An agent-based model for simulating trading of multi-species fisheries quota

Individual transferable quotas (ITQs) are increasingly seen as a way to make fisheries more profitable and halt over-capitalisation. ITQs allocate to users of a resource a share of a total allowable catch (TAC) which they are free to use, lease, or sell. We outline an approach to modelling the effect of an ITQ system in a multi-species, multi-sector fishery and apply it to the Coral Reef Fin Fish Fishery (CRFFF) in Queensland, Australia. An ITQ model, based on the assumption that operators seek to maximize profits, simulates the use of tradeable quota units by operators in the fishery, taking account of the initial quota allocation to operators, seasonal fish prices and individual operator variable costs, their fishing efficiency and experience, and constraints on vessel movements. Rationalization of the fishery is predicted to occur under an ITQ system for the CRFFF, which will lead to reductions in effort, increases in profits, and changes over time in quota prices. The ecological consequences of transferable quota in the multi-species fishery are seen in the catch and discard levels of the less profitable species, even though a TAC was set. This had flow-on effects on biomass. For example, simulations showed that the TAC for the primary target species, coral trout, was used more fully than that for a less valuable target species, red throat emperor, and that this was achieved through increased discarding of red throat emperor. Catches of both coral trout and red throat emperor that were derived from the model were higher than those recently observed in the fishery. The effort predicted by the model, however, closely approximated the actual effort observed in the fishery following implementation of ITQ management.     

建筑物火灾危险性评估的一种工程方法

提出了建筑物火灾危险性评估的一种工程方法。该方法基于建筑火灾的区域模拟理论和人员疏散的最新研究成果，分别计算出火灾中达到危险状态的时间和整个疏散过程所需的时间，通过对比这两个时间，来确定火灾危险性的大小。这种方法概念清晰，简单易行，能在一定程度上对实际建筑物的火灾危险性进行评估，也可用于对火灾的安全工程设计评价和安全咨询。     

Eco-hydrological modelling in a highly regulated lowland catchment to find measures for improving water quality

Water quality modelling in the meso-scale Rhin catchment in the German federal state Brandenburg was done (1) to answer some specific questions concerning identification of point and diffuse sources of nutrient pollution in the catchment, (2) to assess the influences of possible climate and land use changes on water quantity and quality and (3) to evaluate potential measures to be done in order to achieve a “good ecological status” of the river and its lakes as required by the Water Framework Directive (WFD).The Rhin catchment is a typical highly regulated lowland river basin in Northern Germany. The regulations complicate water quantity and quality modelling in the catchment. The research was done by using the eco-hydrological model SWIM (Soil and Water Integrated Model), which simulates water and nutrient fluxes in soil and vegetation, as well as transport of water and nutrients to and within the river network. The modelling period was from 1981 until 2005. After calibrating the hydrological processes at different gauges within the basin with satisfactory results, water quality (nitrogen and phosphorus) modelling was done taking into account the emissions of different point sources (sewage treatment plants, etc.) and identifying the amount of diffuse pollution caused mainly by agriculture.For suggesting some feasible measures to improve water quality and to reduce diffuse pollution considering possible climate and land use changes, different reasonable scenarios were applied in consultation with the Environmental Agency of Brandenburg (LUA). The study revealed that the amount of water discharge has significant influence on the concentration of nutrients in the river network, and that nitrogen pollution, caused mainly by diffuse sources, could be notably reduced by application of agricultural measures, whereas the pollution by phosphorus could be diminished most effectively by the reduction of point source emissions.     

