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After a decade of reform, China has laid the initial foundations for a unified national market. With the tilting toward a "dual-directional division" (shuangxiang fenquan) of administrative power, however, the abnormal phenomena of increasingly strong local power, fragmented markets, and regional blockades have appeared. The primary market structures, distribution channels, and organization have all become more complicated and order has been disrupted. Since 1990, in particular, many regions, in an effort to invigorate their own markets, have used economic and administrative means to practice local protectionism, reinforce regional blockades and market divisions, and obstruct the lateral flow of production factors. As a result, interregional conflicts have escalated and trade barriers have risen throughout the nation. All this has seriously affected macroeconomic coordination and orderly development and has become a major impediment to improvement of the economic environment and straightening out of economic order, as well as revitalization of the market. This article aims to make a systematic and in-depth study of the origins and dangers of regional blockades, and seeks to present a cure for this problem.

This paper proposes an adaptive impedance control method for a robot's end-effector while it slides steadily on an arbitrarily inclined panel; it concentrates on robot force position tracking control for the inclined plane with an unknown normal direction and varying environmental damping and stiffness. The proposed control strategy uses the Recursive Least Squares (RLS) algorithm to estimate environmental damping and stiffness parameters during the impact-contact process between the robot and the environment. It achieves the expected posture adjustment of the robot's end-effector based on the measured contact torques and, during the robot's end-effector's sliding on the inclined plane, a fuzzy control is developed to adjust the robot impedance model parameters on-line and adaptively for changes in environmental damping and stiffness. The designed robot force position control method is robust to the changes of the environmental parameters but the implementation of the proposed control algorithms is simple. Finally, experiments demonstrate the effectiveness of the proposed method.

Bayesian method for estimating human error probability (HEP) is presented. The main idea of the method is incorporating human performance data into the HEP estimation process. By integrating human performance data and prior information about human performance together, a more accurate and specific HEP estimation can be achieved. For the time-unrelated task without rigorous time restriction, the HEP estimated by the common-used human reliability analysis (HRA) methods or expert judgments is collected as the source of prior information. And for the time-related task with rigorous time restriction, the human error is expressed as non-response making. Therefore, HEP is the time curve of non-response probability (NRP). The prior information is collected from system safety and reliability specifications or by expert judgments. The (joint) posterior distribution of HEP or NRP-related parameter(s) is constructed after prior information has been collected. Based on the posterior distribution, the point or interval estimation of HEP/NRP is obtained. Two illustrative examples are introduced to demonstrate the practicality of the aforementioned approach. [ABSTRACT FROM AUTHOR]