Motivic analysis and its relevance to raga identification in carnatic music

A raga is a collective melodic expression consisting of motifs. A raga can be identified using motifs which areunique to it. Motifs can be thought of as signature prosodic phrases. Different ragas may be composed of the same setof notes, or even phrases, but the prosody may be completely different. In this paper, an attempt is made to determinethe characteristic motifs that enable identification of a raga and distinguish between them. To determine this, motifs are first manually marked for a set of five popular raga by a professional musician. The motifs are then normalisedwith respect to the tonic. HMMs are trained for each motif using 80% of the data and about 20% are used for testing. The results do indicate that about 80% of the motifs are identified as belonging to a specific raga accurately.

Features for analysis of Makam music

For computational studies of makam music, it is essential to gather a list of characteristics that constitute a makam and explore corresponding quantitative features for automaticanalysis. This study is such an attempt where we address the characteristics for makams as defined in theory books and deduce a list of quantitative features. The target here is to evoke discussions on some measurable features other than providing complete analysis on thediscriminative potentials of each proposed feature which could be the subject of a few larger studies.

GSVA: gene set variation analysis for microarray and RNA-seq data

Gene set enrichment (GSE) analysis is a popular framework for condensing information from gene expression profiles into a pathway or signature summary. The strengths of this approach over single gene analysis include noise and dimension reduction, as well as greater biological interpretability. As molecular profiling experiments move beyond simple case-control studies, robust and flexible GSE methodologies are needed that can model pathway activity within highly heterogeneous data sets. To address this challenge, we introduce Gene Set Variation Analysis (GSVA), a GSE method that estimates variation of pathway activity over a sample population in an unsupervised manner. We demonstrate the robustness of GSVA in a comparison with current state of the art sample-wise enrichment methods. Further, we provide examples of its utility in differential pathway activity and survival analysis. Lastly, we show how GSVA works analogously with data from both microarray and RNA-seq experiments. GSVA provides increased power to detect subtle pathway activity changes over a sample population in comparison to corresponding methods. While GSE methods are generally regarded as end points of a bioinformatic analysis, GSVA constitutes a starting point to build pathway-centric models of biology. Moreover, GSVA contributes to the current need of GSE methods for RNA-seq data. GSVA is an open source software package for R which forms part of the Bioconductor project and can be downloaded at http://www.bioconductor.org.

Multiway Array Decomposition Analysis of EEGs in Alzheimer’s Disease

Methods for the extraction of features from physiological datasets are growing needs as clinical investigations of Alzheimer’s disease (AD) in large and heterogeneous population increase. General tools allowing diagnostic regardless of recording sites, such as different hospitals, are essential and if combined to inexpensive non-invasive methods could critically improve mass screening of subjects with AD. In this study, we applied three state of the art multiway array decomposition (MAD) methods to extract features from electroencephalograms (EEGs) of AD patients obtained from multiple sites. In comparison to MAD, spectral-spatial average filter (SSFs) of control and AD subjects were used as well as a common blind source separation method, algorithm for multiple unknown signal extraction (AMUSE). We trained a feed-forward multilayer perceptron (MLP) to validate and optimize AD classification from two independent databases. Using a third EEG dataset, we demonstrated that features extracted from MAD outperformed features obtained from SSFs AMUSE in terms of root mean squared error (RMSE) and reaching up to 100% of accuracy in test condition. We propose that MAD maybe a useful tool to extract features for AD diagnosis offering great generalization across multi-site databases and opening doors to the discovery of new characterization of the disease.

Subclinical thyroid dysfunction and the risk for fractures: a systematic review and meta-analysis.

BACKGROUND: Data on the association between subclinical thyroid dysfunction and fractures conflict. PURPOSE: To assess the risk for hip and nonspine fractures associated with subclinical thyroid dysfunction among prospective cohorts. DATA SOURCES: Search of MEDLINE and EMBASE (1946 to 16 March 2014) and reference lists of retrieved articles without language restriction. STUDY SELECTION: Two physicians screened and identified prospective cohorts that measured thyroid function and followed participants to assess fracture outcomes. DATA EXTRACTION: One reviewer extracted data using a standardized protocol, and another verified data. Both reviewers independently assessed methodological quality of the studies. DATA SYNTHESIS: The 7 population-based cohorts of heterogeneous quality included 50,245 participants with 1966 hip and 3281 nonspine fractures. In random-effects models that included the 5 higher-quality studies, the pooled adjusted hazard ratios (HRs) of participants with subclinical hyperthyroidism versus euthyrodism were 1.38 (95% CI, 0.92 to 2.07) for hip fractures and 1.20 (CI, 0.83 to 1.72) for nonspine fractures without statistical heterogeneity (P = 0.82 and 0.52, respectively; I2= 0%). Pooled estimates for the 7 cohorts were 1.26 (CI, 0.96 to 1.65) for hip fractures and 1.16 (CI, 0.95 to 1.42) for nonspine fractures. When thyroxine recipients were excluded, the HRs for participants with subclinical hyperthyroidism were 2.16 (CI, 0.87 to 5.37) for hip fractures and 1.43 (CI, 0.73 to 2.78) for nonspine fractures. For participants with subclinical hypothyroidism, HRs from higher-quality studies were 1.12 (CI, 0.83 to 1.51) for hip fractures and 1.04 (CI, 0.76 to 1.42) for nonspine fractures (P for heterogeneity = 0.69 and 0.88, respectively; I2 = 0%). LIMITATIONS: Selective reporting cannot be excluded. Adjustment for potential common confounders varied and was not adequately done across all studies. CONCLUSION: Subclinical hyperthyroidism might be associated with an increased risk for hip and nonspine fractures, but additional large, high-quality studies are needed. PRIMARY FUNDING SOURCE: Swiss National Science Foundation.

