日粮中铜胁迫对吉富罗非鱼幼鱼抗氧化、脂质过氧化及肝脏组织结构的影响

吉富罗非鱼是我国南方沿海地区水产养殖中的主要经济鱼类之一,但近年来,随着我国城镇化和工业化进程的推进,罗非鱼养殖面临着前所未有的铜富集的挑战。为探明日粮中铜胁迫对吉富罗非鱼幼鱼抗氧化系统和肝脏组织结构的影响,将1 080条罗非鱼幼鱼暴露于6个浓度梯度(0、3、30、300、1 000、3 000 mg·kg-1)的高铜日粮中,通过60 d的暴露试验,实时测定罗非鱼血清与肝脏抗氧化能力,监测肝脏病理变化。结果表明,在本试验条件下,罗非鱼幼鱼血清和肝脏中MDA的含量随日粮中铜含量的增加和胁迫时间的延长显著升高,而SOD、GSH-PX和Cu Zn-SOD的活性表现出先升高后降低的趋势;各组间肝脏表现出不同程度的病变,主要是浊肿变性和脂肪变性,且第Ⅲ、Ⅳ、Ⅴ组肝脏病变严重。综上,日粮中铜胁迫对吉富罗非鱼幼鱼的抗氧化机能有较明显的抑制作用,长时间的暴露能严重损伤其肝脏的组织结构,因此,建议吉富罗非鱼幼鱼日粮中铜的实际含量应控制在42.36 mg·kg-1以下。     

胎盘内多环芳烃分布及源解析研究

探讨多环芳烃在胎盘中的分布,并对其进行源解析。从2012年6月—2013年6月在云南省第一人民医院产科分娩的产妇中随机抽取30例,利用气相色谱-质谱联用仪(GC-MS)检测其胎盘中多环芳烃的含量;比较胎盘的中央部分和边缘部分多环芳烃含量的差异;对多环芳烃进行源解析,探讨其主要来源。胎盘中检测到多种多环芳烃成分;其中2~4个苯环的多环芳烃占总量的90%以上,尤其是萘、苊、芴、菲、蒽、芘、荧蒽的含量较高;萘、苊烯、苊、茚并(1,2,3-c,d)芘、二苯并(a,h)蒽5种多环芳烃在胎盘中央的含量高于边缘,具有显著性差异(P0.05),其他多环芳烃在胎盘中央和边缘的含量无显著性差异(P0.05)。多环芳烃源解析提示80%研究对象体内的多环芳烃主要来自石油产品的燃烧或暴露于石油产品。     

江苏陆地海岸线绿潮藻种类组成及分布特征

2012年12月—2013年5月对江苏启东蒿枝港至连云港西大堤长约730 km岸线内的69个岸滩堤坝站点进行了绿潮藻种类组成及数量分布调查.结果表明:绿潮藻出现的站点占总设置站点的26.09%,出现绿潮藻岸线长度约占整个江苏调查岸线长度的22.83%;岸滩上绿潮藻主要生长在沿岸石堤、养殖围坝和植被较浅相对稀疏的草滩上,绿潮藻种类组成主要有浒苔(Ulva prolifera)、曲浒苔(Ulva flexuosa)和缘管浒苔(Ulva linza).1—3月浒苔为主要优势种,4—5月曲浒苔为主要优势种,缘管浒苔在历次调查中其湿重生物量均很低.5月岸滩上固着绿潮藻量约36.7 t,不及海上飘来附着在岸滩上绿潮藻量的1/10,岸滩上固着绿潮藻中浒苔的量约为同期海上飘来浒苔湿重生物量的0.6%,岸滩堤坝不会是引起绿潮暴发的主要源头.     

Low-carbon transition of iron and steel industry in China: Carbon intensity, economic growth and policy intervention

As the biggest iron and steel producer in the world and one of the highest CO₂ emission sectors, China's iron and steel industry is undergoing a low-carbon transition accompanied by remarkable technological progress and investment adjustment, in response to the macroeconomic climate and policy intervention. Many drivers of the CO₂ emissions of the iron and steel industry have been explored, but the relationships between CO₂ abatement, investment and technological expenditure, and their connections with the economic growth and governmental policies in China, have not been conjointly and empirically examined. We proposed a concise conceptual model and an econometric model to investigate this crucial question. The results of regression, Granger causality test and impulse response analysis indicated that technological expenditure can significantly reduce CO₂ emissions, and that investment expansion showed a negative impact on CO₂ emission reduction. It was also argued with empirical evidence that a good economic situation favored CO₂ abatement in China's iron and steel industry, while achieving CO₂ emission reduction in this industrial sector did not necessarily threaten economic growth. This shed light on the dispute over balancing emission cutting and economic growth. Regarding the policy aspects, the year 2000 was found to be an important turning point for policy evolution and the development of the iron and steel industry in China. The subsequent command and control policies had a significant, positive effect on CO₂ abatement.     

