Effect of 2% Chlorhexidine Digluconate on the Bond Strength to Normal Versus Caries-affected Dentin

This study evaluated the effect of 2% chlorhexidine digluconate (CHX) used as a therapeutic primer on the long-term bond strengths of two etch-and-rinse adhesives to normal (ND) and caries-affected (CAD) dentin. Forty extracted human molars with coronal carious lesions, surrounded by normal dentin, were selected for this study. The flat surfaces of two types of dentin (ND and CAD) were prepared with a water-cooled high-speed diamond disc, then acidetched, rinsed and air-dried. In the control groups, the dentin was re-hydrated with distilled water, blot-dried and bonded with a three-step (Scotchbond Multi-Purpose-MP) or two-step (Single Bond 2-SB) etch-and-rinse adhesive. In the experimental groups, the dentin was rehydrated with 2% CHX (60 seconds), blot-dried and bonded with the same adhesives. Resin composite build-ups were made. The specimens were prepared for microtensile bond testing in accordance with the non-trimming technique, then tested either immediately or after six-months storage in artificial saliva. The data were analyzed by ANOVA/Bonferroni tests (alpha=0.05). CHX did not affect the immediate bond strength to ND or CAD (p>0.05). CHX treatment significantly lowered the loss of bond strength after six months as seen in the control bonds for ND (p<0.05), but it did not alter the bond strength of CAD (p>0.05). The application of NIP on CHX-treated ND or CAD produced bonds that did not change over six months of storage.

Couple distress after sudden infant or perinatal death: A 30-month follow up

Objective: To examine, using a 30-month prospective study, patterns of anxiety, depression and alcohol use in couples following stillbirth, neonatal death or sudden infant death syndrome. Methodology: One hundred and thirty-eight bereaved and 156 non-bereaved couples completed standardized interviews at 2, 8, 15 and 30 months post-loss. Results: At all interviews, bereaved couples were significantly more likely than non-bereaved couples to have at least one distressed partner. Rarely were both partners distressed in either group. For bereaved couples, 'mother only' distress declined from 21% to 10% during the study. 'Father only' distress ranged from 7% to 15%, peaking at 30 months. Bereaved mothers who were distressed at 2 months reported significantly lower marital satisfaction at 30 months. Conclusions: At the couple level, the experience of a baby's death is multifaceted. Gender differences are common and partners' needs may change over time. Early recognition of these differences may facilitate longer-term adjustment for both partners.

Relationship between ISO 9001 certification maturity and EFQM business excellence model results

Purpose: This exploratory research evaluates if there is a relationship between the number of years since an organization has achieved ISO 9001 certification and the highest level of recognition received by the same organization with the EFQM Business Excellence Model. Methodology/Approach: After state of the art review a detailed comparison between both models was made. Fifty two Portuguese organizations were considered and Correlation coefficient Spearman Rho was used to investigate the possible relationships. Findings: Conclusion is that there is indeed a moderate positive correlation between these two variables, the higher the number of years of ISO 9001 certification, the higher the results of the organization EFQM model evaluation and recognition. This supports the assumption that ISO 9001 International Standard by incorporating many of the principles present in the EFQM Business Excellence Model is consistent with this model and can be considered as a step towards that direction. Research Limitation/implication: Due to the dynamic nature of these models that might change over time and the possible time delays between implementation and results, more in-depth studies like experimental design or a longitudinal quasi-experimental design could be used to confirm the results of this investigation. Originality/Value of paper: This research gives additional insights on conjunct studies of both models. The use of external evaluation results carried out by the independent EFQM assessors minimizes the possible bias of previous studies accessing the value of ISO 9001 certification.

