Design and validation of a practical index for trauma assessment

In the past 20 years a variety of indices have been suggested for measuring the severity of trauma, however none of them meets the requirement of being a simple and objective instrument that can be utilized efficiently by lay persons and providers of health services without previous experience in triaging. A new system has been proposed which meets this requirement and which has been validated with 197 injured persons at the emergency ward of the Valle University Hospital in Call, Colombia. The instrument showed a high level of concordance with the conventional triaging method and classifies victims into four categories: critical with recovery unlikely, critical but recoverable, moderately serious, and ambulatory. There is discussion on the reliability of this instrument and it is recommended that it be validated with victims from larger disasters. Regardless, it has the advantage of being specific and free of the subjectivity that characterizes other indices.     

Inorganic nitrogen metabolism inUlva rigida illuminated with blue light

Inorganic nitrogen metabolism in blue light was studied for the green algaUlva rigida C. Agardh collected in the south of Spain (Punta Carnero, Algeciras) in the winter of 1987. NH₄ ⁺ has been reported to inhibit NO₃ ^- uptake; however,U. rigida showed a net NO₃ ^- uptake even when the NH₄ ⁺ concentration of the external medium was three or four times greater than the concentration of NO₃ ^-. NO₃ ^- uptake rates were similar in both darkness and in blue light of various photon fluence rates (PFR) ranging from 17 to 160 mol m^-2 s^-1. Since NO₃ ^- uptake is an active mechanism involving the consumption of ATP, respiratory metabolism can provide enough ATP to maintain the energetic requirement of NO₃ ^- transport even in darkness. In contrast, NO₃ ^- reduction inU. rigida was highly dependent on the net photosynthetic rate. After 7 h in blue light, intracellular NO₃ ^- concentrations ([NO₃ ^-] _i ) were higher in specimens exposed to intensities below the light compensation point (LCP) than in those incubated at a PFR above the LCP. When PFR is below the light compensation point, NO₃ ^- reduction is low, probably because all the NADH produced by the cells is oxidized in the respiratory chain in order to produce ATP to maintain a steady NO₃ ^- transport rate. The total nitrogen (TN) and carbon (TC) contents decreased from darkness to 33 mol m^-2 s^-1 in blue light. In this range, catabolic processes prevailed over anabolic ones. In contrast, increases in TN and TC contents were observed above the light compensation point. The C : N ratio increased with light intensity, reaching a stable value of 17 at 78 mol m^-2 s^-1 in blue light. Intracellular NO₃ ^- concentration and NO₃ ^- reduction appear to be directly controlled by light intensity. This external control of [NO₃ ^-]_i and the small capacity ofU. rigida to retain incorporated NO₃ ^-, NO₂ ^- and NH₄ ⁺ ions may explain its nitrophilic character.     

海水入侵指标对比分析与评价—以珠江口地下水含水层为例

合理评价海水入侵对于地下水含水层管理和居民生活健康有着重要的意义。当前海水入侵评价应用较广泛的为包含单一因子和基于统计分析的多种水化学方法。本文综合阐述了海水入侵评价中所用的水化学指标、原理与方法,包括在国内评价体系中少见的一些方法,并以珠江口地下水含水层为例,对比了各种指标的有效性,评价了各类方法的优缺点以及在实际应用中可能产生的问题。结果显示,以Cl-和TDS作为简单直接的单因子可以快速评价海水入侵,尤其对于大范围的海水入侵评价十分有效。而和Ca2+,HCO₃-,SO₄2-等变化有关的指标具有地域性,在研究区对海水入侵的指示并不是十分敏感。在复杂评价因子中,与离子交换有关SAR,BEX以及GQI_SWI与Cl-相关性较高,可以较好的指示海水入侵及水岩相互作用。经过分析,受到地下含水层和地表水道双重介质入侵的影响,研究区海水入侵范围在过去几个年代有向北推进的趋势。本研究对于高速经济发展下的沿海地下水含水层管理和评价有重要的指导意义。     

Optimal range of plug-in electric vehicles in Beijing and Shanghai

Both China’s national subsidy policies for plug-in electric vehicles (PEVs) purchasers and passenger cars corporate average fuel consumption and new vehicle credit regulation (dual-credit policy) favor long-range 300+ km battery electric vehicles (BEVs) and 80+ km plug-in hybrid electric vehicles (PHEVs). However, these electric vehicles tend to have lower energy efficiency and higher purchase and operation costs. Vehicle with larger batteries can also be less equitable because the subsidies are often provided to more expensive vehicles and wealthier owners. This study takes advantage of a novel dataset of daily driving data from 39,854 conventional gasoline vehicles in Beijing and 4999 PHEVs in Shanghai to determine the optimal range of BEVs and PHEVs within their respective cities. We simulate a model to explore ranges with which PEVs emit less GHGs than that of a baseline hybrid and conventional gasoline vehicle while ensuring that all daily travel demands are met. Our findings indicate that in both cities, the optimal ranges to balance cost and travel demand for BEVs are 350 km or less and for PHEVs are 60 km or less in Beijing and 80 km or less in Shanghai. We also find that to minimize carbon dioxide (CO₂) emissions, the ranges are even lower 10 km in Beijing and 30 km in Shanghai. Our study suggests that instead of encouraging long-range PEVs, governments should subsidize PEV models with shorter ranges. Parallel efforts should also be made to both increase renewable energy over fossil fuels and expand charging facilities. Although individual mobility demand varies, the government could reduce occasional long-distance driving by subsidizing alternative transportation choices. Providing week-long driving trials to consumers before their purchases may help decrease the demand of very long range PEVs by alleviating the range anxiety through a learning process.

