Comparison of factor-analytic and reduced rank models for test-day milk yield in Gyr dairy cattle (Bos indicus)

We analyzed 46,161 monthly test-day records of milk production from 7453 first lactations of crossbred dairy Gyr (Bos indicus) x Holstein cows. The following seven models were compared: standard multivariate model (M10), three reduced rank models fitting the first 2, 3, or 4 genetic principal components, and three models considering a 2-, 3-, or 4-factor structure for the genetic covariance matrix. Full rank residual covariance matrices were considered for all models. The model fitting the first two principal components (PC2) was the best according to the model selection criteria. Similar phenotypic, genetic, and residual variances were obtained with models M10 and PC2. The heritability estimates ranged from 0.14 to 0.21 and from 0.13 to 0.21 for models M10 and PC2, respectively. The genetic correlations obtained with model PC2 were slightly higher than those estimated with model M10. PC2 markedly reduced the number of parameters estimated and the time spent to reach convergence. We concluded that two principal components are sufficient to model the structure of genetic covariances between test-day milk yields. © FUNPEC-RP.

Storage moduli, loss moduli and damping factor of GaAs and Ga1-xMnxAs thin films using DMA 2980

The spin injector part of spintronic FET and diodes suffers from fatigue due to rising heat on the depletion layer. In this study the stiffness of Ga1-xMnxAs spin injector in terms of storage modulus with respect to a varying temperature, 45 degrees C <= T <= 70 degrees C was determined. It was observed that the storage modulus for MDLs (Manganese Doping Levels) of 0%, 1% and 10% decreased with increase in temperature while that with MDLs of 20% and 50% increase with increase in temperature. MDLs of 20% and 50% appear not to allow for damping but MDLs <= 20% allow damping at temperature range of 45 degrees C <= T <= 70 degrees C. The magnitude of storage moduli of GaAs is smaller than that for ferromagnetic Ga1-xMnxAs systems. The loss moduli for GaAs were found to reduce with increase in temperature. Its magnitude of reducing gradient is smaller than Ga1-xMnxAs systems. The two temperature extremes show a general reduction in loss moduli for different MDLs at the study temperature range. From damping factor analysis, damping factors for ferromagnetic Ga1-xMnxAs was found to increase with decrease in MDLs contrary to GaAs which recorded the largest damping factor at 45 degrees C <= T <= 70 degrees C Hence, MDL of 20% shows little damping followed by 50% while MDL of 0% has the most damping in an increasing trend with temperature. (C) 2013 Elsevier Ltd. All rights reserved.

Comprehensive two-dimensional gas chromatography combined to multivariate data analysis for detection of disease-resistant clones of Eucalyptus

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

Exploratory analysis of differences in sperm morphology in Nelore and Gir (Bos indicus) bulls

The aim of this study was to evaluate the effects of breed and season on semen quality parameters of zebu bulls. Data (1,632 registers) of semen production from Gir (n = 4) and Nelore (n = 15) bulls were collected between October 2005 and November 2009. The ejaculates were collected twice a week during various seasons (summer, fall, winter, and spring) and evaluated for the following semen parameters: ejaculate volume, sperm concentration, sperm motility, forward progressive motility (FPM), and sperm morphology. Factor analysis was used to determine the relationship among variables. The effect of breed (Gir and Nelore) and season and their cross effect on each parameter and extracted factor were tested using ANOVA. A negative correlation (P < 0.05) was observed between FPM and proximal droplet, as well as with abnormal loose head, abnormal small head, pouch formation, abnormal mid-peace, and strongly folded tail. Gir bull sperm showed more major defects, detached acrosome, and minor FPM (P < 0.01), whereas Nelore bulls showed a higher number of sperm with normally loose head.

Human-calf relationship and its implications on animal welfare

Pós-graduação em Zootecnia - FCAV

Trauma and countertransference: development and validity of the Assessment of Countertransference Scale (ACS)

