商行为与重大误解规则之适用

《民法典》规定了当事人可以基于重大误解撤销合同,然而重大误解在商事领域由于价值理念与民法领域有别,更加注重交易的安全和效率,应当对重大误解在商事领域的应用进行合理的限制,可以考虑通过对商行为做必要的类型化区分,在某些特定商行为的交易场景中需要限制重大误解的适用。以商事领域中的组织法行为为例,会涉及一系列的法律关系,更应当谨慎地适用重大误解规则的适用。The Civil Code stipulates that parties may rescind a contract based on material misunderstanding. However, due to differing value concepts between commercial law and civil law, with a greater emphasis on transactional security and efficiency in the commercial realm, the application of material misunderstanding should be reasonably restricted in this context. This could involve making necessary typological distinctions among commercial acts and limiting the applicability of material misunderstanding in specific commercial transaction scenarios. Taking organizational legal acts in the commercial sphere as an example, these involve a series of legal relationships, and the rule of material misunderstanding should be applied with caution.

HRM and Quantitatives： Decision Tree and Vector Analysis in HRM Theory

Research topic of this paper is to discuss theory of Human Resources Management （HRM） and to discuss using of quantitative methods in HRM. Firstly, five variables establish HRM theory. They are HRM practices, positive organizational behaviors, individual performance, performance of business departments, and firm performance. Transactions among those variables enable Human Resources （HR） practitioners to apply HRM theory in their organizations. Secondly, this paper discusses use of quantitative methods in HRM. They are vector analysis and decision tree analysis. Those analyses enable HR practitioners to make effective HR decisions. Decision tree sets HR alternatives to efficiently implement HRM practices in organizations. Research question is how HR practitioners apply quantitative methods in department of HRM in firms. Finally this research comes out a conclusion that quantitative methods may be used in HRM.

Expression and significance of cyclin E in gastric carcinoma

Objective:The aim of the study was to investigate the expression and significance of cyclin E in gastric carcinoma.Methods:We detected the expression of cyclin E in three different pathologic types gastric carcinoma samples by immuno-histochemical staining technique (SP method).Results:In 59 gastric carcinoma samples the positive rate of cyclin E expression in gastric carcinoma was 55.93% (33/59), and it was significantly higher than that of normal gastric mucosa (10.53%, 2/19).The positive rates of cyclin E expression in poor differentiation group and mucoid carcinoma group were 68.75% (11/16) and 66.67% (16/24), respectively, and these were significantly higher than that in well-middle differentiation group (31.58%, 6/19), but there was no significant difference between the fronted two groups (P>0.05).Conclusion:The high expression of cyclin E is associated with the progression of gastric carcinoma and probably related to the behavior of cellular biology.

The Effect of Power upon Unethical Behavior in the Organization

Based on the undertaken research, it is explored whether power can affect the judgment made by individual about unethical behavior. Research 1 uses questionnaire as measuring method. The results demonstrate that individuals with different levels of power make judgment on various unethical behaviors. Their judgments are not different. It does not agree with the hypothesis. The reason may lie in that it may be affected by social desirability, or that there exist defects in the design of questionnaire. Research 2 uses laboratory investigation. The results demonstrate that individuals in high-power group conduct unethical behavior more frequently and more fiercely. It agrees with the hypothesis. The inconsistent results of the two researches can be reasonably explained from the two angles of moral permission and moral hypocrisy.

Adaptive Clustering Algorithm by Ants＇ Optimization

Inspired by the swarm intelligence in self-organizing behavior of real ant colonies, various ant-based algorithms were proposed recently for many research fields in data mining such as clustering. Compared with the previous clustering approaches such as K-means, the main advantage of ant-based clustering algorithms is that no additional information is needed, such as the initial partitioning of the data or the number of clusters. In this paper, we present an adaptive ant clustering algorithm ACAD. The algorithm uses a digraph where the vertexes represent the data to be clustered. The weighted edges represent the acceptance rate between the two data it connected. The pheromone on the edges is adaptively updated by the ants passing it. Some edges with less pheromone are progressively removed under a threshold in the process. Strong connected components of the final digraph are extracted as clusters. Experimental results on several real datasets and benchmarks indicate that ACAD is conceptually simpler, more efficient and more robust than previous research such as the classical K-means clustering algorithm and LF algorithm which.is also based on ACO