Modeling data with structural and temporal correlation using lower level and higher level multilevel models

Novel imaging techniques are playing an increasingly important role in drug development, providing insight into the mechanism of action of new chemical entities. The data sets obtained by these methods can be large with complex inter-relationships, but the most appropriate statistical analysis for handling this data is often uncertain - precisely because of the exploratory nature of the way the data are collected. We present an example from a clinical trial using magnetic resonance imaging to assess changes in atherosclerotic plaques following treatment with a tool compound with established clinical benefit. We compared two specific approaches to handle the correlations due to physical location and repeated measurements: two-level and four-level multilevel models. The two methods identified similar structural variables, but higher level multilevel models had the advantage of explaining a greater proportion of variation, and the modeling assumptions appeared to be better satisfied.

Small archaeohyracids (Typotheria, Notoungulata) from Chubut Province, Argentina, and central Chile : implications for Trans-Andean temporal correlation / Marcelo Reguero -- [et al.].

n.s. no.48(2003)

A Steganalysis System Utilizing Temporal Pixel Correlation Of HEVC Video

High Efficiency Video Coding (HEVC) is the most recent video codec coming after currently most popular H.264/MPEG4 codecs and has promising compression capabilities. It is conjectured that it will be a substitute for current video compression standards. However, to the best knowledge of the authors, none of the current video steganalysis methods designed or tested with HEVC video. In this paper, pixel domain steganography applied on HEVC video is targeted for the first time. Also, its the first paper that employs accordion unfolding transformation, which merges temporal and spatial correlation, in pixel domain video steganalysis. With help of the transformation, temporal correlation is incorporated into the system. Its demonstrated for three different feature sets that integrating temporal dependency substantially increased the detection accuracy.

Spatio-temporal correlations in aqueous systems: computational studies of static and dynamic heterogeneity by 2D-IR spectroscopy

Local heterogeneity is ubiquitous in natural aqueous systems. It can be caused locally by external biomolecular subsystems like proteins, DNA, micelles and reverse micelles, nanoscopic materials etc., but can also be intrinsic to the thermodynamic nature of the aqueous solution itself (like binary mixtures or at the gas-liquid interface). The altered dynamics of water in the presence of such diverse surfaces has attracted considerable attention in recent years. As these interfaces are quite narrow, only a few molecular layers thick, they are hard to study by conventional methods. The recent development of two dimensional infra-red (2D-IR) spectroscopy allows us to estimate length and time scales of such dynamics fairly accurately. In this work, we present a series of interesting studies employing two dimensional infra-red spectroscopy (2D-IR) to investigate (i) the heterogeneous dynamics of water inside reverse micelles of varying sizes, (ii) supercritical water near the Widom line that is known to exhibit pronounced density fluctuations and also study (iii) the collective and local polarization fluctuation of water molecules in the presence of several different proteins. The spatio-temporal correlation of confined water molecules inside reverse micelles of varying sizes is well captured through the spectral diffusion of corresponding 2D-IR spectra. In the case of supercritical water also, we observe a strong signature of dynamic heterogeneity from the elongated nature of the 2D-IR spectra. In this case the relaxation is ultrafast. We find remarkable agreement between the different tools employed to study the relaxation of density heterogeneity. For aqueous protein solutions, we find that the calculated dielectric constant of the respective systems unanimously shows a noticeable increment compared to that of neat water. However, the `effective' dielectric constant for successive layers shows significant variation, with the layer adjacent to the protein having a much lower value. Relaxation is also slowest at the surface. We find that the dielectric constant achieves the bulk value at distances more than 3 nm from the surface of the protein.

Temporal Locality in Web Request Streams: Sources, Characteristics, and Caching Implications

