Lessons learned for process safety management in China

A number of chemical accidents have occurred in China over the past two decades with significant impact on humans and the environment. It is expected that lessons will have been learned from these accidents that will help industries to reduce the risk that catastrophic chemical accidents occur in future. In fact, to some extent there is evidence that lessons have been learned, to the extent that the Chinese government has substantially strengthened legislation and regulatory standards. Nonetheless, there remains a concern that much more still needs to be done to reduce chemical accidents risks in China. Important progress in this area requires not only government support but a commitment across all hazardous industries to learn from past accidents that may in many cases require establishment or considerable improvement of their safety management systems. To assist small and medium-sized enterprises (SMEs), in this effort, results of an analysis of common causes of the chemical accidents reported in the Major Accident Information (MAI) website of Chinese State Administration of Work Safety (SAWS) are presented in this paper In particular, inadequate process hazard analysis (PHA), training and emergency response planning (ERP) were identified as the top three process safety management (PSM) elements that contribute to most of the SMEs accidents in China. Seven recommendations are proposed in order to improve the effectiveness of lesson learning for government agencies and SMEs.     

A density projection approach for non-trivial information dynamics: Adaptive management of stochastic natural resources

We demonstrate a density projection approximation method for solving resource management problems with imperfect state information. The method expands the set of partially-observed Markov decision process (POMDP) problems that can be solved with standard dynamic programming tools by addressing dimensionality problems in the decision maker's belief state. Density projection is suitable for uncertainty over both physical states (e.g. resource stock) and process structure (e.g. biophysical parameters). We apply the method to an adaptive management problem under structural uncertainty in which a fishery manager's harvest policy affects both the stock of fish and the belief state about the process governing reproduction. We solve for the optimal endogenous learning policy—the active adaptive management approach—and compare it to passive learning and non-learning strategies. We demonstrate how learning improves efficiency but typically follows a period of costly short-run investment.     

基于高斯过程机器学习算法的矿柱稳定性分析

矿柱是地下矿山支撑顶板围岩、维持采场稳定的关键结构要素。为迅速准确地判别矿柱稳定性,选取矿柱宽度、矿柱高度、矿柱宽高比、矿岩单轴抗压强度和矿柱承受载荷作为影响指标,利用高斯过程机器学习算法建立矿柱状态与其主要影响因素之间的非线性映射关系,进而提出一种基于高斯过程二元分类(GPC)的矿柱状态识别模型。结合工程实例,以40组样本数据进行训练,以10组样本数据对该模型进行检验,并与ANN和SVM进行对比。结果表明,矿柱状态识别的高斯过程模型是科学可行的,该模型具有参数自适应化获取、分类精度高、计算复杂度低等优点,还可对矿柱状态判别结果的不确定性或可信度进行定量化评价。     

Sensori-motor learning and its relevance for task specialization in bumble bees

Individual bees often restrict their visits to only a few species out of the multitude of available plants. This flower constancy is likely caused by limitations of memory for motor patterns, sensory stimuli, or reward levels. Here we test the implications of sensori-motor learning and memory for flower constancy. Artificial “flowers” with two distinct “morphologies” were used, so that in each flower type, a different motor pattern was needed to reach the nectar. As in natural flowers, these morphological types were associated with sensory signals (blue and yellow color stimuli). Bees which learned only a single task were more efficient in several ways than those which had learned two: they made fewer errors, had shorter flower handling times, took shorter times to correct errors, and transitions between flowers were initially more rapid. For bees which had learned two tasks, performance depended strongly on the training schedule: if each task was learned with blocked trials, the memory for the second appeared to interfere with that for the first. Interference affected only the association between flower signal and motor pattern, not the motor pattern itself. This was not the case if bees were trained for both tasks with alternating trials. In that case, bees rapidly learned both tasks, albeit with worse saturation levels than bees which had learned only one. Bees transferred the experience gained on one task to a second task: their initial performance on the second task was better than their initial performance on the first. On the other hand, performance on the second task in the saturation level (in which bees no longer improve their efficiency) was worse than on the first task (negative transfer). In the saturation phase, performance did not directly depend on switch frequency, but on whether the bee had one or two options in memory. Thus, while bees would become proficient at two tasks more quickly if their acquisition phase included switches, such switches had no measurable effect in the saturation phase. The implications of these findings for foraging are discussed using modern learning theory. Received: 4 April 1997 / Accepted after revision: 8 August 1997     

