Covid 19: Determination of the Relationship between Sex, Having Handkerchief or Staying Indoor and Facial Touch

Background:Covid-19 outbreak is the current pandemic confronting nations in the world. The virus had caused so much loss of lives, loss of jobs and serious damages to global economy. One major way of preventing the spread of the virus and guide against being infected is to avoid face touching with unwashed hand(s).Objective:The objective of this study is to investigate the association between sex, having handkerchief or staying indoor and number of time a person touches face (mouth, eyes or nose). Methodology:A sample size of n = 130 people were randomly selected and observed obliviously for 120 seconds. The number of times they touched their faces were recorded with other variables like sex, having handkerchief and staying indoor or outdoor. Since the response variable is count, appropriate models for such data were used. Results and Conclusion:The Poisson results shown that there exist overdispersion, hence, a model that can account for the dispersion parameter was used to obtain accurate results. The results of the analysis shown that there is no association between the number of time a person touches face and sex, having handkerchief or staying indoor. The expected number time people touch their faces within 120 seconds is twice while the minimum and maximum number of times are zero and eight respectively.Recommendation:It is recommended that there ought to be adequate public enlightenment and sensitization on the peril of the novel COVID-19 pandemic and the reason why individuals ought to stick carefully to the exhortation of abstaining from touching of faces (without washing with soap and water) so as to forestall its spread. If a person's hands are contaminated with the virus, he/she isn't infected until he/she touches the face (nose, eye or mouth) with thehands unwashed

Structure of the parasites communities in two Erythrinidae fish from Amazon river system (Brazil) / Estrutura da comunidade de parasitos em dois Erythrinidae do sistema do Rio Amazonas (Brasil)

This study compared the parasite communities of Hoplias malabaricus and Hoplerythrinus unitaeniatus from Amazon river system. Hoplias malabaricus were infected by Ichthyophthirius multifiliis, Piscinoodinium pillulare, Tetrahymena sp., Urocleidoides eremitus, Braga patagonica, metacercariae of Clinostomum marginatum, Procamallanus (Spirocamallanus) inopinatus, larvae of Contracaecum sp. and larvae of Nomimoscolex matogrossensis. Hoplerythrinus unitaeniatus were also infected by these same species of protozoans, nematodes, digeneans and cestodes, except for Tetrahymena sp. and B. patagonica, which were replaced by Argulus pestifer, Urocleidoides sp., Whittingtonocotyle caetei, Whittingtonocotyle jeju and Gorytocephalus spectabilis. For both hosts, I. multifiliis and P. pillulare were the predominant parasites. Most of the parasites presented an overdispersion. Parasite species richness, Brillouin diversity, evenness and Berger-Parker dominance were similar for the two hosts. The length and weight of H. malabaricus showed a positive correlation with the abundance of U. eremitus and Contracaecum sp., while the weight of H. unitaeniatus showed a positive correlation with the abundance of I. multifiliis. The diversity of ectoparasites seemed to be influenced by the behavior of these two hosts. This was shown by the similar parasite communities and was characterized by low species diversity, low evenness and low richness, and by a high prevalence of ectoparasites.

Este estudo comparou a comunidade parasitária de Hoplias malabaricus e Hoplerythrinus unitaeniatus do sistema do Rio Amazonas. Hoplias malabaricus estavam infectados por Ichthyophthirius multifiliis, Piscinoodinium pillulare, Tetrahymena sp., Urocleidoides eremitus, Braga patagonica, metacercarias de Clinostomum marginatum, Procamallanus (Spirocamallanus) inopinatus, larvas de Contracaecum sp. e larvas de Nomimoscolex matogrossensis. Hoplerythrinus unitaeniatus estavam também infectados por essas mesmas espécies de protozoários, nematoides, digeneas e cestóide, exceto Tetrahymena sp. e B. patagonica, que foram substituídos por Argulus pestifer, Urocleidoides sp., Whittingtonocotyle caetei, Whittingtonocotyle jeju e Gorytocephalus spectabilis. Para ambos os hospedeiros, a dominância foi de I. multifiliis e P. pillulare. Houve dispersão agregada para a maioria dos parasitos e similar riqueza de espécies de parasitos, diversidade de Brillouin, uniformidade e dominância de Berger-Parker, para ambos os hospedeiros. O comprimento e peso de H. malabaricus mostrou correlação positiva com a abundância de U. eremitus e Contracaecum sp., enquanto o peso de H. unitaeniatus mostrou correlação positiva com abundância de I. multifiliis. A diversidade de ectoparasitos parece influenciada pelo comportamento desses dois hospedeiros. Isso é mostrado pela similar comunidade de parasitos e caracterizada por uma baixa diversidade de espécies, baixa uniformidade e baixa riqueza de espécies, e pela elevada prevalência de ectoparasitos.

