On discovery of extremely low-dimensional clusters using semi-supervised projected clustering

Recent studies suggest that projected clusters with extremely low dimensionality exist in many real datasets. A number of projected clustering algorithms have been proposed in the past several years, but few can identify clusters with dimensionality lower than 10% of the total number of dimensions, which are commonly found in some real datasets such as gene expression profiles. In this paper we propose a new algorithm that can accurately identify projected clusters with relevant dimensions as few as 5% of the total number of dimensions. It makes use of a robust objective function that combines object clustering and dimension selection into a single optimization problem. The algorithm can also utilize domain knowledge in the form of labeled objects and labeled dimensions to improve its clustering accuracy. We believe this is the first semi-supervised projected clustering algorithm. Both theoretical analysis and experimental results show that by using a small amount of input knowledge, possibly covering only a portion of the underlying classes, the new algorithm can be further improved to accurately detect clusters with only 1% of the dimensions being relevant. The algorithm is also useful in getting a target set of clusters when there are multiple possible groupings of the objects. © 2005 IEEE.published_or_final_versio

A model for stripping multicomponent vapor from unsaturated soil with free and trapped residual nonaqueous phase liquid

We present a model for the multicomponent vapor transport due to air venting in an unsaturated zone in the presence of free and trapped phases of residual nonaqueous phase liquid (NAPL). On the microscale the soil particles are assumed to form spherical aggregates with micropores filled with-immobile water, trapped phases of NAPL and air. The interaggregate space is occupied with mobile air, and a thin film of free NAPL adheres on the aggregate surface. While the free NAPL can readily be in equilibrium with macropore vapor, the mass transfer from immobile phases inaggregates is rate-limited by aqueous diffusion. This model enables us to predict the vapor concentrations of various chemical species and the free NAPL saturation over the macroscale, based on the detailed understanding of the aqueous concentrations of the species and the trapped NAPL saturation within the aggregates. The model is compared favorably with some experimental data of sparging multicomponent vapor out of an intact core taken from a contaminated site. The distinctive features of multicomponent transport, clearly exhibited by the data, are further examined in the simulations of a hypothetical case of three-aromatic vapor transport under a radial flow field. It is found that while the vapor concentration of the most volatile component drops monotonically with time, those of the less volatile may rise as their mole fractions in the NAPL increase. The vapor concentration of a heavy component may have a local maximum at the evaporation front of the free NAPL. In the case of radial flow the free NAPL has two receding evaporation fronts. Condensation of the heavy component downstream of the far front causes a temporary increase of its total concentration there. With trapped NAPL and soil aggregation the macroscale transport is retarded, and the effluent concentrations end up in noticeable tailing.published_or_final_versio

HARP: A practical projected clustering algorithm

In high-dimensional data, clusters can exist in subspaces that hide themselves from traditional clustering methods. A number of algorithms have been proposed to Identify such projected clusters, but most of them rely on some user parameters to guide the clustering process. The clustering accuracy can be seriously degraded If incorrect values are used. Unfortunately, in real situations, it is rarely possible for users to supply the parameter values accurately, which causes practical difficulties in applying these algorithms to real data. In this paper, we analyze the major challenges of projected clustering and suggest why these algorithms need to depend heavily on user parameters. Based on the analysis, we propose a new algorithm that exploits the clustering status to adjust the internal thresholds dynamically without the assistance of user parameters. According to the results of extensive experiments on real and synthetic data, the new method has excellent accuracy and usability. It outperformed the other algorithms even when correct parameter values were artificially supplied to them. The encouraging results suggest that projected clustering can be a practical tool for various kinds of real applications.published_or_final_versio

Identifying projected clusters from gene expression profiles

In microarray gene expression data, clusters may hide in subspaces. Traditional clustering algorithms that make use of similarity measurements in the full input space may fail to detect the clusters. In recent years a number of algorithms have been proposed to identify this kind of projected clusters, but many of them rely on some critical parameters whose proper values are hard for users to determine. In this paper a new algorithm that dynamically adjusts its internal thresholds is proposed. It has a low dependency on user parameters while allowing users to input some domain knowledge should they be available. Experimental results show that the algorithm is capable of identifying some interesting projected clusters from real microarray data.published_or_final_versio

Prevalence and awareness of lower urinary tract symptoms among males in the Outpatient Clinics of Universiti Kebangsaan Malaysia Medical Centre.