Trypanosoma cruzi in marsupial didelphids (Philander frenata and Didelhis marsupialis): differences in the humoral immune response in natural and experimental infections

Philander frenata and Didelphis marsupialis harbor parasitism by Trypanosoma cruzi without developing any apparent disease and on the contrary to D. marsupialis, P. frenata maintains parasitism by T. cruzi II subpopulations. Here we compared the humoral immune response of the two didelphids naturally and experimentally infected with T. cruzi II group, employing SDS-PAGE/Western blot techniques and by an Indirect immunofluorescence assay. We also studied the histopathological pattern of naturally and experimentally infected P. frenata with T. cruzi. P. frenata sera recognized more antigens than D. marsupialis, and the recognition pattern did not show any change over the course of the follow up of both didelphid species. Polypeptides of 66 and 90kDa were the most prominent antigens recognized by both species in the soluble and enriched membrane fractions. P. frenata recognized intensely also a 45kDa antigen. Our findings indicate that: 1) there were no quantitative or qualitative differences in the patent or subpatent phases in the recognition pattern of P. frenata; 2) the significant differences in the recognition pattern of parasitic antigens by P. frenata and D. marsupialis sera suggest that they probably "learned" to live in harmony with T. cruzi by different strategies; 3) although P. frenata do not display apparent disease, tissular lesions tended to be more severe than has been described in D. marsupialis; and 4) Both didelphids probably acquired infection by T. cruzi after their evolutionary divergence.

Application of wavelets to the study of political history

\The idea that social processes develop in a cyclical manner is somewhat like a `Lorelei'. Researchers are lured to it because of its theoretical promise, only to become entangled in (if not wrecked by) messy problems of empirical inference. The reasoning leading to hypotheses of some kind of cycle is often elegant enough, yet the data from repeated observations rarely display the supposed cyclical pattern. (...) In addition, various `schools' seem to exist which frequently arrive at di erent conclusions on the basis of the same data." (van der Eijk and Weber 1987:271). Much of the empirical controversies around these issues arise because of three distinct problems: the coexistence of cycles of di erent periodicities, the possibility of transient cycles and the existence of cycles without xed periodicity. In some cases, there are no reasons to expect any of these phenomena to be relevant. Seasonality caused by Christmas is one such example (Wen 2002). In such cases, researchers mostly rely on spectral analysis and Auto-Regressive Moving-Average (ARMA) models to estimate the periodicity of cycles.1 However, and this is particularly true in social sciences, sometimes there are good theoretical reasons to expect irregular cycles. In such cases, \the identi cation of periodic movement in something like the vote is a daunting task all by itself. When a pendulum swings with an irregular beat (frequency), and the extent of the swing (amplitude) is not constant, mathematical functions like sine-waves are of no use."(Lebo and Norpoth 2007:73) In the past, this di culty has led to two di erent approaches. On the one hand, some researchers dismissed these methods altogether, relying on informal alternatives that do not meet rigorous standards of statistical inference. Goldstein (1985 and 1988), studying the severity of Great power wars is one such example. On the other hand, there are authors who transfer the assumptions of spectral analysis (and ARMA models) into fundamental assumptions about the nature of social phenomena. This type of argument was produced by Beck (1991) who, in a reply to Goldstein (1988), claimed that only \ xed period models are meaningful models of cyclic phenomena".We argue that wavelet analysis|a mathematical framework developed in the mid-1980s (Grossman and Morlet 1984; Goupillaud et al. 1984) | is a very viable alternative to study cycles in political time-series. It has the advantage of staying close to the frequency domain approach of spectral analysis while addressing its main limitations. Its principal contribution comes from estimating the spectral characteristics of a time-series as a function of time, thus revealing how its di erent periodic components may change over time. The rest of article proceeds as follows. In the section \Time-frequency Analysis", we study in some detail the continuous wavelet transform and compare its time-frequency properties with the more standard tool for that purpose, the windowed Fourier transform. In the section \The British Political Pendulum", we apply wavelet analysis to essentially the same data analyzed by Lebo and Norpoth (2007) and Merrill, Grofman and Brunell (2011) and try to provide a more nuanced answer to the same question discussed by these authors: do British electoral politics exhibit cycles? Finally, in the last section, we present a concise list of future directions.

