Modeling transient aspects of coherence-driven electron transport

Non-equilibrium Green's function formalism (NEGF) by employing time-dependent (TD) perturbation theory is used to solve the electronic equations of motion of model systems under potential biasing conditions. The time propagation is performed in the full frequency domain of the two time variables representation. We analyze transient aspects of the resulting conductance under effects of applied direct-current and alternating current potentials. The coherence induced response dependence on different aspects of the applied perturbation is resolved in time and analyzed using calculated TD distributions of the current operator.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85419/1/jpconf10_220_012008.pd

Bone Marrow Transplantation for Feline Mucopolysaccharidosis I

Severe mucopolysaccharidosis type I (MPS I) is a fatal neuropathic lysosomal storage disorder with significant skeletal involvement. Treatment involves bone marrow transplantation (BMT), and although effective, is suboptimal, due to treatment sequelae and residual disease. Improved approaches will need to be tested in animal models and compared to BMT. Herein we report on bone marrow transplantation to treat feline mucopolysaccharidosis I (MPS I). Five MPS I stably engrafted kittens, transplanted with unfractionated bone marrow (6.3 × 107–1.1 × 109 nucleated bone marrow cells per kilogram) were monitored for 13–37 months post-engraftment. The tissue total glycosaminoglycan (GAG) content was reduced to normal levels in liver, spleen, kidney, heart muscle, lung, and thyroid. Aorta GAG content was between normal and affected levels. Treated cats had a significant decrease in the brain GAG levels relative to untreated MPS I cats and a paradoxical decrease relative to normal cats. The α-l-iduronidase (IDUA) activity in the livers and spleens of transplanted MPS I cats approached heterozygote levels. In kidney cortex, aorta, heart muscle, and cerebrum, there were decreases in GAG without significant increases in detectable IDUA activity. Treated animals had improved mobility and decreased radiographic signs of disease. However, significant pathology remained, especially in the cervical spine. Corneal clouding appeared improved in some animals. Immunohistochemical and biochemical analysis documented decreased central nervous system ganglioside storage. This large animal MPS I study will serve as a benchmark of future therapies designed to improve on BMT

Academic Performance and Behavioral Patterns

Identifying the factors that influence academic performance is an essential part of educational research. Previous studies have documented the importance of personality traits, class attendance, and social network structure. Because most of these analyses were based on a single behavioral aspect and/or small sample sizes, there is currently no quantification of the interplay of these factors. Here, we study the academic performance among a cohort of 538 undergraduate students forming a single, densely connected social network. Our work is based on data collected using smartphones, which the students used as their primary phones for two years. The availability of multi-channel data from a single population allows us to directly compare the explanatory power of individual and social characteristics. We find that the most informative indicators of performance are based on social ties and that network indicators result in better model performance than individual characteristics (including both personality and class attendance). We confirm earlier findings that class attendance is the most important predictor among individual characteristics. Finally, our results suggest the presence of strong homophily and/or peer effects among university students

Argumentation for explainable reasoning with conflicting medical recommendations

Designing a treatment path for a patient suffering from mul- tiple conditions involves merging and applying multiple clin- ical guidelines and is recognised as a difficult task. This is especially relevant in the treatment of patients with multiple chronic diseases, such as chronic obstructive pulmonary dis- ease, because of the high risk of any treatment change having potentially lethal exacerbations. Clinical guidelines are typi- cally designed to assist a clinician in treating a single condi- tion with no general method for integrating them. Addition- ally, guidelines for different conditions may contain mutually conflicting recommendations with certain actions potentially leading to adverse effects. Finally, individual patient prefer- ences need to be respected when making decisions. In this work we present a description of an integrated frame- work and a system to execute conflicting clinical guideline recommendations by taking into account patient specific in- formation and preferences of various parties. Overall, our framework combines a patient’s electronic health record data with clinical guideline representation to obtain personalised recommendations, uses computational argumentation tech- niques to resolve conflicts among recommendations while re- specting preferences of various parties involved, if any, and yields conflict-free recommendations that are inspectable and explainable. The system implementing our framework will allow for continuous learning by taking feedback from the decision makers and integrating it within its pipeline