MODELING THE DISTRIBUTION OF DIFFUSE NITROGEN SOURCES AND SINKS IN THE NEUSE RIVER BASIN OF NORTH CAROLINA,USA1

This study quantified nonpoint source nitrogen (NPS‐N) sources and sinks across the 14,582 km² Neuse River Basin (NRB) located in North Carolina, to provide tabular data summaries and graphic overlay products to support the development of management approaches to best achieve established N reduction goals. First, a remote sensor derived, land cover classification was performed to support modeling needs. Modeling efforts included the development of a mass balance model to quantify potential N sources and sinks, followed by a precipitation event driven hydrologic model to effectively transport excess N across the landscape to individual stream reaches to support subsequent labeling of transported N values corresponding to source origin. Results indicated that agricultural land contributed 55 percent of the total annual NPS‐N loadings, followed by forested land at 23 percent (background), and urban areas at 21 percent. Average annual N source contributions were quantified for agricultural (1.4 kg/ha), urban (1.2 kg/ha), and forested cover types (0.5 kg/ha). Nonpoint source‐N contributions were greatest during the winter (40 percent), followed by spring (32 percent), summer (28 percent), and fall (0.3 percent). Seasonal total N loadings shifted from urban dominated and forest dominated sources during the winter, to agricultural sources in the spring and summer. A quantitative assessment of the significant NRB land use activities indicated that high (greater than 70 percent impervious) and medium (greater than 35 percent impervious) density urban development were the greatest contributors of NPS‐N on a unit area basis (1.9 and 1.6 kg/ha/yr, respectively), followed by row crops and pasture/hay cover types (1.4 kg/ha/yr).     

Food justice youth development: using Photovoice to study urban school food systems*

How do youth learn through participation in efforts to study and change the school food system? Through our participatory youth action research (YPAR) project, we move beyond the “youth as consumer” frame to a food justice youth development (FJYD) approach. We track how a group of youth learned about food and the public policy process through their efforts to transform their own school food systems by conducting a participatory evaluation of farm-to-school efforts in collaboration with university and community partners. We used the Photovoice research method, placing cameras in the hands of young people so that they themselves could document and discuss their concerns and perspectives. The research was designed to gain insight about youths’ knowledge of food, health, and community food systems. Drawing upon the youth group’s insights, we build a framework for building critical consciousness through FJYD.     

Developing an interdisciplinary and cross‐sectoral community of practice in the domain of forests and livelihoods

Although significant resources are being spent researching and fostering the relationship between forests and livelihoods to promote mutually beneficial outcomes, critical gaps in understanding persist. A core reason for such gaps is that researchers, practitioners, and policy makers lack the structured space to interact and collaborate, which is essential for effective, interdisciplinary research, practice, and evaluation. Thus, scientific findings, policy recommendations, and measured outcomes have not always been synthesized into deep, systemic understanding; learning from practice and implementation does not easily find its way into scientific analyses, and science often fails to influence policy. Communities of practice (CofPs) are dynamic sociocultural systems that bring people together to share and create knowledge around a common topic of interest. They offer participants a space and structure within which to develop new, systemic approaches to multidimensional problems on a common theme. Uniquely informed by a systems‐thinking perspective and drawing from the scientific and gray literatures and in‐depth interviews with representatives of established CofPs in the natural resource management and development domain, we argue that a well‐designed and adequately funded CofP can facilitate interdisciplinary and cross‐sectoral relationships and knowledge exchange. Well‐designed CofPs integrate a set of core features and processes to enhance individual, collective, and domain outcomes; they set out an initial but evolving purpose, encourage diverse leadership, and promote collective‐identity development. Funding facilitates effective communication strategies (e.g., in person meetings). We urge our colleagues across sectors and disciplines to take advantage of CofPs to advance the domain of forests and livelihoods.     

基于GM-SVR的小样本条件下化工设备可靠性预测

为了准确预测化工设备可靠性趋势，针对化工设备失效寿命数据为小样本的情形，基于灰色估计法与支持向量回归机在小样本数据处理中的优势，建立了失效寿命时间服从三参数威布尔分布的化工设备可靠性模型；结合GM（1，1）和SVR对模型进行参数估计，在压缩机可靠性分析中进行了实例应用，对比分析了最小二乘法、灰色估计法和GM-SVR的估计效果。研究结果表明:GM-SVR对威布尔分布参数的估计精度明显优于最小二乘法和灰色估计法，可以有效地应用于化工设备失效数据为小样本时的可靠性预测。     

State of research on the automation of HAZOP studies

For more than 30 years, multiple research groups have worked on the automation of hazard and operability (HAZOP) studies, or more specifically on the hazard identification process. So far, very few of these approaches have been used in the chemical process industry. Automatic hazard identification is a knowledge-intensive process that demands high standards with regard to the way in which knowledge is stored and made available. There are various suitable approaches to the qualitative modeling of processes and plants, which are the foundation for reasoning systems that are used for the identification of hazards. Additionally, there are quantitative methods that are based on process simulations and can be used to identify potential hazards. The investigation of the state of research demonstrates that there are sophisticated technologies for automated systems that include powerful reasoning techniques. The benefits and shortcomings of existing technologies are discussed with regard to their industrial applicability. Often, the quality of the necessary specific and generic knowledge is not sufficient to detect potential hazardous events and operational malfunctions. Computer-aided HAZOP systems should be integrated with computer-aided design- or process simulation software using common data models based on the digital representation of the process plant. In order to be used by HAZOP practitioners automated systems need to be comprehensive, serve as specialized decision support systems, and be tested and evaluated using round robin tests.     

