The cumulative effects of dam project on river ecosystem based on multi-scale ecological network analysis

AbstractThe importance of addressing cumulative environmental impact of large development projects on rivers has been increasingly highlighted. Consideration to potential impact pathways may be difficult, however, without appropriate analytical methods. By introducing ecological network model, this paper focuses on the quantification of the cause-effect relationships inherent the cumulative effects of dam construction from a holistic perspective. With Lancang river of Longitudinal Range-Gorge Region (LRGR) as an example, the risk-based interaction instead of the conventional energy or material flow of ecological network model has been created to conceptualize the cumulative effects network model. Based on this model, the network structural and functional analysis were adjusted for the assessment of potential eco-environmental impact within the ecosystem, thus demonstrating how the risk-based ecological network analysis can be used to characterize the holistic cumulative effects of dams on the temporal and spatial scale

A Predictive Analysis of China's Energy Security Based on Supply Chain Theory

AbstractChina's energy dependence on energy supply chain have been increasing rapidly in recent years. The long-term energy supply plays an important role to guarantee the energy security. Therefore, our emphasis placed on energy supply chain predictive analysis and security evaluation in China. In this study, a linked MARKAL-CGE-EIA model system is proposed to simulate the macro-level energy technology, macro-level economy and environmental impacts of China. The CGE module is used to produce a multi-sector simulation of economic growth and industrial structure change. A MARKAL module is used to analyze particular technologies within the energy system, given estimates of associated energy demand and the relative prices of fuel and other inputs. A third module of Environmental Impact is applied to make an analysis of pollutant emissions. The energy indicators are used to perform an assessment of the dynamic behavior and security trends of a national energy system's trajectory from 2000 to 2050. The results of our study will enable energy policy planners to understand these inter-linkages by addressing energy early-warming indicators and scenarios to the aggregate industrial sectors, the energy technology details, and environmental impacts

Dynamic Carbon Emission Linkages Across Boundaries

Cities are increasingly linked to domestic and foreign markets during rapid globalization of trade. While transboundary carbon footprints of cities have been recently highlighted, we still have limited understanding of how carbon emission linkages between sectors are reshaping urban carbon footprints through time. In this study, we propose an integrated input-output approach to trace the dynamics of various types of carbon emission linkages associated with a city. This approach quantifies full linkages in the urban carbon system from both production- and consumption-based perspectives. We assess the dynamic roles that economic sectors and activities play in manipulating multiscale linkages induced by local, domestic, and international inputs. Using Beijing as a case study, we find that imports from domestic and foreign markets have an increasing impact on the city's carbon footprint with more distant linkages during the period from 1990 to 2012. The manufacturing-related carbon emission linkages have been increasingly transferred outside the urban boundary since 2005, while the linkages from the energy sector to services sectors remain important in Beijing's local economy. Applying systems thinking to input-output linkage analysis provides important details on when and how carbon emission linkages evolved in cities, whereby sector-oriented and activity-oriented carbon mitigation policies can be formulated

Emergency Online Learning in Low-Resource Settings: Effective Student Engagement Strategies

We aim to identify the engagement strategies that higher education students, engaging in emergency online learning in low-resource settings, perceive to be effective. We conducted a sequential mixed-methods study based on Moore’s interaction framework for distance education. We administered a questionnaire to 313 students engaging in emergency online learning in low-resource settings to examine their perceptions of different engagement strategies. Our results showed that student–content engagement strategies, e.g., screen sharing, summaries, and class recordings, are perceived as the most effective, closely followed by student–teacher strategies, e.g., Q and A sessions and reminders. Student–student strategies, e.g., group chat and collaborative work, are perceived as the least effective. The perceived effectiveness of engagement strategies varies based on the students’ gender and technology access. To support instructors, instructional designers, and researchers, we propose a 10-level guide for engaging students during emergency online classes in low-resource settings

The Harder You Work, the Higher Your Satisfaction With Life? The Influence of Police Work Engagement on Life Satisfaction: A Moderated Mediation Model