Intergovernmental relationships after disaster: state and local government learning during flood recovery in Colorado

ABSTRACT

When communities experience disaster, emergency response and recovery are led internally, based on local-level policy decisions and priorities. Decisions about how or whether to rebuild are made by local governments. Higher governmental authorities such as states and provinces may institute their own disaster recovery processes and policies in addition to or in competition with local governments. Greater intergovernmental engagement could increase resources and knowledge, which would yield higher levels of learning and result in superior disaster recovery policy outcomes. The role of higher authorities, then, can have important implications for policy processes and outcomes. The learning literature includes a dearth of studies that analyze the relationships between state and local governments during disaster recovery. We move the learning literature forward by analyzing intergovernmental relationships during disaster recovery. We find that learning within local governments is associated with higher levels of resource flows from state agencies as well as more collaborative intergovernmental relationships. We also find that state governments can improve processes for disaster recovery assistance and bring together disaster-affected local governments to promote learning during the recovery process. While this study focused on relationships constrained by U.S. federal dynamics, the lessons are useful to other multilevel governance systems.     

Collaborative learning for policy innovations: sustainable urban drainage systems in Leicester,England

ABSTRACT

Collaboration among multiple stakeholders is crucial in decentralised governance settings. The success of such collaboration hinges upon collaborative learning – the acquiring, translating, and disseminating of policy-relevant knowledge. However, despite much research, a knowledge gap persists in the public policy literature on the relationship between learning and policy change. It is debated whether learning is necessary and sufficient for policy change, and if so, under what conditions. To contribute to this debate, this paper examined whether collaborative learning has had any impact on the emergence and implementation of sustainable urban drainage systems (SuDS) in Leicester, England. We first examined implementation of SuDS in Leicester, and then study collaborative learning focused on SuDS. We found that implementation of SuDS in Leicester is marginal despite active collaborative learning that has resulted in the change in beliefs and attitudes towards SuDS among all policy actors in the setting. Social dynamics factors and leadership of two SuDS champions proved crucial for collaborative learning. We conclude that collaborative learning, while essential for legitimacy of a policy innovation, is not sufficient for policy change and a national legal and institutional framework is required to incentivise broader SuDS practices in Leicester and England.     

How floral odours are learned inside the bumblebee (Bombus terrestris) nest

Recruitment in social insects often involves not only inducing nestmates to leave the nest, but also communicating crucial information about finding profitable food sources. Although bumblebees transmit chemosensory information (floral scent), the transmission mechanism is unknown as mouth-to-mouth fluid transfer (as in honeybees) does not occur. Because recruiting bumblebees release a pheromone in the nest that triggers foraging in previously inactive workers, we tested whether this pheromone helps workers learn currently rewarding floral odours, as found in food social learning in rats. We exposed colonies to artificial recruitment pheromone, paired with anise scent. The pheromone did not facilitate learning of floral scent. However, we found that releasing floral scent in the air of the colony was sufficient to trigger learning and that learning performance was improved when the chemosensory cue was provided in the nectar in honeypots; probably because it guarantees a tighter link between scent and reward, and possibly because gustatory cues are involved in addition to olfaction. Scent learning was maximal when anise-scented nectar was brought into the nest by demonstrator foragers, suggesting that previously unidentified cues provided by successful foragers play an important role in nestmates learning new floral odours.     

