Human maternal uniparental disomy for chromosome 16 and fetal development

Two severely growth-retarded fetuses found to have maternal uniparental disomy (UPD) for chromosome 16 and trisomy 16 placental mosaicism both had an unfavourable outcome. Antenatally, the first case was complicated by an unexplained raised maternal serum alpha-fetoprotein concentration, preterm premature rupture of the membranes, and growth retardation detectable at 21 weeks' gestation, whilst the other had an unexplained raised maternal serum human chorionic gonadotrophin level, a two-vessel cord on ultrasound, and cessation of growth at 25 weeks. At post-mortem, both babies had an imperforate anus. Fetal maternal UPD may explain the poor outcome that occurs in some cases of confined placental mosaicism for chromosome 16 and is also associated with specific fetal abnormalities.     

煤中痕量元素分布的多变量分析及实验研究

本文用多变量分析法研究了煤中痕量元素的分布，并用实验研究了有机溶剂提取前后青山烟煤中痕量元素的变化。多变量分析结果表明：Ａｓ，Ｃｒ，Ｃｏ，Ｎｉ，Ｃｕ，Ｃｄ，Ｖ，Ｐｂ等元素与Ｂｅ，Ｇｅ在煤中具有不同的分布特征，对青山烟煤的实验研究结果则表明：Ｃｒ，Ｃｏ，Ｎｉ，Ｃｕ，Ｃｄ，Ｐｂ等元素趋向于与煤中的矿物质相结合，而Ｂｅ，Ｇｅ两元素有较强的有机亲和性。实验研究结果与多变量分析结果相符。     

Studies on lethal concentrations and toxicity stress of some xenobiotics on aquatic organisms

Three widely used xenobiotics pentachlorophenol (PCP), 2,4-dichlorophenoxyacetic acid (2,4-D) and 2-chloro-2,6-diethyl-N-(butoxymethyl) acetanilide (Butachlor) are evaluated for acute toxicity and stress behavior on freshwater fish (Heteropneustes fossilis, Clarias batrachus, Channa punctatus) and mosquito larvae (Culex pipiens fatigans). The experiment was carried out by medium treatment using intermittent flow-through system. Median lethal concentrations (LC50) were calculated by probit analysis. The LC50 values and 95% confidence intervals showed variable range for tested chemicals. Mosquito larvae generally appeared resistant than fish, while H. fossilis was found to be most sensitive. Stress signs in the form of behavioral changes are also observed. Both types of organisms are recommended as good bioindicator for the risk assessment of aquatic environment due to chemicals tested.     

Comparing estimates of fugitive landfill methane emissions using inverse plume modeling obtained with Surface Emission Monitoring (SEM), Drone Emission Monitoring (DEM), and Downwind Plume Emission Monitoring (DWPEM)

ABSTRACT

As part of the global effort to quantify and manage anthropogenic greenhouse gas emissions, there is considerable interest in quantifying methane emissions in municipal solid waste landfills. A variety of analytical and experimental methods are currently in use for this task. In this paper, an optimization-based estimation method is employed to assess fugitive landfill methane emissions. The method combines inverse plume modeling with ambient air methane concentration measurements. Three different measurement approaches are tested and compared. The method is combined with surface emission monitoring (SEM), above ground drone emission monitoring (DEM), and downwind plume emission monitoring (DWPEM). The methodology is first trialed and validated using synthetic datasets in a hand-generated case study. A field study is also presented where SEM, DEM and DWPEM are tested and compared. Methane flux during two-days measurement campaign was estimated to be between 228 and 350 g/s depending on the type of measurements used. Compared to SEM, using unmanned aerial systems (UAS) allows for a rapid and comprehensive coverage of the site. However, as showed through this work, advancement of DEM-based methane sampling is governed by the advances that could be made in UAS-compatible measurement instrumentations. Downwind plume emission monitoring led to a smaller estimated flux compared with SEM and DEM without information about positions of major leak points in the landfill. Even though, the method is simple and rapid for landfill methane screening. Finally, the optimization-based methodology originally developed for SEM, shows promising results when it is combined with the drone-based collected data and downwind concentration measurements. The studied cases also discovered the limitations of the studied sampling strategies which is exploited to identify improvement strategies and recommendations for a more efficient assessment of fugitive landfill methane emissions.

Implications: Fugitive landfill methane emission estimation is tackled in the present study. An optimization-based method combined with inverse plume modeling is employed to treat data from surface emission monitoring, drone-based emission monitoring and downwind plume emission monitoring. The study helped revealing the advantages and the limitations of the studied sampling strategies. Recommendations for an efficient assessment of landfill methane emissions are formulated. The method trialed in this study for fugitive landfill methane emission could also be appropriate for rapid screening of analogous greenhouse gas emission hotspots.     

