Computation and Analysis of Multiple Structural-Change Models

In a recent paper, Bai and Perron (1998) considered theoretical issues related to the limiting distribution of estimators and test statistics in the linear model with multiple structural changes. In this companion paper, we consider practical issues for the empirical applications of the procedures. We first address the problem of estimation of the break dates and present an efficient algorithm to obtain global minimizers of the sum of squared residuals. This algorithm is based on the principle of dynamic programming and requires at most least-squares operations of order O(T 2) for any number of breaks. Our method can be applied to both pure and partial structural-change models. Secondly, we consider the problem of forming confidence intervals for the break dates under various hypotheses about the structure of the data and the errors across segments. Third, we address the issue of testing for structural changes under very general conditions on the data and the errors. Fourth, we address the issue of estimating the number of breaks. We present simulation results pertaining to the behavior of the estimators and tests in finite samples. Finally, a few empirical applications are presented to illustrate the usefulness of the procedures. All methods discussed are implemented in a GAUSS program available upon request for non-profit academic use.

Evaluation of multiple reaction monitoring cubed for the analysis of tachykinin related peptides in rat spinal cord using a hybrid triple quadrupole–linear ion trap mass spectrometer

Targeted peptide methods generally use HPLC-MS/MRM approaches. Although dependent on the instrumental resolution, interferences may occur while performing analysis of complex biological matrices. HPLC-MS/MRM3 is a technique, which provides a significantly better selectivity, compared with HPLC-MS/MRM assay. HPLC-MS/MRM3 allows the detection and quantitation by enriching standard MRM with secondary product ions that are generated within the linear ion trap. Substance P (SP) and neurokinin A (NKA) are tachykinin peptides playing a central role in pain transmission. The objective of this study was to verify whether HPLC-HPLCMS/ MRM3 could provide significant advantages over a more traditional HPLC-MS/MRM assay for the quantification of SP and NKA in rat spinal cord. The results suggest that reconstructed MRM3 chromatograms display significant improvements with the nearly complete elimination of interfering peaks but the sensitivity (i.e. signal-to-noise ratio) was severely reduced. The precision (%CV) observed was between 3.5% - 24.1% using HPLC-MS/MRM and in the range of 4.3% - 13.1% with HPLC-MS/MRM3, for SP and NKA. The observed accuracy was within 10% of the theoretical concentrations tested. HPLC-MS/MRM3 may improve the assay sensitivity to detect difference between samples by reducing significantly the potential of interferences and therefore reduce instrumental errors.

Qualitative Air Flow Modelling and Analysis of Data Centre Air Conditioning as Multiple Jet Array

Data centre is a centralized repository,either physical or virtual,for the storage,management and dissemination of data and information organized around a particular body and nerve centre of the present IT revolution.Data centre are expected to serve uniinterruptedly round the year enabling them to perform their functions,it consumes enormous energy in the present scenario.Tremendous growth in the demand from IT Industry made it customary to develop newer technologies for the better operation of data centre.Energy conservation activities in data centre mainly concentrate on the air conditioning system since it is the major mechanical sub-system which consumes considerable share of the total power consumption of the data centre.The data centre energy matrix is best represented by power utilization efficiency(PUE),which is defined as the ratio of the total facility power to the IT equipment power.Its value will be greater than one and a large value of PUE indicates that the sub-systems draw more power from the facility and the performance of the data will be poor from the stand point of energy conservation. PUE values of 1.4 to 1.6 are acievable by proper design and management techniques.Optimizing the air conditioning systems brings enormous opportunity in bringing down the PUE value.The air conditioning system can be optimized by two approaches namely,thermal management and air flow management.thermal management systems are now introduced by some companies but they are highly sophisticated and costly and do not catch much attention in the thumb rules.

Modelling and Analysis of Recurrent Event Data with Multiple Causes

This thesis Entitled “modelling and analysis of recurrent event data with multiple causes.Survival data is a term used for describing data that measures the time to occurrence of an event.In survival studies, the time to occurrence of an event is generally referred to as lifetime.Recurrent event data are commonly encountered in longitudinal studies when individuals are followed to observe the repeated occurrences of certain events. In many practical situations, individuals under study are exposed to the failure due to more than one causes and the eventual failure can be attributed to exactly one of these causes.The proposed model was useful in real life situations to study the effect of covariates on recurrences of certain events due to different causes.In Chapter 3, an additive hazards model for gap time distributions of recurrent event data with multiple causes was introduced. The parameter estimation and asymptotic properties were discussed .In Chapter 4, a shared frailty model for the analysis of bivariate competing risks data was presented and the estimation procedures for shared gamma frailty model, without covariates and with covariates, using EM algorithm were discussed. In Chapter 6, two nonparametric estimators for bivariate survivor function of paired recurrent event data were developed. The asymptotic properties of the estimators were studied. The proposed estimators were applied to a real life data set. Simulation studies were carried out to find the efficiency of the proposed estimators.