Temporal locality of reference in Web request streams emerges from two distinct phenomena: the popularity of Web objects and the {\em temporal correlation} of requests. Capturing these two elements of temporal locality is important because it enables cache replacement policies to adjust how they capitalize on temporal locality based on the relative prevalence of these phenomena. In this paper, we show that temporal locality metrics proposed in the literature are unable to delineate between these two sources of temporal locality. In particular, we show that the commonly-used distribution of reference interarrival times is predominantly determined by the power law governing the popularity of documents in a request stream. To capture (and more importantly quantify) both sources of temporal locality in a request stream, we propose a new and robust metric that enables accurate delineation between locality due to popularity and that due to temporal correlation. Using this metric, we characterize the locality of reference in a number of representative proxy cache traces. Our findings show that there are measurable differences between the degrees (and sources) of temporal locality across these traces, and that these differences are effectively captured using our proposed metric. We illustrate the significance of our findings by summarizing the performance of a novel Web cache replacement policy---called GreedyDual*---which exploits both long-term popularity and short-term temporal correlation in an adaptive fashion. Our trace-driven simulation experiments (which are detailed in an accompanying Technical Report) show the superior performance of GreedyDual* when compared to other Web cache replacement policies.

GreedyDual* Web Caching Algorithm: Exploiting the Two Sources of Temporal Locality in Web Request Streams

The relative importance of long-term popularity and short-term temporal correlation of references for Web cache replacement policies has not been studied thoroughly. This is partially due to the lack of accurate characterization of temporal locality that enables the identification of the relative strengths of these two sources of temporal locality in a reference stream. In [21], we have proposed such a metric and have shown that Web reference streams differ significantly in the prevalence of these two sources of temporal locality. These finding underscore the importance of a Web caching strategy that can adapt in a dynamic fashion to the prevalence of these two sources of temporal locality. In this paper, we propose a novel cache replacement algorithm, GreedyDual*, which is a generalization of GreedyDual-Size. GreedyDual* uses the metrics proposed in [21] to adjust the relative worth of long-term popularity versus short-term temporal correlation of references. Our trace-driven simulation experiments show the superior performance of GreedyDual* when compared to other Web cache replacement policies proposed in the literature.

Relação temporal entre apnéia obstrutiva e refluxo gastroesofágico em lactentes

O refluxo gastroesofágico (RGE) tem sido diagnosticado em uma elevada proporção de lactentes com apnéia e episódios de ALTE (apparent life threatening events) ou eventos com aparente risco de vida, entretanto, a relação entre eles per-manece pouco entendida. A proposta deste estudo é avaliar a coexistência de apnéia e refluxo gastroesofágico em um grupo de lactentes durante o sono e vigília, através da utilização da polissonografia e, pela inclusão de um canal para aferição do pH na porção distal do esôfago, determinar a relação temporal entre estes dois eventos e aferir a associação entre ALTE e RGE. Método: A população em estudo constituiu-se de lactentes com história clínica compatível com eventos sugestivos de RGE, além de alguma anormalidade do ponto de vista ventilatório, os quais realizaram polissonografia com a inclusão de um canal para registro contínuo do pH esofágico. Os estudos polissonográficos foram analisados individualmente, em três etapas assim constituídas: Etapa 1 - realização do escore dos eventos respiratórios e dos estágios de sono e vigília, com o pesquisador cego para a ocorrência de RGE; Etapa 2 - indicação do escore isolado dos eventos de RGE; Etapa 3 - reintrodução de canal do pH e estabelecimento da correlação temporal entre os dois eventos, levando-se em consideração o período compreendido entre um minuto antes da queda do pH abaixo de 4,0, até um minuto após a elevação do pH acima de 4,0. A relação entre a história clínica de ALTE e a ocorrência de RGE durante o estudo polissonográfico também foi aferida. A partir de dados publicados na literatura, foi calculada uma amostra de 88 indivíduos (lactentes). A amostra final constituiu-se de 89 pacientes. Resultados: Quarenta pacientes apresentaram RGE e quarenta e nove não. Ambos os grupos tinham composição semelhante quanto à idade, peso, duração total do estudo polissonográfico, duração do tempo total de sono durante o estudo e história de ALTE. Ocorreu uma média de 2,82 episódios de RGE por paciente (1-20 episódios/ paciente). Os episódios de RGE foram mais freqüentes e longos durante o sono que durante os períodos de vigília. O número de eventos obstrutivos/minuto de sono (densidade de apnéias) foi significativamente maior durante os períodos de RGE (mediana 0,4), se comparados aos períodos sem RGE (mediana 0,2), p = 0,002. Em relação às apnéias centrais, não houve diferença estatisticamente significativa, p = 0, 039. Em 62% dos períodos de RGE, houve associação temporal com eventos obstrutivos, dos quais a apnéia obstrutiva precedeu o RGE em 67% dos casos. A correlação entre história de ALTE e a presença de RGE não foi estatisticamente significativa. Conclusões: Os resultados sugerem que a apnéia obstrutiva em lacten-tes está freqüentemente associada com RGE do ponto de vista de temporalidade, e é mais provável que ela ocorra precedendo um episódio de refluxo. Especula-se que a apnéia obstrutiva no lactente possa, em algumas circunstâncias, ser a causa e não a conseqüência do RGE.