This study aims to determine the prevalence of lower urinary tract symptoms (LUTS) and level of awareness among male outpatients in Universiti Kebangsaan Malaysia Medical Centre (UKMMC). A questionnaire consisting of demographic data, questions related to knowledge, attitude and practice on BPH and the International Prostate Symptom Score (IPSS) was used for this study. Uroflowmetry and bladder scan were used to evaluate the function of the urinary tract and severity of BPH. Urine dipstick was done for glycosuria, proteinuria and haematuria. A total of 220 respondents were surveyed. The prevalence of moderately and severely symptomatic LUTS was 42.7%. The most commonly reported LUTS were nocturia (78.2%), frequency (58.2%) and incomplete emptying (44.6%). The prevalence of glycosuria, proteinuria and haematuria were 23.6%, 11.4% and 1.8% respectively. There was a significant association between increasing age with the severity of LUTS (p=0.005). Out of 102 respondents with voided urine volume greater than 150 mL, there was a significant decrease in maximum (Qmax) (p=0.039) and average (Qave) urine flow rates with every 10 years increase of age (p=0.001). The majority of respondents (59.5%) have heard of BPH before. Over 78.2% of the respondents would seek medical attention if they have LUTS with 15.9% saying they would seek traditional treatment. In conclusion, the prevalence of LUTS was high and the level of awareness was satisfactory

Identification of BRCA1/2 Founder Mutations in Southern Chinese Breast Cancer Patients Using Gene Sequencing and High Resolution DNA Melting Analysis

Background: Ethnic variations in breast cancer epidemiology and genetics have necessitated investigation of the spectra of BRCA1 and BRCA2 mutations in different populations. Knowledge of BRCA mutations in Chinese populations is still largely unknown. We conducted a multi-center study to characterize the spectra of BRCA mutations in Chinese breast and ovarian cancer patients from Southern China. Methodology/Principal Findings: A total of 651 clinically high-risk breast and/or ovarian cancer patients were recruited from the Hong Kong Hereditary Breast Cancer Family Registry from 2007 to 2011. Comprehensive BRCA1 and BRCA2 mutation screening was performed using bi-directional sequencing of all coding exons of BRCA1 and BRCA2. Sequencing results were confirmed by in-house developed full high resolution DNA melting (HRM) analysis. Among the 451 probands analyzed, 69 (15.3%) deleterious BRCA mutations were identified, comprising 29 in BRCA1 and 40 in BRCA2. The four recurrent BRCA1 mutations (c.470_471delCT, c.3342_3345delAGAA, c.5406+1_5406+3delGTA and c.981_982delAT) accounted for 34.5% (10/29) of all BRCA1 mutations in this cohort. The four recurrent BRCA2 mutations (c.2808_2811delACAA, c.3109C>T, c.7436_7805del370 and c.9097_9098insA) accounted for 40% (16/40) of all BRCA2 mutations. Haplotype analysis was performed to confirm 1 BRCA1 and 3 BRCA2 mutations are putative founder mutations. Rapid HRM mutation screening for a panel of the founder mutations were developed and validated. Conclusion: In this study, our findings suggest that BRCA mutations account for a substantial proportion of hereditary breast/ovarian cancer in Southern Chinese population. Knowing the spectrum and frequency of the founder mutations in this population will assist in the development of a cost-effective rapid screening assay, which in turn facilitates genetic counseling and testing for the purpose of cancer risk assessment. © 2012 Kwong et al.published_or_final_versio

Whither Capitalism? Financial externalities and crisis

As with global warming, so with financial crises – externalities have a lot to answer for. We look at three of them. First the financial accelerator due to ‘fire sales’ of collateral assets -- a form of pecuniary externality that leads to liquidity being undervalued. Second the ‘risk- shifting’ behaviour of highly-levered financial institutions who keep the upside of risky investment while passing the downside to others thanks to limited liability. Finally, the network externality where the structure of the financial industry helps propagate shocks around the system unless this is checked by some form of circuit breaker, or ‘ring-fence’. The contrast between crisis-induced Great Recession and its aftermath of slow growth in the West and the rapid - and (so far) sustained - growth in the East suggests that successful economic progress may depend on how well these externalities are managed

Digital PCR methods improve detection sensitivity and measurement precision of low abundance mtDNA deletions

Mitochondrial DNA (mtDNA) mutations are a common cause of primary mitochondrial disorders, and have also been implicated in a broad collection of conditions, including aging, neurodegeneration, and cancer. Prevalent among these pathogenic variants are mtDNA deletions, which show a strong bias for the loss of sequence in the major arc between, but not including, the heavy and light strand origins of replication. Because individual mtDNA deletions can accumulate focally, occur with multiple mixed breakpoints, and in the presence of normal mtDNA sequences, methods that detect broad-spectrum mutations with enhanced sensitivity and limited costs have both research and clinical applications. In this study, we evaluated semi-quantitative and digital PCR-based methods of mtDNA deletion detection using double-stranded reference templates or biological samples. Our aim was to describe key experimental assay parameters that will enable the analysis of low levels or small differences in mtDNA deletion load during disease progression, with limited false-positive detection. We determined that the digital PCR method significantly improved mtDNA deletion detection sensitivity through absolute quantitation, improved precision and reduced assay standard error