Evaluating sampling strategies and logistic regression methods for modelling complex land cover changes

The role of land cover change as a significant component of global change has become increasingly recognized in recent decades. Large databases measuring land cover change, and the data which can potentially be used to explain the observed changes, are also becoming more commonly available. When developing statistical models to investigate observed changes, it is important to be aware that the chosen sampling strategy and modelling techniques can influence results. We present a comparison of three sampling strategies and two forms of grouped logistic regression models (multinomial and ordinal) in the investigation of patterns of successional change after agricultural land abandonment in Switzerland. Results indicated that both ordinal and nominal transitional change occurs in the landscape and that the use of different sampling regimes and modelling techniques as investigative tools yield different results. Synthesis and applications. Our multimodel inference identified successfully a set of consistently selected indicators of land cover change, which can be used to predict further change, including annual average temperature, the number of already overgrown neighbouring areas of land and distance to historically destructive avalanche sites. This allows for more reliable decision making and planning with respect to landscape management. Although both model approaches gave similar results, ordinal regression yielded more parsimonious models that identified the important predictors of land cover change more efficiently. Thus, this approach is favourable where land cover change pattern can be interpreted as an ordinal process. Otherwise, multinomial logistic regression is a viable alternative.

Bayesian Model Averaging in the Instrumental Variable Regression Model

This paper considers the instrumental variable regression model when there is uncertainty about the set of instruments, exogeneity restrictions, the validity of identifying restrictions and the set of exogenous regressors. This uncertainty can result in a huge number of models. To avoid statistical problems associated with standard model selection procedures, we develop a reversible jump Markov chain Monte Carlo algorithm that allows us to do Bayesian model averaging. The algorithm is very exible and can be easily adapted to analyze any of the di¤erent priors that have been proposed in the Bayesian instrumental variables literature. We show how to calculate the probability of any relevant restriction (e.g. the posterior probability that over-identifying restrictions hold) and discuss diagnostic checking using the posterior distribution of discrepancy vectors. We illustrate our methods in a returns-to-schooling application.

Reversible behavioural autistic-like regression: A manifestation of a special (new?) epileptic syndrome in a 28-month-old child. A 2-year longitudinal study .

A 28-month-old boy was referred for acute onset of abnormal head movements. History revealed an insidious progressive regression in behaviour and communication over several months. Head and shoulder 'spasms' with alteration of consciousness and on one occasion ictal laughter were seen. The electroencephalograph (EEG) showed repeated bursts of brief generalized polyspikes and spike-wave during the 'spasms', followed by flattening, a special pattern which never recurred after treatment. Review of family videos showed a single 'minor' identical seizure 6 months previously. Magnetic resonance imaging was normal. Clonazepam brought immediate cessation of seizures, normalization of the EEG and a parallel spectacular improvement in communication, mood and language. Follow-up over the next 10 months showed a new regression unaccompained by recognized seizures, although numerous seizures were discovered during the videotaped neuropsychological examination, when stereotyped subtle brief paroxysmal changes in posture and behaviour could be studied in slow motion and compared with the 'prototypical' initial ones. The EEG showed predominant rare left-sided fronto-temporal discharges. Clonazepam was changed to carbamazepin with marked improvement in behaviour, language and cognition which has been sustained up to the last control at 51 months. Videotaped home observations allowed the documentation of striking qualitative and quantitative variations in social interaction and play of autistic type in relation to the epileptic activity. We conclude that this child has a special characteristic epileptic syndrome with subtle motor and vegetative symptomatology associated with an insidious catastrophic 'autistic-like' regression which could be overlooked. The methods used to document such fluctuating epileptic behavioural manifestations are discussed.

Model Switching and Model Averaging in Time- Varying Parameter Regression Models

This paper investigates the usefulness of switching Gaussian state space models as a tool for implementing dynamic model selecting (DMS) or averaging (DMA) in time-varying parameter regression models. DMS methods allow for model switching, where a different model can be chosen at each point in time. Thus, they allow for the explanatory variables in the time-varying parameter regression model to change over time. DMA will carry out model averaging in a time-varying manner. We compare our exact approach to DMA/DMS to a popular existing procedure which relies on the use of forgetting factor approximations. In an application, we use DMS to select different predictors in an in ation forecasting application. We also compare different ways of implementing DMA/DMS and investigate whether they lead to similar results.

Estimation of lean meat content in pig carcasses using X-ray Computed Tomography and PLS regression

Lean meat percentage (LMP) is an important carcass quality parameter. The aim of this work is to obtain a calibration equation for the Computed Tomography (CT) scans with the Partial Least Square Regression (PLS) technique in order to predict the LMP of the carcass and the different cuts and to study and compare two different methodologies of the selection of the variables (Variable Importance for Projection — VIP- and Stepwise) to be included in the prediction equation. The error of prediction with cross-validation (RMSEPCV) of the LMP obtained with PLS and selection based on VIP value was 0.82% and for stepwise selection it was 0.83%. The prediction of the LMP scanning only the ham had a RMSEPCV of 0.97% and if the ham and the loin were scanned the RMSEPCV was 0.90%. Results indicate that for CT data both VIP and stepwise selection are good methods. Moreover the scanning of only the ham allowed us to obtain a good prediction of the LMP of the whole carcass.