Background: Life satisfaction is a key component of quality of life; it is associated with many factors, including occupational and family life. The results of existing studies examining associations among work engagement, work-family conflict, and life satisfaction have been inconsistent.Objective: We explored the mechanism of action of police work engagement on life satisfaction, and analyzed the relationships among work engagement, work-family conflict, psychological detachment, and police life satisfaction from the angle of family and work relationships.Methods: A total of 760 police officers completed the Utrecht Work Engagement Scale, Satisfaction with Life Scale, Work-Family Conflict Scale, and Psychological Detachment Scale; 714 questionnaires were valid.Results: Work engagement both directly affected police life satisfaction (β = 0.58, p < 0.001), and indirectly influenced police life satisfaction through work-family conflict (β = -0.07, p < 0.05). Different levels of psychological detachment moderated both the relationship between work engagement and work-family conflict (β = 0.17, p < 0.001), and the relationship between work-family conflict and life satisfaction (β = 0.07, p < 0.05).Conclusion: A moderated mediation model was established. Work-family conflict partially mediates the relationship between work engagement and police life satisfaction. Psychological detachment moderates the first and second half of the mediating process by which work engagement affects police life satisfaction through work-family conflict

Obesity Challenge Drives Distinct Maternal Immune Response Changes in Normal Pregnant and Abortion-Prone Mouse Models

Obesity is prevalent among women of reproductive age and is associated with increased risk of developing multiple pregnancy disorders. Pregnancy must induce immune tolerance to avoid fetal rejection, while obesity can cause chronic inflammation through activating the immune system. Impaired maternal immuno-tolerance leads to pregnancy failure, such as recurrent spontaneous abortion (RSA), one of the most common complications during early pregnancy. How does maternal immune response change under obesity stress in normal pregnancy and RSA? In turn, is obesity affected by different gestational statuses? Limited information is presently available now. Our study investigated pregnancy outcomes and maternal immune responses in two murine models (normal pregnancy and spontaneous abortion models) after obesity challenge with a high-fat diet (HFD). Abortion-prone mice fed HFD had significantly higher weight gains during pregnancy than normal pregnant mice with HFD feeding. Nonetheless, the embryo implantation and resorption rates were comparable between HFD and normal chow diet (NCD)-fed mice in each model. Evaluation of immune cell subsets showed HFD-induced obesity drove the upregulation of activated NK cell-activating receptor (NKp46)+ NK cells and pro-inflammatory macrophages (MHCIIhigh Mφ) as well as CD4+ and CD8+ T cells in the normal pregnancy group. However, in the abortion-prone group, relative more immature NK cells with decreased activity phenotypes were found in obese mice. Moreover, there were increased DCreg (CD11bhigh DC) cells and decreased CD4+ and CD8+ T cells detected in the HFD abortion-prone mice relative to those fed the NCD diet. Our findings reveal how pregnancy obesity and maternal immune regulation are mutually influenced. It is worth noting that the abortion-prone model where active maternal immune status was intensified by obesity, in turn stimulated an overcompensation response, leading to an over-tolerized immune status, and predisposing to potential risks of perinatal complications

Broadly conserved roles of TMEM131 family proteins in intracellular collagen assembly and secretory cargo trafficking.

Collagen is the most abundant protein in animals. Its dysregulation contributes to aging and many human disorders, including pathological tissue fibrosis in major organs. How premature collagen proteins in the endoplasmic reticulum (ER) assemble and route for secretion remains molecularly undefined. From an RNA interference screen, we identified an uncharacterized Caenorhabditis elegans gene tmem-131, deficiency of which impairs collagen production and activates ER stress response. We find that amino termini of human TMEM131 contain bacterial PapD chaperone-like domains, which recruit premature collagen monomers for proper assembly and secretion. Carboxy termini of TMEM131 interact with TRAPPC8, a component of the TRAPP tethering complex, to drive collagen cargo trafficking from ER to the Golgi. We provide evidence that previously undescribed roles of TMEM131 in collagen recruitment and secretion are evolutionarily conserved in C. elegans, Drosophila, and humans

