A hybrid approach to combining CART and logistic regression for stock ranking

The benefits of applying tree-based methods to the purpose of modelling financial assets as opposed to linear factor analysis are increasingly being understood by market practitioners. Tree-based models such as CART (classification and regression trees) are particularly well suited to analysing stock market data which is noisy and often contains non-linear relationships and high-order interactions. CART was originally developed in the 1980s by medical researchers disheartened by the stringent assumptions applied by traditional regression analysis (Brieman et al. [1984]). In the intervening years, CART has been successfully applied to many areas of finance such as the classification of financial distress of firms (see Frydman, Altman and Kao [1985]), asset allocation (see Sorensen, Mezrich and Miller [1996]), equity style timing (see Kao and Shumaker [1999]) and stock selection (see Sorensen, Miller and Ooi [2000])...

Quantile regression without the curse of unsmoothness

We consider quantile regression models and investigate the induced smoothing method for obtaining the covariance matrix of the regression parameter estimates. We show that the difference between the smoothed and unsmoothed estimating functions in quantile regression is negligible. The detailed and simple computational algorithms for calculating the asymptotic covariance are provided. Intensive simulation studies indicate that the proposed method performs very well. We also illustrate the algorithm by analyzing the rainfall–runoff data from Murray Upland, Australia.

Akt, AS160, metabolic risk factors and aerobic fitness in middle-aged women

Aims: This study investigated the association between the basal (rest) insulin-signaling proteins, Akt, and the Akt substrate AS160, metabolic risk factors, inflammatory markers and aerobic fitness, in middle-aged women with varying numbers of metabolic risk factors for type 2 diabetes. Methods: Sixteen women (n = 16) aged 51.3+/-5.1 (mean +/-SD) years provided muscle biopsies and blood samples at rest. In addition, anthropometric characteristics and aerobic power were assessed and the number of metabolic risk factors for each participant was determined (IDF criteria). Results: The mean number of metabolic risk factors was 1.6+/-1.2. Total Akt was negatively correlated with IL-1 beta (r = -0.45, p = 0.046), IL-6 (r = -0.44, p = 0.052) and TNF-alpha (r = -0.51, p = 0.025). Phosphorylated AS160 was positively correlated with HDL (r = 0.58, p = 0.024) and aerobic fitness (r = 0.51, p = 0.047). Furthermore, a multiple regression analysis revealed that both HDL (t = 2.5, p = 0.032) and VO(2peak) (t = 2.4, p = 0.037) were better predictors for phosphorylated AS160 than TNF-alpha or IL-6 (p>0.05). Conclusions: Elevated inflammatory markers and increased metabolic risk factors may inhibit insulin-signaling protein phosphorylation in middle-aged women, thereby increasing insulin resistance under basal conditions. Furthermore, higher HDL and fitness levels are associated with an increased AS160 phosphorylation, which may in turn reduce insulin resistance.

The asthmatic athlete, inhaled beta agonists, and performance

INTRODUCTION: The large increase in the number of athletes who apply to use inhaled beta agonists (IBAs) at the Olympic Games is a concern to the medical community. This review will examine the use of IBAs in the asthmatic athlete, the variability that exists between countries and sport, and outline a plan to justify the use of these medications. DATA SOURCES: Much of this article is a result of an International Olympic Committee (IOC) Medical Commission-sponsored meeting that took place in May 2001. Records of the use of IBAs at previous Olympics were reviewed. MEDLINE Searches (PubMed interface) were performed using key words to locate published work relating to asthma, elite athletes, performance, treatment, and ergogenic aids. MAIN RESULTS: Since 1984 there have been significant increases in the use of IBAs at the Olympic Games as well as marked geographical differences in the percentage of athletes requesting the use of IBAs. There are large differences in the incidence of IBA use between sports with a trend towards increased use in endurance sports. There are no ergogenic effects of any IOC-approved IBA given in a therapeutic dose. CONCLUSIONS: In many cases, the prescription of IBAs to this population has been made on empirical grounds. Beginning with the 2002 Winter Games, athletes will be required to submit to the IOC Medical Commission clinical and laboratory evidence that justifies the use of this medication. The eucapnic voluntary hyperpnea test will be used to assess individuals who have not satisfied an independent medical panel of the need to use an IBA.

Can slide positivity rates predict malaria transmission?