Impact of vaccination on the spatial correlation and persistence of measles dynamics.

The onset of measles vaccination in England and Wales in 1968 coincided with a marked drop in the temporal correlation of epidemic patterns between major cities. We analyze a variety of hypotheses for the mechanisms driving this change. Straightforward stochastic models suggest that the interaction between a lowered susceptible population (and hence increased demographic noise) and nonlinear dynamics is sufficient to cause the observed drop in correlation. The decorrelation of epidemics could potentially lessen the chance of global extinction and so inhibit attempts at measles eradication.

A distributed spatial-temporal weighted model on MapReduce for short-term traffic flow forecasting

Accurate and timely traffic flow prediction is crucial to proactive traffic management and control in data-driven intelligent transportation systems (D2ITS), which has attracted great research interest in the last few years. In this paper, we propose a Spatial-Temporal Weighted K-Nearest Neighbor model, named STW-KNN, in a general MapReduce framework of distributed modeling on a Hadoop platform, to enhance the accuracy and efficiency of short-term traffic flow forecasting. More specifically, STW-KNN considers the spatial-temporal correlation and weight of traffic flow with trend adjustment features, to optimize the search mechanisms containing state vector, proximity measure, prediction function, and K selection. urthermore, STW-KNN is implemented on a widely adopted Hadoop distributed computing platform with the MapReduce parallel processing paradigm, for parallel prediction of traffic flow in real time. inally, with extensive experiments on real-world big taxi trajectory data, STW-KNN is compared with the state-of-the-art prediction models including conventional K-Nearest Neighbor (KNN), Artificial Neural Networks (ANNs), Naïve Bayes (NB), Random orest (R), and C4.. The results demonstrate that the proposed model is superior to existing models on accuracy by decreasing the mean absolute percentage error (MAPE) value more than 11.9% only in time domain and even achieves 89.71% accuracy improvement with the MAPEs of between 4% and 6.% in both space and time domains, and also significantly improves the efficiency and scalability of short-term traffic flow forecasting over existing approaches.

Big data analytics and visualization with spatio-temporal correlations for traffic accidents

Big data analytics for traffic accidents is a hot topic and has significant values for a smart and safe traffic in the city. Based on the massive traffic accident data from October 2014 to March 2015 in Xiamen, China, we propose a novel accident occurrences analytics method in both spatial and temporal dimensions to predict when and where an accident with a specific crash type will occur consequentially by whom. Firstly, we analyze and visualize accident occurrences in both temporal and spatial view. Second, we illustrate spatio-temporal visualization results through two case studies in multiple road segments, and the impact of weather on crash types. These findings of accident occurrences analysis and visualization would not only help traffic police department implement instant personnel assignments among simultaneous accidents, but also inform individual drivers about accident-prone sections and the time span which requires their most attention.

Persistence of income inequality : does child mortality matter?

Many developing countries are afflicted by persistent inequality in the distribution of income. While a growing body of literature emphasizes differential fertility as a channel through which income inequality persists, this paper investigates differential child mortality – differences in the incidence of child mortality across socioeconomic groups – as a critical link in this regard. Using evidence from cross-country data to evaluate this linkage, we find that differential child mortality serves as a stronger channel than differential fertility in the transmission of income inequality over time. We use random effects and generalized estimating equations techniques to account for temporal correlation within countries. The results are robust to the use of an alternate definition of fertility that reflects parental preference for children instead of realized fertility.