The cientificWorldJOURNAL Research Article Greenhouse Gas Emission Accounting and Management of Low-Carbon Community

As the major source of greenhouse gas (GHG) emission, cities have been under tremendous pressure of energy conservation and emission reduction for decades. Community is the main unit of urban housing, public facilities, transportation, and other properties of city's land use. The construction of low-carbon community is an important pathway to realize carbon emission mitigation in the context of rapid urbanization. Therefore, an efficient carbon accounting framework should be proposed for CO 2 emissions mitigation at a subcity level. Based on life-cycle analysis (LCA), a three-tier accounting framework for the carbon emissions of the community is put forward, including emissions from direct fossil fuel combustion, purchased energy (electricity, heat, and water), and supply chain emissions embodied in the consumption of goods. By compiling a detailed CO 2 emission inventory, the magnitude of carbon emissions and the mitigation potential in a typical high-quality community in Beijing are quantified within the accounting framework proposed. Results show that emissions from supply chain emissions embodied in the consumption of goods cannot be ignored. Specific suggestions are also provided for the urban decision makers to achieve the optimal resource allocation and further promotion of low-carbon communities

Maternal ambient air pollution exposure with spatial-temporal variations and preterm birth risk assessment during 2013-2017 in Zhejiang Province, China.

Preterm birth (PTB) can give rise to significant neonatal morbidity and mortality, as well as children's long-term health defects. Many studies have illustrated the associations between ambient air pollution exposure during gestational periods and PTB risks, but most of them only focused on one single air pollutant, such as PM2.5. In this population-based environmental-epidemiology study, we recruited 6275 pregnant mothers in Zhejiang Province, China, and evaluated their gestational exposures to various air pollutants during 2013-2017. Time-to-event logistic regressions were performed to estimate risk associations after adjusting all confounders, and Quasi-AQI model and PCA-GLM analysis were applied to resolve the collinearity issues in multi-pollutant regression models. It was found that gestational exposure to ambient air pollutants was significantly associated with the occurrence of PTB, and SO2 was the largest contributor with a proportion of 29.4%. Three new variables, prime factor (a combination of PM2.5, PM10, SO2, and NO2), carbon factor (CO), and ozone factor (O3), were generated by PCA integration, contributing 63.4%, 17.1%, and 19.5% to PTB risks, respectively. The first and third trimester was the most crucial exposure window, suggesting the pregnant mothers better to avoid severe air pollution exposures during these sensitive periods

An environment-driven hybrid evolutionary algorithm for dynamic multi-objective optimization problems

open access articleIn dynamic multi-objective optimization problems, the environmental parameters may change over time, which makes the Pareto fronts shifting. To address the issue, a common idea is to track the moving Pareto front once an environmental change occurs. However, it might be hard to obtain the Pareto optimal solutions if the environment changes rapidly. Moreover, it may be costly to implement a new solution. By contrast, robust Pareto optimization over time provides a novel framework to find the robust solutions whose performance is acceptable for more than one environment, which not only saves the computational costs for tracking solutions, but also minimizes the cost for switching solutions. However, neither of the above two approaches can balance between the quality of the obtained non-dominated solutions and the computation cost. To address this issue, environment-driven hybrid dynamic multi-objective evolutionary optimization method is proposed, aiming to fully use strengths of TMO and RPOOT under various characteristics of environmental changes. Two indexes, i.e., the frequency and intensity of environmental changes, are first defined. Then, a criterion is presented based on the characteristics of dynamic environments and the switching cost of solutions, to select an appropriate optimization method in a given environment. The experimental results on a set of dynamic benchmark functions indicate that the proposed hybrid dynamic multi-objective evolutionary optimization method can choose the most rational method that meets the requirements of decision makers, and balance the convergence and robustness of the obtained non-dominated solutions