Mathematical Modeling of Stress Strain Behavior of Newborn Mouse Aorta

The stress-strain behavior of materials is very important in determining their physical and mechanical properties. Whereas the stress-strain behaviors of different metals (isotropic and linear) can be easily determined by Hooke’s law, determining that of newborn mouse aorta (anisotropic and nonlinear) needs different approaches. The stress-strain behavior of newborn mouse aorta is highly nonlinear, and previous constitutive equations have been used to model the stress-strain behaviors of only adult mouse aorta. In other words, previous equations do not accurately represent the stress-strain behavior of newborn mouse aorta. This paper proposes a constitutive equation that represents the stress-strain behavior of newborn mice aortae. This strain energy function incorporates exponentials, but has some important differences from the previous models. Regression analysis in MATLAB shows that the proposed strain energy equation can accurately represent the stress-strain behavior of newborn mouse aorta

Mathematical Modeling of Stress Strain Behavior of Newborn Mouse Aorta with Genetic Defects

This project continues to fit the experimental data on the stress-strain behavior of newborn mice’s ascending aorta. The stress-strain behavior of newborn mouse aorta is highly nonlinear because of its unique composition of elastin and collagen in the arterial wall. To mathematically describe this behavior, more strain energy functions of different biological materials were used in fitting. Multiple error functions were used to improve accuracy. K-fold cross-validation was applied in regression to avoid overfitting. In addition to the data of aorta with elastin knockout, those of aorta with lysyl oxidase knockout and fibulin 4 knockout are also evaluated in this project using the strain energy functions found. It is noteworthy that in this report, acronyms for these types of aorta are used. Elastin knockout = ELN KO, Fibulin 4 Knockout = FIB 4 KO, Lysyl Oxidase knockout = LOX KO, Wild Type = WT. Regression results from MATLAB shows that while the strain energy functions provide accurate fitting overall, improvements on the regression model can still be made to minimize the errors in cross validation. The strain energy and stiffness in the loading cycle are computed using the results returned by MATLAB: the strain energy for aorta with genetic defects is smaller than that for wild type samples. Comparing this difference may help to understand cardiovascular disease related to genetic defects

Brand strategy and brand evolution: welcome to the world of the meme

This paper explores the idea of the meme as it relates to branding. In evolutionary theory the meme is the cultural equivalent of the gene. Memes are seen as self replicating entities which jump from human host to human host. In a similar way to the gene in the biological world, there is a complex changing business environment where some memes are successful and others are not. This paper argues that brands are meme like entities, conforming to the dictates of evolutionary theory. An important question is also raised concerning the most appropriate way to research the meme phenomenon. Considerable existing research in branding argues that success results from the increasing complexity of brand management and strategy. The memetic approach provides a different perspective on brand success however. Memetics does not argue for sophistication and complexity as a route to success. Natural selection is based purely on the fitness of the meme. The ability of the latter to survive is depended on its fitness of reproduction in a hostile environment. This theory and its research applicability to branding is explored. Finally, another property of evolution, the concept of mutation, is also briefly examined. It is argued here that brand mutations can have both positive and negative impact on brand building. Consumers, as the hosts of brand memes, could play a vital part in the reproduction process where error copying occurs

MEMS 411: Design of a wiffle ball pitching machine

This project designs a wiffle ball pitching machine that would demonstrate the Magus Effect to the audience in St. Louis Science Center. Primarily made out of wood, this design is portable and able to pitch wiffle balls both indoor and outdoor. With two spinning wheels whose maximum spinning rate is 5044 rpm, this design is able to pitch balls with topspin, backspin, and no spin, and the trajectory of the traveling balls can be recorded by naked eye. The highest recorded traveling velocity of the pitched ball is 67 mph. Several function that would facilitate the demo process are included in this design: accurate pitching and angle adjusting--it is able to pitch balls at an angle range of 0 degrees to 90 degrees and in the testing trial, 12/12 balls are able to hit a 20\u27 by 20\u27 target placed 20 feet away from the machine. There are several risks that a user might take notice of when using the machine: the spinning wheels might scratch a user\u27s hand when it gets too close; the wires connected to the motor would trip users; a user might be hit by a traveling wiffle ball; and if used improperly, a user may get electric shock. Warning signs are prepared on the device to prevent the such risks for happening

