Reducing UK-means to k-means

This paper proposes an optimisation to the UK-means algorithm, which generalises the k-means algorithm to handle objects whose locations are uncertain. The location of each object is described by a probability density function (pdf). The UK-means algorithm needs to compute expected distances (EDs) between each object and the cluster representatives. The evaluation of ED from first principles is very costly operation, because the pdf's are different and arbitrary. But UK-means needs to evaluate a lot of EDs. This is a major performance burden of the algorithm. In this paper, we derive a formula for evaluating EDs efficiently. This tremendously reduces the execution time of UK-means, as demonstrated by our preliminary experiments. We also illustrate that this optimised formula effectively reduces the UK-means problem to the traditional clustering algorithm addressed by the k-means algorithm. © 2007 IEEE.published_or_final_versionThe 7th IEEE International Conference on Data Mining (ICDM) Workshops 2007, Omaha, NE., 28-31 October 2007. In Proceedings of the 7th ICDM, 2007, p. 483-48

Clustering uncertain data using voronoi diagrams and R-tree index

We study the problem of clustering uncertain objects whose locations are described by probability density functions (pdfs). We show that the UK-means algorithm, which generalizes the k-means algorithm to handle uncertain objects, is very inefficient. The inefficiency comes from the fact that UK-means computes expected distances (EDs) between objects and cluster representatives. For arbitrary pdfs, expected distances are computed by numerical integrations, which are costly operations. We propose pruning techniques that are based on Voronoi diagrams to reduce the number of expected distance calculations. These techniques are analytically proven to be more effective than the basic bounding-box-based technique previously known in the literature. We then introduce an R-tree index to organize the uncertain objects so as to reduce pruning overheads. We conduct experiments to evaluate the effectiveness of our novel techniques. We show that our techniques are additive and, when used in combination, significantly outperform previously known methods. © 2006 IEEE.published_or_final_versio

Naive bayes classification of uncertain data

Traditional machine learning algorithms assume that data are exact or precise. However, this assumption may not hold in some situations because of data uncertainty arising from measurement errors, data staleness, and repeated measurements, etc. With uncertainty, the value of each data item is represented by a probability distribution function (pdf). In this paper, we propose a novel naive Bayes classification algorithm for uncertain data with a pdf. Our key solution is to extend the class conditional probability estimation in the Bayes model to handle pdf's. Extensive experiments on UCI datasets show that the accuracy of naive Bayes model can be improved by taking into account the uncertainty information. © 2009 IEEE.published_or_final_versionThe 9th IEEE International Conference on Data Mining (ICDM), Miami, FL., 6-9 December 2009. In Proceedings of the 9th ICDM, 2009, p. 944-94

Mining Order-Preserving Submatrices from Data with Repeated Measurements

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Modelos de sobrevivência para o estudo dos fatores de prognóstico até à ocorrência da resposta ao tratamento de fisioterapia em utentes com dor lombar crónica

