ocular manifestations, arthritic changes, orofacial features and deafness, in variable degrees. We report the first case of prenatal diagnosis of Stickler syndrome in a child with a Pierre–Robin sequence (PRS) causing a polyhydramnios. When isolated polyhydramnios is not explained by immunological, metabolic or infectious causes, swallowing difficulty due to PRS must be considered. As PRS is aetiologically heterogenous, the prognosis depends on the cause. Genetic investigations and familial history must be taken into account. Here, in a context of familial Stickler syndrome, making the prenatal diagnosis of PRS as part of Stickler syndrome allowed us to reassure the parents and to anticipate airway trouble at the child's birth. Copyright © 2002 John Wiley & Sons, Ltd.     

Enhancing e-waste estimates: Improving data quality by multivariate Input–Output Analysis

Waste electrical and electronic equipment (or e-waste) is one of the fastest growing waste streams, which encompasses a wide and increasing spectrum of products. Accurate estimation of e-waste generation is difficult, mainly due to lack of high quality data referred to market and socio-economic dynamics. This paper addresses how to enhance e-waste estimates by providing techniques to increase data quality. An advanced, flexible and multivariate Input–Output Analysis (IOA) method is proposed. It links all three pillars in IOA (product sales, stock and lifespan profiles) to construct mathematical relationships between various data points. By applying this method, the data consolidation steps can generate more accurate time-series datasets from available data pool. This can consequently increase the reliability of e-waste estimates compared to the approach without data processing. A case study in the Netherlands is used to apply the advanced IOA model. As a result, for the first time ever, complete datasets of all three variables for estimating all types of e-waste have been obtained. The result of this study also demonstrates significant disparity between various estimation models, arising from the use of data under different conditions. It shows the importance of applying multivariate approach and multiple sources to improve data quality for modelling, specifically using appropriate time-varying lifespan parameters. Following the case study, a roadmap with a procedural guideline is provided to enhance e-waste estimation studies.     

SUBSCRIPTION INFORMATION

<正>Chinese Journal of Population Resources and Environment,Print ISSN 1004-2857,Online ISSN 2325-4262,Volume 11,2013.Chinese Journal of Population Resources and Environment(www.tandfonline.com/tpre)is a peer-reviewed journal published in March,June,September,and December by TaylorFrancis,4 Park Square,Milton Park,Abingdon,Oxon,OX14 4RN,UK.     

Carbon price impacts on sector cost: based on an input–output model of Beijing

Under the pressure of sustained growth in energy consumption in China, the implementation of a carbon pricing mechanism is an effective economic policy measure for promoting emission reduction, as well as a hotspot of research among scholars and policy makers. In this paper, the effects of carbon prices on Beijing’s economy are analyzed using input–output tables. The carbon price costs are levied in accordance with the products’ embodied carbon emission. By calculation, given the carbon price rate of 10 RMB/t-CO₂, the total carbon costs of Beijing account for approximately 0.22–0.40% of its gross revenue the same year. Among all industries, construction bears the largest carbon cost. Among export sectors, the coal mining and washing industry has much higher export carbon price intensity than other industries. Apart from traditional energy-intensive industries, tertiary industry, which accounts for more than 70% of Beijing’s economy, also bears a major carbon cost because of its large economic size. However, from 2007 to 2010, adjustment of the investment structure has reduced the emission intensity in investment sectors, contributing to the reduction of overall emissions and carbon price intensity.     

Decomposition of factors influencing carbon emissions in the region of Beijing–Tianjin–Hebei,based on the perspective of terminal energy consumption

In order to analyze the factors influencing carbon emissions in the region of Beijing–Tianjin–Hebei and to explore the pathways to developing a low-carbon economy, this paper begins with the terminal energy consumption of three industries and residential consumption, and constructs an identical equation which is composed of population size, level of economic development, energy intensity, the proportion of energy consumption, energy structure, and the coefficient of carbon emissions. Based on the data of terminal energy consumption during 2000–2012, various factors are analyzed and their contribution is measured by Logarithmic Mean Divisia Index (LMDI). The results show that the levels of population and economy have a positive driving effect while energy intensity, energy structure, and carbon intensity have a negative driving effect; the proportion of energy consumption had a negative driving effect prior to 2006, then changed to positive. Among suggestions for a low-carbon economy are controlling population size, improving the quality of economic development, supporting research into new energy technology, accelerating regional integration and optimizing industrial structure, and enhancing environmental protection and spreading the concept of a low-carbon economy.     

