Fifteen UM Students Receive Engineering Scholarships

Brevard, John G. Adler and Harper Johnson recipients hail from five state

Seniors Maximize Co-Op Experiences

Maddie Costelli and Adam Vonder Haar sharpened skills while working at Neel-Schaffer, Raytheo

Critical enabling conditions and challenges in the start-up phase of an international new venture : a social entrepreneur's perspective

This thesis explores the enabling conditions and challenges two entrepreneurs interpret critical in their relationships in the start-up phase of 5i, a social entrepreneurial international new venture (INV). The thesis delivers both interpretive ethnographic and auto-ethnographic accounts, weaving the voices of the two co-founders of 5i into a textual dialogue. The reader explores the relationship between the two entrepreneurs, and their relationships with their network partners, as they develop 5i into a small, innovative social entrepreneurial consulting practice that delivers innovative business incubation and financial engineering services from the firm's home base in New Delhi, India into rural markets in Brazil and China, as well as into the company's home market in India. The two entrepreneurs put to use their team and network relationships to mobilize knowledge, know-how, and capital; marshalling resources for their firm far beyond those they control. However, the entrepreneurs' relationships deliver more than functional, resource-based benefits. It is the, shared mission-related values, and the trust and the open communications they engender, in the entrepreneurs' relationships that emerge as key enabling conditions in the development of 5i. When mission-related values are not shared, significant challenges are confronted. The research presented in this thesis emphasizes interpretation and understanding grounded in the formation processes in a new enterprise, there where it is happening, not in rational explanation and prediction. Messy, thick, interpretive ethnographic and auto ethnographic texts provide rich detail which is then provoked through engagement with interpretive grounded theory methods to offer three pragmatic theoretical threads that contribute to our understanding of the roles of TMT and network relationships in the creation of social enterprises that move across international borders from birth. This combination of interpretive methods will not meet the positivist cry for testable hypothesis and universal theories, but it is hoped these methods deliver a compelling, local story. This thesis works to bring the voice of the entrepreneur back into research on entrepreneurship

Intersection Information based on Common Randomness

The introduction of the partial information decomposition generated a flurry of proposals for defining an intersection information that quantifies how much of "the same information" two or more random variables specify about a target random variable. As of yet, none is wholly satisfactory. A palatable measure of intersection information would provide a principled way to quantify slippery concepts, such as synergy. Here, we introduce an intersection information measure based on the G\'acs-K\"orner common random variable that is the first to satisfy the coveted target monotonicity property. Our measure is imperfect, too, and we suggest directions for improvement.Comment: 19 pages, 5 figure

Electrochemically directed synthesis of oligonucleotides for DNA microarray fabrication

We demonstrate a new method for making oligonucleotide microarrays by synthesis in situ. The method uses conventional DNA synthesis chemistry with an electrochemical deblocking step. Acid is delivered to specific regions on a glass slide, thus allowing nucleotide addition only at chosen sites. The acid is produced by electrochemical oxidation controlled by an array of independent microelectrodes. Deblocking is complete in a few seconds, when competing side-product reactions are minimal. We demonstrate the successful synthesis of 17mers and discrimination of single base pair mismatched hybrids. Features generated in this study are 40 μm wide, with sharply defined edges. The synthetic technique may be applicable to fabrication of other molecular arrays

A High-Speed Portable Ground Heat Exchanger Model for Use in Various Energy Simulation Software

A portable component model (PCM) of a ground source heat pump system was developed and used as a test case in the creating of a PCM development framework. By developing this framework, new building energy simulation models will be able to be easily integrated into existing simulation software such as EnergyPlus and the Modelica Buildings Library. Our model uses a time responsive g-function and numerical methods to simulate ground source heat pumps for single time steps as well as long time scales. We validated our model against GHESim and GLHEPro and found that our model agrees with these two standards within acceptable ranges of error. This allows for development of the PCM framework to have a functional test case for trouble shooting errors during the development process. Future work on this model to include non-uniform time steps would allow it to be used independent on other software as a standalone system

Coracoid Process Fracture in a High School Football Player

We presented a unique case of a high school athlete who suffered from a coracoid process fracture following a collision with an opposing player. This fracture is commonly misdiagnosed as a clavicular fracture or AC joint sprain. Initial radiographic examination may fail to identify the fracture site. Understanding the clinical features of this injury is an important prerequisite to its overall management. Any misdiagnosis or alteration from the appropriate course of treatment can inhibit return to play and may be avoided by using indicated diagnostic evaluation tools

Contextual directed acyclic graphs

Estimating the structure of directed acyclic graphs (DAGs) from observational data remains a significant challenge in machine learning. Most research in this area concentrates on learning a single DAG for the entire population. This paper considers an alternative setting where the graph structure varies across individuals based on available "contextual" features. We tackle this contextual DAG problem via a neural network that maps the contextual features to a DAG, represented as a weighted adjacency matrix. The neural network is equipped with a novel projection layer that ensures the output matrices are sparse and satisfy a recently developed characterization of acyclicity. We devise a scalable computational framework for learning contextual DAGs and provide a convergence guarantee and an analytical gradient for backpropagating through the projection layer. Our experiments suggest that the new approach can recover the true context-specific graph where existing approaches fail