Objectives: The aim of the present study was to investigate the construct validity of the Assessment of Countertransference Scale (ACS) in the context of the trauma care, through the identification of the underlying latent constructs of the measured items and their homogeneity. Methods: ACS assesses 23 feelings of CT in three factors: closeness, rejection and indifference. ACS was applied to 50 residents in psychiatry after the first appointment with 131 victims of trauma consecutively selected during 4 years. ACS was analyzed by exploratory (EFA) and confirmatory (CFA) factor analysis, internal consistence and convergent-discriminant validity. Results: In spite of the fact that closeness items obtained the highest scores, the EFA showed that the factor rejection (24% of variance, alpha = 0.88) presented a more consistent intercorrelation of the items, followed by closeness (15% of variance, alpha = 0.82) and, a distinct factor, sadness (9% of variance, alpha = 0.72). Thus, a modified version was proposed. In the comparison between the original and the proposed version, CFA detected better goodness-of-fit indexes for the proposed version (GFI = 0.797, TLI = 0.867, CFI = 0.885 vs. GFI = 0.824, TLI = 0.904, CFI = 0.918). Conclusions: ACS is a promising instrument for assessing CT feelings, making it valid to access during the care of trauma victims.

Psychometric properties of the Spanish version of the mindful attention awareness scale (MAAS) in patients with fibromyalgia

Background Mindful-based interventions improve functioning and quality of life in fibromyalgia (FM) patients. The aim of the study is to perform a psychometric analysis of the Spanish version of the Mindful Attention Awareness Scale (MAAS) in a sample of patients diagnosed with FM. Methods The following measures were administered to 251 Spanish patients with FM: the Spanish version of MAAS, the Chronic Pain Acceptance Questionnaire, the Pain Catastrophising Scale, the Injustice Experience Questionnaire, the Psychological Inflexibility in Pain Scale, the Fibromyalgia Impact Questionnaire and the Euroqol. Factorial structure was analysed using Confirmatory Factor Analyses (CFA). Cronbach's α coefficient was calculated to examine internal consistency, and the intraclass correlation coefficient (ICC) was calculated to assess the test-retest reliability of the measures. Pearson’s correlation tests were run to evaluate univariate relationships between scores on the MAAS and criterion variables. Results The MAAS scores in our sample were low (M = 56.7; SD = 17.5). CFA confirmed a two-factor structure, with the following fit indices [sbX2 = 172.34 (p < 0.001), CFI = 0.95, GFI = 0.90, SRMR = 0.05, RMSEA = 0.06. MAAS was found to have high internal consistency (Cronbach’s α = 0.90) and adequate test-retest reliability at a 1–2 week interval (ICC = 0.90). It showed significant and expected correlations with the criterion measures with the exception of the Euroqol (Pearson = 0.15). Conclusion Psychometric properties of the Spanish version of the MAAS in patients with FM are adequate. The dimensionality of the MAAS found in this sample and directions for future research are discussed.

Multivariate spectroscopic methods for the analysis of solutions

In this thesis some multivariate spectroscopic methods for the analysis of solutions are proposed. Spectroscopy and multivariate data analysis form a powerful combination for obtaining both quantitative and qualitative information and it is shown how spectroscopic techniques in combination with chemometric data evaluation can be used to obtain rapid, simple and efficient analytical methods. These spectroscopic methods consisting of spectroscopic analysis, a high level of automation and chemometric data evaluation can lead to analytical methods with a high analytical capacity, and for these methods, the term high-capacity analysis (HCA) is suggested. It is further shown how chemometric evaluation of the multivariate data in chromatographic analyses decreases the need for baseline separation. The thesis is based on six papers and the chemometric tools used are experimental design, principal component analysis (PCA), soft independent modelling of class analogy (SIMCA), partial least squares regression (PLS) and parallel factor analysis (PARAFAC). The analytical techniques utilised are scanning ultraviolet-visible (UV-Vis) spectroscopy, diode array detection (DAD) used in non-column chromatographic diode array UV spectroscopy, high-performance liquid chromatography with diode array detection (HPLC-DAD) and fluorescence spectroscopy. The methods proposed are exemplified in the analysis of pharmaceutical solutions and serum proteins. In Paper I a method is proposed for the determination of the content and identity of the active compound in pharmaceutical solutions by means of UV-Vis spectroscopy, orthogonal signal correction and multivariate calibration with PLS and SIMCA classification. Paper II proposes a new method for the rapid determination of pharmaceutical solutions by the use of non-column chromatographic diode array UV spectroscopy, i.e. a conventional HPLC-DAD system without any chromatographic column connected. In Paper III an investigation is made of the ability of a control sample, of known content and identity to diagnose and correct errors in multivariate predictions something that together with use of multivariate residuals can make it possible to use the same calibration model over time. In Paper IV a method is proposed for simultaneous determination of serum proteins with fluorescence spectroscopy and multivariate calibration. Paper V proposes a method for the determination of chromatographic peak purity by means of PCA of HPLC-DAD data. In Paper VI PARAFAC is applied for the decomposition of DAD data of some partially separated peaks into the pure chromatographic, spectral and concentration profiles.