The effect of larval and early adult experience on behavioural plasticity of the aphid parasitoid <Emphasis Type="Italic">Aphidius ervi</Emphasis> (Hymenoptera,Braconidae, Aphidiinae)

The relevance of the integration of preimaginal and eclosion experiences on the subsequent habitat preferences and mate finding by the adult has been rarely tested in holometabolous insects. In this work, the effect of larval and early adult experiences on the behavioural responses of adult males of the aphid parasitoid, Aphidius ervi, towards volatiles from the host–plant complex (HPC) and from conspecific females were evaluated. Two experience factors were considered: host diet (normal diet=ND; artificial diet=AD), and eclosion, i.e. extraction or non-extraction of the parasitoid larva from the parasitised aphid (extracted=EX; non-extracted=NE). Thus, four treatments were set up: ND/NE, ND/EX, AD/NE and AD/EX. Glass Y-tube olfactometers were used to investigate the responses of adult A. ervi males to the odour sources used. Males from the ND/NE treatment showed a shorter latency to the first choice of olfactometer arms, displayed a marked preference towards the HPC olfactometer arm, and spent more time in the HPC arm than males from the other treatments. Only the interaction of host diet and eclosion experiences proved to be relevant in explaining the differences in latency to first choice, time spent in olfactometers arms, and behaviours displayed in the olfactometer arms. These results show the importance of the integration of larval and eclosion experiences in the development of stereotyped responses of the adults. This process may involve memory retention from the preimaginal and emergence period, but further research is needed to disentangle the contribution of each stage. The response to conspecific females was much less affected by the treatments in relation to first arm choice and times in olfactometer arms, suggesting a pheromone-mediated behaviour, even though a prompter and more intense wing fanning courtship behaviour was registered in the ND/NE males compared to males from the AD/NE treatment. These results show that sexual behaviours are less affected by early experiences than behaviours related with finding a HPC for foraging or oviposition. Taken together, our results demonstrate for first time that larval and eclosion experiences affect in a differential way the early responses of the adult towards environment-derived cues and mate related cues.     

吉林省COD排放环境学习曲线及减排潜力分析

基于2000-2009年吉林省9个市（州）COD排放量,对人均COD排放量和万元GDPCOD排放量的区域分布格局及其成因进行了定量分析;同时,基于2000-2009年COD排放量和人均GDP,建立了吉林省万元GDPCOD排放量随人均GDP变化的环境学习曲线,分析了2000-2009年COD排放环境负荷变化及减排潜力,对《吉林省国民经济和社会发展第十二五个五年规划纲要》确定的削减8．8％目标的可达性进行了预测。结果表明：在吉林省国民经济和社会发展指标条件下,目标值和预测值的误差小于2％,能够实现COD削减的约束性指标。     

太原市PM2.5浓度的气象特征影响分析及预报

利用2016～2020年太原市污染物浓度资料、以及国家基准气象观测站的同期地面气象资料,重点分析了太原市PM_2.5浓度的变化特征以及湿度、降水、风和混合层厚度等气象条件对PM_2.5浓度的影响,同时探讨了污染物浓度变化的成因,建立基于LSTM神经网络的PM_2.5浓度预报模型.结果表明,2016～2020年太原市区冬季出现的重污染天数最多,其中2017年冬季出现天数最多为28 d, PM_2.5浓度总体呈现出秋冬季节高,春夏季节低,周末PM_2.5浓度高于工作日浓度,PM_2.5浓度日变化大致呈现双峰型分布,分别出现在09:00左右和23:00至翌日01:00.除相对湿度和冬季气温外,其余气象要素与PM_2.5浓度在四季均表现为负相关.影响太原市区PM_2.5浓度升高的污染源主要位于其NE-ENE-E方向,西北部地区的相对不明显.汛期当达到中雨(降水量≥10 mm)以上级别的降水都对PM_2.5浓度降低有明...