A Contextual Bandit Approach for Value-oriented Prediction Interval Forecasting

Prediction interval (PI) is an effective tool to quantify uncertainty and usually serves as an input to downstream robust optimization. Traditional approaches focus on improving the quality of PI in the view of statistical scores and assume the improvement in quality will lead to a higher value in the power systems operation. However, such an assumption cannot always hold in practice. In this paper, we propose a value-oriented PI forecasting approach, which aims at reducing operational costs in downstream operations. For that, it is required to issue PIs with the guidance of operational costs in robust optimization, which is addressed within the contextual bandit framework here. Concretely, the agent is used to select the optimal quantile proportion, while the environment reveals the costs in operations as rewards to the agent. As such, the agent can learn the policy of quantile proportion selection for minimizing the operational cost. The numerical study regarding a two-timescale operation of a virtual power plant verifies the superiority of the proposed approach in terms of operational value. And it is especially evident in the context of extensive penetration of wind power.Comment: submitted to IEEE Transactions on Smart Gri

Invariant Random Forest: Tree-Based Model Solution for OOD Generalization

Out-Of-Distribution (OOD) generalization is an essential topic in machine learning. However, recent research is only focusing on the corresponding methods for neural networks. This paper introduces a novel and effective solution for OOD generalization of decision tree models, named Invariant Decision Tree (IDT). IDT enforces a penalty term with regard to the unstable/varying behavior of a split across different environments during the growth of the tree. Its ensemble version, the Invariant Random Forest (IRF), is constructed. Our proposed method is motivated by a theoretical result under mild conditions, and validated by numerical tests with both synthetic and real datasets. The superior performance compared to non-OOD tree models implies that considering OOD generalization for tree models is absolutely necessary and should be given more attention.Comment: AAAI Conference on Artificial Intelligence, 2024 (Oral Presentation

China and international ownership: exploring consumer perceptions of brand equity and a new country of origin

Exploring perceptions of brand in country of origin. Many A2 Business Studies and Economics courses now have aspects of international business as part of the specification content. This article is a summary of work being conducted on the effects of changes in brand ownership on consumer perceptions. Emerging economies are not only developing their own businesses but also acquiring brand names and businesses from around the world. Will this have effects on the way consumers perceive these businesses and brands? Will it necessitate a change in global marketing strategies? This article outlines some of the thinking on these important issues. Some questions are provided to enable teachers to use the article with students in the classroom to promote thinking in this important are

Fan‘s commitment to sport team : a case study of FC Barcelona

Treballs Finals del Màster en Direcció d'Empreses de l'Esport, Facultat d'Economia i Empresa, Universitat de Barcelona. Curs: 2021-2022. Tutor: Mel Solé MoroDebido a diversas razones, la asistencia del FC Barcelona ha disminuido, la pérdida de seguidores ha sido importante y el compromiso psicológico de los aficionados se ha visto muy afectado. Basándose en el modelo de investigación existente, este artículo resume seis factores que influyen en el compromiso psicológico de los aficionados, y luego introduce el compromiso psicológico como variable de resultado para construir un modelo conceptual del compromiso psicológico de los aficionados del FC Barcelona, que se utiliza para estudiar la magnitud de la influencia de los seis factores diferentes. Se recogieron datos de los aficionados del FC Barcelona y los resultados indicaron efectos positivos significativos de la identidad personal, el compromiso afectivo, el coste de los recursos, el coste psicológico y el tribalismo regional en el compromiso psicológico de los aficionados; por último, basándonos en la situación de desarrollo del FC Barcelona, presentamos sugerencias y perspectivas de gestión sobre cómo mejorar la eficacia de la marca, potenciar la construcción de la marca y estabilizar el compromiso psicológico de los aficionados, proporcionando orientación teórica y práctica para su funcionamiento y desarrollo futuros