Form measurements of micro-holes

The form measurement and gauge repeatability and reproducibility (R&R) of a micro-hole using a coordinate measurement machine (CMM) with a combination of optical and contact sensors were conducted in this study. The micro-holes, about 160 µm in diameter and 0.9 mm in depth, were fabricated using the electrical discharge machining process for diesel fuel injectors. The shape and size of micro-holes are important for the desired spray pattern, fuel economy and exhaust emission of diesel engines. In this study, the setup of the measurement machine and the procedure to determine the contact points are presented. Five form characteristics, the cylindricity, diameter, roundness, straightness and taper, of the micro-hole are analyzed from measurement points. The gauge R&R test is conducted to determine the micro-hole form measurement capability and to calculate the tolerance specifications for each characteristic that the CMM is capable of measuring. An example to quantify the change in the shape of the micro-holes before and after the abrasive flow machining is presented.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/58130/2/mst7_11_045.pd

Streaming Graph Challenge: Stochastic Block Partition

An important objective for analyzing real-world graphs is to achieve scalable performance on large, streaming graphs. A challenging and relevant example is the graph partition problem. As a combinatorial problem, graph partition is NP-hard, but existing relaxation methods provide reasonable approximate solutions that can be scaled for large graphs. Competitive benchmarks and challenges have proven to be an effective means to advance state-of-the-art performance and foster community collaboration. This paper describes a graph partition challenge with a baseline partition algorithm of sub-quadratic complexity. The algorithm employs rigorous Bayesian inferential methods based on a statistical model that captures characteristics of the real-world graphs. This strong foundation enables the algorithm to address limitations of well-known graph partition approaches such as modularity maximization. This paper describes various aspects of the challenge including: (1) the data sets and streaming graph generator, (2) the baseline partition algorithm with pseudocode, (3) an argument for the correctness of parallelizing the Bayesian inference, (4) different parallel computation strategies such as node-based parallelism and matrix-based parallelism, (5) evaluation metrics for partition correctness and computational requirements, (6) preliminary timing of a Python-based demonstration code and the open source C++ code, and (7) considerations for partitioning the graph in streaming fashion. Data sets and source code for the algorithm as well as metrics, with detailed documentation are available at GraphChallenge.org.Comment: To be published in 2017 IEEE High Performance Extreme Computing Conference (HPEC

Engineered yeast for enhanced CO2 mineralization

In this work, a biologically catalysed CO2 mineralization process for the capture of CO2 from point sources was designed, constructed at a laboratory scale, and, using standard chemical process scale-up protocols, was modelled and evaluated at an industrial scale. A yeast display system in Saccharomyces cerevisae was used to screen several carbonic anhydrase isoforms and mineralization peptides for their impact on CO2 hydration, CaCO3 mineralization, and particle settling rate. Enhanced rates for each of these steps in the CaCO3 mineralization process were confirmed using quantitative techniques in lab-scale measurements. The effect of these enhanced rates on the CO2 capture cost in an industrial scale CO2 mineralization process using coal fly ash as the CaO source was evaluated. The model predicts a process using bCA2-yeast and fly ash is [similar]10% more cost effective per tonne of CO2 captured than a process with no biological molecules, a savings not realized by wild-type yeast and high-temperature stable recombinant CA2 alone or in combination. The levelized cost of electricity for a power plant using this process was calculated and scenarios in which this process compares favourably to CO2 capture by MEA absorption process are presented.MIT Energy InitiativeEni S.p.A. (Firm)National Institutes of Health (U.S.) (NIH Biotechnology Training Program)Thomas and Stacey Siebel Foundatio

Community structure and ethnic preferences in school friendship networks

Recently developed concepts and techniques of analyzing complex systems provide new insight into the structure of social networks. Uncovering recurrent preferences and organizational principles in such networks is a key issue to characterize them. We investigate school friendship networks from the Add Health database. Applying threshold analysis, we find that the friendship networks do not form a single connected component through mutual strong nominations within a school, while under weaker conditions such interconnectedness is present. We extract the networks of overlapping communities at the schools (c-networks) and find that they are scale free and disassortative in contrast to the direct friendship networks, which have an exponential degree distribution and are assortative. Based on the network analysis we study the ethnic preferences in friendship selection. The clique percolation method we use reveals that when in minority, the students tend to build more densely interconnected groups of friends. We also find an asymmetry in the behavior of black minorities in a white majority as compared to that of white minorities in a black majority.Comment: submitted to Physica

GraphChallenge.org: Raising the Bar on Graph Analytic Performance

The rise of graph analytic systems has created a need for new ways to measure and compare the capabilities of graph processing systems. The MIT/Amazon/IEEE Graph Challenge has been developed to provide a well-defined community venue for stimulating research and highlighting innovations in graph analysis software, hardware, algorithms, and systems. GraphChallenge.org provides a wide range of pre-parsed graph data sets, graph generators, mathematically defined graph algorithms, example serial implementations in a variety of languages, and specific metrics for measuring performance. Graph Challenge 2017 received 22 submissions by 111 authors from 36 organizations. The submissions highlighted graph analytic innovations in hardware, software, algorithms, systems, and visualization. These submissions produced many comparable performance measurements that can be used for assessing the current state of the art of the field. There were numerous submissions that implemented the triangle counting challenge and resulted in over 350 distinct measurements. Analysis of these submissions show that their execution time is a strong function of the number of edges in the graph, $N_e$, and is typically proportional to $N_e^{4/3}$ for large values of $N_e$. Combining the model fits of the submissions presents a picture of the current state of the art of graph analysis, which is typically $10^8$ edges processed per second for graphs with $10^8$ edges. These results are $30$ times faster than serial implementations commonly used by many graph analysts and underscore the importance of making these performance benefits available to the broader community. Graph Challenge provides a clear picture of current graph analysis systems and underscores the need for new innovations to achieve high performance on very large graphs.Comment: 7 pages, 6 figures; submitted to IEEE HPEC Graph Challenge. arXiv admin note: text overlap with arXiv:1708.0686