Phylogenetic overdispersion of plant species in southern Brazilian savannas / Dispersão filogenética de espécies de plantas em savanas no Sudeste do Brasil

Ecological communities are the result of not only present ecological processes, such as competition among species and environmental filtering, but also past and continuing evolutionary processes. Based on these assumptions, we may infer mechanisms of contemporary coexistence from the phylogenetic relationships of the species in a community. We studied the phylogenetic structure of plant communities in four cerrado sites, in southeastern Brazil. We calculated two raw phylogenetic distances among the species sampled. We estimated the phylogenetic structure by comparing the observed phylogenetic distances to the distribution of phylogenetic distances in null communities. We obtained null communities by randomizing the phylogenetic relationships of the regional pool of species. We found a phylogenetic overdispersion of the cerrado species. Phylogenetic overdispersion has several explanations, depending on the phylogenetic history of traits and contemporary ecological interactions. However, based on coexistence models between grasses and trees, density-dependent ecological forces, and the evolutionary history of the cerrado flora, we argue that the phylogenetic overdispersion of cerrado species is predominantly due to competitive interactions, herbivores and pathogen attacks, and ecological speciation. Future studies will need to include information on the phylogenetic history of plant traits.

Comunidades ecológicas resultam não somente de processos ecológicos atuais, como a competição e os filtros ambientais, mas também de processos evolutivos passados e contínuos. Com base nessas premissas, podemos inferir mecanismos de coexistência contemporânea a partir das relações filogenéticas das espécies em uma comunidade. Estudamos a estrutura filogenética das comunidades de plantas de quatro áreas de cerrado, no Sudeste do Brasil. Calculamos duas medidas das distâncias filogenéticas das espécies amostradas. Estimamos a estrutura filogenética comparando suas distâncias observadas com a distribuição dessas distâncias em comunidades nulas. Obtivemos comunidades nulas aleatorizando as relações filogenéticas do banco regional de espécies. Encontramos uma dispersão filogenética de espécies de cerrado. Há várias explicações para essa dispersão, dependendo da história filogenética dos traços e das interações ecológicas contemporâneas. Entretanto, com base nos modelos de coexistência entre árvores e gramíneas, nas forças ecológicas dependentes da densidade e na história evolutiva da flora do cerrado, argumentamos que a dispersão filogenética das espécies do cerrado é predominantemente devida às interações competitivas, aos ataques de herbívoros e patógenos e à especiação ecológica. Estudos futuros precisarão incluir informações sobre a história filogenética dos traços das plantas.

Regression Methods for Overdispersed Dichotomous Response Data / 신경정신의학

In neuropsychiatrical research, many problems of statistical inference concern the relationship between the PTSD and traumatic experiences. The logistic model is widely used for modeling a relationship between the covariate and the magnitude of the PTSD. A common complication in the logistic model for dichotomous response data is overdispersion. In this study, two different methods for analyzing dichotomous response data are illustrated and compared. One method is the logistic regression approach, where the numbers of dichotomous responses are predicted by the logistic function of covariates. The other one is the overdispersed logistic regression approach, where the overdispersion is measured by a scale parameter in the variance function of the dichotomous response. In dichotomous response model, when reponses are overdispersed, the overdispersed logistic regression produces more appropriate standard errors of the regression coefficients and the 95% confidence intervals of odds ratios. Therefore, in neuropsychiatrical research, it is recommended to examine the overdispersion problems for their data set before applying the logistic regression model.

Regression Methods for Overdispersed Dichotomous Response Data / 신경정신의학

In neuropsychiatrical research, many problems of statistical inference concern the relationship between the PTSD and traumatic experiences. The logistic model is widely used for modeling a relationship between the covariate and the magnitude of the PTSD. A common complication in the logistic model for dichotomous response data is overdispersion. In this study, two different methods for analyzing dichotomous response data are illustrated and compared. One method is the logistic regression approach, where the numbers of dichotomous responses are predicted by the logistic function of covariates. The other one is the overdispersed logistic regression approach, where the overdispersion is measured by a scale parameter in the variance function of the dichotomous response. In dichotomous response model, when reponses are overdispersed, the overdispersed logistic regression produces more appropriate standard errors of the regression coefficients and the 95% confidence intervals of odds ratios. Therefore, in neuropsychiatrical research, it is recommended to examine the overdispersion problems for their data set before applying the logistic regression model.