Cortisol, family coping and burden in informal caregivers of addicts

This study focuses on the prospective mediation role of family coping between burden and cortisol levels in informal caregivers of addicts as well as on the feasible use of two different ways to analyse the salivary cortisol levels. Participants were 120 Portuguese informal caregivers of addicts. The cortisol samples were collected at awakening, 45 minutes later and after a 30 minute presentation of images taken from the International Affective Picture System. Family coping and caregiver burden were measured using the Portuguese versions of the Caregiver Reaction Assessment, and the Family Crisis Oriented Personal Evaluation Scale. Cortisol samples were collected in salivettes and the results were computed in order to determine the Area Under the Curve scores (AUCg, AUCi). Results found family coping to be negatively correlated with burden and AUCg levels (i.e. overall intensity) and positively correlated with either AUCg and AUCi (i.e. change over time). The mediation model revealed that family coping was a partial mediator in the relationship between the burden and AUCg levels. Therefore, Family Coping appears to be an essential variable in understanding the stress response and should be considered in further studies and interventions. In addition, the use of two different formulas for calculating cortisol levels provided important new information concerning the relationship between cortisol, burden and family coping. It seems that burden has a more profound effect on the overall intensity of the neuroendocrine response to caregiver stress and not so much on the sensitivity of the system.

Melhoria do desempenho de uma secção de montagem final de uma empresa usando ferramentas Lean Production

Dissertação de mestrado integrado em Engenharia e Gestão Industrial

Couple's willingness to donate embryos for research: a longitudinal study

Introduction. Decision-making on embryo disposition is a source of distress and is subject to change over time. This paper analyses the willingness of couples undergoing in vitro fertilization to donate cryopreserved embryos for research from 15 days after embryo transfer to 12 months later, taking into account the influence of psychosocial, demographic, and reproductive factors. Materials and methods. Prospective longitudinal study, with 74 heterosexual couples undergoing in vitro fertilization in a public fertility centre in Portugal, recruited between 2011 and 2012. Participants were evaluated twice: 15 days after embryo transfer and 12 months later. Results. A significant decrease in patients’ willingness to donate embryos for research over time was observed [86.5% to 73.6%; relative risk (RR) = 0.85; 95% CI 0.76–0.95]. A higher education level (>12 years) [adjusted RR (RRadj) = 0.79; 95% CI 0.64–0.96], considering research on human embryos to be important (vs. very important) (RRadj = 0.59; 95% CI 0.39–0.85) and practicing a religion less than once a month (vs. at least once a month) (RRadj = 0.73; 95% CI 0.53–1.00) seemed associated with unwillingness to donate embryos for research over time. Change towards non-donation happened mainly among couples who first considered that it was better to donate than wasting the embryos. Change towards donation occurred mostly among those stating that their priority at time 1 was to have a baby and who became pregnant in the meantime. Conclusions. Quality of care guided by patients’ characteristics, values, preferences, and needs calls for considering the factors and reasons underlying couples’ willingness to donate embryos for research over time as a topic in psychosocial guidelines for infertility and medically assisted reproductive care.

24-h urinary free cortisol from mid-pregnancy to 3-months postpartum: gender and parity differences and effects

Background: Pregnancy and postpartum have been associated to several physiological changes;however, empirical evidence was almost exclusively obtained in primiparous women and few studies focus on hormonal changes in men and second-time parents. The main aim of this study is to examine 24-h urinary free cortisol from mid-pregnancy to 3-months postpartum, comparing women/men and first/second-time parents.Methods: Twenty-six women and 22 men (N = 48) were recruited from an antenatal obstetric unit in Porto, Portugal. 24-h urinary free cortisol was measured at the 2nd and 3rd trimester and at 3-months postpartum. Repeated measures analyses of variance were conducted, in order to analyze 24-h urinary free cortisol patterns of change over this period. Gender and parity were included in the analyses as potential modifiers, in order to compare women and men, and first-and second-time parents.Results: An increase from the 2nd to the 3rd trimester (p = .006) and a decrease from the 3rd trimester to 3-months postpartum (p = .005) were reported in all parents’ 24-h urinary free cortisol. The interaction effects for Time * Gender (p = .03) and Time * Parity (p = .02) were found. Women and first-time parents revealed higher levels, while men and second-time parents showed lower 24-h urinary free cortisol levels at the 2nd trimester than at 3-months postpartum.Conclusions: Findings appear to clarify the direction, as well as, the timing, gender and parity extension of 24-h urinary free cortisol changes from mid-pregnancy to 3-months postpartum.The same pattern of change in all parents’ 24-h urinary free cortisol from mid-pregnancy to 3-months postpartum is consistent with the proposed role of hormones in preparation to parenting.

