Efficient Processing of k Nearest Neighbor Joins using MapReduce

k nearest neighbor join (kNN join), designed to find k nearest neighbors from a dataset S for every object in another dataset R, is a primitive operation widely adopted by many data mining applications. As a combination of the k nearest neighbor query and the join operation, kNN join is an expensive operation. Given the increasing volume of data, it is difficult to perform a kNN join on a centralized machine efficiently. In this paper, we investigate how to perform kNN join using MapReduce which is a well-accepted framework for data-intensive applications over clusters of computers. In brief, the mappers cluster objects into groups; the reducers perform the kNN join on each group of objects separately. We design an effective mapping mechanism that exploits pruning rules for distance filtering, and hence reduces both the shuffling and computational costs. To reduce the shuffling cost, we propose two approximate algorithms to minimize the number of replicas. Extensive experiments on our in-house cluster demonstrate that our proposed methods are efficient, robust and scalable.Comment: VLDB201

NATURE OF THE LATE CARBONIFEROUS TO TRIASSIC MAGMATISM ALONG THE NORTHERN MARGIN OF THE NORTH CHINA BLOCK: LINK WITH THE EVOLUTION OF THE CENTRAL ASIAN OROGEN

There are two episodes of magmatism along the northern margin of the North China block during the Late Carboniferous to Late Triassic, one at 310–250 Ma (Late Carboniferous to Permian) and the other at 235–210 Ma (Late Triassic). The former group comprises plutonic rocks (gabbro-diorite-monzodioritemonzogranite-granite), mafic to intermediate dykes (diorite to dolerite) and a few felsic volcanics (andesite to dacite).There are two episodes of magmatism along the northern margin of the North China block during the Late Carboniferous to Late Triassic, one at 310–250 Ma (Late Carboniferous to Permian) and the other at 235–210 Ma (Late Triassic). The former group comprises plutonic rocks (gabbro-diorite-monzodioritemonzogranite-granite), mafic to intermediate dykes (diorite to dolerite) and a few felsic volcanics (andesite to dacite)

COX-2 Inhibitor Nimesulide Analogs are Aromatase Suppressors in Breast Cancer Cells

Cyclooxygenase-2 (COX-2) inhibitor nimesulide derivatives compounds A and B decreased aromatase activity in breast cancer cells via a novel mechanism different to aromatase inhibitors (AIs), and were defined as “aromatase suppressors”. Breast carcinoma cells (MCF-7aro and T47Daro) transfected with aromatase full gene were used to explore the mechanisms of the two compounds. They dose and time-dependently suppressed aromatase activity in MCF-7aro and T47Daro cells in the nanomole range. However, they neither directly inhibited aromatase, nor improved aromatase degradation even at much higher concentrations. They could also suppress androgen stimulated cell growth, but did not affect estrogen enhanced cell proliferation. These results suggest that compounds A and B selectively interfere with aromatase in breast cancer cells, but not estrogen receptor (ER) downstream to disrupt androgen mediated cell growth. Interestingly, compound B effectively inhibited LTED (long-term estrogen deprived MCF-7aro cell) cell growth, which is a model for AIs resistance, with an IC50 of 4.68 ± 0.54 μM. The results indicate that compound B could potentially overcome AI resistance in breast cancer cell and could be used as a lead to design more potent derivatives

A Fast Learning Method for Multilayer Perceptrons in Automatic Speech Recognition Systems

We propose a fast learning method for multilayer perceptrons (MLPs) on large vocabulary continuous speech recognition (LVCSR) tasks. A preadjusting strategy based on separation of training data and dynamic learning-rate with a cosine function is used to increase the accuracy of a stochastic initial MLP. Weight matrices of the preadjusted MLP are restructured by a method based on singular value decomposition (SVD), reducing the dimensionality of the MLP. A back propagation (BP) algorithm that fits the unfolded weight matrices is used to train the restructured MLP, reducing the time complexity of the learning process. Experimental results indicate that on LVCSR tasks, in comparison with the conventional learning method, this fast learning method can achieve a speedup of around 2.0 times with improvement on both the cross entropy loss and the frame accuracy. Moreover, it can achieve a speedup of approximately 3.5 times with only a little loss of the cross entropy loss and the frame accuracy. Since this method consumes less time and space than the conventional method, it is more suitable for robots which have limitations on hardware

Growth Factor Signaling Enhances Aromatase Activity of Breast Cancer Cells Via Post-Transcriptional Mechanisms

It has been demonstrated that growth factors produced by breast cancer cells stimulate aromatase expression in both breast cancer and adjacent adipose fibroblasts and stromal cells. However, whether these growth factors affect aromatase activity by other mechanisms still remain unclear. In the current study, MCF-7aro and T47Daro aromatase transfected breast carcinoma cells were used to explore the mechanisms of post-transcriptional regulation of aromatase activity by growth factor pathways. Our study reveals that PI3K/Akt and MAPK inhibitors suppressed aromatase activity in MCF-7aro cells. However, PI3K/Akt pathway inhibitors stimulated aromatase activity in T47Daro cells. This is due to enhanced MAPK phosphorylation as compensation after the PI3K/Akt pathway has been blocked. IGF-1 treatment increased aromatase activity in both breast cancer cell lines. In addition, LTEDaro cells (long-term estrogen deprived MCF-7aro cells) which have enhanced MAPK activity, show higher aromatase activity compared to parental MCF-7aro cells, but the aromatase protein level remains the same. These results suggest that aromatase activity could be enhanced by growth factor signaling pathways via post-transcriptional mechanisms

Ethnic differences and heritability of blood pressure circadian rhythm in African and European American youth and young adults

Background: The aim of this study was to investigate whether blood pressure (BP) circadian rhythm in African Americans differed from that in European Americans. We further examined the genetic and/or environmental sources of variances of the BP circadian rhythm parameters and the extent to which they depend on ethnicity or sex. Method: Quantification of BP circadian rhythm was obtained using Fourier transformation from the ambulatory BP monitoring data of 760 individuals (mean age, 17.2 +/- 3.3; 322 twin pairs and 116 singletons; 351 African Americans). Results: BP circadian rhythm showed a clear difference by ethnic group with African Americans having a lower amplitude (P = 1.5e-08), a lower percentage rhythm (P = 2.8e-11), a higher MESOR (P = 2.5e-05) and being more likely not to display circadian rhythm (P = 0.002) or not in phase (P = 0.003). Familial aggregation was identified for amplitude, percentage rhythm and acrophase with genetic factors and common environmental factors together accounting for 23 to 33% of the total variance of these BP circadian rhythm parameters. Unique environmental factors were the largest contributor explaining up to 67--77% of the total variance of these parameters. No sex or ethnicity difference in the variance components of BP circadian rhythm was observed. Conclusion: This study suggests that ethnic differences in BP circadian rhythm already exist in youth with African Americans having a dampened circadian rhythm and better BP circadian rhythm may be achieved by changes in environmental factors

CacBDD: A BDD Package with Dynamic Cache Management

Abstract. In this paper, we present CacBDD, a new efficient BDD (Binary Decision Diagrams) package. It implements a dynamic cache management algorithm, which takes account of the hit-rate of computed table and available memory. Experiments on the BDD benchmarks of both combinational circuits and model checking show that CacBDD is more efficient compared with the state-of-the-art BDD package CUDD