Ceramics, Trade, Provenience and Geology: Cyprus in the Late Bronze Age

The island of Cyprus was a major producer of copper and stood at the heart of east Mediterranean trade networks during the Late Bronze Age. It may also have been the source of the Red Lustrous Wheelmade Ware that has been found in mortuary contexts in Egypt and the Levant, and in Hittite temple assemblages in Anatolia. Neutron Activation Analysis (NAA) has enabled the source area of this special ceramic to be located in a geologically highly localised and geochemically distinctive area of western Cyprus. This discovery offers a new perspective on the spatial organisation of Cypriot economies in the production and exchange of elite goods around the eastern Mediterranean at this time.

Comparison of univariate and multivariate calibration for the determination of micronutrients in pellets of plant materials by laser induced breakdown spectrometry

The application of laser induced breakdown spectrometry (LIBS) aiming the direct analysis of plant materials is a great challenge that still needs efforts for its development and validation. In this way, a series of experimental approaches has been carried out in order to show that LIBS can be used as an alternative method to wet acid digestions based methods for analysis of agricultural and environmental samples. The large amount of information provided by LIBS spectra for these complex samples increases the difficulties for selecting the most appropriated wavelengths for each analyte. Some applications have suggested that improvements in both accuracy and precision can be achieved by the application of multivariate calibration in LIBS data when compared to the univariate regression developed with line emission intensities. In the present work, the performance of univariate and multivariate calibration, based on partial least squares regression (PLSR), was compared for analysis of pellets of plant materials made from an appropriate mixture of cryogenically ground samples with cellulose as the binding agent. The development of a specific PLSR model for each analyte and the selection of spectral regions containing only lines of the analyte of interest were the best conditions for the analysis. In this particular application, these models showed a similar performance. but PLSR seemed to be more robust due to a lower occurrence of outliers in comparison to the univariate method. Data suggests that efforts dealing with sample presentation and fitness of standards for LIBS analysis must be done in order to fulfill the boundary conditions for matrix independent development and validation. (C) 2009 Elsevier B.V. All rights reserved.

Evaluating multivariate forecast densities: a comparison of two approaches

We consider methods of evaluating multivariate density forecasts. A recently proposed method is found to lack power when the correlation structure is mis-specified. Tests that have good power to detect mis-specifications of this sort are described. We also consider the properties of the tests in the presence of more general mis-specifications.

Comparison of the univariate and multivariate methods in the optimization of experimental conditions for determining Cu, Pb, Ni and Cd in biodiesel by GFAAS

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The use of multivariate methods in the identification of subtypes of Alzheimer's disease: a comparison of principal components and cluster analysis

Two contrasting multivariate statistical methods, viz., principal components analysis (PCA) and cluster analysis were applied to the study of neuropathological variations between cases of Alzheimer's disease (AD). To compare the two methods, 78 cases of AD were analyzed, each characterised by measurements of 47 neuropathological variables. Both methods of analysis revealed significant variations between AD cases. These variations were related primarily to differences in the distribution and abundance of senile plaques (SP) and neurofibrillary tangles (NFT) in the brain. Cluster analysis classified the majority of AD cases into five groups which could represent subtypes of AD. However, PCA suggested that variation between cases was more continuous with no distinct subtypes. Hence, PCA may be a more appropriate method than cluster analysis in the study of neuropathological variations between AD cases.

Predicting class I major histocompatibility complex (MHC) binders using multivariate statistics:comparison of discriminant analysis and multiple linear regression

The accurate in silico identification of T-cell epitopes is a critical step in the development of peptide-based vaccines, reagents, and diagnostics. It has a direct impact on the success of subsequent experimental work. Epitopes arise as a consequence of complex proteolytic processing within the cell. Prior to being recognized by T cells, an epitope is presented on the cell surface as a complex with a major histocompatibility complex (MHC) protein. A prerequisite therefore for T-cell recognition is that an epitope is also a good MHC binder. Thus, T-cell epitope prediction overlaps strongly with the prediction of MHC binding. In the present study, we compare discriminant analysis and multiple linear regression as algorithmic engines for the definition of quantitative matrices for binding affinity prediction. We apply these methods to peptides which bind the well-studied human MHC allele HLA-A*0201. A matrix which results from combining results of the two methods proved powerfully predictive under cross-validation. The new matrix was also tested on an external set of 160 binders to HLA-A*0201; it was able to recognize 135 (84%) of them.