Forecasting Inflation Using Dynamic Model Averaging

We forecast quarterly US inflation based on the generalized Phillips curve using econometric methods which incorporate dynamic model averaging. These methods not only allow for coe¢ cients to change over time, but also allow for the entire forecasting model to change over time. We nd that dynamic model averaging leads to substantial forecasting improvements over simple benchmark regressions and more sophisticated approaches such as those using time varying coe¢ cient models. We also provide evidence on which sets of predictors are relevant for forecasting in each period.

Forecasting the European Carbon Market

In an effort to meet its obligations under the Kyoto Protocol, in 2005 the European Union introduced a cap-and-trade scheme where mandated installations are allocated permits to emit CO2. Financial markets have developed that allow companies to trade these carbon permits. For the EU to achieve reductions in CO2 emissions at a minimum cost, it is necessary that companies make appropriate investments and policymakers design optimal policies. In an effort to clarify the workings of the carbon market, several recent papers have attempted to statistically model it. However, the European carbon market (EU ETS) has many institutional features that potentially impact on daily carbon prices (and associated nancial futures). As a consequence, the carbon market has properties that are quite different from conventional financial assets traded in mature markets. In this paper, we use dynamic model averaging (DMA) in order to forecast in this newly-developing market. DMA is a recently-developed statistical method which has three advantages over conventional approaches. First, it allows the coefficients on the predictors in a forecasting model to change over time. Second, it allows for the entire fore- casting model to change over time. Third, it surmounts statistical problems which arise from the large number of potential predictors that can explain carbon prices. Our empirical results indicate that there are both important policy and statistical bene ts with our approach. Statistically, we present strong evidence that there is substantial turbulence and change in the EU ETS market, and that DMA can model these features and forecast accurately compared to conventional approaches. From a policy perspective, we discuss the relative and changing role of different price drivers in the EU ETS. Finally, we document the forecast performance of DMA and discuss how this relates to the efficiency and maturity of this market.

Forecasting Inflation Using Dynamic Model Averaging

We forecast quarterly US inflation based on the generalized Phillips curve using econometric methods which incorporate dynamic model averaging. These methods not only allow for coe¢ cients to change over time, but also allow for the entire forecasting model to change over time. We nd that dynamic model averaging leads to substantial forecasting improvements over simple benchmark regressions and more sophisticated approaches such as those using time varying coe¢ cient models. We also provide evidence on which sets of predictors are relevant for forecasting in each period.

Large Time-Varying Parameter VARs

In this paper we develop methods for estimation and forecasting in large timevarying parameter vector autoregressive models (TVP-VARs). To overcome computational constraints with likelihood-based estimation of large systems, we rely on Kalman filter estimation with forgetting factors. We also draw on ideas from the dynamic model averaging literature and extend the TVP-VAR so that its dimension can change over time. A final extension lies in the development of a new method for estimating, in a time-varying manner, the parameter(s) of the shrinkage priors commonly-used with large VARs. These extensions are operationalized through the use of forgetting factor methods and are, thus, computationally simple. An empirical application involving forecasting inflation, real output, and interest rates demonstrates the feasibility and usefulness of our approach.

Time Variation in the Dynamics of Worker Flows: Evidence from the US and Canada

VAR methods have been used to model the inter-relationships between inflows and outfl ows into unemployment and vacancies using tools such as impulse response analysis. In order to investigate whether such impulse responses change over the course of the business cycle or or over time, this paper uses TVP-VARs for US and Canadian data. For the US, we find interesting differences between the most recent recession and earlier recessions and expansions. In particular, we find the immediate effect of a negative shock on both in ow and out flow hazards to be larger in 2008 than in earlier times. Furthermore, the effect of this shock takes longer to decay. For Canada, we fi nd less evidence of time-variation in impulse responses.

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.