Plant blindness and the implications for plant conservation

Plant conservation initiatives lag behind and receive considerably less funding than animal conservation projects. We explored a potential reason for this bias: a tendency among humans to neither notice nor value plants in the environment. Experimental research and surveys have demonstrated higher preference for, superior recall of, and better visual detection of animals compared with plants. This bias has been attributed to perceptual factors such as lack of motion by plants and the tendency of plants to visually blend together but also to cultural factors such as a greater focus on animals in formal biological education. In contrast, ethnographic research reveals that many social groups have strong bonds with plants, including nonhierarchical kinship relationships. We argue that plant blindness is common, but not inevitable. If immersed in a plant‐affiliated culture, the individual will experience language and practices that enhance capacity to detect, recall, and value plants, something less likely to occur in zoocentric societies. Therefore, conservation programs can contribute to reducing this bias. We considered strategies that might reduce this bias and encourage plant conservation behavior. Psychological research demonstrates that people are more likely to support conservation of species that have human‐like characteristics and that support for conservation can be increased by encouraging people to practice empathy and anthropomorphism of nonhuman species. We argue that support for plant conservation may be garnered through strategies that promote identification and empathy with plants.     

Solar energy for electricity and fuels

Solar energy conversion into electricity by photovoltaic modules is now a mature technology. We discuss the need for materials and device developments using conventional silicon and other materials, pointing to the need to use scalable materials and to reduce the energy payback time. Storage of solar energy can be achieved using the energy of light to produce a fuel. We discuss how this can be achieved in a direct process mimicking the photosynthetic processes, using synthetic organic, inorganic, or hybrid materials for light collection and catalysis. We also briefly discuss challenges and needs for large-scale implementation of direct solar fuel technologies.     

Fuzzy experts on recreational vessels, a risk modelling approach for marine invasions

Understanding risks from the human-mediated spread of non-indigenous species (NIS) is a critical component of marine biosecurity management programmes. Recreational boating is well-recognised as a NIS pathway, especially at a regional scale. Assessment of risks from this pathway is therefore desirable for coastal environments where recreational boating occurs. However, formal or quantitative risk assessment for the recreational vessel pathway is often hampered by lack of data, hence often relies on expert opinion. The use of expert opinion itself is sometimes limited by its inherent vagueness, which can be an important source of uncertainty that reduces the validity and applicability of the assessment. Fuzzy logic, specifically interval type-2 fuzzy logic, is able to model and propagate this type of uncertainty, and is a useful technique in risk assessment where expert opinion is relied upon. The present paper describes the implementation of a NIS fuzzy expert system (FES) for assessing the risk of invasion in marine environments via recreational vessels. The FES was based on expert opinion gathered through systematic elicitation exercises, designed to acknowledge important uncertainty sources (e.g., underspecificity and ambiguity). The FES, using interval type-2 fuzzy logic, calculated an invasion risk value (integrating NIS infection and detection probabilities) for a range of invasion scenarios. These scenarios were defined by all possible combinations of two vessel types (moored and trailered), five vessel components (hull, deck, internal spaces, anchor, fishing gear), two infection modes (fouling, water/sediment retention) and six frequently visited marine habitats (marina, mooring, farm, ramp, wharf, anchorage). Although invasion risk values determined using the FES approach was scenario-specific, general patterns were identified. Moored vessels consistently showed higher invasion risk values than trailered vessels. Invasion risk values were higher for anchorages, moorings and wharves. Similarly, hull-fouling was revealed as the highest infection risk mode after pooling results across all habitats. The NIS fuzzy expert system presented here appears as a valuable prioritising and decision-making tool for NIS research, prevention and control activities. Its easy implementation and wide applicability should encourage the development and application of this type of system as an integral part of biosecurity, and other environmental management plans.     

ABC算法优化SVR的磨损故障预测模型

目的为了提高故障预测的精度,针对支持向量回归SVR(Support vector machine for regression,SVR)参数选择困难的问题,提出一种采用人工蜂群(artificial bee colony,ABC)算法优化支持向量回归(SVR)的故障预测模型(ABC-SVR)。方法该模型先对样本数据进行重构,然后将故障预测误差(适应度)作为优化目标,通过ABC算法寻优找到最优的SVR参数,建立故障预测模型。最后通过实例仿真验证模型的优越性。结果采用ABC算法优化的SVR故障预测模型进行时间序列预测,能够较好地跟踪发动机滑油金属元素浓度的变化过程,并且能够提前2个取样时间预测异常情况的出现。结论 ABC-SVR模型有效解决了SVR参数选择难题,能够更加准确地表现故障变化规律,提高了故障预测精度。     

电化学强化低能耗废水生物处理技术研究

以碳布为阴阳极材料构建一种新型的生物电化学系统（BES）,研究该系统在不曝气条件下对城市污水的处理效果,并与传统的厌氧和好氧处理方法进行比较。结果表明,该BES处理城市污水是可行的,与传统曝气法相比能够显著降低能耗。在进水CODcr,为350mg／L、NH3-N为15mg／L、水力停留时间（HRT）为24h时,电化学强化生物处理系统对CODcr和NH3-N的去除率达84％和80％,优于同等条件下的厌氧、好氧生物处理方法。BES的输出电压最高为211mV。