Background: Malaria is a significant threat to population health in the border areas of Yunnan Province, China. How to accurately measure malaria transmission is an important issue. This study aimed to examine the role of slide positivity rates (SPR) in malaria transmission in Mengla County, Yunnan Province, China. Methods: Data on annual malaria cases, SPR and socio-economic factors for the period of 1993 to 2008 were obtained from the Center for Disease Control and Prevention (CDC) and the Bureau of Statistics, Mengla, China. Multiple linear regression models were conducted to evaluate the relationship between socio-ecologic factors and malaria incidence. Results: The results show that SPR was significantly positively associated with the malaria incidence rates. The SPR (beta = 1.244, p = 0.000) alone and combination (SPR, beta = 1.326, p < 0.001) with other predictors can explain about 85% and 95% of variation in malaria transmission, respectively. Every 1% increase in SPR corresponded to an increase of 1.76/100,000 in malaria incidence rates. Conclusion: SPR is a strong predictor of malaria transmission, and can be used to improve the planning and implementation of malaria elimination programmes in Mengla and other similar locations. SPR might also be a useful indicator of malaria early warning systems in China.

Therapeutic immunisation of rabbits with cottontail rabbit papillomavirus (CRPV) virus-like particles (VLP) induces regression of established papillomas

There is overwhelming evidence that persistent infection with high-risk human papillomaviruses (HR-HPV) is the main risk factor for invasive cancer of the cervix. Due to this global public health burden, two prophylactic HPV L1 virus-like particles (VLP) vaccines have been developed. While these vaccines have demonstrated excellent type-specific prevention of infection by the homologous vaccine types (high and low risk HPV types), no data have been reported on the therapeutic effects in people already infected with the low-risk HPV type. In this study we explored whether regression of CRPV-induced papillomas could be achieved following immunisation of out-bred New Zealand White rabbits with CRPV VLPs. Rabbits immunised with CRPV VLPs had papillomas that were significantly smaller compared to the negative control rabbit group (P ≤ 0.05). This data demonstrates the therapeutic potential of PV VLPs in a well-understood animal model with potential important implications for human therapeutic vaccination for low-risk HPVs. © 2008 Govan et al; licensee BioMed Central Ltd.

The cancer stem-cell hypothesis : its emerging role in lung cancer biology and its relevance for future therapy

The cancer stem-cell (CSC) hypothesis suggests that there is a small subset of cancer cells that are responsible for tumor initiation and growth, possessing properties such as indefinite self-renewal, slow replication, intrinsic resistance to chemotherapy and radiotherapy, and an ability to give rise to differentiated progeny. Through the use of xenotransplantation assays, putative CSCs have been identified in many cancers, often identified by markers usually expressed in normal stem cells. This is also the case in lung cancer, and the accumulated data on side population cells, CD133, CD166, CD44 and ALDH1 are beginning to clarify the true phenotype of the lung cancer stem cell. Furthermore, it is now clear that many of the pathways of normal stem cells, which guide cellular proliferation, differentiation, and apoptosis are also prominent in CSCs; the Hedgehog (Hh), Notch, and Wnt signaling pathways being notable examples. The CSC hypothesis suggests that there is a small reservoir of cells within the tumor, which are resistant to many standard therapies, and can give rise to new tumors in the form of metastases or relapses after apparent tumor regression. Therapeutic interventions that target CSC pathways are still in their infancy and clinical data of their efficacy remain limited. However Smoothened inhibitors, gamma-secretase inhibitors, anti-DLL4 antagonists, Wnt antagonists, and CBP/β-catenin inhibitors have all shown promising anticancer effects in early studies. The evidence to support the emerging picture of a lung cancer CSC phenotype and the development of novel therapeutic strategies to target CSCs are described in this review.

Cytokine synthesis by intestinal intraepithelial lymphocytes. Both gamma/delta T cell receptor-positive and alpha/beta T cell receptor-positive T cells in the G1 phase of cell cycle produce IFN-gamma and IL-5

Murine intestinal intraepithelial lymphocytes (IEL) have been shown to contain subsets of alpha/beta TCR+ and gamma/delta TCR+ T cells that spontaneously produce cytokines such as IFN-gamma and IL-5. We have now determined the nature and cell cycle stage of these cytokine-producing T lymphocytes in EIL by using IFN-gamma- and IL-5-specific ELISPOT assay, cytokine-specific mRNA-cDNA dot-blot hybridization and polymerase chain reaction, and flow cytometry (FACS) for DNA analysis. When CD3+ T cells from IEL of normal C3H/HeN mice were separated into low and high density fractions by discontinuous Percoll gradients, IFN-gamma and IL-5 spot-forming cells were only found in the former population. Analysis of mRNA for these cytokines by both IFN-gamma- and IL-5-specific dot-blot hybridization and polymerase chain reaction revealed that higher levels of message for IFN-gamma and IL-5 were also seen in the low density fraction. However, cell cycle analysis of these two fractions by FACS using propidium iodide showed a similar pattern of cell cycle stages in both low and high density populations (G0 + G1 approximately 96 to 98% and S/G2 + M approximately 2 to 4%). Finally, mRNA from gamma/delta TCR+ and alpha/beta TCR+ T cells in both low and high density fractions of IEL were analyzed for IFN-gamma and IL-5 message by polymerase chain reaction. After 35 cycles of amplification, both gamma/delta TCR+ and alpha/beta TCR+ T cells in the low density fraction expressed higher levels of message for these two cytokines when compared with the high density population. These results have now shown that both gamma/delta and alpha/beta TCR+ IEL can be separated into low and high density subsets and both fractions possess a similar stage of cell cycle. However, only the low density cells (in G1 phase) of both gamma/delta and alpha/beta TCR types possess increased cytokine-specific mRNA and produce the cytokines IFN-gamma and IL-5. Our results suggest that alpha/beta TCR+ and gamma/delta TCR+ IEL can produce cytokines without cell proliferation.