     

纳米涂层/铝合金在不同pH值的海水溶液中的腐蚀行为研究

目的评价纳米涂层/铝合金在不同pH值海水溶液中的腐蚀行为。方法通过测试纳米涂层/铝合金试样在不同pH值海水溶液中的EIS值,分析试样阻抗谱图及Bode谱图的演化规律,建立不同EIS图谱的不同电极阻抗模型,并采用ZView软件解析涂层体系不同时期的电化学阻抗谱,获得涂层电阻的变化趋势,及不同pH值海水浸泡的纳米涂层体系腐蚀失效速度。结果随着浸泡时间的增加及pH值的降低,纳米涂层/铝合金体系腐蚀损伤失效速率在浸泡前期整体趋势增大,但中后期由于腐蚀产物逐渐堵塞了涂层的微孔,腐蚀介质向铝合金表面渗透的速率逐渐减小。结论 pH为2.0海水浸泡下的3涂层失效最快,其次是pH为4.0海水浸泡下的2涂层,最后为p H为6.0海水浸泡下的1涂层,该涂层体系应采用等效电路模型C进行拟合。     

Application of cryofocusing hydride generation and atomic fluorescence detection for dissolved mercury species determination in natural water samples

The concentration levels of mercury (Hg) species in natural water samples are usually low. Consequently, accurate analysis with low detection limits is still a major problem. In this work, a method was applied for the simultaneous direct determination of dissolved mercury species in water samples by on-line hydride generation (HG), cryogenic trapping (CT), gas chromatography (GC) and detection by atomic fluorescence spectrometry (AFS). The suitability of the method for real samples with different organic matter and chloride contents was evaluated by recovery experiments in synthetic and natural spiked water samples. The HG method was compared with other current available methods for mercury analysis with respect to the different fraction of mercury analysed, i.e. 'reactive', 'reducible' or total. HG derivatization and SnCl2 reduction (with and without previous oxidation with BrCl) were applied to synthetic and natural (spiked and non-spiked) water samples. The influence of chloride and dissolved organic matter concentrations was studied. The results suggest that the HG procedure is suitable for the simultaneous determination of Hg2+ and MeHg+ in surface water samples. Inorganic mercury analysed by HG (i.e. reducible) is close to the total inorganic mercury.     

官厅水库富营养化的评价

综述了官厅水库水系的近期状况 ;在库区选择了 8个具有代表性的断面 ,分析测试了 1 1项水质指标 ,采用 Vol-lenweider的理论评价了库区水质为中 -富营养等级 ;提出了改善水库水系的 4点建议     

Speciation of arsenic using solid phase extraction cartridges

Various solid phase extraction (SPE) cartridges were investigated for speciation of arsenite [As(III)], arsenate [As(v)], monomethylarsonic acid (MMA) and dimethylarsinic acid (DMA). Cartridges containing different types of sorbent materials were tested for arsenic retention and elution characteristics. Alumina cartridges were found to completely retain all the four target arsenic species, and are suitable for removal and preconcentration purposes. For speciation analysis, different arsenic species were separated on the basis of their selective retention on and elution from specific cartridges. DMA was retained on a resin-based strong cation exchange cartridge and eluted with 1.0 M HCl. MMA and As(v) were both retained on a silica-based strong anion exchange cartridge and sequentially eluted with 60 mM acetic acid (for MMA) and 1.0 M HCl [for As(v)]. As(III) was not retained on either cartridge and remained in solution. Arsenic species in solution and those eluted from the cartridges were subsequently quantified by using flow injection with hydride generation atomic fluorescence spectrometry (FI-HGAFS) and hydride generation atomic absorption spectrometry (FI-HGAAS). A detection limit of 0.05 microg L(-1) arsenic in water sample was achieved using HGAFS. An application of the method was demonstrated at a drinking water treatment facility. As(III) and As(v) species were determined in water at various stages of treatment. The method is suitable for routine determination of trace levels of arsenic in drinking water to comply with more stringent environmental regulations.     

Development of an ombrotrophic peat bog (low ash) reference material for the determination of elemental concentrations

Given the increasing interest in using peat bogs as archives of atmospheric metal deposition, the lack of validated sample preparation methods and suitable certified reference materials has hindered not only the quality assurance of the generated analytical data but also the interpretation and comparison of peat core metal profiles from different laboratories in the international community. Reference materials play an important role in the evaluation of the accuracy of analytical results and are essential parts of good laboratory practice. An ombrotrophic peat bog reference material has been developed by 14 laboratories from nine countries in an inter-laboratory comparison between February and October 2002. The material has been characterised for both acid-extractable and total concentrations of a range of elements, including Al, As, Ca, Cd, Cr, Cu, Fe, Hg, Mg, Mn, Na, Ni, P, Pb, Ti, V and Zn. The steps involved in the production of the reference material (i.e. collection and preparation, homogeneity and stability studies, and certification) are described in detail.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.