Kinetics of martensitic transitions in Cu-Al-Mn under thermal cycling: Analysis at multiple length scales

In this paper we study the evolution of the kinetic features of the martensitic transition in a Cu-Al-Mn single crystal under thermal cycling. The use of several experimental techniques including optical microscopy, calorimetry, and acoustic emission, has enabled us to perform an analysis at multiple scales. In particular, we have focused on the analysis of avalanche events (associated with the nucleation and growth of martensitic domains), which occur during the transition. There are significant differences between the kinetics at large and small length scales. On the one hand, at small length scales, small avalanche events tend to sum to give new larger events in subsequent loops. On the other hand, at large length scales the large domains tend to split into smaller ones on thermal cycling. We suggest that such different behavior is the necessary ingredient that leads the system to the final critical state corresponding to a power-law distribution of avalanches.

Qualitative air flow modelling and analysis of data centre air conditioning as multiple jet array

This work identifies the importance of plenum pressure on the performance of the data centre. The present methodology followed in the industry considers the pressure drop across the tile as a dependant variable, but it is shown in this work that this is the only one independent variable that is responsible for the entire flow dynamics in the data centre, and any design or assessment procedure must consider the pressure difference across the tile as the primary independent variable. This concept is further explained by the studies on the effect of dampers on the flow characteristics. The dampers have found to introduce an additional pressure drop there by reducing the effective pressure drop across the tile. The effect of damper is to change the flow both in quantitative and qualitative aspects. But the effect of damper on the flow in the quantitative aspect is only considered while using the damper as an aid for capacity control. Results from the present study suggest that the use of dampers must be avoided in data centre and well designed tiles which give required flow rates must be used in the appropriate locations. In the present study the effect of hot air recirculation is studied with suitable assumptions. It identifies that, the pressure drop across the tile is a dominant parameter which governs the recirculation. The rack suction pressure of the hardware along with the pressure drop across the tile determines the point of recirculation in the cold aisle. The positioning of hardware in the racks play an important role in controlling the recirculation point. The present study is thus helpful in the design of data centre air flow, based on the theory of jets. The air flow can be modelled both quantitatively and qualitatively based on the results.

“Qualitative Air Flow Modelling And Analysis Of Data Centre Air Conditioning As Multiple Jet Array

In the present study the effect of hot air recirculation is studied with suitable assumptions. It identifies that, the pressure drop across the tile is a dominant parameter which governs the recirculation. The rack suction pressure of the hardware along with the pressure drop across the tile determines the point of recirculation in the cold aisle. The positioning of hardware in the racks play an important role in controlling the recirculation point. The present study is thus helpful in the design of data centre air flow, based on the theory of jets. The air flow can be modelled both quantitatively and qualitatively based on the results

A compositional data analysis package for R providing multiple approaches

”compositions” is a new R-package for the analysis of compositional and positive data. It contains four classes corresponding to the four different types of compositional and positive geometry (including the Aitchison geometry). It provides means for computation, plotting and high-level multivariate statistical analysis in all four geometries. These geometries are treated in an fully analogous way, based on the principle of working in coordinates, and the object-oriented programming paradigm of R. In this way, called functions automatically select the most appropriate type of analysis as a function of the geometry. The graphical capabilities include ternary diagrams and tetrahedrons, various compositional plots (boxplots, barplots, piecharts) and extensive graphical tools for principal components. Afterwards, ortion and proportion lines, straight lines and ellipses in all geometries can be added to plots. The package is accompanied by a hands-on-introduction, documentation for every function, demos of the graphical capabilities and plenty of usage examples. It allows direct and parallel computation in all four vector spaces and provides the beginner with a copy-and-paste style of data analysis, while letting advanced users keep the functionality and customizability they demand of R, as well as all necessary tools to add own analysis routines. A complete example is included in the appendix