A new approach to assessment and management of the impact from medical liquid radioactive waste

The Swedish regulations concerning disposal of clinical radioactive waste are currently under revision and a graded approach is proposed for risk limitation purposes. To assist the revision procedures, a screening study was performed to estimate public exposures from liquid releases from hospitals to public sewers. The results showed that doses to sewage workers were above the dose constraint of 100muSva(-1) especially for (131)I and (99m)Tc. Hence, a dynamic model, LUCIA, was developed for realistic assessments in which radionuclide transportation in sewers was modelled. Probabilistic simulations were performed to obtain probability distributions of radionuclide concentrations in sludge. Concurrently, estimates of the effective doses to sewage workers decreased significantly and were below 10muSva(-1) except for (111)In and (131)I. However, the Kd-coefficients representing the partition of radioactivity between water and sludge in sewers are highly uncertain for (111)In. As shown by sensitivity studies, these values are the major determinant of the exposures in sewers.     

Review of hydrogen safety during storage,transmission, and applications processes

Hydrogen is considered an excellent clean fuel with potential applications in several fields. There are serious safety concerns associated with the hydrogen process. These concerns need to be thoroughly understood and addressed to ensure its safe operation. To better understand the safety challenges of hydrogen use, application, and process, it is essential to undertake a detailed risk analysis. This can be achieved by performing detailed consequence modellings and assessing risk using the computational fluid dynamics (CFD) approach. This study comprehensively reviews and analyses safety challenges related to hydrogen, focusing on hydrogen storage, transmission, and application processes. Range of release and dispersion scenarios are investigated to analyse associated hazards. Approaches to quantitative risk assessment are also briefly discussed.     

基于ANN的土壤重金属分布和污染评价研究

农田土壤重金属污染与备受关注的农产品安全问题有密切联系,因此对其进行研究意义重大。以江苏省南通市为研究区,利用采样点实测数据,借助神经网络模型(ANN)并结合3S技术对问题进行研究,从而对土壤重金属的空间动态分布进行描述,并对各个空间位点重金属的污染状况进行评价。结果表明,神经网络模型能够智能地学习各个样点的空间位置与该点各重金属含量之间的映射关系和预先设计好的分类评价模式,并能够稳健地对各个空间插值点处的重金属含量和各个位点的重金属污染状况进行预测和评价。结论显示,南通市大部分农田土壤重金属污染较轻,但也存在局部地区的严重污染。结论与实际情况相符,表明神经网络模型可以为农田土壤重金属的研究提供一个新的思路和方法。     

Value of information in product recovery decisions: a Bayesian approach

There is a widespread recognition of the need for better information sharing and provision to improve the viability of end-of-life (EOL) product recovery operations. The emergence of automated data capture and sharing technologies such as RFID, sensors and networked databases has enhanced the ability to make product information; available to recoverers, which will help them make better decisions regarding the choice of recovery option for EOL products. However, these technologies come with a cost attached to it, and hence the question ‘what is its value?’ is critical. This paper presents a probabilistic approach to model product recovery decisions and extends the concept of Bayes' factor for quantifying the impact of product information on the effectiveness of these decisions. Further, we provide a quantitative examination of the factors that influence the value of product information, this value depends on three factors: (i) penalties for Type I and Type II errors of judgement regarding product quality; (ii) prevalent uncertainty regarding product quality and (iii) the strength of the information to support/contradict the belief. Furthermore, we show that information is not valuable under all circumstances and derive conditions for achieving a positive value of information.     

Improving inverse model fitting in trees—Anisotropy,multiplicative effects,and Bayes estimation

Model fitting for individual-based effects in forests has some problems. Because samples measuring the separate influence of each individual are rarely available, the measured value in the sample represents the influence of all surrounding individual trees. Therefore, it is helpful to build inverse models that use the spatial pattern of the variable as well as that of the source trees. For example, since seed dispersal is influenced by wind effects, a model is discussed describing anisotropic effects to ensure an unbiased estimate of the total fruit number. Further, we present a model describing the absorption of radiation by trees. In this case a multiplicative combination of individual effects yields the total effect. Our approach uses logarithmic transformations of the original data to model multiplicative combinations as sum of transformed single effects. For fitting model parameters we propose an approach based on Bayesian statistics, to ensure ecologically interpretable parameters.