Comparison of Multivariate and Univariate Models for Genetic Evaluation of Milk Yield based on Test Day Data

2000 Mathematics Subject Classification: 62H12, 62P99

Breed comparison for heat adaptation in rams using multivariate analysis.

2016

Comparison of HRT-3 glaucoma probability score and subjective stereophotograph assessment for prediction of progression in glaucoma

PURPOSE. To assess whether baseline Glaucoma Probability Score (GPS; HRT-3; Heidelberg Engineering, Dossenheim, Germany) results are predictive of progression in patients with suspected glaucoma. The GPS is a new feature of the confocal scanning laser ophthalmoscope that generates an operator-independent, three-dimensional model of the optic nerve head and gives a score for the probability that this model is consistent with glaucomatous damage. METHODS. The study included 223 patients with suspected glaucoma during an average follow-up of 63.3 months. Included subjects had a suspect optic disc appearance and/or elevated intraocular pressure, but normal visual fields. Conversion was defined as development of either repeatable abnormal visual fields or glaucomatous deterioration in the appearance of the optic disc during the study period. The association between baseline GPS and conversion was investigated by Cox regression models. RESULTS. Fifty-four (24.2%) eyes converted. In multivariate models, both higher values of GPS global and subjective stereophotograph assessment ( larger cup-disc ratio and glaucomatous grading) were predictive of conversion: adjusted hazard ratios (95% CI): 1.31 (1.15 - 1.50) per 0.1 higher global GPS, 1.34 (1.12 - 1.62) per 0.1 higher CDR, and 2.34 (1.22 - 4.47) for abnormal grading, respectively. No significant differences ( P > 0.05 for all comparisons) were found between the c-index values ( equivalent to area under ROC curve) for the multivariate models (0.732, 0.705, and 0.699, respectively). CONCLUSIONS. GPS values were predictive of conversion in our population of patients with suspected glaucoma. Further, they performed as well as subjective assessment of the optic disc. These results suggest that GPS could potentially replace stereophotograph as a tool for estimating the likelihood of conversion to glaucoma.

Exploraty Multivariate Statistical Methods Applied to Pharmaceutical Industry CRM Data

Dissertação apresentada como requisito parcial para obtenção do grau de Mestre em Estatística e Gestão de Informação

Safety and efficacy of angioplasty with intracoronary stenting in patients with unstable coronary syndromes. Comparison with stable coronary syndromes

OBJECTIVE: To assess safety and efficacy of coronary angioplasty with stent implantation in unstable coronary syndromes. METHODS: Retrospective analysis of in-hospital and late evolution of 74 patients with unstable coronary syndromes (unstable angina or infarction without elevation of the ST segment) undergoing coronary angioplasty with stent placement. These 74 patients were compared with 31 patients with stable coronary syndromes (stable angina or stable silent ischemia) undergoing the same procedure. RESULTS: No death and no need for revascularization of the culprit artery occurred in the in-hospital phase. The incidences of acute non-Q-wave myocardial infarction were 1.4% and 3.2% (p=0.6) in the unstable and stable coronary syndrome groups, respectively. In the late follow-up (11.2±7.5 months), the incidences of these events combined were 5.7% in the unstable coronary syndrome group and 6.9% (p=0.8) in the stable coronary syndrome group. In the multivariate analysis, the only variable with a tendency to significance as an event predictor was diabetes mellitus (p=0.07; OR=5.2; 95% CI=0.9-29.9). CONCLUSION: The in-hospital and late evolutions of patients with unstable coronary syndrome undergoing angioplasty with intracoronary stent implantation are similar to those of the stable coronary syndrome group, suggesting that this procedure is safe and efficacious when performed in unstable coronary syndrome patients.

Molecular epidemiology of predominant clones and sporadic strains of methicillin resistant Staphylococcus aureus in Switzerland and comparison with European epidemic clones.

