ClubGrove

The current Santa Clara University Club system does not provide the necessary information in a relevant and concise fashion. As a solution, we built a system that caters towards students who are looking for clubs. In addition, the system also caters towards club leaders who want to increase their clubs’ visibility. Our system allows students to look up clubs, search club events, and look at interested clubs as well as previously joined clubs. The goal of this project is to provide an easy way for students to be involved in more clubs and allow clubs to gain members without spending much financial or temporal resources

Polymorphism in glutathione S-transferase P1 is associated with susceptibility to chemotherapyinduced leukemia

Glutathione S-transferases (GSTs) detoxify potentially mutagenic and toxic DNA-reactive electrophiles, including metabolites of several chemotherapeutic agents, some of which are suspected human carcinogens. Functional polymorphisms exist in at least three genes that encode GSTs, including GSTM1, GSTT1, and GSTP1. We hypothesize, therefore, that polymorphisms in genes that encode GSTs alter susceptibility to chemotherapy-induced carcinogenesis, specifically to therapy-related acute myeloid leukemia (t-AML), a devastating complication of long-term cancer survival. Elucidation of genetic determinants may help to identify individuals at increased risk of developing t-AML. To this end, we have examined 89 cases of t-AML, 420 cases of de novo AML, and 1,022 controls for polymorphisms in GSTM1, GSTT1, and GSTP1. Gene deletion of GSTM1 or GSTT1 was not specifically associated with susceptibility to t-AML. Individuals with at least one GSTP1 codon 105 Val allele were significantly over-represented in t-AML cases compared with de novo AML cases [odds ratio (OR), 1.81; 95% confidence interval (CI), 1.11–2.94]. Moreover, relative to de novo AML, the GSTP1 codon 105 Val allele occurred more often among t-AML patients with prior exposure to chemotherapy (OR, 2.66; 95% CI, 1.39–5.09), particularly among those with prior exposure to known GSTP1 substrates (OR, 4.34; 95% CI, 1.43–13.20), and not among those t-AML patients with prior exposure to radiotherapy alone (OR,1.01; 95% CI, 0.50–2.07). These data suggest that inheritance of at least one Val allele at GSTP1 codon 105 confers a significantly increased risk of developing t-AML after cytotoxic chemotherapy, but not after radiotherapy

The Wide Brown Dwarf Binary Oph 1622-2405 and Discovery of A Wide, Low Mass Binary in Ophiuchus (Oph 1623-2402): A New Class of Young Evaporating Wide Binaries?

We imaged five objects near the star forming clouds of Ophiuchus with the Keck Laser Guide Star AO system. We resolved Allers et al. (2006)'s #11 (Oph 16222-2405) and #16 (Oph 16233-2402) into binary systems. The #11 object is resolved into a 243 AU binary, the widest known for a very low mass (VLM) binary. The binary nature of #11 was discovered first by Allers (2005) and independently here during which we obtained the first spatially resolved R~2000 near-infrared (J & K) spectra, mid-IR photometry, and orbital motion estimates. We estimate for 11A and 11B gravities (log(g)>3.75), ages (5+/-2 Myr), luminosities (log(L/Lsun)=-2.77+/-0.10 and -2.96+/-0.10), and temperatures (Teff=2375+/-175 and 2175+/-175 K). We find self-consistent DUSTY evolutionary model (Chabrier et al. 2000) masses of 17+4-5 MJup and 14+6-5 MJup, for 11A and 11B respectively. Our masses are higher than those previously reported (13-15 MJup and 7-8 MJup) by Jayawardhana & Ivanov (2006b). Hence, we find the system is unlikely a ``planetary mass binary'', (in agreement with Luhman et al. 2007) but it has the second lowest mass and lowest binding energy of any known binary. Oph #11 and Oph #16 belong to a newly recognized population of wide (>100 AU), young (<10 Myr), roughly equal mass, VLM stellar and brown dwarf binaries. We deduce that ~6+/-3% of young (<10 Myr) VLM objects are in such wide systems. However, only 0.3+/-0.1% of old field VLM objects are found in such wide systems. Thus, young, wide, VLM binary populations may be evaporating, due to stellar encounters in their natal clusters, leading to a field population depleted in wide VLM systems.Comment: Accepted version V2. Now 13 pages longer (45 total) due to a new discussion of the stability of the wide brown dwarf binary population, new summary Figure 17 now included, Astrophysical Journal 2007 in pres

Visualizing landscapes of the superconducting gap in heterogeneous superconductor thin films: geometric influences on proximity effects