Innovation sources and productivity in Catalonian firms: a quantile regression analysis

This paper explores the effects of two main sources of innovation - intramural and external R&D— on the productivity level in a sample of 3,267 Catalonian firms. The data set used is based on the official innovation survey of Catalonia which was a part of the Spanish sample of CIS4, covering the years 2002-2004. We compare empirical results by applying usual OLS and quantile regression techniques both in manufacturing and services industries. In quantile regression, results suggest different patterns at both innovation sources as we move across conditional quantiles. The elasticity of intramural R&D activities on productivity decreased when we move up the high productivity levels both in manufacturing and services sectors, while the effects of external R&D rise in high-technology industries but are more ambiguous in low-technology and knowledge-intensive services. JEL codes: O300, C100, O140 Keywords: Innovation sources, R&D, Productivity, Quantile Regression

Selective lysis of activated cells in oncorna virus infection.

The authors devised a cytotoxic assay based on cytofluorometric analysis of target surface markers in order to compare lysis exerted in vitro by cytotoxic T lymphocytes (CTLs) on different cell subsets in the context of a single lymphoid target cell population. Using this assay, the authors evaluated when oncorna virus-infected lymphocytes become a suitable target for virus-specific T cell effectors. A lymphocyte population from Moloney-murine leukaemia virus (M-MuLV)-infected (carrier) mice, in which the proliferation of selective V beta T-cell receptor (TCR) families was induced in response to Mlsa encoded antigens, was utilized as a target. The authors observed that a virus-specific T cell clone exerted lytic activity preferentially against activated cell subsets. Moreover, virus-specific CTLs generated in mixed leucocyte tumour cell cultures (MLTC) were also able to impair the concomitant anti-Mlsa response of lymphocytes from M-MuLV carrier mice. It was found that the proliferative status of oncorna virus-infected target cells played an important role in limiting the in vitro efficacy of the immune response, and it is speculated that this phenomenon might represent an in vivo escape mechanism from immunosurveillance.

Modelling dependence in a ratemaking procedure with multivariate Poisson regression models

When actuaries face with the problem of pricing an insurance contract that contains different types of coverage, such as a motor insurance or homeowner's insurance policy, they usually assume that types of claim are independent. However, this assumption may not be realistic: several studies have shown that there is a positive correlation between types of claim. Here we introduce different regression models in order to relax the independence assumption, including zero-inflated models to account for excess of zeros and overdispersion. These models have been largely ignored to multivariate Poisson date, mainly because of their computational di±culties. Bayesian inference based on MCMC helps to solve this problem (and also lets us derive, for several quantities of interest, posterior summaries to account for uncertainty). Finally, these models are applied to an automobile insurance claims database with three different types of claims. We analyse the consequences for pure and loaded premiums when the independence assumption is relaxed by using different multivariate Poisson regression models and their zero-inflated versions.

Difference in susceptibility to lysis between clones of the Y strain of Trypanosoma cruzi

Three clones isolated from the Y strain of Trypanosoma cruzi - YP1, YP2 and YP3 - were adapted to in vitro cultivation in VERO cells. The recovery of the parasites from the Y strain and clone YP3 was similar after 24 hr of contact with cells (3.2% and 2.7%, respectively) and much lower than the recovery of clones YP1 and YP2 (56.7% and 60.0% of inoculum, respectively). After five days incubation, the ratio Trypomastigotes/Amastigotes released into the supernatants was about 90/10 for clone YP1, YP3 and Y strain, and 50/50 for clone YP2. After nine days, the ratio was 62/38 for clone YP1, 97/3 for clone YP3, 81/19 for Y strain and 50/50 for clone YP2. The susceptibility of tissue culture derived trypomastigotes (TCT) to lysis in the presence of chronic chagasic human sera and human complement was assessed using Complement Mediated Lysis reaction (CML). Trypomastigotes from clone YP2 were consistently less susceptible to CML (% lysis less than 20), than parasites from the other clones and Y strain. Parasites of clone YP3 had susceptibility to CML comparable to that of the Y strain (about 70%), while TCT of clone YP1 had intermediary susceptibility (40%).

