Randomized clinical trial to evaluate two methods of caries risk assessment in schoolchildren: the CARDEC-PEL 04 study protocol

Background Caries risk assessment is an essential element for managing and preventing dental caries in children. Individual caries risk assessment can be conducted to evaluate the presence or absence of single factors, or using multivariate models, a combination of factors. The subject has been extensively studied, but no previous research has compared whether a more elaborate and individualized method of caries risk benefits the patient than more straightforward strategies. Thus, this protocol evaluates the efficacy of two risk assessment methods for caries control in children, a simplified method based on caries experience evaluation and a multivariate method described in the literature. Methods This is a randomized, double-blind, controlled, parallel-treatment trial protocol. Two groups will be tested for two forms of caries risk assessment: an individualized and detailed multivariate method based on the guidelines of the Caries Care International 4D and another simplified process, based only on caries experience in primary and/or permanent dentition, considering the presence of decayed, missing and filled teeth using the DMFT/dmft index. Participants will be children aged 8 to 11 years, followed up at 12 and 24 months. The primary outcome will be a composite outcome representing the number of tooth surfaces requiring operative intervention (account variable). In addition, the Shapiro–Wilk normality test and Student's t-test will be performed. A multivariate analysis using negative binomial regression will compare groups in the intention-to-treat population, considering a two-tailed significance level of 5%. Discussion This is the first randomized clinical trial aiming to compare dental caries-related treatment and follow-up based on a detailed, multivariate and individualized assessment of caries risk in school-age children to a simpler risk assessment strategy based on caries experience. This study will define whether there are essential benefits to the patient that justify the choice of one method over the other. Trial registration Clinicaltrials.gov registration: NCT03969628. Registered on May 31th, 2019.

Developing Intercultural Efficiency: The Relationship between Cultural Intelligence and Self-Efficacy

Cultural intelligence measures an individual’s ability to succeed in a culturally unknown environment. Self-efficacy expresses self-confidence in one’s own ability to handle a situation. The two concepts are closely linked, as confirmed by a number of previous studies. Using the multivariate method PLS-SEM, the predictive effect of CQ on self-efficacy is investigated; compared to previous studies, the relationship causality is reversed. A sample of 190 university students was also tested for how this relationship is moderated by two categorical variables: work experience abroad and gender. The results showed that cultural intelligence is a predictor of intercultural self-efficacy in communication. Its impact on the endogenous variable (self-efficacy) is rather weak, but significantly strengthened by work experience abroad. Gender has no effect on this relationship.

CHARACTERISTICS OF CONSUMTIVE BEHAVIOR IN ONLINE SHOP: SHOPPING TRENDS DURING THE COVID-19 PANDEMIC

The aim of the research to find out whether there is a relationship between conformity and consumptive behavior of Muslim fashion products on online shop hijup consumers during the covid-19 pandemic?, to find out Is there a relationship between celebrity support and consumptive behavior in Muslim fashion products for online shop hijup consumers during the COVID-19 pandemic?, and to find out is there a relationship between conformity and celebrity support with the consumptive behavior of Muslim fashion products in online shop hijup consumers during the covid-19 pandemic?. . The research focuses on the relationship between conformity and celebrity support with the consumptive behavior of Muslim fashion products that are marketed online. The population of this research is online shop consumers who have purchased muslim fashion products at online shops and the sampling technique uses incidental sampling. The data collection method used a questionnaire with a Likert scale model given to online shop consumers. Data analysis used multiple regression stepwise method using bivariate and multivariate method. The results of the analysis found that there is a relationship between conformity and celebrity support with consumptive behavior in online consumer muslim fashion products with a contribution of 67%. Thus the results of this research can state that the higher the conformity and support of celebrities, the higher the consumptive behavior of online shop consumers and vice versa

Study of Temporal Variations in Species–Environment Association through an Innovative Multivariate Method: MixSTATICO

The study of biotic and abiotic factors and their interrelationships is essential in the preservation of sustainable marine ecosystems and for understanding the impact that climate change can have on different species. For instance, phytoplankton are extremely vulnerable to environmental changes and thus studying the factors involved is important for the species’ conservation. This work examines the relationship between phytoplankton and environmental parameters of the eastern equatorial Pacific, known as one of the most biologically rich regions in the world. For this purpose, a new multivariate method called MixSTATICO has been developed, allowing mixed-type data structured in two different groups (environment and species) to be related and measured on a space–time scale. The results obtained show how seasons have an impact on species–environment relations, with the most significant association occurring in November and the weakest during the month of May (change of season). The species Lauderia borealis, Chaetoceros didymus and Gyrodinium sp. were not observed in the coastal profiles during the dry season at most stations, while during the rainy season, the species Dactyliosolen antarcticus, Proboscia alata and Skeletonema costatum were not detected. Using MixSTATICO, species vulnerable to specific geographical locations and environmental variations were identified, making it possible to establish biological indicators for this region.

Phylogenomic subsampling and the search for phylogenetically reliable loci

Phylogenomic subsampling is a procedure by which small sets of loci are selected from large genome-scale datasets and used for phylogenetic inference. This step is often motivated by either computational limitations associated with the use of complex inference methods, or as a means of testing the robustness of phylogenetic results by discarding loci that are deemed potentially misleading. Although many alternative methods of phylogenomic subsampling have been proposed, little effort has gone into comparing their behavior across different datasets. Here, I calculate multiple gene properties for a range of phylogenomic datasets spanning animal, fungal and plant clades, uncovering a remarkable predictability in their patterns of covariance. I also show how these patterns provide a means for ordering loci by both their rate of evolution and their relative phylogenetic usefulness. This method of retrieving phylogenetically useful loci is found to be among the top performing when compared to alternative subsampling protocols. Relatively common approaches such as minimizing potential sources of systematic bias or increasing the clock-likeness of the data are found to fare worse than selecting loci at random. Likewise, the general utility of rate-based subsampling is found to be limited: loci evolving at both low and high rates are among the least effective, and even those evolving at optimal rates can still widely differ in usefulness. This study shows that many common subsampling approaches introduce unintended effects in off-target gene properties, and proposes an alternative multivariate method that simultaneously optimizes phylogenetic signal while controlling for known sources of bias.