Finite Element Analysis of Knee Injury Risks in Car-to-Pedestrian Impacts

In vehicle–pedestrian collisions, lower extremities of pedestrians are frequently injured by vehicle front structures. In this study, a finite element (FE) model of THUMS (total human model for safety) was modified in order to assess injuries to a pedestrian lower extremity. Dynamic impact responses of the knee joint of the FE model were validated on the basis of data from the literature. Since in real-world accidents, the vehicle bumper can impact the lower extremities in various situations, the relations between lower extremity injury risk and impact conditions, such as between impact location, angle, and impactor stiffness, were analyzed. The FE simulation demonstrated that the motion of the lower extremity may be classified into a contact effect of the impactor and an inertia effect from a thigh or leg. In the contact phase, the stress of the bone is high in the area contacted by the impactor, which can cause fracture. Thus, in this phase the impactor stiffness affects the fracture risk of bone. In the inertia phase, the behavior of the lower extremity depends on the impact locations and angles, and the knee ligament forces become high according to the lower extremity behavior. The force of the collateral ligament is high compared with other knee ligaments, due to knee valgus motions in vehicle-pedestrian collisions.     

Visible light sensitive activated carbon-metal oxide (TiO2, WO3, NiO,and SnO) nano-catalysts for photo-degradation of methylene blue: a comparative study

Four composites of metal oxide doped with activated carbon with a metal oxide weight of 20% were prepared using mechano-mixing method. The nano-catalysts were characterized by N₂-adsorption–desorption, X-ray diffraction analysis, transmission electron microscopy, Fourier-transform infrared spectroscopy, UV-diffuse reflectance, and photoluminescence spectroscopy. Photo-catalytic degradation of methylene blue dye under UV 254 nm and visible light was examined. In general, prepared catalysts are more active for degradation of dye under visible light than UV, reaching 96% within 180?min irradiation using the SnO catalyst. Photo-degradation of methylene blue followed pseudo first order reaction mechanism with a rate constant of 14.8?×?10^?3?min^?1, and the time required for removal of 50% of dye was 47?min.     

EVAPOTRANSPIRATION MEASUREMENT AND ESTIMATION OF THREE WETLAND ENVIRONMENTS IN THE UPPER ST. JOHNS RIVER BASIN,FLORIDA1

ABSTRACT: Accurate estimates of evapotranspiration from areas dominated by wetland vegetation are needed in the water budget of the Upper St. Johns River Basin. However, local data on evapotranspiration rates, especially in wetland environments, were lacking in the project area. In response to this need, the St. Johns River Water Management District collected evapotranspiration field data in Fort Drum Marsh Conservation Area over the period 1996 through 1999. Three large lysimeters were installed to measure the evapotranspiration from different wetland environments: sawgrass (Cladium jamaicense), cattail (Typha domingensis), and open water. In addition, pan evaporation was measured with a standard class “A” pan. Concurrently, meteorological data including rainfall, solar radiation, wind speed, relative humidity, air temperature, and atmospheric pressure were collected. By comparing computed evapotranspiration rates with those measured in the lysimeters, parameters in the Penman‐Monteith, the Priestley‐Taylor, and Reference‐ET methods, and evaporation pan coefficients were estimated for monthly and seasonal cycles. The results from the data collected in this study show that mean monthly evapotranspiration rates, computed by the different methods, are relatively close. From a practical point of view, results indicate that the evaporation pan can be used equally well as the more complex and data‐intensive methods. This paper presents the measured evapotranspiration rates, evaporation pan coefficients, and the estimated parameter values for three different methods to compute evapotranspiration in the project area. Since local data on evaporation are often scarce or lacking, this information may be useful to watershed hydrologists for practical application in other project regions.