We develop and examine a framework for the knowledge spillover theory of entrepreneurship in alliances. Our framework regards entrepreneurial opportunity as endogenous, and entrepreneurial firms as heterogeneous. The empirical findings show that partners' knowledge protection, which is regarded as a knowledge filter, can increase knowledge spillovers in an alliance. Moreover, this relationship is contingent on the strength of a focal firm's entrepreneurial orientation and on alliance type (equity joint venture versus nonequity joint venture). Results also reveal that knowledge spillovers in an alliance enhance alliance performance more significantly than they enhance firm performance.

Cassava (Manihot esculenta Crantz) is a major tuberous crop produced worldwide. In this study, we sequenced 158 diverse cassava varieties and identified 349,827 single-nucleotide polymorphisms (SNPs) and indels. In each chromosome, the number of SNPs and the physical length of the respective chromosome were in agreement. Population structure analysis indicated that this panel can be divided into three subgroups. Genetic diversity analysis indicated that the average nucleotide diversity of the panel was 1.21 × 10-4 for all sampled landraces. This average nucleotide diversity was 1.97 × 10-4, 1.01 × 10-4, and 1.89 × 10-4 for subgroups 1, 2, and 3, respectively. Genome-wide linkage disequilibrium (LD) analysis demonstrated that the average LD was about ∼8 kb. We evaluated 158 cassava varieties under 11 different environments. Finally, we identified 36 loci that were related to 11 agronomic traits by genome-wide association analyses. Four loci were associated with two traits, and 62 candidate genes were identified in the peak SNP sites. We found that 40 of these genes showed different expression profiles in different tissues. Of the candidate genes related to storage roots, Manes.13G023300, Manes.16G000800, Manes.02G154700, Manes.02G192500, and Manes.09G099100 had higher expression levels in storage roots than in leaf and stem; on the other hand, of the candidate genes related to leaves, Manes.05G164500, Manes.05G164600, Manes.04G057300, Manes.01G202000, and Manes.03G186500 had higher expression levels in leaves than in storage roots and stem. This study provides basis for research on genetics and the genetic improvement of cassava.

Simulation of behaviors in emergencies is an interesting subject that helps to understand evacuation processes and to give out warnings for contingency plans. Individual and crowd behaviors in the earthquake are different from those under normal circumstances. Panic will spread in the crowd and cause chaos. Without considering emotion, most existing behavioral simulation methods analyze the movement of people from the point of view of mechanics. After summarizing existing studies, a new simulation method is discussed in this paper. First, 3D virtual scenes are constructed with the proposed platform. Second, an individual cognitive architecture, which integrates perception, motivation, behavior, emotion, and personality, is proposed. Typical behaviors are analyzed and individual evacuation animations are realized with data captured by motion capture devices. Quantitative descriptions are presented to describe emotional changes in individual evacuation. Facial expression animation is used to represent individuals' emotions. Finally, a crowd behavior model is designed on the basis of a social force model. Experiments are carried out to validate the proposed method. Results showed that individuals' behavior, emotional changes, and crowd aggregation can be well simulated. Users can learn evacuation processes from many angles. The method can be an intuitional approach to safety education and crowd management.

The increasing number of vehicles in cities brings new challenges to urban traffic management. Analyzing and modeling traffic is of great practical significance to urban intelligent traffic management. In this paper, the existing traffic simulation research is reviewed and summarized. Firstly, the crowd modeling and crowd animation are analyzed by referring to the idea of crowd simulation. Secondly, it compares and analyzes various existing car following technologies, and points out that animated traffic simulation is a hotspot in traffic simulation research. And then the concept of affective computing is integrated into the traffic simulation, considering the impacts of drivers’ emotion on vehicle driving and it is pointed out that the emotion-driven traffic flow is more authentic. Finally, combined with the status quo, the existing research drawbacks are analyzed, and the direction of future traffic simulation is pointed out.