Advanced spectroscopic techniques and chemometric analysis for atmospheric organic aerosol characterization and source apportionment

Atmospheric aerosol particles directly impact air quality and participate in controlling the climate system. Organic Aerosol (OA) in general accounts for a large fraction (10–90%) of the global submicron (PM1) particulate mass. Chemometric methods for source identification are used in many disciplines, but methods relying on the analysis of NMR datasets are rarely used in atmospheric sciences. This thesis provides an original application of NMR-based chemometric methods to atmospheric OA source apportionment. The method was tested on chemical composition databases obtained from samples collected at different environments in Europe, hence exploring the impact of a great diversity of natural and anthropogenic sources. We focused on sources of water-soluble OA (WSOA), for which NMR analysis provides substantial advantages compared to alternative methods. Different factor analysis techniques are applied independently to NMR datasets from nine field campaigns of the project EUCAARI and allowed the identification of recurrent source contributions to WSOA in European background troposphere: 1) Marine SOA; 2) Aliphatic amines from ground sources (agricultural activities, etc.); 3) Biomass burning POA; 4) Biogenic SOA from terpene oxidation; 5) “Aged” SOAs, including humic-like substances (HULIS); 6) Other factors possibly including contributions from Primary Biological Aerosol Particles, and products of cooking activities. Biomass burning POA accounted for more than 50% of WSOC in winter months. Aged SOA associated with HULIS was predominant (> 75%) during the spring-summer, suggesting that secondary sources and transboundary transport become more important in spring and summer. Complex aerosol measurements carried out, involving several foreign research groups, provided the opportunity to compare source apportionment results obtained by NMR analysis with those provided by more widespread Aerodyne aerosol mass spectrometers (AMS) techniques that now provided categorization schemes of OA which are becoming a standard for atmospheric chemists. Results emerging from this thesis partly confirm AMS classification and partly challenge it.

Analysis of the Slow Food movement impact on the farmers and rural areas’ sustainable development

The evaluation of the farmers’ communities’ approach to the Slow Food vision, their perception of the Slow Food role in supporting their activity and their appreciation and expectations from participating in the event of Mother Earth were studied. The Unified Theory of Acceptance and Use of Technology (UTAUT) model was adopted in an agro-food sector context. A survey was conducted, 120 questionnaires from farmers attending the Mother Earth in Turin in 2010 were collected. The descriptive statistical analysis showed that both Slow Food membership and participation to Mother Earth Meeting were much appreciated for the support provided to their business and the contribution to a more sustainable and fair development. A positive social, environmental and psychological impact on farmers also resulted. Results showed also an interesting perspective on the possible universality of the Slow Food and Mother Earth values. Farmers declared that Slow Food is supporting them by preserving the biodiversity and orienting them to the use of local resources and reducing the chemical inputs. Many farmers mentioned the language/culture and administration/bureaucratic issues as an obstacle to be a member in the movement and to participate to the event. Participation to Mother Earth gives an opportunity to exchange information with other farmers’ communities and to participate to seminars and debates, helpful for their business development. The absolute majority of positive answers associated to the farmers’ willingness to relate to Slow Food and participate to the next Mother Earth editions negatively influenced the UTAUT model results. A factor analysis showed that the variables associated to the UTAUT model constructs Performance Expectancy and Effort Expectancy were consistent, able to explain the construct variability, and their measurement reliable. Their inclusion in a simplest Technology Acceptance Model could be considered in future researches.

Institutional Processes and Discursive Strategies: Rhetoric and Vocabulary Analysis of CSR and Sustainability

The candidate tackled an important issue in contemporary management: the role of CSR and Sustainability. The research proposal focused on a longitudinal and inductive research, directed to specify the evolution of CSR and contribute to the new institutional theory, in particular institutional work framework, and to the relation between institutions and discourse analysis. The documental analysis covers all the evolution of CSR, focusing also on a number of important networks and associations. Some of the methodologies employed in the thesis have been employed as a consequence of data analysis, in a truly inductive research process. The thesis is composed by two section. The first section mainly describes the research process and the analyses results. The candidates employed several research methods: a longitudinal content analysis of documents, a vocabulary research with statistical metrics as cluster analysis and factor analysis, a rhetorical analysis of justifications. The second section puts in relation the analysis results with theoretical frameworks and contributions. The candidate confronted with several frameworks: Actor-Network-Theory, Institutional work and Boundary Work, Institutional Logic. Chapters are focused on different issues: a historical reconstruction of CSR; a reflection about symbolic adoption of recurrent labels; two case studies of Italian networks, in order to confront institutional and boundary works; a theoretical model of institutional change based on contradiction and institutional complexity; the application of the model to CSR and Sustainability, proposing Sustainability as a possible institutional logic.