Greenhouse gas emission from small clinics solid waste management scenarios in an urban area of an underdeveloping country: A life cycle perspective

This study aimed to investigate the effects on the environment of small clinics solid waste management by applying a life cycle analysis approach. Samples were collected from 371 private clinics situated in densely populated areas of Hyderabad, Pakistan. The solid waste from surveyed clinics was categorically quantified on daily basis for 30 consecutive days. The functional unit for waste was defined as 1 tonne. System limitations were defined as landfilling, incineration, composting, material recovery, and transportation of solid waste. The treatment and disposal methods were assessed according to their greenhouse gas emission rate. For the evaluation, three different scenarios were designed. The second scenario resulted in the highest emission value of 1491.78 kg CO₂ eq/tonne of solid waste due to mixed waste incineration, whereas the first scenario could not offer any saving because of uncovered landfilling and 67.5% higher transport fuel consumption than the proposed network. The proposed third scenario was found to be a better solution for urban clinics solid waste management, as it resulted in savings of 951.38 kg CO₂ eq/tonne of solid waste. This integrated design is practicable by resource-constrained economy. This system consists of composting, material recovery, and incineration of hazardous waste. The proposed system also includes a feasible transportation method for urban area collection networks. The findings of the present study can play a vital role in documenting evidence and for policymakers to plan the solid waste management of clinics, as previously no studies have been conducted on this particular case.

Implications: This study aims to highlight the impact of small clinics solid waste management scenarios on the environment in a developing country’s urban area. Life cycle analysis is used for comparison of greenhouse gase emission from different scenarios, including the purposed integrated method. Small clinics play a very important role in health care, and their waste management is a very serious issue; however, there are no previous studies on this particular case to the best knowledge of the authors. This study can be considered as forerunner effort to quantify the environmental footprint of small clinics solid waste in urban areas of a developing country.     

The effects of drug and alcohol consumption on driver injury severities in single-vehicle crashes

Objective: It is well known that alcohol and drugs influence driving behavior by affecting the central nervous system, awareness, vision, and perception/reaction times, but the resulting effect on driver injuries in car crashes is not fully understood. The purpose of this study was to identify factors affecting the injury severities of unimpaired, alcohol-impaired, and drug-impaired drivers.

Method: The current article applies a random parameters logit model to study the differences in injury severities among unimpaired, alcohol-impaired, and drug-impaired drivers. Using data from single-vehicle crashes in Cook County, Illinois, over a 9-year period from January 1, 2004, to December 31, 2012, separate models for unimpaired, alcohol-impaired, and drug-impaired drivers were estimated. A wide range of variables potentially affecting driver injury severity was considered, including roadway and environmental conditions, driver attributes, time and location of the crash, and crash-specific factors.

Results: The estimation results show significant differences in the determinants of driver injury severities across groups of unimpaired, alcohol-impaired, and drug-impaired drivers. The findings also show that unimpaired drivers are understandably more responsive to variations in lighting, adverse weather, and road conditions, but these drivers also tend to have much more heterogeneity in their behavioral responses to these conditions, relative to impaired drivers. In addition, age and gender were found to be important determinants of injury severity, but the effects varied significantly across all drivers, particularly among alcohol-impaired drivers.

Conclusions: The model estimation results show that statistically significant differences exist in driver injury severities among the unimpaired, alcohol-impaired, and drug-impaired driver groups considered. Specifically, we find that unimpaired drivers tend to have more heterogeneity in their injury outcomes in the presence potentially adverse weather and road surface conditions. This makes sense because one would expect unimpaired drivers to apply their full knowledge/judgment range to deal with these conditions, and the variability of this range across the driver population (with different driving experiences, etc.) should be great. In contrast, we find, for the most part, that alcohol-impaired and drug-impaired drivers have far less heterogeneity in the factors that affect injury severity, suggesting an equalizing effect resulting from the decision-impairing substance.     

Groundwaters at Risk: Wetland Loss Changes Sources,Lengthens Pathways,and Decelerates Rejuvenation of Groundwater Resources

Wetland loss alters the hydrology of wetlandscapes in poorly understood ways. To quantify the effects of wetland loss on subsurface hydrology, a physically based hydrologic model that simulates the timing and pathways of subsurface hydrologic connections was coupled with wetland inventories over a 50‐year period during which substantial wetland loss occurred. The model revealed, based on vertical variations in saturated hydraulic conductivities, wetland loss of different degrees led to a contraction of catchment contributing areas to local surface waters but an expansion of contributing areas to the regional surface water body. This shift in groundwater contributing areas reflected (1) a decrease in baseflow contribution to the local surface water bodies, and (2) an increase in the transit time and length of subsurface hydrologic connections with an associated increase in the magnitude and age of baseflow discharging to the regional surface water body. The model also showed regions with thick permeable aquifers were particularly sensitive to the loss of wetlands. Our ability to predict these changes in hydrology of the watershed provides important support for designing science‐based policies to promote sustainable water resource management.     

A novel framework-based cuckoo search algorithm for sizing and optimization of grid-independent hybrid renewable energy systems

Hybrid renewable energy systems (HRES) turned into an appealing choice for supplying loads in remote areas. The application of smart grid principals in HRES provides a communication between the load and generation from the HRES. Using smart grid in the HRES will optimally utilize the generating resources to reschedule the loads depending on its importance. This paper presents a new proposed design and optimization simulation program for techno-economic sizing of grid-independent hybrid PV/wind/diesel/battery energy system using Cuckoo search (CS) optimization algorithm. Using of CS will help to get the global minimum cost condition and prevent the simulation to be stuck around local minimum. A new proposed simulation program (NPSP) is acquainted using CS to determine the optimum size of each component of the HRES for the lowest cost of generated energy and the lowest value of dummy energy, at highest reliability. A detailed economic methodology to obtain the price of the generated energy has been introduced. Results showed that using CS reduced the time required to obtain the optimal size with higher accuracy than other techniques used iterative techniques, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). Numerous significant outcomes can be extracted from the proposed program that could help scientists and decision makers.