A time‐lagged investigation of the impact of coworker behavior on the effects of demographic dissimilarity

Although it is clear that coworker absenteeism, tardiness, and turnover can influence an employee's actions, scholars have yet to consider the impact of relational demography on the adoption of these behavioral norms. Inspired by social identity, situational strength, and attraction‐selection‐attrition theories, we proposed that individuals who differ from their coworkers in age, sex, or racioethnicity would feel threatened by their outnumbered status and subsequently motivated to be absent, tardy, or more likely to turnover. However, we expected coworker withdrawal behavior to moderate whether or not dissimilar personnel act on these desires. Results from hierarchical multilevel modeling analyses of data from 470 U.S. call center workers nested in 51 work groups revealed that racioethnic dissimilarity was positively related to time‐lagged changes in absenteeism and tardiness as well as heightened turnover likelihood. These effects emerged only among employees whose coworkers engaged in greater withdrawal behavior. Importantly, racioethnically dissimilar employees working in more permissive climates (i.e., those with high levels of coworker absenteeism, tardiness, or turnover) exhibited the greatest increases in absenteeism and tardiness over three months and had the highest supervisor‐rated turnover likelihood. Implications for diversity management are discussed. Copyright © 2015 John Wiley & Sons, Ltd.     

Estimated Injury Risk for Specific Injuries and Body Regions in Frontal Motor Vehicle Crashes

Objective: Injury risk curves estimate motor vehicle crash (MVC) occupant injury risk from vehicle, crash, and/or occupant factors. Many vehicles are equipped with event data recorders (EDRs) that collect data including the crash speed and restraint status during a MVC. This study's goal was to use regulation-required data elements for EDRs to compute occupant injury risk for (1) specific injuries and (2) specific body regions in frontal MVCs from weighted NASS-CDS data.

Methods: Logistic regression analysis of NASS-CDS single-impact frontal MVCs involving front seat occupants with frontal airbag deployment was used to produce 23 risk curves for specific injuries and 17 risk curves for Abbreviated Injury Scale (AIS) 2+ to 5+ body region injuries. Risk curves were produced for the following body regions: head and thorax (AIS 2+, 3+, 4+, 5+), face (AIS 2+), abdomen, spine, upper extremity, and lower extremity (AIS 2+, 3+). Injury risk with 95% confidence intervals was estimated for 15–105 km/h longitudinal delta-Vs and belt status was adjusted for as a covariate.

Results: Overall, belted occupants had lower estimated risks compared to unbelted occupants and the risk of injury increased as longitudinal delta-V increased. Belt status was a significant predictor for 13 specific injuries and all body region injuries with the exception of AIS 2+ and 3+ spine injuries. Specific injuries and body region injuries that occurred more frequently in NASS-CDS also tended to carry higher risks when evaluated at a 56 km/h longitudinal delta-V. In the belted population, injury risks that ranked in the top 33% included 4 upper extremity fractures (ulna, radius, clavicle, carpus/metacarpus), 2 lower extremity fractures (fibula, metatarsal/tarsal), and a knee sprain (2.4–4.6% risk). Unbelted injury risks ranked in the top 33% included 4 lower extremity fractures (femur, fibula, metatarsal/tarsal, patella), 2 head injuries with less than one hour or unspecified prior unconsciousness, and a lung contusion (4.6–9.9% risk). The 6 body region curves with the highest risks were for AIS 2+ lower extremity, upper extremity, thorax, and head injury and AIS 3+ lower extremity and thorax injury (15.9–43.8% risk).

Conclusions: These injury risk curves can be implemented into advanced automatic crash notification (AACN) algorithms that utilize vehicle EDR measurements to predict occupant injury immediately following a MVC. Through integration with AACN, these injury risk curves can provide emergency medical services (EMS) and other patient care providers with information on suspected occupant injuries to improve injury detection and patient triage.