Relatório do Projeto de Investigação apresentado para cumprimento dos requisitos necessários à obtenção do grau de Mestre em Fisioterapia, área de especialização em Fisioterapia em Condições Músculo-EsqueléticasIntrodução: A recuperação, da função e/ou dor, é comummente utilizada em estudos relacionados com a dor lombar crónica não específica (DLCNE), contudo, os desenhos utilizados para medir a resposta ao tratamento não permitem saber quando, no decorrer da intervenção, é atingido um determinado critério de resposta ao tratamento, e consequentemente quais os fatores que aumentam o risco/ a probabilidade de obter esse critério de resposta ao tratamento ao longo do tempo. Objetivo: Este estudo pretendeu identificar fatores de prognóstico que influenciem significativamente o tempo até à ocorrência de um evento de interesse, definido como resposta ao tratamento multimodal de fisioterapia na intensidade da dor, incapacidade funcional e perceção de melhoria em indivíduos com DCLNE, recorrendo a avaliações repetidas semanalmente, durante 8 semanas. Metodologia: Estudo observacional de coorte prospetivo com 135 indivíduos com DLCNE referenciados para a fisioterapia, que foram avaliados no início da intervenção de fisioterapia e semanalmente desde a segunda até à oitava semana de intervenção. O “evento” definido foi a obtenção do critério de sucesso na resposta ao tratamento, estabelecido para cada outcome com base no valor da respetiva DCMI, definida como a diminuição ≥ 30% na escala numérica da dor (END) e na versão portuguesa da Quebec Back Pain Disability Scale (QBPDS-PT) e diferença mínima de 3 pontos para a versão portuguesa da Global Back Recovery Scale (GBRS-PT), mantidas durante um mínimo de 7 dias. Resultados: A proporção de utentes que alcançou a recuperação para a intensidade da dor e incapacidade funcional, no período de 8 semanas de tratamento, foi de 51.11% (n=69) e de 50.37% (n=68), respetivamente. A proporção de utentes que alcançou a recuperação na perceção de melhoria foi de 55.56% (n=75). A mediana do tempo de recuperação para os 3 outcomes ocorreu na 6ª semana de tratamento. Os indivíduos com maior intensidade de dor na baseline (HR:1.26, 95%IC: 1.12-1.43), que nunca ou raramente se sentiram “desamparados” (HR:2.09, 95%IC: 1.07-4.08), têm maior possibilidade de atingir o critério de recuperação para a dor, comparativamente aos utentes que não possuem estas características. Os indivíduos que vivem sozinhos (HR: 1.83, 95%IC: 1,05-3,19) têm maior possibilidade de atingir o critério de recuperação para a incapacidade funcional. Os utentes com inferior nível de ensino têm uma maior probabilidade de recuperação da perceção global de melhoria (IR:1.65; 95%IC: 1.02-2.67) comparativamente com utentes com mais formação. Conclusão: A recuperação da intensidade da dor e da incapacidade funcional ocorre nas primeiras 6 semanas de tratamento, sendo que aproximadamente metade dos utentes recuperados alcançaram o critério de resposta após as 2 primeiras semanas de tratamento. Maior intensidade da dor na baseline, baixos níveis de fatores psicossociais, viver sozinho e ter um nível educacional mais baixo, parece favorecer a probabilidade de recuperar destes utentes, ao longo do tempo.Introduction: The recovery from pain or function is usualy used in nonspecific chronic low back pain (NCLBP) studies. The designs to measure the response to treatment don’t allow to know when, whithin the intervention, the criteria of recovery is achieved and, therefore, which are the factors that increase the possibility of achieving the defined sucess along the time. Objective: The aim of this study is to identify prognosis factors that favour significantly the time until reaching the event of interest, defined as the response to the multimodal physiotherapy treatment for pain intensity, disability and global perception of recovery in patients with NCLBP, using repetitive assessments on a weekly basis for 8 weeks. Methodology: In this prospective cohort study were 135 NCLBP patients who were referred for physiotherapy and assessed 8 times (baseline and every week from 2nd to the 8th week) The event of interest was defined as the achievement of the recovery criteria on the treatment response, established for each outcome, considering the minimal important change (MIC) defined as a reduction of ≥ 30% on numeric rate scale (NRS) and portuguese version of Quebec Back Pain Disability Scale (QBPDS-PT) and a reduction of 3 points on the portuguese version of Global Back Recovery Scale (GBRS-PT), maintened for at least 7 days. Results: The proportion of patients that have acheived the recovery for pain intensity and disability, on the 8 weeks treatment was 51.11% (n=69) and 50.37% (n=68), respectivetly. The proportion of patiens that have acheived recovery for the global perception was 55.56% (n=75). The median of recovery time for the 3 outcomes occured on the 6th week. The NCLBP patients who have more pain intensity on baseline (HR: 1.26; 95%IC: 1.12-1.43) and who didn’t feel with support on the previous week (HR: 2.09; 95%IC: 1.07-4.08) have more possibility to achieve the recovery criteria for pain, compared with those that don’t have that caracteristics. The patients that live alone (HR: 1.83, 95%IC: 1,05-3,19) have more possibility of achieve the disability recovery, when compared with those who don´t. Patients with lower levels of education have more probability to recovery from global perception of recovery (IR:1.65; 95%IC: 1.02-2.67), compared with patients with higher levels of education. Conclusions: The recovery for pain intensity and disability occurs on the 6 first weeks of treatment, and approximetely half of the patients achieved the response criteria in the 2 first weeks. Higher levels of pain intensity on the baseline, lower levels for the psycosocial factors, living alone ad lower levels of education, seems to favour the probability or recovery on NCLBP patients, along the time

Decision trees for uncertain data

Traditional decision tree classifiers work with data whose values are known and precise. We extend such classifiers to handle data with uncertain information. Value uncertainty arises in many applications during the data collection process. Example sources of uncertainty include measurement/ quantization errors, data staleness, and multiple repeated measurements. With uncertainty, the value of a data item is often represented not by one single value, but by multiple values forming a probability distribution. Rather than abstracting uncertain data by statistical derivatives (such as mean and median), we discover that the accuracy of a decision tree classifier can be much improved if the "complete information" of a data item (taking into account the probability density function (pdf)) is utilized. We extend classical decision tree building algorithms to handle data tuples with uncertain values. Extensive experiments have been conducted which show that the resulting classifiers are more accurate than those using value averages. Since processing pdfs is computationally more costly than processing single values (e.g., averages), decision tree construction on uncertain data is more CPU demanding than that for certain data. To tackle this problem, we propose a series of pruning techniques that can greatly improve construction efficiency. © 2006 IEEE.link_to_subscribed_fulltex

Beta defensin-2 is reduced in central but not in distal airways of smoker COPD patients

