Personality Traits of an Entrepreneur, Determinants of Successful Microenterprise in Ireland

Why do certain individuals become entrepreneur and are successful, whereas others do not? The researchers in the entrepreneurship field attempt to answer that question by studying the personality traits of entrepreneurs for decades. Many confirm that the personality traits have a positive correlation with entrepreneurial intention and performance. Various studies suggest that the main entrepreneurial characteristics are risk attitudes, need for achievement, internal locus of control, innovativeness, and self-efficacy. However, debate exist if the personality traits are born or inherited and if the entrepreneurs’ actions are influenced by factors such as family, culture, education and market conditions. Although these aspects will be reviewed the focus of this study is on entrepreneurs’ personality traits only. Consequently, the aim of this study is to identify which of the personality traits, and whether there are traits, that are associated with operating successful microenterprise, from a perspective of an owner-manager of an established business in Ireland. The findings of this research revealed that the participants perceive themselves as individuals who possess indirectly four out of five most cited traits in the literature, which are need for achievement, locus of control, innovativeness and self-efficacy. In addition, they mentioned ability to relate to others, being organized and perform a quality work as the most important characteristics of a successful business owner. Also, other factors of environment influenced the participants’ decision to become an entrepreneur and Ireland was perceived as an attractive country to set up a business. Still, most of the participants do not perceive themselves as a successful entrepreneur. In summary, the inconclusiveness of this study generate more questions than it provide answers, coupled with this study limitations it is suggested that additional and more extensive research is desired

Expression of matrix metalloproteinases in patients with bipolar disorder

Objective: High cardiovascular mortality rates have been reported in patients with bipolar disorder (BD). Studies indicate that matrix metalloproteinases (MMPs) are implicated in cardiovascular diseases. We evaluated the expression pattern of MMP-2 and MMP-9 in blood from patients with BD during acute mania and after euthymia, in comparison with healthy controls. Methods: Twenty patients and 20 controls were recruited and matched for sex and age. MMP messenger RNA (mRNA) levels were measured using real-time quantitative polymerase chain reaction (PCR). Body mass index (BMI) was calculated for all subjects. Results: There were no significant differences in MMP-2 and MMP-9 mRNA expression between patients and controls. mRNA levels were not significantly different during mania and euthymia. However, MMP-2 mRNA levels were negatively associated with BMI in BD patients and positively associated with BMI in controls. There was no difference in the pattern of MMP-9 expression between patients and controls. Conclusions: Our results suggest a different pattern of association between MMP-2 and BMI in BD patients as compared with controls. Despite some study limitations, we believe that the role of MMPs in BD should be further investigated to elucidate its relationship with cardiovascular risk

The use of Obstacle Motion Tracking for Car-like Mobile Robots Collision Avoidance in Dynamic Urban Environments

Abstract: One of the most challenging tasks for mobile robots is to track mobile obstacles that surround them. This task is especially difficult in outdoor environments where a great variety of obstacles may induce the robot to take erroneous decisions. The mobile robot needs as much information as possible concerning the obstacle positions and speeds (direction and magnitude) in order to plan evasive maneuvers that avoid collisions. Unfortunately, obstacles close to robot’s sensors frequently cause blind zones behind them where other obstacles could be hidden. In this situation, the robot may lose vital information about these obstructed obstacles that could avoid future collisions. In order to overcome this problem an obstacle tracking module based only on 2D laser scan data was developed. Its main parts consist of obstacle detection, obstacle classification, and obstacle tracking. Different methods were evaluated for extracting data from the laser data. Geometrical feature extraction itself, i.e. lines and corners, was not found sufficient. Therefore, a motion detection module using scan matching was developed. The research was mostly conducted using a MatLab simulator that reproduces a simple 2D urban-like environment with parked and moving cars, buses, trucks, and people, buildings, streets, and trees. Aiming to adjust and validate the algorithms, some samplings of real data were carried out. The tests proved the applicability of the algorithms in real urba