Complex regulation of membrane-type matrix metalloproteinase expression and matrix metalloproteinase-2 activation by concanavalin A in MDA-MB-231 human breast cancer cells

Matrix Metalloproteinase-2 (MMP-2) is secreted as a zymogen, the activation of which has been associated with metastatic progression in human breast cancer (HBC). Concanavalin A (Con A) has been found to induce activation of MMP-2 in invasive HBC cell lines. Con A effects on the expression of mRNA for membrane-type matrix metalloproteinase (MT-MMP), a newly described cell surface-associated MMP, showed a close temporal correlation with induction of MMP-2 activation. It is surprising that MT-MMP mRNA is constitutively present in the uninduced MDA-MB-231 cell, despite a lack of MMP-2 activation. We have used actinomycin D to demonstrate a partial requirement for de novo gene expression in the induction of MMP-2 activation by Con A in MDA-MB-231 HBC cells. Furthermore, this transcriptional response to Con A appeared to require the continued presence of Con A for its manifestation. The nontranscriptional component of the Con A induction manifests rapidly, is quite substantial, and persists strongly despite actinomycin D abrogation of both constitutive and Con A-induced MT-MMP. Cycloheximide analyses suggest that protein synthesis may be involved in this rapid transcription-independent response. These studies suggest that Con A induces MMP-2-activation in part by up-regulation of MT-MMP expression but has a more complicated mode of action, involving additional nontranscriptional effects, which apparently require protein synthesis.

Statistical modelling and power analysis for detecting trends in total suspended sediment loads

The export of sediments from coastal catchments can have detrimental impacts on estuaries and near shore reef ecosystems such as the Great Barrier Reef. Catchment management approaches aimed at reducing sediment loads require monitoring to evaluate their effectiveness in reducing loads over time. However, load estimation is not a trivial task due to the complex behaviour of constituents in natural streams, the variability of water flows and often a limited amount of data. Regression is commonly used for load estimation and provides a fundamental tool for trend estimation by standardising the other time specific covariates such as flow. This study investigates whether load estimates and resultant power to detect trends can be enhanced by (i) modelling the error structure so that temporal correlation can be better quantified, (ii) making use of predictive variables, and (iii) by identifying an efficient and feasible sampling strategy that may be used to reduce sampling error. To achieve this, we propose a new regression model that includes an innovative compounding errors model structure and uses two additional predictive variables (average discounted flow and turbidity). By combining this modelling approach with a new, regularly optimised, sampling strategy, which adds uniformity to the event sampling strategy, the predictive power was increased to 90%. Using the enhanced regression model proposed here, it was possible to detect a trend of 20% over 20 years. This result is in stark contrast to previous conclusions presented in the literature. (C) 2014 Elsevier B.V. All rights reserved.

Systematic Construction of Linear Transform Based Full-Diversity, Rate-One Space-Time Frequency Codes

In this paper, we generalize the existing rate-one space frequency (SF) and space-time frequency (STF) code constructions. The objective of this exercise is to provide a systematic design of full-diversity STF codes with high coding gain. Under this generalization, STF codes are formulated as linear transformations of data. Conditions on these linear transforms are then derived so that the resulting STF codes achieve full diversity and high coding gain with a moderate decoding complexity. Many of these conditions involve channel parameters like delay profile (DP) and temporal correlation. When these quantities are not available at the transmitter, design of codes that exploit full diversity on channels with arbitrary DIP and temporal correlation is considered. Complete characterization of a class of such robust codes is provided and their bit error rate (BER) performance is evaluated. On the other hand, when channel DIP and temporal correlation are available at the transmitter, linear transforms are optimized to maximize the coding gain of full-diversity STF codes. BER performance of such optimized codes is shown to be better than those of existing codes.

A hidden Markov model approach for determining vessel activity from vessel monitoring system data.

Many fisheries worldwide have adopted vessel monitoring systems (VMS) for compliance purposes. An added benefit of these systems is that they collect a large amount of data on vessel locations at very fine spatial and temporal scales. This data can provide a wealth of information for stock assessment, research, and management. However, since most VMS implementations record vessel location at set time intervals with no regard to vessel activity, some methodology is required to determine which data records correspond to fishing activity. This paper describes a probabilistic approach, based on hidden Markov models (HMMs), to determine vessel activity. A HMM provides a natural framework for the problem and, by definition, models the intrinsic temporal correlation of the data. The paper describes the general approach that was developed and presents an example of this approach applied to the Queensland trawl fishery off the coast of eastern Australia. Finally, a simulation experiment is presented that compares the misallocation rates of the HMM approach with other approaches.