The proximity effect is a central feature of superconducting junctions as it underlies many important applications in devices and can be exploited in the design of new systems with novel quantum functionality. Recently, exotic proximity effects have been observed in various systems, such as superconductor-metallic nanowires and graphene-superconductor structures. However, it is still not clear how superconducting order propagates spatially in a heterogeneous superconductor system. Here we report intriguing influences of junction geometry on the proximity effect for a 2D heterogeneous superconductor system comprised of 2D superconducting islands on top of a surface metal. Depending on the local geometry, the superconducting gap induced in the surface metal region can either be confined to the boundary of the superconductor, in which the gap decays within a short distance (~ 15 nm), or can be observed nearly uniformly over a distance of many coherence lengths due to non-local proximity effects.Comment: 17 pages, 4 figure

Exascale Deep Learning to Accelerate Cancer Research

Deep learning, through the use of neural networks, has demonstrated remarkable ability to automate many routine tasks when presented with sufficient data for training. The neural network architecture (e.g. number of layers, types of layers, connections between layers, etc.) plays a critical role in determining what, if anything, the neural network is able to learn from the training data. The trend for neural network architectures, especially those trained on ImageNet, has been to grow ever deeper and more complex. The result has been ever increasing accuracy on benchmark datasets with the cost of increased computational demands. In this paper we demonstrate that neural network architectures can be automatically generated, tailored for a specific application, with dual objectives: accuracy of prediction and speed of prediction. Using MENNDL--an HPC-enabled software stack for neural architecture search--we generate a neural network with comparable accuracy to state-of-the-art networks on a cancer pathology dataset that is also $16\times$ faster at inference. The speedup in inference is necessary because of the volume and velocity of cancer pathology data; specifically, the previous state-of-the-art networks are too slow for individual researchers without access to HPC systems to keep pace with the rate of data generation. Our new model enables researchers with modest computational resources to analyze newly generated data faster than it is collected.Comment: Submitted to IEEE Big Dat

Design and Evaluation of a Retrofittable Electric Snow Melting System for Pavements

Gemstone Team SnowMeltThe objective of this research is to develop a novel electrically conductive heating system that can be retrofitted to existing asphalt pavements. This system is designed for permanent installation on the pavement surface, thus eliminating the expensive reconstruction required for embedded systems and the inconvenience of placing and then removing portable heating mats. The research approach combined theoretical analyses based on the physics of the problem, laboratory explorations of potential system components, and large scale testing to evaluate the constructability, functionality, and efficiency of the full system. The final system design consisted of a low-voltage grid of Nickel Chromium wire resistance heaters embedded in an asphalt sealcoat surface layer. Outdoor testing during an actual snowstorm conclusively demonstrated the effectiveness of the system for melting snow, even during continuing accumulations. Based on these evaluations, several practical designs suitable for production use are suggested. Installation and operating costs are also evaluated

Prospecting environmental mycobacteria: combined molecular approaches reveal unprecedented diversity

Background: Environmental mycobacteria (EM) include species commonly found in various terrestrial and aquatic environments, encompassing animal and human pathogens in addition to saprophytes. Approximately 150 EM species can be separated into fast and slow growers based on sequence and copy number differences of their 16S rRNA genes. Cultivation methods are not appropriate for diversity studies; few studies have investigated EM diversity in soil despite their importance as potential reservoirs of pathogens and their hypothesized role in masking or blocking M. bovis BCG vaccine. Methods: We report here the development, optimization and validation of molecular assays targeting the 16S rRNA gene to assess diversity and prevalence of fast and slow growing EM in representative soils from semi tropical and temperate areas. New primer sets were designed also to target uniquely slow growing mycobacteria and used with PCR-DGGE, tag-encoded Titanium amplicon pyrosequencing and quantitative PCR. Results: PCR-DGGE and pyrosequencing provided a consensus of EM diversity; for example, a high abundance of pyrosequencing reads and DGGE bands corresponded to M. moriokaense, M. colombiense and M. riyadhense. As expected pyrosequencing provided more comprehensive information; additional prevalent species included M. chlorophenolicum, M. neglectum, M. gordonae, M. aemonae. Prevalence of the total Mycobacterium genus in the soil samples ranged from 2.3×107 to 2.7×108 gene targets g−1; slow growers prevalence from 2.9×105 to 1.2×107 cells g−1. Conclusions: This combined molecular approach enabled an unprecedented qualitative and quantitative assessment of EM across soil samples. Good concordance was found between methods and the bioinformatics analysis was validated by random resampling. Sequences from most pathogenic groups associated with slow growth were identified in extenso in all soils tested with a specific assay, allowing to unmask them from the Mycobacterium whole genus, in which, as minority members, they would have remained undetected