Organic geochemistry of Jurassic-Cretaceous source rocks and oil seeps from the profile across the Adriatic-Dinaric carbonate platform

Organic geochemical and stable isotope investigations were performed to provide an insight into the depositional environments, origin and maturity of the organic matter in Jurassic and Cretaceous formations of the External Dinarides. A correlation is made among various parameters acquired from Rock-Eval, gas chromatography-mass spectrometry data and isotope analysis of carbonates and kerogen. Three groups of samples were analysed. The first group includes source rocks derived from Lower Jurassic limestone and Upper Jurassic ``Leme'' beds, the second from Upper Cretaceous carbonates, while the third group comprises oil seeps genetically connected with Upper Cretaceous source rocks. The carbon and oxygen isotopic ratios of all the carbonates display marine isotopic composition. Rock-Eval data and maturity parameter values derived from biomarkers define the organic matter of the Upper Cretaceous carbonates as Type I-S and Type II-S kerogen at the low stage of maturity up to entering the oil-generating window. Lower and Upper Jurassic source rocks contain early mature Type III mixed with Type IV organic matter. All Jurassic and Cretaceous potential source rock extracts show similarity in triterpane and sterane distribution. The hopane and sterane distribution pattern of the studied oil seeps correspond to those from Cretaceous source rocks. The difference between Cretaceous oil seeps and potential source rock extracts was found in the intensity and distribution of n-alkanes, as well as in the abundance of asphaltenes which is connected to their biodegradation stage. In the Jurassic and Cretaceous potential source rock samples a mixture of aromatic hydrocarbons with their alkyl derivatives were indicated, whereas in the oil seep samples extracts only asphaltenes were observed.

Use of LIDAR-based Elevation Data for Highway Drainage Analysis: A Qualitative Assessment, 2003

US Geological Survey (USGS) based elevation data are the most commonly used data source for highway hydraulic analysis; however, due to the vertical accuracy of USGS-based elevation data, USGS data may be too “coarse” to adequately describe surface profiles of watershed areas or drainage patterns. Additionally hydraulic design requires delineation of much smaller drainage areas (watersheds) than other hydrologic applications, such as environmental, ecological, and water resource management. This research study investigated whether higher resolution LIDAR based surface models would provide better delineation of watersheds and drainage patterns as compared to surface models created from standard USGS-based elevation data. Differences in runoff values were the metric used to compare the data sets. The two data sets were compared for a pilot study area along the Iowa 1 corridor between Iowa City and Mount Vernon. Given the limited breadth of the analysis corridor, areas of particular emphasis were the location of drainage area boundaries and flow patterns parallel to and intersecting the road cross section. Traditional highway hydrology does not appear to be significantly impacted, or benefited, by the increased terrain detail that LIDAR provided for the study area. In fact, hydrologic outputs, such as streams and watersheds, may be too sensitive to the increased horizontal resolution and/or errors in the data set. However, a true comparison of LIDAR and USGS-based data sets of equal size and encompassing entire drainage areas could not be performed in this study. Differences may also result in areas with much steeper slopes or significant changes in terrain. LIDAR may provide possibly valuable detail in areas of modified terrain, such as roads. Better representations of channel and terrain detail in the vicinity of the roadway may be useful in modeling problem drainage areas and evaluating structural surety during and after significant storm events. Furthermore, LIDAR may be used to verify the intended/expected drainage patterns at newly constructed highways. LIDAR will likely provide the greatest benefit for highway projects in flood plains and areas with relatively flat terrain where slight changes in terrain may have a significant impact on drainage patterns.

Phenotypic and functional analysis of human fetal liver hematopoietic stem cells in culture.