The multiple autoimmune syndromes. A clue for the autoimmune tautology

The multiple autoimmune syndromes (MAS) consist on the presence of three or more well-defined autoimmune diseases (ADs) in a single patient. The aim of this study was to analyze the clinical and genetic characteristics of a large series of patients with MAS. A cluster analysis and familial aggregation analysis of ADs was performed in 84 patients. A genome-wide microsatellite screen was performed in MAS families, and associated loci were investigated through the pedigree disequilibrium test. Systemic lupus erythematosus (SLE), autoimmune thyroid disease (AITD), and Sjögren's syndrome together were the most frequent ADs encountered. Three main clusters were established. Aggregation for type 1 diabetes, AITD, SLE, and all ADs as a trait was found. Eight loci associated with MAS were observed harboring autoimmunity genes. The MAS represent the best example of polyautoimmunity as well as the effect of a single genotype on diverse phenotypes. Its study provides important clues to elucidate the common mechanisms of ADs (i.e., autoimmune tautology). © Springer Science+Business Media, LLC 2012.

Organic solvents as risk factor for autoimmune diseases: a systematic review and meta-analysis

Background: Genetic and epigenetic factors interacting with the environment over time are the main causes of complex diseases such as autoimmune diseases (ADs). Among the environmental factors are organic solvents (OSs), which are chemical compounds used routinely in commercial industries. Since controversy exists over whether ADs are caused by OSs, a systematic review and meta-analysis were performed to assess the association between OSs and ADs. Methods and Findings: The systematic search was done in the PubMed, SCOPUS, SciELO and LILACS databases up to February 2012. Any type of study that used accepted classification criteria for ADs and had information about exposure to OSs was selected. Out of a total of 103 articles retrieved, 33 were finally included in the meta-analysis. The final odds ratios (ORs) and 95% confidence intervals (CIs) were obtained by the random effect model. A sensitivity analysis confirmed results were not sensitive to restrictions on the data included. Publication bias was trivial. Exposure to OSs was associated to systemic sclerosis, primary systemic vasculitis and multiple sclerosis individually and also to all the ADs evaluated and taken together as a single trait (OR: 1.54; 95% CI: 1.25-1.92; p-value, 0.001). Conclusion: Exposure to OSs is a risk factor for developing ADs. As a corollary, individuals with non-modifiable risk factors (i.e., familial autoimmunity or carrying genetic factors) should avoid any exposure to OSs in order to avoid increasing their risk of ADs.

GC/multiple collector-ICPMS method for chlorine stable isotope analysis of chlorinated aliphatic hydrocarbons

Stable isotopic characterization of chlorine in chlorinated aliphatic pollution is potentially very valuable for risk assessment and monitoring remediation or natural attenuation. The approach has been underused because of the complexity of analysis and the time it takes. We have developed a new method that eliminates sample preparation. Gas chromatography produces individually eluted sample peaks for analysis. The He carrier gas is mixed with Ar and introduced directly into the torch of a multicollector ICPMS. The MC-ICPMS is run at a high mass resolution of >= 10 000 to eliminate interference of mass 37 ArH with Cl. The standardization approach is similar to that for continuous flow stable isotope analysis in which sample and reference materials are measured successively. We have measured PCE relative to a laboratory TCE standard mixed with the sample. Solvent samples of 200 nmol to 1.3 mu mol ( 24- 165 mu g of Cl) were measured. The PCE gave the same value relative to the TCE as measured by the conventional method with a precision of 0.12% ( 2 x standard error) but poorer precision for the smaller samples.

The use of a multiple criteria decision analysis to evaluate the effectiveness of landscape and habitat enhancement mechanisms: an example from the South Downs

A range of funding schemes and policy instruments exist to effect enhancement of the landscapes and habitats of the UK. While a number of assessments of these mechanisms have been conducted, little research has been undertaken to compare both quantitatively and qualitatively their relative effectiveness across a range of criteria. It is argued that few tools are available for such a multi-faceted evaluation of effectiveness. A form of Multiple Criteria Decision Analysis (MCDA) is justified and utilized as a framework in which to evaluate the effectiveness of nine mechanisms in relation to the protection of existing areas of chalk grassland and the creation of new areas in the South Downs of England. These include established schemes, such as the Countryside Stewardship and Environmentally Sensitive Area Schemes, along with other less common mechanisms, for example, land purchase and tender schemes. The steps involved in applying an MCDA to evaluate such mechanisms are identified and the process is described. Quantitative results from the comparison of the effectiveness of different mechanisms are presented, although the broader aim of the paper is that of demonstrating the performance of MCDA as a tool for measuring the effectiveness of mechanisms aimed at landscape and habitat enhancement.