A sequential Cox approach for estimating the causal effect of treatment in the presence of time-dependent confounding applied to data from the Swiss HIV Cohort Study

When estimating the effect of treatment on HIV using data from observational studies, standard methods may produce biased estimates due to the presence of time-dependent confounders. Such confounding can be present when a covariate, affected by past exposure, is both a predictor of the future exposure and the outcome. One example is the CD4 cell count, being a marker for disease progression for HIV patients, but also a marker for treatment initiation and influenced by treatment. Fitting a marginal structural model (MSM) using inverse probability weights is one way to give appropriate adjustment for this type of confounding. In this paper we study a simple and intuitive approach to estimate similar treatment effects, using observational data to mimic several randomized controlled trials. Each 'trial' is constructed based on individuals starting treatment in a certain time interval. An overall effect estimate for all such trials is found using composite likelihood inference. The method offers an alternative to the use of inverse probability of treatment weights, which is unstable in certain situations. The estimated parameter is not identical to the one of an MSM, it is conditioned on covariate values at the start of each mimicked trial. This allows the study of questions that are not that easily addressed fitting an MSM. The analysis can be performed as a stratified weighted Cox analysis on the joint data set of all the constructed trials, where each trial is one stratum. The model is applied to data from the Swiss HIV cohort study.

Modeling Yield Surfaces of Various Structural Shapes

This study investigates the possibility of custom fitting a widely accepted approximate yield surface equation (Ziemian, 2000) to the theoretical yield surfaces of five different structural shapes, which include wide-flange, solid and hollow rectangular, and solid and hollow circular shapes. To achieve this goal, a theoretically “exact” but overly complex representation of the cross section’s yield surface was initially obtained by using fundamental principles of solid mechanics. A weighted regression analysis was performed with the “exact” yield surface data to obtain the specific coefficients of three terms in the approximate yield surface equation. These coefficients were calculated to determine the “best” yield surface equation for a given cross section geometry. Given that the exact yield surface shall have zero percentage of concavity, this investigation evaluated the resulting coefficient of determination (

Regulation of phosphatidylinositide turnover in the myometrium by cAMP: Implications for the control of uterine contraction

Regulation of uterine quiescence involves the integration of the signaling pathways regulating uterine contraction and relaxation. Uterine contractants increase intracellular calcium through receptor/GαqPLC coupling, resulting in contraction of the myometrium. Elevation of cAMP concentration has been correlated with relaxation of the myometrium. However, the mechanism of cAMP action in the uterus is unclear. ^ Both endogenous and exogenous increases in cAMP inhibited oxytocin-stimulated phosphatidylinositide turnover in an immortalized pregnant human myometrial cell line (PHM1-41). This inhibition was reversed by cAMP-dependent protein kinase (PKA) inhibitors, suggesting the involvement of PKA. cAMP inhibited phosphatidyinositide turnover stimulated by different agonists in different cell lines. These data suggest that the cAMP inhibitory mechanism is neither cell nor receptor dependent, and inhibits Gαq/PLCβ1 and PLCβ3 coupling. ^ The subcellular localization of PKA occurs via PKA binding to A-Kinase-Anchoring-Proteins (AKAP), and peptides that inhibit this association have been developed (S-Ht31). S-Ht31 blocked cAMP-stimulated PKA activity and decreased PKA concentration in PHM1-41 cell plasma membranes. S-Ht31 reversed the ability of CPT-cAMP, forskolin and relaxin to inhibit phosphatidylinositide turnover in PHM1-41 cells. Overlay analysis of both PHM1-41 cell and nonpregnant rat myometrium found an AKAPs of 86 kDa and 150 kDa associated with the plasma membrane, respectively. These data suggest that PKA anchored to the plasma membrane via AKAP150/PKA anchoring is involved in the cAMP inhibitory mechanism. ^ CPT-cAMP and isoproterenol inhibited phosphatidylinositide turnover in rat myometrium from days 12 through 20 of gestation. In contrast, neither agent was effective in the 21 day pregnant rat myometrium. The decrease in the cAMP inhibitory mechanism was correlated with a decrease in PKA and an increase in protein phosphatase 2B (PP2B) concentration in rat myometrial plasma membranes on day 21 of gestation. In myometrial total cell homogenates, both PKA and PP2B concentration increased on day 21. S-Ht31 inhibited cAMP inhibition of phosphatidylinositide turnover in day 19 pregnant rat myometrium. Both PKA and PP2B coimmunoprecipitated with an AKAP150 in a gestational dependent manner, suggesting this AKAP localizes PKA and PP2B to the plasma membrane. ^ These data presented demonstrate the importance of the cAMP inhibitory mechanism in regulating uterine contractility. ^

Descrição morfológica e posicionamento filogenético de um lagarto (Reptilia, Squamata) do Mioceno Inferior da Formação Chichínales, General Roca, Província de Río Negro, Argentina