Steady-state hematopoiesis and hematopoietic transplantation rely on the unique potential of stem cells to undergo both self-renewal and multilineage differentiation. Fetal liver (FL) represents a promising alternative source of hematopoietic stem cells (HSCs), but limited by the total cell number obtained in a typical harvest. We reported that human FL nonobese diabetic/severe combined immunodeficient (NOD/SCID) repopulating cells (SRCs) could be expanded under simple stroma-free culture conditions. Here, we sought to further characterize FL HSC/SRCs phenotypically and functionally before and following culture. Unexpanded or cultured FL cell suspensions were separated into various subpopulations. These were tested for long-term culture potential and for in vivo repopulating function following transplantation into NOD/SCID mice. We found that upon culture of human FL cells, a tight association between classical stem cell phenotypes, such as CD34(+) /CD38(-) and/or side population, and NOD/SCID repopulating function was lost, as observed with other sources. Although SRC activity before and following culture consistently correlated with the presence of a CD34(+) cell population, we provide evidence that, contrary to umbilical cord blood and adult sources, stem cells present in both CD34(+) and CD34(-) FL populations can sustain long-term hematopoietic cultures. Furthermore, upon additional culture, CD34-depleted cell suspensions, devoid of SRCs, regenerated a population of CD34(+) cells possessing SRC function. Our studies suggest that compared to neonatal and adult sources, the phenotypical characteristics of putative human FL HSCs may be less strictly defined, and reinforce the accumulated evidence that human FL represents a unique, valuable alternative and highly proliferative source of HSCs for clinical applications.

Minimal requirements for parameters to be used for the development of predictive models for microbial source tracking. The example of the pair somatic coliphages and phages infecting Bacteroides

Several methods and approaches for measuring parameters to determine fecal sources of pollution in water have been developed in recent years. No single microbial or chemical parameter has proved sufficient to determine the source of fecal pollution. Combinations of parameters involving at least one discriminating indicator and one universal fecal indicator offer the most promising solutions for qualitative and quantitative analyses. The universal (nondiscriminating) fecal indicator provides quantitative information regarding the fecal load. The discriminating indicator contributes to the identification of a specific source. The relative values of the parameters derived from both kinds of indicators could provide information regarding the contribution to the total fecal load from each origin. It is also essential that both parameters characteristically persist in the environment for similar periods. Numerical analysis, such as inductive learning methods, could be used to select the most suitable and the lowest number of parameters to develop predictive models. These combinations of parameters provide information on factors affecting the models, such as dilution, specific types of animal source, persistence of microbial tracers, and complex mixtures from different sources. The combined use of the enumeration of somatic coliphages and the enumeration of Bacteroides-phages using different host specific strains (one from humans and another from pigs), both selected using the suggested approach, provides a feasible model for quantitative and qualitative analyses of fecal source identification.

Mesoscale numerical analysis of the historical November 1982 heavy precipitation event over Andorra (Eastern Pyrenees)

From 6 to 8 November 1982 one of the most catastrophic flash-flood events was recorded in the Eastern Pyrenees affecting Andorra and also France and Spain with rainfall accumulations exceeding 400 mm in 24 h, 44 fatalities and widespread damage. This paper aims to exhaustively document this heavy precipitation event and examines mesoscale simulations performed by the French Meso-NH non-hydrostatic atmospheric model. Large-scale simulations show the slow-evolving synoptic environment favourable for the development of a deep Atlantic cyclone which induced a strong southerly flow over the Eastern Pyrenees. From the evolution of the synoptic pattern four distinct phases have been identified during the event. The mesoscale analysis presents the second and the third phase as the most intense in terms of rainfall accumulations and highlights the interaction of the moist and conditionally unstable flows with the mountains. The presence of a SW low level jet (30 m s-1) around 1500 m also had a crucial role on focusing the precipitation over the exposed south slopes of the Eastern Pyrenees. Backward trajectories based on Eulerian on-line passive tracers indicate that the orographic uplift was the main forcing mechanism which triggered and maintained the precipitating systems more than 30 h over the Pyrenees. The moisture of the feeding flow mainly came from the Atlantic Ocean (7-9 g kg-1) and the role of the Mediterranean as a local moisture source was very limited (2-3 g kg-1) due to the high initial water vapour content of the parcels and the rapid passage over the basin along the Spanish Mediterranean coast (less than 12 h).

On-line desorption of dried blood spots coupled to hydrophilic interaction/reversed-phase LC/MS/MS system for the simultaneous analysis of drugs and their polar metabolites.

