机械脱污及其应用研究

给出了颗粒在离心力作用下的数学模型，并进行了计算机模拟在其在设计装置时的应用，还给出了实际脱污的测试结果。     

Setting Realistic Recovery Targets for Two Interacting Endangered Species,Sea Otter and Northern Abalone

Failure to account for interactions between endangered species may lead to unexpected population dynamics, inefficient management strategies, waste of scarce resources, and, at worst, increased extinction risk. The importance of species interactions is undisputed, yet recovery targets generally do not account for such interactions. This shortcoming is a consequence of species‐centered legislation, but also of uncertainty surrounding the dynamics of species interactions and the complexity of modeling such interactions. The northern sea otter (Enhydra lutris kenyoni) and one of its preferred prey, northern abalone (Haliotis kamtschatkana), are endangered species for which recovery strategies have been developed without consideration of their strong predator–prey interactions. Using simulation‐based optimization procedures from artificial intelligence, namely reinforcement learning and stochastic dynamic programming, we combined sea otter and northern abalone population models with functional‐response models and examined how different management actions affect population dynamics and the likelihood of achieving recovery targets for each species through time. Recovery targets for these interacting species were difficult to achieve simultaneously in the absence of management. Although sea otters were predicted to recover, achieving abalone recovery targets failed even when threats to abalone such as predation and poaching were reduced. A management strategy entailing a 50% reduction in the poaching of northern abalone was a minimum requirement to reach short‐term recovery goals for northern abalone when sea otters were present. Removing sea otters had a marginally positive effect on the abalone population but only when we assumed a functional response with strong predation pressure. Our optimization method could be applied more generally to any interacting threatened or invasive species for which there are multiple conservation objectives. Definición de Metas de Recuperación Realistas para Dos Especies en Peligro Interactuantes, Enhydra lutris y Haliotis kamtschatkana     

井下运输人—机—环境系统安全性灰色多层次综合评判

为了分析与评价井下运输系统的安全状况,笔者基于灰色关联分析理论,确定了井下运输系统安全状况综合评判的指标体系,建立了灰色多层次安全综合评判模型。通过对影响井下运输系统安全的人、机、环境的１１ 种因素进行的实际分析与计算,指出了井下不同运输子系统的安全状况及其薄弱环节。该方法使评判结果更具科学性、可比性和实用性,而且为进一步搞好安全评价工作提供了理论依据。     

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.     

慢性氟暴露致小鼠海马损伤及L-型钙拮抗剂的干预作用

探讨了慢性氟暴露致小鼠海马损伤及L-型钙通道拮抗剂的干预作用.将140只初断乳ICR雄性小鼠随机分为7组：对照组（C组）、高氟组（HF组,饮用30 mg·L^-1 NaF溶液）、低氟组（LF组,饮用5 mg·L^-1 NaF溶液）、高/低氟+L-型钙通道激动剂组（FPL64176）（HF/LF+FPL）、高/低氟+L-型钙通道拮抗剂组（Nifedipine）（HF/LF+NIF）.染氟6个月,染氟结束前1周,HF/LF+FPL和HF/LF+NIF组分别每天腹腔注射激动剂或拮抗剂（5 mg·kg^-1·d^-1）.用TUNEL法检测小鼠海马CA₁区细胞凋亡水平,用Western Blot法检测细胞膜L-型钙通道Cav1.2、Ca²⁺信号通路分子和下游凋亡调节相关分子蛋白表达水平等.结果表明,与对照组比,HF/LF组小鼠海马组织抗氧化能力显著降低（p<0.05或p<0.01）,细胞凋亡水平极显著上升（p<0.01）,Cav1.2与Bcl-2蛋白表达水平显著下降（p<0.05或p<0.01）,Ca²⁺信号转导通路CaM、CaMKII和促凋亡Bax、Bax/Bcl-2蛋白表达水平显著上升（p<0.05或p<0.01）.注射FPL64176的小鼠海马细胞和上述分子指标的损伤加剧,而注射NIF对海马细胞和上述分子蛋白表达有一定的逆转作用.提示L-型钙离子通道介导了氟暴露致小鼠海马损伤,氟暴露致海马细胞膜L-型钙离子通道Cav1.2蛋白、细胞内Ca²⁺信号转导通路分子和下游凋亡调节相关蛋白表达异常是其分子机制之一,而L-型钙通道拮抗剂NIF可能是一种新型有效的抗氟药物.     

加大英语教学改革力度,提高我院英语教学质量

高职英语教学有其特殊性,即强调基础性、实用性、和针对性.因此从高职英语教学的特点及影响因素出发,需确立正确的教学指导思想,培养学生的自主学习能力,改革和完善英语教学管理,加强英语教师队伍建设.     

SOIL MOISTURE PREDICTION USING SUPPORT VECTOR MACHINES1

ABSTRACT: Herein, a recently developed methodology, Support Vector Machines (SVMs), is presented and applied to the challenge of soil moisture prediction. Support Vector Machines are derived from statistical learning theory and can be used to predict a quantity forward in time based on training that uses past data, hence providing a statistically sound approach to solving inverse problems. The principal strength of SVMs lies in the fact that they employ Structural Risk Minimization (SRM) instead of Empirical Risk Minimization (ERM). The SVMs formulate a quadratic optimization problem that ensures a global optimum, which makes them superior to traditional learning algorithms such as Artificial Neural Networks (ANNs). The resulting model is sparse and not characterized by the “curse of dimensionality.” Soil moisture distribution and variation is helpful in predicting and understanding various hydrologic processes, including weather changes, energy and moisture fluxes, drought, irrigation scheduling, and rainfall/runoff generation. Soil moisture and meteorological data are used to generate SVM predictions for four and seven days ahead. Predictions show good agreement with actual soil moisture measurements. Results from the SVM modeling are compared with predictions obtained from ANN models and show that SVM models performed better for soil moisture forecasting than ANN models.     

新颖复合叶轮倒伞表曝机及其应用

本文介绍了国产化高动力效率、低能耗的污水处理关键设备—复合叶轮倒伞型表面曝气机的技术性能及实际应用效果。     

布袋除尘器在烧结机机尾除尘中的应用

介绍了用旋风除尘器、布袋除尘器组成的二级串联除尘系统在小型烧结机机尾烟气除尘中的实际应用。实际运行结果表明，该系统运行可靠，除尘效率高，系统出口含尘浓度达到了国家允许的排放标准，并针对相关问题进行了探讨。