Regression and hypothesis tests for multivariate GNSS state time series

A satellite based observation system can continuously or repeatedly generate a user state vector time series that may contain useful information. One typical example is the collection of International GNSS Services (IGS) station daily and weekly combined solutions. Another example is the epoch-by-epoch kinematic position time series of a receiver derived by a GPS real time kinematic (RTK) technique. Although some multivariate analysis techniques have been adopted to assess the noise characteristics of multivariate state time series, statistic testings are limited to univariate time series. After review of frequently used hypotheses test statistics in univariate analysis of GNSS state time series, the paper presents a number of T-squared multivariate analysis statistics for use in the analysis of multivariate GNSS state time series. These T-squared test statistics have taken the correlation between coordinate components into account, which is neglected in univariate analysis. Numerical analysis was conducted with the multi-year time series of an IGS station to schematically demonstrate the results from the multivariate hypothesis testing in comparison with the univariate hypothesis testing results. The results have demonstrated that, in general, the testing for multivariate mean shifts and outliers tends to reject less data samples than the testing for univariate mean shifts and outliers under the same confidence level. It is noted that neither univariate nor multivariate data analysis methods are intended to replace physical analysis. Instead, these should be treated as complementary statistical methods for a prior or posteriori investigations. Physical analysis is necessary subsequently to refine and interpret the results.

Language affects length of stay in emergency departments in Queensland public hospitals

BACKGROUND: A long length of stay (LOS) in the emergency department (ED) associated with overcrowding has been found to adversely affect the quality of ED care. The objective of this study is to determine whether patients who speak a language other than English at home have a longer LOS in EDs compared to those whose speak only English at home. METHODS: A secondary data analysis of a Queensland state-wide hospital EDs dataset (Emergency Department Information System) was conducted for the period, 1 January 2008 to 31 December 2010. RESULTS: The interpreter requirement was the highest among Vietnamese speakers (23.1%) followed by Chinese (19.8%) and Arabic speakers (18.7%). There were significant differences in the distributions of the departure statuses among the language groups (Chi-squared=3236.88, P<0.001). Compared with English speakers, the Beta coeffi cient for the LOS in the EDs measured in minutes was among Vietnamese, 26.3 (95%CI: 22.1–30.5); Arabic, 10.3 (95%CI: 7.3–13.2); Spanish, 9.4 (95%CI: 7.1–11.7); Chinese, 8.6 (95%CI: 2.6–14.6); Hindi, 4.0 (95%CI: 2.2–5.7); Italian, 3.5 (95%CI: 1.6–5.4); and German, 2.7 (95%CI: 1.0–4.4). The fi nal regression model explained 17% of the variability in LOS. CONCLUSION: There is a close relationship between the language spoken at home and the LOS at EDs, indicating that language could be an important predictor of prolonged LOS in EDs and improving language services might reduce LOS and ease overcrowding in EDs in Queensland's public hospitals.

What drives the commodity price beta of oil industry stocks

We test theoretical drivers of the oil price beta of oil industry stocks. The strongest statistical and economic support comes for market conditions-type variables as the prime drivers: namely, oil price (+), bond rate (+), volatility of oil returns (−) and cost of carry (+). Though statistically significant, exogenous firm characteristics and oil firms' financing decisions have less compelling economic significance. There is weaker support for the prediction that financial risk management reduces the exposure of oil stocks to crude oil price variation. Finally, extended modelling shows that mean reversion in oil prices also helps explain cross-sectional variation in the oil beta.

Gradual training of cascaded shape regression for facial landmark localization and pose estimation

Facial landmarks play an important role in face recognition. They serve different steps of the recognition such as pose estimation, face alignment, and local feature extraction. Recently, cascaded shape regression has been proposed to accurately locate facial landmarks. A large number of weak regressors are cascaded in a sequence to fit face shapes to the correct landmark locations. In this paper, we propose to improve the method by applying gradual training. With this training, the regressors are not directly aimed to the true locations. The sequence instead is divided into successive parts each of which is aimed to intermediate targets between the initial and the true locations. We also investigate the incorporation of pose information in the cascaded model. The aim is to find out whether the model can be directly used to estimate head pose. Experiments on the Annotated Facial Landmarks in the Wild database have shown that the proposed method is able to improve the localization and give accurate estimates of pose.