Embora os escamados sejam comumente encontrados em sítios fossilíferos cenozóicos sul−americanos, materiais esqueléticos completos são raros. Apenas alguns poucos exemplares assim foram registrados, com a maioria dos achados representando materiais fragmentários de crânio e mandíbulas ou vértebras isoladas. Dentre as localidades provedoras de vertebrados fósseis na América do Sul, a Formação Chichínales se destaca pela recente descoberta, em seus sedimentos, de um crânio quase completo de um lagarto teiídeo previamente desconhecido. Dada a fauna associada, a idade da formação é definida como Mioceno Temprano (Colhuehuapense). No presente estudo, conclui−se, através de uma análise filogenética contendo 39 espécies viventes e fósseis de escamados e 149 caracteres osteológicos, que este material pertence a uma nova espécie do gênero contemporâneo Callopistes. Uma descrição morfológica detalhada do fóssil, obtida através de análises estereoscópicas e de microtomografia computadorizada de alta resolução (CT Scan), também é apresentada. A matriz morfológica foi analisada com o auxílio do software TNT Versão 1.1, seguindo o princípio de máxima parcimônia, com todos os caracteres tratados com a mesma pesagem, resultando em quatro árvores igualmente parcimoniosas, que foram então utilizadas para a construção de uma árvore de consenso estrito. Em todas as quatro árvores, o novo táxon posicionou−se dentro da família Teiidae como um membro do clado formado pelas demais espécies viventes de Callopistes. Entretanto, não foi possível estabelecer uma relação de grupo−irmão inequívoca entre as duas espécies de Callopistes presentes na análise e o fóssil. A atual distribuição das duas espécies viventes de Callopistes e a localidade de onde foi recuperado o fóssil em estudo indicam que esse gênero possuía uma distribuição muito mais ampla no passado, chegando a áreas patagônicas cis−Andinas, diferentemente das áreas trans−Andinas de altitude onde as duas espécies atuais estão restritas

Enabling long journeys in electric vehicles:design and demonstration of an infrastructure location model

This research develops a methodology and model formulation which suggests locations for rapid chargers to help assist infrastructure development and enable greater battery electric vehicle (BEV) usage. The model considers the likely travel patterns of BEVs and their subsequent charging demands across a large road network, where no prior candidate site information is required. Using a GIS-based methodology, polygons are constructed which represent the charging demand zones for particular routes across a real-world road network. The use of polygons allows the maximum number of charging combinations to be considered whilst limiting the input intensity needed for the model. Further polygons are added to represent deviation possibilities, meaning that placement of charge points away from the shortest path is possible, given a penalty function. A validation of the model is carried out by assessing the expected demand at current rapid charging locations and comparing to recorded empirical usage data. Results suggest that the developed model provides a good approximation to real world observations, and that for the provision of charging, location matters. The model is also implemented where no prior candidate site information is required. As such, locations are chosen based on the weighted overlay between several different routes where BEV journeys may be expected. In doing so many locations, or types of locations, could be compared against one another and then analysed in relation to siting practicalities, such as cost, land permission and infrastructure availability. Results show that efficient facility location, given numerous siting possibilities across a large road network can be achieved. Slight improvements to the standard greedy adding technique are made by adding combination weightings which aim to reward important long distance routes that require more than one charge to complete.

Development and evaluation of a geographic information system based method to estimate flooding susceptibility in an area of Broward County, Florida

The objective of this study was to develop a GIS-based multi-class index overlay model to determine areas susceptible to inland flooding during extreme precipitation events in Broward County, Florida. Data layers used in the method include Airborne Laser Terrain Mapper (ALTM) elevation data, excess precipitation depth determined through performing a Soil Conservation Service (SCS) Curve Number (CN) analysis, and the slope of the terrain. The method includes a calibration procedure that uses "weights and scores" criteria obtained from Hurricane Irene (1999) records, a reported 100-year precipitation event, Doppler radar data and documented flooding locations. Results are displayed in maps of Eastern Broward County depicting types of flooding scenarios for a 100-year, 24-hour storm based on the soil saturation conditions. As expected the results of the multi-class index overlay analysis showed that an increase for the potential of inland flooding could be expected when a higher antecedent moisture condition is experienced. The proposed method proves to have some potential as a predictive tool for flooding susceptibility based on a relatively simple approach.

