Improving multivariate data streams clustering.

Clustering data streams is an important task in data mining research. Recently, some algorithms have been proposed to cluster data streams as a whole, but just few of them deal with multivariate data streams. Even so, these algorithms merely aggregate the attributes without touching upon the correlation among them. In order to overcome this issue, we propose a new framework to cluster multivariate data streams based on their evolving behavior over time, exploring the correlations among their attributes by computing the fractal dimension. Experimental results with climate data streams show that the clusters' quality and compactness can be improved compared to the competing method, leading to the thoughtfulness that attributes correlations cannot be put aside. In fact, the clusters' compactness are 7 to 25 times better using our method. Our framework also proves to be an useful tool to assist meteorologists in understanding the climate behavior along a period of time.Edição dos Proceedings do 16th International Conference on Computational Science, San Diego, 2016

Protocol for a pragmatic feasibility randomised controlled trial of peer coaching for adults with long-term conditions: PEER CONNECT.

INTRODUCTION: Patients with low levels of knowledge, skills and confidence to manage their health and well-being (activation) are more likely to have unmet health needs, delay seeking healthcare and need emergency care. National Health Service England estimates that this may be applicable to 25%-40% of patients with long-term health conditions. Volunteer peer coaching may support people to increase their level of activation. This form of intervention may be particularly effective for people with low levels of activation. METHODS AND ANALYSIS: This single site, two-arm randomised controlled trial has been designed to assess the feasibility of conducting a definitive trial of volunteer peer health and well-being coaching for people with long-term health conditions (multiple sclerosis, rheumatic diseases or chronic pain) and low activation. Feasibility outcomes include recruitment and retention rates, and intervention adherence. We will measure patient activation, mental health and well-being as potential outcomes for a definitive trial. These outcomes will be summarised descriptively for each time point by allocated group and help to inform sample size calculation for the definitive trial. Criteria for progression to a full trial will be used. ETHICS AND DISSEMINATION: Ethical approval has been granted by the London - Surrey Research Ethics Committee, reference 21/LO/0715. Results from this feasibility trial will be shared directly with participants, presented at local, regional and national conferences and published in an open-access journal. TRIAL REGISTRATION NUMBER: ISRCTN12623577

A competitive enzyme immunoassay for the quantitative detection of cocaine from banknotes and latent fingermarks

A sensitive and versatile competitive enzyme immunoassay (cEIA) has been developed for the quantitative detection of cocaine in complex forensic samples. Polyclonal anti-cocaine antibody was purified from serum and deposited onto microtiter plates. The concentration of the cocaine antibody adsorbed onto the plates, and the dilution of the cocaine-HRP hapten were both studied to achieve an optimised immunoassay. The method was successfully used to quantify cocaine in extracts taken from both paper currency and latent fingermarks. The limit of detection (LOD) of 0.162 ng mL-1 achieved with the assay compares favourably to that of conventional chromatography-mass spectroscopy techniques, with an appropriate sensitivity for the quantification of cocaine at the low concentrations present in some forensic samples. The cEIA was directly compared to LC-MS for the analysis of ten UK banknote samples. The results obtained from both techniques were statistically similar, suggesting that the immunoassay was unaffected by cross-reactivity with potentially interfering compounds. The cEIA was used also for the detection of cocaine in extracts from latent fingermarks. The results obtained were compared to the cocaine concentrations detected in oral fluid sampled from the same individual. Using the cEIA, we have shown, for the first time, that endogeneously excreted cocaine can be detected and quantified from a single latent fingermark. Additionally, it has been shown that the presence of cocaine, at similar concentrations, in more than one latent fingermark from the same individual can be linked with those concentrations found in oral fluid. These results show that detection of drugs in latent fingermarks could directly indicate whether an individual has consumed the drug. The specificity and feasibility of measuring low concentrations of cocaine in complex forensic samples demonstrates the effectiveness and robustness of the assay. The immunoassay presents a simple and cost-effective alternative to the current mass spectrometry based techniques for the quantitation of cocaine at forensically significant concentrations

Elevated amygdala responses to emotional faces in youths with chronic irritability or bipolar disorder

AbstractA major controversy in child psychiatry is whether bipolar disorder (BD) presents in children as severe, non-episodic irritability (operationalized here as severe mood dysregulation, SMD), rather than with manic episodes as in adults. Both classic, episodic BD and SMD are severe mood disorders characterized by deficits in processing emotional stimuli. Neuroimaging techniques can be used to test whether the pathophysiology mediating these deficits are similar across the two phenotypes. Amygdala dysfunction during face emotion processing is well-documented in BD, but little is known about amygdala dysfunction in chronically irritable youth. We compared neural activation in SMD (n=19), BD (n=19), and healthy volunteer (HV; n=15) youths during an implicit face-emotion processing task with angry, fearful and neutral expressions. In the right amygdala, both SMD and BD exhibited greater activity across all expressions than HV. However, SMD and BD differed from each other and HV in posterior cingulate cortex, posterior insula, and inferior parietal lobe. In these regions, only SMD showed deactivation in response to fearful expressions, whereas only BD showed deactivation in response to angry expressions. Thus, during implicit face emotion processing, youth with BD and those with SMD exhibit similar amygdala dysfunction but different abnormalities in regions involved in information monitoring and integration

Determination of steroid estrogens in wastewater by high performance liquid chromatography-tandem mass spectrometry

This paper discusses the requirement for, and presents an analytical procedure for, the determination of four unconjugated steroid hormones and a conjugated steroid (estrone-3-sulfate) in wastewaters. The method quantifies the steroids by LC/MS/MS following solid phase extraction and a two stage clean-up procedure. Samples were extracted using C18 cartridges and eluates were then purified by gel permeation chromatography, followed by a further clean-up step on an aminopropyl cartridge. The limits of detection achieved were 0.2 ng l-1 for estriol, 17β-estradiol and 17α-ethinylestradiol, and 0.1 ng l-1 for estrone and the conjugate. The robustness of the method was demonstrated by achieving recoveries of >83% for all steroids in settled sewage and final effluent samples with relative standard deviations of 0.5 - 12%. The method was used to analyse a range of samples from a wastewater treatment works in south east England which demonstrated a >80% removal for estrone, estradiol and estriol with little impact on concentrations of ethinylestradiol or the conjugate

Clustering multivariate climate data streams using fractal dimension

A data stream is a flow of data produced continuously along the time. Storing and analyzing such information become challenging due to exponential growth of the data volume collected. In this context, some methods were proposed to cluster data streams with similar behavior along the time. However, those methods have failed on clustering data flows with more than one attribute, i.e., multivariate flows. This paper introduces a new method to cluster multivariate data streams, based on fractal dimension, reading the data only once. We evaluated our method over real multivariate data streams generated by climate sensors. Not only was our method able to cluster the flows of data, but also identified sensors with similar behavior during the analyzed period.CAPESCNPQFAPES