Morphological aspects of the myocarditis and myositis in Calomys callosus experimentally infected with Trypanosoma cruzi: fibrogenesis and spontaneous regression of fibrosis

Calomys callosus a wild rodent, is a natural host of Trypanosoma cruzi. Twelve C. callosus were infected with 10(5) trypomastigotes of the F strain (a myotropic strain) of T. cruzi. Parasitemia decreased on the 21 st day becoming negative around the 40th day of infection. All animals survived but had positive parasitological tests, until the end of the experiment. The infected animals developed severe inflammation in the myocardium and skeletal muscle. This process was pronounced from the 26 th to the 30th day and gradually subsided from the 50 th day becoming absent or residual on the 64 th day after infection. Collagen was identified by the picro Sirius red method. Fibrogenesis developed early, but regression of fibrosis occurred between the 50th and 64th day. Ultrastructural study disclosed a predominance of macrophages and fibroblasts in the inflammatory infiltrates, with small numbers of lymphocytes. Macrophages had active phagocytosis and showed points of contact with altered muscle cells. Different degrees of matrix expansion were present, with granular and fibrilar deposits and collagen bundles. These alterations subsided by the 64th days. Macrophages seem to be the main immune effector cell in the C. callosus model of infection with T. cruzi. The mechanisms involved in the rapid fibrogenesis and its regression deserve further investigation.

The use of classification and regression trees to predict the likelihood of seasonal influenza.

Background Individual signs and symptoms are of limited value for the diagnosis of influenza. Objective To develop a decision tree for the diagnosis of influenza based on a classification and regression tree (CART) analysis. Methods Data from two previous similar cohort studies were assembled into a single dataset. The data were randomly divided into a development set (70%) and a validation set (30%). We used CART analysis to develop three models that maximize the number of patients who do not require diagnostic testing prior to treatment decisions. The validation set was used to evaluate overfitting of the model to the training set. Results Model 1 has seven terminal nodes based on temperature, the onset of symptoms and the presence of chills, cough and myalgia. Model 2 was a simpler tree with only two splits based on temperature and the presence of chills. Model 3 was developed with temperature as a dichotomous variable (≥38°C) and had only two splits based on the presence of fever and myalgia. The area under the receiver operating characteristic curves (AUROCC) for the development and validation sets, respectively, were 0.82 and 0.80 for Model 1, 0.75 and 0.76 for Model 2 and 0.76 and 0.77 for Model 3. Model 2 classified 67% of patients in the validation group into a high- or low-risk group compared with only 38% for Model 1 and 54% for Model 3. Conclusions A simple decision tree (Model 2) classified two-thirds of patients as low or high risk and had an AUROCC of 0.76. After further validation in an independent population, this CART model could support clinical decision making regarding influenza, with low-risk patients requiring no further evaluation for influenza and high-risk patients being candidates for empiric symptomatic or drug therapy.

Antibody-conjugated MHC class I tetramers can target tumor cells for specific lysis by T lymphocytes.

To demonstrate that antibody-guided targeting of antigenic MHC class I-peptide tetramer on tumor cells can render them susceptible to lysis by relevant cytotoxic T lymphocytes (CTL), biotinylated HLA-A*0201/Flu matrix peptide complexes were tetramerized on streptavidin molecules previously coupled to Fab' fragments from monoclonal antibodies (mAb) specific for cell surface markers such as carcinoembryonic antigen (CEA), ErbB-2 or CD20. Flow cytometry analysis showed that coating of the HLA-A2-peptide complexes on the four HLA-A2-negative human cancer lines tested (including a CEA-positive colon carcinoma, an ErbB-2(+) breast carcinoma and two CD20(+) B lymphomas) was entirely dependent upon the specificity of the conjugated antibody fragments. More importantly, HLA-A2-restricted Flu matrix peptide-specific CTL were then found to lyse specifically and efficiently the MHC-coated target cells. These results open the way to the development of new immunotherapy strategies based on antibody targeting of MHC class I-peptide complexes.

Complete immunization against Trypanosoma cruzi verified in individual mice by complement-mediated lysis

Experimental systems to assay immunity against Trypanosoma cruzi usually demonstrate partial resistance without excluding the establishment of sub-patent infections in protected animals. To test whether Swiss mice immunized with attenuated parasites might develop complete resistance against virulent T. cruzi, experiments were performed involving challenge with low numbers of parasites, enhancement of local inflammation and the combination of natural and acquired resistance. Absence of infection was established after repeated negative parasitological tests (including xenodiagnosis and hemoculture), and lack of lytic antibody was tested by complement mediated lysis. Immunization with 10(7) attenuated epimastigotes conferred protection against the development of high levels of parasitemia after challenge with Tulahuen strain, but was unable to reduce the number of infected animals. However, when a strong, delayed-type hypersensitivity reaction was triggered at the site of infection by injecting a mixture of virulent and attenuated T. cruzi, a significant proportion of immunized animals remained totally free of virulent infection. The same result was obtained when the immunization experiment was performed in four month old Swiss mice, displaying a relatively high natural resistance and challenged with wild, vector-borne parasites. These experiments demonstrate that complete resistance against T. cruzi can be obtained in a significant proportion of animals, under conditions which replicate natural, vector delivered infection by the parasite.