Uncertainty analysis of pollutant build-up modelling based on a Bayesian Weighted Least Squares approach

Reliable pollutant build-up prediction plays a critical role in the accuracy of urban stormwater quality modelling outcomes. However, water quality data collection is resource demanding compared to streamflow data monitoring, where a greater quantity of data is generally available. Consequently, available water quality data sets span only relatively short time scales unlike water quantity data. Therefore, the ability to take due consideration of the variability associated with pollutant processes and natural phenomena is constrained. This in turn gives rise to uncertainty in the modelling outcomes as research has shown that pollutant loadings on catchment surfaces and rainfall within an area can vary considerably over space and time scales. Therefore, the assessment of model uncertainty is an essential element of informed decision making in urban stormwater management. This paper presents the application of a range of regression approaches such as ordinary least squares regression, weighted least squares Regression and Bayesian Weighted Least Squares Regression for the estimation of uncertainty associated with pollutant build-up prediction using limited data sets. The study outcomes confirmed that the use of ordinary least squares regression with fixed model inputs and limited observational data may not provide realistic estimates. The stochastic nature of the dependent and independent variables need to be taken into consideration in pollutant build-up prediction. It was found that the use of the Bayesian approach along with the Monte Carlo simulation technique provides a powerful tool, which attempts to make the best use of the available knowledge in the prediction and thereby presents a practical solution to counteract the limitations which are otherwise imposed on water quality modelling.

Supplementary information : weighted tree kernels for sequence analysis

Genomic sequences are fundamentally text documents, admitting various representations according to need and tokenization. Gene expression depends crucially on binding of enzymes to the DNA sequence at small, poorly conserved binding sites, limiting the utility of standard pattern search. However, one may exploit the regular syntactic structure of the enzyme's component proteins and the corresponding binding sites, framing the problem as one of detecting grammatically correct genomic phrases. In this paper we propose new kernels based on weighted tree structures, traversing the paths within them to capture the features which underpin the task. Experimentally, we and that these kernels provide performance comparable with state of the art approaches for this problem, while offering significant computational advantages over earlier methods. The methods proposed may be applied to a broad range of sequence or tree-structured data in molecular biology and other domains.

Weighted rank regression for clustered data analysis

We consider ranked-based regression models for clustered data analysis. A weighted Wilcoxon rank method is proposed to take account of within-cluster correlations and varying cluster sizes. The asymptotic normality of the resulting estimators is established. A method to estimate covariance of the estimators is also given, which can bypass estimation of the density function. Simulation studies are carried out to compare different estimators for a number of scenarios on the correlation structure, presence/absence of outliers and different correlation values. The proposed methods appear to perform well, in particular, the one incorporating the correlation in the weighting achieves the highest efficiency and robustness against misspecification of correlation structure and outliers. A real example is provided for illustration.

Analysis of two degrees of freedom systems through weighted mean square linearization approach

In this paper a study of the free, forced and self-excited vibrations of non-linear, two degrees of freedom systems is reported. The responses are obtained by linearizing the nonlinear equations using the weighted mean square linearization approach. The scope of this approach, in terms of the type of non-linearities the method can tackle, is also discussed.

Analysis of two degrees of freedom systems through weighted mean square linearization approach

In this paper a study of the free, forced and self-excited vibrations of non-linear, two degrees of freedom systems is reported. The responses are obtained by linearizing the nonlinear equations using the weighted mean square linearization approach. The scope of this approach, in terms of the type of non-linearities the method can tackle, is also discussed.

BER Analysis of Weighted Interference Cancellation in Multicarrier DS-CDMA Systems

In this paper, we present the design and bit error performance analysis of weighted linear parallel interference cancellers (LPIC) for multicarrier (MC) DS-CDMA systems. We propose an LPIC scheme where we estimate (and cancel) the multiple access interference (MAI) based on the soft outputs on individual subcarriers, and the interference cancelled outputs on different subcarriers are combined to form the final decision statistic. We scale the MAI estimate on individual subcarriers by a weight before cancellation; these weights are so chosen to maximize the signal-to-interference ratios at the individual subcarrier outputs. For this weighted LPIC scheme, using an approach involving the characteristic function of the decision variable, we derive exact bit error rate (BER) expressions for different cancellation stages. Using the same approach, we also derive exact BER expressions for the matched filter (MF) and decorrelating detectors for the considered MC DS-CDMA system. We show that the proposed weighted LPIC scheme performs better than the MF detector and the conventional LPIC (where the weights are taken to be unity), and close to the decorrelating detector.

Weighted subspace methods and spatial smoothing: analysis and comparison

The effect of using a spatially smoothed forward-backward covariance matrix on the performance of weighted eigen-based state space methods/ESPRIT, and weighted MUSIC for direction-of-arrival (DOA) estimation is analyzed. Expressions for the mean-squared error in the estimates of the signal zeros and the DOA estimates, along with some general properties of the estimates and optimal weighting matrices, are derived. A key result is that optimally weighted MUSIC and weighted state-space methods/ESPRIT have identical asymptotic performance. Moreover, by properly choosing the number of subarrays, the performance of unweighted state space methods can be significantly improved. It is also shown that the mean-squared error in the DOA estimates is independent of the exact distribution of the source amplitudes. This results in a unified framework for dealing with DOA estimation using a uniformly spaced linear sensor array and the time series frequency estimation problems.