Background: Altered pulmonary defenses in chronic obstructive pulmonary disease (COPD) may promote distal airways bacterial colonization. The expression/activation of Toll Like receptors (TLR) and beta 2 defensin (HBD2) release by epithelial cells crucially affect pulmonary defence mechanisms. Methods: The epithelial expression of TLR4 and of HBD2 was assessed in surgical specimens from current smokers COPD (s-COPD; n = 17), ex-smokers COPD (ex-s-COPD; n = 8), smokers without COPD (S; n = 12), and from non-smoker non-COPD subjects (C; n = 13). Results: In distal airways, s-COPD highly expressed TLR4 and HBD2. In central airways, S and s-COPD showed increased TLR4 expression. Lower HBD2 expression was observed in central airways of s-COPD when compared to S and to ex-s-COPD. s-COPD had a reduced HBD2 gene expression as demonstrated by real-time PCR on micro-dissected bronchial epithelial cells. Furthermore, HBD2 expression positively correlated with FEV1/FVC ratio and inversely correlated with the cigarette smoke exposure. In a bronchial epithelial cell line (16 HBE) IL-1β significantly induced the HBD2 mRNA expression and cigarette smoke extracts significantly counteracted this IL-1 mediated effect reducing both the activation of NFkB pathway and the interaction between NFkB and HBD2 promoter. Conclusions: This study provides new insights on the possible mechanisms involved in the alteration of innate immunity mechanisms in COPD. © 2012 Pace et al

Computational modelling of cancerous mutations in the EGFR/ERK signalling pathway

This article has been made available through the Brunel Open Access Publishing Fund - Copyright @ 2009 Orton et al.BACKGROUND: The Epidermal Growth Factor Receptor (EGFR) activated Extracellular-signal Regulated Kinase (ERK) pathway is a critical cell signalling pathway that relays the signal for a cell to proliferate from the plasma membrane to the nucleus. Deregulation of the EGFR/ERK pathway due to alterations affecting the expression or function of a number of pathway components has long been associated with numerous forms of cancer. Under normal conditions, Epidermal Growth Factor (EGF) stimulates a rapid but transient activation of ERK as the signal is rapidly shutdown. Whereas, under cancerous mutation conditions the ERK signal cannot be shutdown and is sustained resulting in the constitutive activation of ERK and continual cell proliferation. In this study, we have used computational modelling techniques to investigate what effects various cancerous alterations have on the signalling flow through the ERK pathway. RESULTS: We have generated a new model of the EGFR activated ERK pathway, which was verified by our own experimental data. We then altered our model to represent various cancerous situations such as Ras, B-Raf and EGFR mutations, as well as EGFR overexpression. Analysis of the models showed that different cancerous situations resulted in different signalling patterns through the ERK pathway, especially when compared to the normal EGF signal pattern. Our model predicts that cancerous EGFR mutation and overexpression signals almost exclusively via the Rap1 pathway, predicting that this pathway is the best target for drugs. Furthermore, our model also highlights the importance of receptor degradation in normal and cancerous EGFR signalling, and suggests that receptor degradation is a key difference between the signalling from the EGF and Nerve Growth Factor (NGF) receptors. CONCLUSION: Our results suggest that different routes to ERK activation are being utilised in different cancerous situations which therefore has interesting implications for drug selection strategies. We also conducted a comparison of the critical differences between signalling from different growth factor receptors (namely EGFR, mutated EGFR, NGF, and Insulin) with our results suggesting the difference between the systems are large scale and can be attributed to the presence/absence of entire pathways rather than subtle difference in individual rate constants between the systems.This work was funded by the Department of Trade and Industry (DTI), under their Bioscience Beacon project programme. AG was funded by an industrial PhD studentship from Scottish Enterprise and Cyclacel

Social Modulation during Songbird Courtship Potentiates Midbrain Dopaminergic Neurons

Synaptic transmission onto dopaminergic neurons of the mammalian ventral tegmental area (VTA) can be potentiated by acute or chronic exposure to addictive drugs. Because rewarding behavior, such as social affiliation, can activate the same neural circuitry as addictive drugs, we tested whether the intense social interaction of songbird courtship may also potentiate VTA synaptic function. We recorded glutamatergic synaptic currents from VTA of male zebra finches who had experienced distinct social and behavioral conditions during the previous hour. The level of synaptic transmission to VTA neurons, as assayed by the ratio of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) to N-methyl-D-aspartic acid (NMDA) glutamate receptor mediated synaptic currents, was increased after males sang to females, and also after they saw females without singing, but not after they sang while alone. Potentiation after female exposure alone did not appear to result from stress, as it was not blocked by inhibition of glucocorticoid receptors. This potentiation was restricted to synapses of dopaminergic projection neurons, and appeared to be expressed postsynaptically. This study supports a model in which VTA dopaminergic neurons are more strongly activated during singing used for courtship than during non-courtship singing, and thus can provide social context-dependent modulation to forebrain areas. More generally, these results demonstrate that an intense social encounter can trigger the same pathways of neuronal plasticity as addictive drugs