OBJECTIVE: To assess the molecular epidemiology and risk factors of predominant clones and sporadic strains of methicillin-resistant Staphylococcus aureus (MRSA) in Swiss hospitals and to compare them with European strains of epidemic clones. MATERIAL AND METHODS: One-year national survey of MRSA cases. Analysis of epidemiological and molecular typing data (PFGE) of MRSA strains. RESULTS: In 1997, 385 cases of MRSA were recorded in the five Swiss university hospitals and in 47 community hospitals. Half of the cases were found in Geneva hospitals where MRSA was already known to be endemic. Molecular typing of 288 isolates (one per case) showed that 186 (65%) belong to four predominant clones, three of which were mostly present in Geneva hospitals. In contrast, the fourth clone (85 cases) was found in 23 hospitals (in one to 16 cases per hospital). The remaining 35% of the strains were clustered into 62 pulsed field gel electrophoresis types. They accounted for one to five patients per hospital and were defined as sporadic. Multivariate analysis revealed no independent risk factors for harboring a predominant versus a sporadic strain, except that transfer from a foreign hospital increases the risk of harboring a sporadic strain (OR, 42; 95% CI, 5-360). CONCLUSION: While cases with predominant clones were due to the local spread of these clones, most sporadic cases appear to be due to the continuous introduction of new strains into the country. With the exception of a transfer from a hospital outside Switzerland, no difference in the clinical or epidemiological characteristics was observed between patients harboring a predominant clone and those with a sporadic strain.

Ultra-high pressure liquid chromatography-mass spectrometry for plant metabolomics: a systematic comparison of high-resolution quadrupole-time-of-flight and single stage Orbitrap mass spectrometers.

The response of Arabidopsis to stress caused by mechanical wounding was chosen as a model to compare the performances of high resolution quadrupole-time-of-flight (Q-TOF) and single stage Orbitrap (Exactive Plus) mass spectrometers in untargeted metabolomics. Both instruments were coupled to ultra-high pressure liquid chromatography (UHPLC) systems set under identical conditions. The experiment was divided in two steps: the first analyses involved sixteen unwounded plants, half of which were spiked with pure standards that are not present in Arabidopsis. The second analyses compared the metabolomes of mechanically wounded plants to unwounded plants. Data from both systems were extracted using the same feature detection software and submitted to unsupervised and supervised multivariate analysis methods. Both mass spectrometers were compared in terms of number and identity of detected features, capacity to discriminate between samples, repeatability and sensitivity. Although analytical variability was lower for the UHPLC-Q-TOF, generally the results for the two detectors were quite similar, both of them proving to be highly efficient at detecting even subtle differences between plant groups. Overall, sensitivity was found to be comparable, although the Exactive Plus Orbitrap provided slightly lower detection limits for specific compounds. Finally, to evaluate the potential of the two mass spectrometers for the identification of unknown markers, mass and spectral accuracies were calculated on selected identified compounds. While both instruments showed excellent mass accuracy (<2.5ppm for all measured compounds), better spectral accuracy was recorded on the Q-TOF. Taken together, our results demonstrate that comparable performances can be obtained at acquisition frequencies compatible with UHPLC on Q-TOF and Exactive Plus MS, which may thus be equivalently used for plant metabolomics.

Multivariate QST-FST comparisons: a neutrality test for the evolution of the g matrix in structured populations.

Neutrality tests in quantitative genetics provide a statistical framework for the detection of selection on polygenic traits in wild populations. However, the existing method based on comparisons of divergence at neutral markers and quantitative traits (Q(st)-F(st)) suffers from several limitations that hinder a clear interpretation of the results with typical empirical designs. In this article, we propose a multivariate extension of this neutrality test based on empirical estimates of the among-populations (D) and within-populations (G) covariance matrices by MANOVA. A simple pattern is expected under neutrality: D = 2F(st)/(1 - F(st))G, so that neutrality implies both proportionality of the two matrices and a specific value of the proportionality coefficient. This pattern is tested using Flury's framework for matrix comparison [common principal-component (CPC) analysis], a well-known tool in G matrix evolution studies. We show the importance of using a Bartlett adjustment of the test for the small sample sizes typically found in empirical studies. We propose a dual test: (i) that the proportionality coefficient is not different from its neutral expectation [2F(st)/(1 - F(st))] and (ii) that the MANOVA estimates of mean square matrices between and among populations are proportional. These two tests combined provide a more stringent test for neutrality than the classic Q(st)-F(st) comparison and avoid several statistical problems. Extensive simulations of realistic empirical designs suggest that these tests correctly detect the expected pattern under neutrality and have enough power to efficiently detect mild to strong selection (homogeneous, heterogeneous, or mixed) when it is occurring on a set of traits. This method also provides a rigorous and quantitative framework for disentangling the effects of different selection regimes and of drift on the evolution of the G matrix. We discuss practical requirements for the proper application of our test in empirical studies and potential extensions.