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Understanding and predicting the pattern formation in groups of pluripotent stem cells has the potential to improve efficiency and efficacy of stem cell therapies. However, the underlying molecular mechanisms of pluripotent stem cell behaviors are highly complex and are currently still not fully understood. A key practical question is whether deep biological modelling of the cells is essential to predict their pattern formation, or whether there is sufficient predictive power in simply modelling their behaviors and interactions at a higher level. This study focuses on the social interactions and behaviors of pluripotent stem cells at a high-level to predict aggregate crowd behaviors within a level of uncertainty. Agent-based modelling was applied to study the pattern formation in pluripotent stem cells. Five models were established to test four biologically plausible rules of cell motility in terms of: a) velocity, b) directional persistence time, c) directional movements, and d) border effect. We found that it is possible that cells' directional movements based on local density play an important role of the pattern formation, and pattern formation in pluripotent stem cells is governed by a complex combination of rules in our agent-based model simulations, which account for much of the variability observed in experimental findings.

Based on the border effect and relevant theories, it is found that measurement precision depends on resolution stability which is much higher than resolution itself. With the help of this new theory and the more sensitive discrimination of the border of a fuzzy area, it is possible to greatly improve the measurement precision. Since there are a lot of complicated frequency signals in quantum frequency standards, telecommunication, fundamental subjects and other fields, precise measurement is significantly important. In a great deal of measurement of complicated frequency signals, discrete fuzzy areas are common. In this paper, we put forward a feasible and high-precision frequency measurement scheme to make it easier to capture border information, which shows great advantages of border effect.

Border effect gravity model for shipping trade is introduced to investigate its theoretical foundation using China-US shipping trade data over the period of 2005-2009. Different ways of robustness tests are conducted to test the validity of the model in this regard. The results show that the established model proves to be useful and border still matters for China-US shipping trade.

This paper puts forward a border effect model derived from the widespread Gravity Model for shipping industry to study the significance of trade barriers caused by the regional border in ports. The result shows that economic size, cargo handling capacity and berth number of a port greatly influence the bilateral shipping trade while pier length does not show an obvious effect on shipping trade. Border effects between China and US for shipping trade do exist but is not quite significant based on the data of 2004–2009.

This paper presents an automatic parallax adjustment method that considers the border effect to produce more realistic stereo images on a stereoscopic augmented reality system. Three-dimensional (3D) imaging is an emerging method of displaying three-dimensional information and providing an immersive and intuitive experience with augmented reality. However, the protruding parts of displayed stereoscopic images may be blurry and cause viewing discomfort. Furthermore, the border effect may make it difficult for an imaging system to display regions next to screen borders, even with considerable negative parallax. This paper proposes a method of automatically adjusting the parallax of displayed stereo images by analyzing the feature points in regions near screen borders to produce better stereo effects. Experimental results and a subjective assessment of human factor issues indicate that the proposed method makes stereoscopic augmented reality systems significantly more attractive and comfortable to view.

Three border effect models capturing the unique characteristics of agricultural trade based on the Gravity Model are put forward and further contrasted to study China-U.S. border effects for agricultural trade covering the panel data over the period of 1987-2007. The results show that the third model -fixed effects model considering the heterogeneity of each trading pair is preferred in this regard. The border effects for agricultural trade tend to be significantly large, and vary from international trade direction and across regions, but the models without considering these differences tend to overestimate the border effects for China-U.S. agricultural trade over this period. Keywords- agricultural trade; border effect models; China-U.S.; gravity model

This paper provides the first comprehensive empirical study on China-U.S. agricultural trade using gravity model to study the border effect between these two countries. The data set covers bilateral trade in agricultural products of the two countries in year 1997, 2002 and 2005. The results indicate that border effect of China-U.S. agricultural trade is significant and tends to drop from 22.4 in year 1997 to 10.2 and 7.0 in year 2002 and 2005 respectively. The standard model is further revised to study the influence of the direction of international trade and regional differences on the border. And it has been found that the China-U.S. border has a large dampening effect on bilateral agricultural trade, is asymmetric and differs greatly across regions.

This paper presents a procedure for implementing fully adaptive interpolated FIR filters with removed border effect. The proposed approach allows reducing the steady-state mean-square error by eliminating the main sources of performance degradation from the adaptive interpolated FIR filters. In addition, the computational effort needed for implementing such a procedure is very small. Simulation results confirm the effectiveness of the proposed approach.

This paper presents a procedure to remove the border effect from interpolated finite impulse response (IFIR) and interpolated Volterra adaptive filters using the LMS algorithm. The used approach permits to reduce the steady-state mean-square error (MSE) of such structures. In situations that the border effect is important, the obtained improvement is noticeable. In addition, the computational burden required to implement such a procedure is slight. Simulation results confirm the effectiveness of the proposed approach.

The technological requirements leads to an unavoidable border at finite grounding via arrays. At a certain frequency an unwanted wave travelling occurs along the border. This paper provides not only detailed analytical and numerical analysis of such crosstalk effect, but also experimental verifications. The presented model achieves very good agreement over a broad range of border length variations.