“好”政策的执行效果也好吗?——基于容错纠错政策的实证检验

容错纠错是鼓励干部担当、激励干部创新的重要政策设计。那么,“好”政策是否意味着执行效果也好呢?论文通过构建政策效果、政策质量和政策执行力三者间因果联系的理想分析框架,借助PMC指数模型对10项容错纠错政策样本质量进行评估,结合政策效果分析,尝试确定该政策在理想分析框架下的类型归属。研究发现,容错纠错政策整体质量较高,呈现出国家级—省市级—新区级“依次递增”的特征,兼具趋同性与趋异性;容错纠错政策属于理想状态下质量较高但执行效果一般、执行力较弱的政策。可见,容错纠错政策效果并非唯一取决于政策质量,而是受到政策质量和政策执行力的共同影响。该发现印证了完全理性模式在政策制定过程中的局限性,政策制定者应基于有限理性模式进行决策。研究丰富了公共政策理论,为容错纠错政策改进提供了具体的依据和方向。

Grassland Variation and Its Driving Factors from 2000 to 2016: A Comparative Assessment between Qinghai-Tibet Plateau and Inner Mongolia Plateau

The grassland of Qinghai-Tibet Plateau (QTP) and Inner Mongolia Plateau (IMP), accounting for 73.9% of the total grassland area in China, is significant to food and ecological safety. Due to climate change and irrational human activities, grasslands on the two plateaus have severely degraded over recent decades. Understanding the dynamic changes of grassland and its driving forces is necessary to make effective measurements to prevent grassland degradation. Here, we selected the net primary productivity (NPP) as an indicator to quantitatively assess the dynamic variation of grassland and the relative roles of climate change and human activities on QTP and IMP from 2000 to 2016. The results found significant spatial variability of grassland on QTP. 28.3% of the grassland experienced degradation and was mainly distributed in the southern QTP, versus 71.7% of the grassland was restored and mainly distributed in the central and northern QTP. In contrast, grassland on IMP didn’t show significant spatial variability. Most of the grassland on IMP was restored during the study period. Climate change (i.e. increased precipitation) was the dominant factor and could explain 72.8% and 84.4% of the restored grassland in QTP and IMP. Irrational human activities (i.e. overgrazing) were the main driving factors and could explain 72.9% and 100.0% of the degraded grassland on the two plateaus during the study period. Ecological restoration projects were favorable for grassland restoration on the two plateaus, and they contributed to 27.2% and 15.6% of the restored grassland in QTP and IMP, respectively. Therefore, climate changes on IMP were more favorable for grassland restoration, and human activities have a greater impact on the grassland variation on QTP.

Multi-objective optimization for task offloading based on network calculus in fog environments

With the widespread application of wireless communication technology and continuous improvements to Internet of Things(IoT)technology,fog computing architecture composed of edge,fog,and cloud layers have become a research hotspot.This architecture uses Fog Nodes(FNs)close to users to implement certain cloud functions while compensating for cloud disadvantages.However,because of the limited computing and storage capabilities of a single FN,it is necessary to offload tasks to multiple cooperating FNs for task completion.To effectively and quickly realize task offloading,we use network calculus theory to establish an overall performance model for task offloading in a fog computing environment and propose a Globally Optimal Multi-objective Optimization algorithm for Task Offloading(GOMOTO)based on the performance model.The results show that the proposed model and algorithm can effectively reduce the total delay and total energy consumption of the system and improve the network Quality of Service(QoS).

国家级一流本科专业建设的问题与对策——以桂林理工大学应用化学专业为例

作为国家一流应用化学专业建设点,如何深刻理会本科专业建设的初心,结合专业发展特点与地区优势,踏踏实实做好国家一流专业的建设成为当前的主要任务。教研室在应用化学一流本科建设方面进行了积极的探索和实践,积累了一定的经验,但也面临一些不可回避的问题。针对存在的问题,需要从目标定位、培养模式、课程建设、实习实践基地建设和教学团队建设等方面多角度梳理专业建设思路,形成科学系统的专业发展规划,对应用化学专业的发展具有巨大的推动作用,对区内其他学科的建设有着良好的借鉴意义。

Virtualized Wireless SDNs:Modelling Delay Through the Use of Stochastic Network Calculus

Software-defined networks （SDN） have attracted much attention recently because of their flexibility in terms of network management. Increasingly, SDN is being introduced into wireless networks to form wireless SDN. One enabling technology for wireless SDN is network virtualization, which logically divides one wireless network element, such as a base station, into multiple slices, and each slice serving as a standalone virtual BS. In this way, one physical mobile wireless network can be partitioned into multiple virtual networks in a software-defined manner. Wireless virtual networks comprising virtual base stations also need to provide QoS to mobile end-user services in the same context as their physical hosting networks. One key QoS parameter is delay. This paper presents a delay model for software-defined wireless virtual networks. Network calculus is used in the modelling. In particular, stochastic network calculus, which describes more realistic models than deterministic network calculus, is used. The model enables theoretical investigation of wireless SDN, which is largely dominated by either algorithms or prototype implementations.

Scheduling optimization for upstream dataflows in edge computing

Edge computing can alleviate the problem of insufficient computational resources for the user equipment,improve the network processing environment,and promote the user experience.Edge computing is well known as a prospective method for the development of the Internet of Things(IoT).However,with the development of smart terminals,much more time is required for scheduling the terminal high-intensity upstream dataflow in the edge server than for scheduling that in the downstream dataflow.In this paper,we study the scheduling strategy for upstream dataflows in edge computing networks and introduce a three-tier edge computing network architecture.We propose a Time-Slicing Self-Adaptive Scheduling(TSAS)algorithm based on the hierarchical queue,which can reduce the queuing delay of the dataflow,improve the timeliness of dataflow processing and achieve an efficient and reasonable performance of dataflow scheduling.The experimental results show that the TSAS algorithm can reduce latency,minimize energy consumption,and increase system throughput.