P-Technique Factor Analyses of the Multiple Affect Adjective Checklist (MAACL)

The Multiple Affect Adjective Check List (MAACL) has been found to have five first-order factors representing Anxiety, Depression, Hostility, Positive Affect, and Sensation Seeking and two second-order factors representing Positive Affect and Sensation Seeking (PASS) and Dysphoria. The present study examines whether these first- and second-order conceptions of affect (based on R-technique factor analysis) can also account for patterns of intraindividual variability in affect (based on P-technique factor analysis) in eight elderly women. Although the hypothesized five-factor model of affect was not testable in all of the present P-technique datasets, the results were consistent with this interindividual model of affect. Moreover, evidence of second-order (PASS and Dysphoria) and third-order (generalized distress) factors was found in one data set. Sufficient convergence in findings between the present P-technique research and prior R-technique research suggests that the MAACL is robust in describing both inter- and intraindividual components of affect in elderly women.

Measurement Properties of the Short Multi-Dimensional Observation Scale for Elderly Subjects (MOSES)

This study evaluated the five-factor measurement model of the abbreviated Multidimensional Observation Scale for Elderly Subjects (MOSES), originally proposed by Pruchno, Kleban, and Resch in 1988. Modifications of the five-factor model were examined and evaluated with regard to their practical significance. A confirmatory second-order factor analysis was performed to examine whether the correlations among the first-order factors were adequately accounted for by a global dysfunction factor. Findings indicated that the proposed measurement model was replicated adequately. Although post hoc modifications resulted in significant improvements in overall model fit, the minor parameters had only a trivial influence on the major parameters of the baseline model. Results from the second-order factor analysis showed that a global dysfunc tion factor accounted adequately for the intercorrelations among the first-order factors.

Influence of residual pockets on progression of periodontitis and tooth loss: results after 11 years of maintenance

BACKGROUND: Limited evidence exists on the significance of residual probing pocket depth (PPD) as a predictive parameter for periodontal disease progression and tooth loss. AIM: The aim of this study was to investigate the influence of residual PPD >or=5 mm and bleeding on probing (BOP) after active periodontal therapy (APT) on the progression of periodontitis and tooth loss. MATERIAL AND METHODS: In this retrospective cohort, 172 patients were examined after APT and supportive periodontal therapy (SPT) for 3-27 years (mean 11.3 years). Analyses were conducted using information at site, tooth and patient levels. The association of risk factors with tooth loss and progression of periodontitis was investigated using multilevel logistic regression analysis. RESULTS: The number of residual PPD increased during SPT. Compared with PPDfactor for tooth loss with odds ratios of 5.8 and 7.7, respectively, at site and tooth levels. The corresponding odds ratios for PPD=6 mm were 9.3 and 11.0 and for PPD>or=7 mm 37.9 and 64.2, respectively. At patient level, heavy smoking, initial diagnosis, duration of SPT and PPD>or=6 mm were risk factors for disease progression, while PPD>or=6 mm and BOP>or=30% represented a risk for tooth loss. CONCLUSION: Residual PPD>or=6 mm represent an incomplete periodontal treatment outcome and require further therapy.

Investigating Research Streams of Conjoint Analysis: A Bibliometric Study

Conjoint analysis (CA) is one of the most important methods for preference elicitation. In this paper we investigate the intellectual structure within the conjoint analytical research community. Analyses based on single papers provide a method-based overview of streams of conjoint research. By using novel bibliometric techniques in this field we complement findings of existing reviews. We use co-citation and factor analysis of the most cited articles in SSCI to identify the most important articles and research streams. Seven research streams are revealed which are visualized by means of multidimensional scaling. Tables and graphics reveal the disciplinary affiliations of contributors to CA, the special structure within the classes as well as links between them.