Interventions for erythema nodosum leprosum

Background Erythema nodosum leprosum (ENL) is a serious immunological complication of leprosy, causing inflammation of skin, nerves, other organs, and general malaise. Many different therapies exist for ENL, but it is unclear if they work or which therapy is optimal. Objectives To assess the effects of interventions for erythema nodosum leprosum. Search strategy We searched the Cochrane Skin Group Specialised Register, the Cochrane Central Register of Controlled Trials (CENTRAL) in The Cochrane Library (Issue 1, 2009), MEDLINE (from 2003), EMBASE (from 2005), LILACS and AMED (from inception), CINAHL (from 1981), and databases of ongoing trials, all in March 2009. We checked reference lists of articles and contacted the American Leprosy Missions in Brazil to locate studies. Selection criteria Randomised controlled trials (RCTs) of interventions for ENL in people with leprosy. Data collection and analysis Two authors performed study selection, assessed trial quality, and extracted data. Main results We included 13 studies with a total of 445 participants. The quality of the trials was generally poor and no results could be pooled due to the treatments being so heterogeneous. Treatment with thalidomide showed a significant remission of skin lesions compared to acetylsalicylic acid (aspirin) (RR 2.43; 95% CI 1.28 to 4.59) (1 trial, 92 participants). Clofazimine treatment was superior to prednisolone (more treatment successes; RR 3.67; 95% CI 1.36 to 9.91) (1 trial, 24 participants), and thalidomide (fewer recurrences; RR0.08; 95% CI 0.01 to 0.56) (1 trial, 72 participants). We did not find any significant benefit for intravenous betamethasone compared to dextrose (1 trial, 10 participants), pentoxifylline compared to thalidomide (1 trial, 44 participants), indomethacin compared to prednisolone, aspirin or chloroquine treatments (2 trials, 80 participants), or levamisole compared to placebo (1 trial, 12 participants). Mild to moderate adverse events were significantly lower in participants taking 100 mg thalidomide compared to 300 mg thalidomide daily (RR 0.46; 95% CI 0.23 to 0.93). Significantly more minor adverse events were reported in participants taking clofazimine compared with prednisolone (RR 1.92; 95% CI 1.10 to 3.35). None of the studies assessed quality of life or economic outcomes. Authors' conclusions There is some evidence of benefit for thalidomide and clofazimine, but generally we did not find clear evidence of benefit for interventions in the management of ENL. However, this does not mean they do not work, because the studies were small and poorly reported. Larger studies using clearly defined participants, outcome measures, and internationally recognised scales are urgently required

Semiparametric models for nonlinear spatio-temporal data with application to the United States housing prices indexes

Modelling spatio-temporal data has received significant attention, recently and is widely applied in many disciplines such as economics, environmental and social sciences. In economics, housing price is a real example that indicates the importance of modeling such data. Estimating the movement in housing prices is an important but challenging problem due to the difficulties associated with spatio-temporal interactions. One main challenge is that there is no natural spatial ordering and thus it is not as straightforward as in time series analysis to transform data to be stationary across space. In addition, it is a challenge to model spatio-temporal data collected at irregularly spaced sampling locations due to the potentially large number of parameters. Moreover, the complexity of the dependence structure requires new effective statistical methods for modeling and analysis. While nonparametric and semiparametric methods have been popular for nonlinear modeling of time series data in econometrics and statistics, they become increasingly challenging when extended to irregularly located spatio-temporal data with complex nonlinear structures. The literature on nonlinear spatio-temporal modelling is still rather rare except a few contributions recently done, for example, by (Lu et al., 2009), (Wikle and Hooten, 2010) and (Wikle and Holan, 2011). Therefore, the main aim of this thesis is to propose a class of semiparametric spatio-temporal autoregressive partially nonlinear regression models as a practical way to overcome these challenges. The main contributions of this thesis are summarised as follows: (1) In Chapter 2, a class of semiparametric spatio-temporal autoregressive partially nonlinear regression models is proposed. The proposed models not only permit location-varying nonlinear relationships between the response variable and the covariates but also allow for the dependence structure to be nonstationary over space while alleviating the ”curse of dimensionality” by using the popular idea of spatial weight matrix measuring the spatial interaction, which is assumed to be well defined as in spatial econometrics. Both the estimation and its finite- and large sample properties for the proposed models are established. (2) In order to more objectively let data decide the spatial interaction in the models, in Chapter 3, we propose a scheme of general data-driven models to estimate the spatial weights in the semiparametric spatio-temporal autoregressive partially nonlinear regression models by applying the adaptive lasso. Both estimation and its finite- and large-sample properties for this class of the general data-driven models are developed. (3) An improved scheme for such data-driven models with spatial weight matrix is presented in Chapter 4. For this class of the improved data-driven models, we develop a computationally feasible method for estimation and thus enable our methodology to be applicable in practice. Asymptotic properties of our proposed estimates are established and comparisons are made, in theory and via simulations, between estimates before and after spatial smoothing. (4) In empirical case studies, the proposed methodologies are applied to investigate the housing prices in relation to the mortgage rates in Chapter 2 and to the consumer price index in Chapter 3 and 4 for the 50 states and District of Columbia (DC) in the United States (U.S.). It is empirically found that such relationships could be of nonlinear features that help to improve the predictions and the third class of the improved data-driven models appears to work promisingly better.Thesis (Ph.D.) -- University of Adelaide, School of Mathematical Sciences, 2016

Combining Two Exponentiated Families to Generate a New Family of Distributions

This article presents a new technique to generate distributions that have the ability to fit any complex data called the exponentiated exponentiated Weibull-X (EEW-X) family, and the exponentiated exponentiated Weibull exponential (EEWE) distribution is presented as a member of this family. The new distribution’s unknown parameters were calculated by applying the maximum likelihood method. Some statistical properties, such as quantile, Rényi entropy, order statistics, and median are obtained for the proposed distribution. A simulation study was performed for different cases to investigate the estimation method’s performance. Three real datasets have been applied in which the new distribution has shown more flexibility compared to some other distributions

Afzalganj Mosque

general view, Exterior view from the ablution tank and courtyard showing the three arched-facade and the two minarets. Photograph by Muhammad Khalidi., 1940

Afzal Ganj Bridge

general view, view of the bridge showing demarcated traffic lanes, 198

Estimation for semiparametric nonlinear regression of irregularly located spatial time-series data

Large spatial time-series data with complex structures collected at irregularly spaced sampling locations are prevalent in a wide range of applications. However, econometric and statistical methodology for nonlinear modeling and analysis of such data remains rare. Asemiparametric nonlinear regression is thus proposed for modelling nonlinear relationship between response and covariates, which is location-based and considers both temporal-lag and spatial-neighbouring effects, allowing data-generating process nonstationary over space (butturned into stationary series along time) while the sampling spatial grids can be irregular. A semiparametric method for estimation is also developed that is computationally feasible and thus enables application in practice. Asymptotic properties of the proposed estimators are established while numerical simulations are carried for comparisons between estimates before and after spatial smoothing. Empirical application to investigation of housing prices in relation to interest rates in the United States is demonstrated, with a nonlinear threshold structure identified

Afzal Ganj Bridge

general view, view toward north, showing demarcated traffic lanes for rickshaws and bicycles, 198

Afzal Ganj Bridge

general view, view from north, showing lanes of traffic, 198

Afzalganj Mosque

general view, movie poster for "Sudden Impact" on Musi River embankment, with Naya Pul on right and Afzalganj Masjid in distance at left, 198