An assay for the simultaneous analysis of pharmaceutical compounds and their metabolites from micro-whole blood samples (i.e. 5 microL) was developed using an on-line dried blood spot (on-line DBS) device coupled with hydrophilic interaction/reversed-phase (HILIC/RP) LC/MS/MS. Filter paper is directly integrated to the LC device using a homemade inox desorption cell. Without any sample pretreatment, analytes are desorbed from the paper towards an automated system of valves linking a zwitterionic-HILIC column to an RP C18 column. In the same run, the polar fraction is separated by the zwitterionic-HILIC column while the non-polar fraction is eluted on the RP C18. Both fractions are detected by IT-MS operating in full scan mode for the survey scan and in product ion mode for the dependant scan using an ESI source. The procedure was evaluated by the simultaneous qualitative analysis of four probes and their relative phase I and II metabolites spiked in whole blood. In addition, the method was successfully applied to the in vivo monitoring of buprenorphine metabolism after the administration of an intraperitoneal injection of 30 mg/kg on adult female Wistar rat.

Partial correlation : Network analysis

The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.

Nonoccupational HIV post-exposure prophylaxis: a 10-year retrospective analysis.

BACKGROUND: We conducted a retrospective analysis of administration of nonoccupational HIV post-exposure prophylaxis (nPEP) in a single centre where tracing and testing of the source of exposure were carried out systematically over a 10-year period. METHODS: Files of all nPEP requests between 1998 and 2007 were reviewed. Characteristics of the exposed and source patients, the type of exposure, and clinical and serological outcomes were analysed. RESULTS: nPEP requests increased by 850% over 10 years. Among 910 events, 58% were heterosexual exposures, 15% homosexual exposures, 6% sexual assaults and 20% nonsexual exposures. In 208 events (23%), the source was reported to be HIV positive. In the remaining cases, active source tracing enabled 298 HIV tests to be performed (42%) and identified 11 HIV infections (3.7%). nPEP was able to be avoided or interrupted in 31% of 910 events when the source tested negative. Of 710 patients who started nPEP, 396 (56%) reported side effects, among whom 39 (5%) had to interrupt treatment. There were two HIV seroconversions, and neither was attributed to nPEP failure. CONCLUSIONS: nPEP requests increased over time. HIV testing of the source person avoided nPEP in 31% of events and was therefore paramount in the management of potential HIV exposures. Furthermore, it allowed active screening of populations potentially at risk for undiagnosed HIV infection, as shown by the increased HIV prevalence in these groups (3.7%) compared with a prevalence of 0.3% in Switzerland as a whole.

Body mass index and risk of head and neck cancer in a pooled analysis of case-control studies in the International Head and Neck Cancer Epidemiology (INHANCE) Consortium.

BACKGROUND: Head and neck cancer (HNC) risk is elevated among lean people and reduced among overweight or obese people in some studies; however, it is unknown whether these associations differ for certain subgroups or are influenced by residual confounding from the effects of alcohol and tobacco use or by other sources of biases. METHODS: We pooled data from 17 case-control studies including 12 716 cases and the 17 438 controls. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated for associations between body mass index (BMI) at different ages and HNC risk, adjusted for age, sex, centre, race, education, tobacco smoking and alcohol consumption. RESULTS: Adjusted ORs (95% CIs) were elevated for people with BMI at reference (date of diagnosis for cases and date of selection for controls) 25.0-30.0 kg/m(2) (0.52, 0.44-0.60) and BMI >/=30 kg/m(2) (0.43, 0.33-0.57), compared with BMI >18.5-25.0 kg/m(2). These associations did not differ by age, sex, tumour site or control source. Although the increased risk among people with BMI 25 kg/m(2) was present only in smokers and drinkers. CONCLUSIONS: In our large pooled analysis, leanness was associated with increased HNC risk regardless of smoking and drinking status, although reverse causality cannot be excluded. The reduced risk among overweight or obese people may indicate body size is a modifier of the risk associated with smoking and drinking. Further clarification may be provided by analyses of prospective cohort and mechanistic studies.

Free Open Source Software and Dual-Use: Loophole or Dissent?

The Free Open Source Software (FOSS) seem far from the military field but in some cases, some technologies normally used for civilian purposes may have military applications. These products and technologies are called dual-use. Can we manage to combine FOSS and dual-use products? On one hand, we have to admit that this kind of association exists - dual-use software can be FOSS and many examples demonstrate this duality - but on the other hand, dual-use software available under free licenses lead us to ask many questions. For example, the dual-use export control laws aimed at stemming the proliferation of weapons of mass destruction. Dual-use export in United States (ITAR) and Europe (regulation 428/2009) implies as a consequence the prohibition or regulation of software exportation, involving the closing of source code. Therefore, the issues of exported softwares released under free licenses arises. If software are dual-use goods and serve for military purposes, they may represent a danger. By the rights granted to licenses to run, study, redistribute and distribute modified versions of the software, anyone can access the free dual-use software. So, the licenses themselves are not at the origin of the risk, it is actually linked to the facilitated access to source codes. Seen from this point of view, it goes against the dual-use regulation which allows states to control these technologies exportation. For this analysis, we will discuss about various legal questions and draft answers from either licenses or public policies in this respect.