A BLUEPRINT FOR IMPLEMENTING GRAND CHALLENGE SCHOLARS’ PROGRAMME: A CASE STUDY OF TAYLOR’S UNIVERSITY

The National Academy for Engineering announced 14 Grand Challenges for the 21st Century engineers to address in order to ensure a sustainable future for the generations to come. These grand challenges are in four broad areas, namely, energy and environment, health, security and learning and computation. This paper reports on a Grand Challenges Scholars’ Programme that is developed to prepare the engineering students to be able to address the grand challenges using the CDIO framework and focusing on five components; research experience, interdisciplinary curriculum, entrepreneurship, global dimension and service learning. The programme is voluntary and the candidates are expected to commit additional learning time. The programme was launched with 16 participants who are expected to graduate in 2016. A preliminary assessment of the programs shows that the participants found the programme useful in developing an array of CDIO skills. The School intends to continue offering this programme with the intention of integrating it with a holistic education approach

Transglutaminase in human corneal epithelial cells

Ph.DDOCTOR OF PHILOSOPH

New Method for Complex Network Reliability Analysis through Probability Propagation

Reliability analysis of complex networks is often limited by increasing dimensionality of the problem as the number of nodes and possible paths in the network increases. This is true particularly for reliability analysis problems that exponentially increase in computational requirements with system size. In this paper, we present a new method for complex network reliability analysis. We call this the probability propagation method (PrPm). The idea originates from the concept of belief propagation for inference in network graphs. In PrPm, the message passed between nodes is a joint probability distribution. At each step, the distribution is updated and passed as the message to its direct neighbors. After the message passes to the terminal node, an estimation of the network reliability is found. The method results in an analytical solution for system reliability. We present the derived updating rules for message passing and apply the method to two test applications: a system distribution network and general grid network. In the message passing, some approximations are made. Results from the applications show high accuracy for the proposed method compared to exact solutions where possible for comparison. In addition, PrPm achieves orders of magnitude increases in computational efficiency compared to existing approaches. This includes reducing the computational cost for analyses from an exponential increase in computation time with the size of the system to a quartic increase. The method enables the accurate and computationally tractable calculation of failure probabilities of large, generally connected systems

Individual differences in valence bias: fMRI evidence of the initial negativity hypothesis

Facial expressions offer an ecologically valid model for examining individual differences in affective decision-making. They convey an emotional signal from a social agent and provide important predictive information about one’s environment (presence of potential rewards or threats). Although some expressions provide clear predictive information (angry, happy), others (surprised) are ambiguous in that they predict both positive and negative outcomes. Thus, surprised faces can delineate an individual’s valence bias, or the tendency to interpret ambiguity as positive or negative. Our initial negativity hypothesis suggests that the initial response to ambiguity is negative, and that positivity relies on emotion regulation. We tested this hypothesis by comparing brain activity during explicit emotion regulation (reappraisal) and while freely viewing facial expressions, and measuring the relationship between brain activity and valence bias. Brain regions recruited during reappraisal showed greater activity for surprise in individuals with an increasingly positive valence bias. Additionally, we linked amygdala activity with an initial negativity, revealing a pattern similarity in individuals with negative bias between viewing surprised faces and maintaining negativity. Finally, these individuals failed to show normal habituation to clear negativity. These results support the initial negativity hypothesis, and are consistent with emotion research in both children and adult populations

Individual differences in valence bias: fMRI evidence of the initial negativity hypothesis

Facial expressions offer an ecologically valid model for examining individual differences in affective decision-making. They convey an emotional signal from a social agent and provide important predictive information about one’s environment (presence of potential rewards or threats). Although some expressions provide clear predictive information (angry, happy), others (surprised) are ambiguous in that they predict both positive and negative outcomes. Thus, surprised faces can delineate an individual’s valence bias, or the tendency to interpret ambiguity as positive or negative. Our initial negativity hypothesis suggests that the initial response to ambiguity is negative, and that positivity relies on emotion regulation. We tested this hypothesis by comparing brain activity during explicit emotion regulation (reappraisal) and while freely viewing facial expressions, and measuring the relationship between brain activity and valence bias. Brain regions recruited during reappraisal showed greater activity for surprise in individuals with an increasingly positive valence bias. Additionally, we linked amygdala activity with an initial negativity, revealing a pattern similarity in individuals with negative bias between viewing surprised faces and maintaining negativity. Finally, these individuals failed to show normal habituation to clear negativity. These results support the initial negativity hypothesis, and are consistent with emotion research in both children and adult populations

Dairy Value Chain In Vietnam: Evidences from Bavi Area

Dairy farming, in Vietnam, existed in the early twentieth century thanks to the favorable natural advantage. During many difficult periods, the Vietnam’s dairy industry has developed constantly and contributed significantly to the food needs ensuring. However, Vietnam’s dairy industry still could not satisfy the domestic milk demand. Retail milk prices in Vietnam are very high, whereas the price of milk sold by the dairy farmers is very low. The cause stems from the control of dairy companies in the quantity and quality of milk. Moreover, that control caused an imbalance in the profits and benefits of each actor in the dairy value chain. This study, hence, finds out the distribution of benefits, costs, value-added among the actors, and problems in the practical management in dairy milk value chain with specific focus on Bavi as the case study

Numerical investigation of injury mechanism on the human knee of long-jumpers

Abstract : Long-jump is a vigorous athletic event with high speed. Due to so fast run-up and take-off velocities in horizontal and vertical badly injured. Based on the physical conditions of an ordinary Chinese man long-jumper, a combination of finite element analysis (FEA) and multi-body dynamics analysis (MDA) approach was tried analyzing the real and detailed long-jump process. Research results show that the maximum resultant force does appear the second phase of the long-jump and that the most notable deformation, displacement and the maximum stresses are all located at the medial sides, especially at the lateral condyle of the articular cartilage. Our results show the feasibility and effectiveness of performing MDA as a preliminary step to FEA, and provide an insight into the injury mechanism on the Human Knee of Long-jumpers.