Delivery of Proteases in Aqueous Two‐Phase Systems Enables Direct Purification of Stem Cell Colonies from Feeder Cell Co‐Cultures for Differentiation into Functional Cardiomyocytes

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/101762/1/1440_ftp.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/101762/2/adhm_201300049_sm_suppl.pd

Recurrent MEIS1-NCOA2/1 fusions in a subset of low-grade spindle cell sarcomas frequently involving the genitourinary and gynecologic tracts

Sarcomas with MEIS1-NCOA2 fusions have been so far reported in 2 cases each of primitive renal sarcomas and intraosseous pelvic rhabdomyosarcomas. Their histologic spectrum, anatomic distribution, and clinical behavior remain poorly defined. In this study, we report 6 additional spindle cell sarcomas with MEIS1-NCOA2 or NCOA1 fusions that fall into the same disease spectrum with the previously reported renal sarcomas. The patients’ age range was wide (20–76 years, mean 46) and all except one were female. The tumors arose in the kidney (n=2), and one each in the uterine corpus, vagina, scrotum, and para-rectal region. The consistent morphology was that of monomorphic spindle to ovoid cells in a storiform, whorling, or solid pattern. Alternating cellularity, myxoid stroma, and microcystic changes were seen in some cases. Mitotic activity varied greatly (<1–33/10 high power fields). The immunophenotype was non-specific, with most cases expressing variable degrees of TLE1, WT1, cyclin D1, CD56, and CD10. Using various platforms of RNA-based targeted sequencing, MEIS1-NCOA2 fusions were recurrently identified in 5 cases, and a novel MEIS1-NCOA1 fusion was found in one renal tumor. The gene fusions were validated by fluorescence in situ hybridization using custom BAC probes. Of the 5 patients with available follow-up (5 months to 8 years), all experienced local recurrences, but no distant spread or death from disease. Our results expand the clinicopathologic spectrum of sarcomas with MEIS1-NCOA2/1 fusions, providing evidence of an undifferentiated spindle cell phenotype with non-specific immunoprofile and low-grade clinical behavior

Small- and large-scale network structure of live fish movements in Scotland

Networks are increasingly being used as an epidemiological tool for studying the potential for disease transmission through animal movements in farming industries. We analysed the network of live fish movements for commercial salmonids in Scotland in 2003. This network was found to have a mixture of features both aiding and hindering disease transmission, hindered by being fragmented, with comparatively low mean number of connections (2.83), and low correlation between inward and outward connections (0.12), with moderate variance in these numbers (coefficients of dispersion of 0.99 and 3.12 for in and out respectively); but aided by low levels of clustering (0.060) and some non-random mixing (coefficient of assortativity of 0.16). Estimated inter-site basic reproduction number R0 did not exceed 2.4 at high transmission rate. The network was strongly organised into communities, resulting in a high modularity index (0.82). Arc (directed connection) removal indicated that effective surveillance of a small number of connections may facilitate a large reduction in the potential for disease spread within the industry. Useful criteria for identification of these important arcs included degree- and betweenness-based measures that could in future prove useful for prioritising surveillance

Soft Tissue Tumors Characterized by a Wide Spectrum of Kinase Fusions Share a Lipofibromatosis-like Neural Tumor Pattern

Gene fusions resulting in oncogenic activation of various receptor tyrosine kinases, including NTRK1-3, ALK, and RET, have been increasingly recognized in soft tissue tumors (STTs), displaying a wide morphologic spectrum and therefore diagnostically challenging. A subset of STT with NTRK1 rearrangements were recently defined as lipofibromatosis-like neural tumors (LPFNTs), being characterized by mildly atypical spindle cells with a highly infiltrative growth in the subcutis and expression of S100 and CD34 immunostains. Other emerging morphologic phenotypes associated with kinase fusions include infantile/adult fibrosarcoma and malignant peripheral nerve sheath tumor-like patterns. In this study, a large cohort of 73 STT positive for various kinase fusions, including 44 previously published cases, was investigated for the presence of an LPFNT phenotype, to better define the incidence of this distinctive morphologic pattern and its relationship with various gene fusions. Surprisingly, half (36/73) of STT with kinase fusions showed at least a focal LPFNT component defined as >10%. Most of the tumors occurred in the subcutaneous tissues of the extremities (n = 25) and trunk (n = 9) of children or young adults (<30 years old) of both genders. Two-thirds (24/36) of these cases showed hybrid morphologies with alternating LPFNT and solid areas of monomorphic spindle to ovoid tumor cells with fascicular or haphazard arrangement, while one-third (12/36) had pure LPFNT morphology. Other common histologic findings included lymphocytic infiltrates, staghorn-like vessels, and perivascular or stromal hyalinization, especially in hybrid cases. Mitotic activity was generally low (<4/10 high power fields in 81% cases), being increased only in a minority of cases. Immunoreactivity for CD34 (92% in hybrid cases, 89% in pure cases) and S100 (89% in hybrid cases, 64% in pure cases) were commonly present. The gene rearrangements most commonly involved NTRK1 (75%), followed by RET (8%) and less commonly NTRK2, NTRK3, ROS1, ALK, and MET