On Generalized Galois Cyclic Orbit Flag Codes

Flag codes that are orbits of a cyclic subgroup of the general linear group acting on flags of a vector space over a finite field, are called cyclic orbit flag codes. In this paper, we present a new contribution to the study of such codes, by focusing this time on the generating flag. More precisely, we examine those ones whose generating flag has at least one subfield among its subspaces. In this situation, two important families arise: the already known Galois flag codes, in case we have just fields, or the generalized Galois flag codes in other case. We investigate the parameters and properties of the latter ones and explore the relationship with their underlying Galois flag code.

Correlation of Anxiety with Pregnancy Symptoms and Maternal-fetal Attachment

Background: Anxiety during pregnancy may affect maternal-fetal attachment (MFA) and the prevalence of pregnancy symptoms. Objectives: The present study aimed to assess the correlation of anxiety with pregnancy symptoms and MFA. Methods: This cross-sectional study was conducted on 220 pregnant women in the health centers of Tabriz, Iran, in 2020. Samples were selected by the cluster sampling method. Data were collected using the socio-demographic questionnaire, Pregnancy-related Anxiety Questionnaire-revised 2 (PRAQ-R2), MFA Scale (MFAS), and Pregnancy Symptoms Inventory (PSI), all of which were completed as self-administered in the second half of pregnancy. The Pearson’s correlation coefficient and adjusted general linear model were used for data analysis. Results: The results of Pearson’s correlation showed no correlation between anxiety during pregnancy and MFA among nulliparous (r = -0.003, P = 0.976) and multiparous (r = -0.003, P = 0.712) pregnant women. However, anxiety and pregnancy symptoms were significantly correlated among nulliparous (r = 0.424, P < 0.001) and multiparous (r = 0.227, P = 0.028) pregnant women. According to the general linear model, after adjusting the socio-demographic variables, a significant correlation was observed between anxiety and pregnancy symptoms (P < 0.001), while no relationship was found between anxiety and MFA (P = 0.705). Conclusions: Given the significant correlation between anxiety and pregnancy symptoms, pregnant women with anxiety symptoms need to be screened and treated by an expert psychological team if their disorder is confirmed.

The reasons why the Regression Tree Method is more suitable than General Linear Model to analyze complex educational datasets

Any quantitative method is shaped by certain rules or assumptions which constitute its own rationale. It is not by chance that these assumptions determine the conditions and constraints which permit the evidence to be constructed. In this article, we argue why the Regression Tree Method’s rationale is more suitable than General Linear Model to analyze complex educational datasets. Furthermore, we apply the CART algorithm of Regression Tree Method and the Multiple Linear Regression in a model with 53 predictors, taking as outcome the students’ scores in reading of the 2011’s edition of the National Exam of Upper Secondary Education (ENEM; N = 3,670,089), which is a complex educational dataset. This empirical comparison illustrates how the Regression Tree Method is better suitable than General Linear Model for furnishing evidence about non-linear relationships, as well as, to deal with nominal variables with many categories and ordinal variables. We conclude that the Regression Tree Method constructs better evidence about the relationships between the predictors and the outcome in complex datasets.

Lower infant mortality and access to contraception reduce fertility in low- and middle-income nations

Although average contraceptive use has increased globally in recent decades, an estimated 222 million (26%) of women of child-bearing age worldwide face an unmet need for family planning - defined as a discrepancy between fertility preferences and contraception practice, or failing to translate desires to avoid pregnancy into preventative behaviours and practices. While many studies have reported relationships between availability of contraception, infant mortality, and fertility, these relationships have not been evaluated quantitatively across a broad range of low- and middle-income countries. Using publicly available data from 46 low- and middle-income countries, we collated test and control variables in six themes: (i) availability of family planning, (ii) quality of family planning, (iii) maternal education, (iv) religion, (v) mortality, and (vi) socio-economic conditions. We predicted that higher nation-level availability/quality of family-planning services, maternal education, and wealth reduce average fertility, whereas higher infant mortality and religious adherence increase it. Given the sample size, we first constructed general linear models to test for relationships between fertility and the variables from each theme, from which we retained those with the highest explanatory power within a final general linear model set to determine the partial correlation of dominant test variables. We also applied boosted regression trees, generalised least-squares models, and a generalised linear mixed-effects models to account for non-linearity and spatial autocorrelation. On average among all countries, we found an association between all main variables and fertility, with reduced infant mortality having the strongest relationship with reduced fertility. Access to contraception was the next-highest correlate with reduced fertility, with female secondary education, home health visitations, and adherence to Catholicism having weak, if any, explanatory power. Our models suggest that decreasing infant mortality and increasing access to contraception will have the greatest effect on decreasing global fertility. We thus provide new evidence that progressing the United Nation's Sustainable Development Goals for reducing infant mortality can be accelerated by increasing access to any form of family planning.

PDSTD - The Portsmouth Dynamic Spontaneous Tears Database

The vast majority of research on human emotional tears has relied on posed and static stimulus materials. In this paper, we introduce the Portsmouth Dynamic Spontaneous Tears Database (PDSTD), a free resource comprising video recordings of 24 female encoders depicting a balanced representation of sadness stimuli with and without tears. Encoders watched a neutral film and a self-selected sad film and reported their emotional experience for 9 emotions. Extending this initial validation, we obtained norming data from an independent sample of naïve observers (N = 91, 45 females) who watched videos of the encoders during three time phases (neutral, pre-sadness, sadness), yielding a total of 72 validated recordings. Observers rated the expressions during each phase on 7 discrete emotions, negative and positive valence, arousal, and genuineness. All data were analyzed by means of general linear mixed modelling (GLMM) to account for sources of random variance. Our results confirm the successful elicitation of sadness, and demonstrate the presence of a tear effect, i.e., a substantial increase in perceived sadness for spontaneous dynamic weeping. To our knowledge, the PDSTD is the first database of spontaneously elicited dynamic tears and sadness that is openly available to researchers. The stimuli can be accessed free of charge via OSF from https://osf.io/uyjeg/?view_only=24474ec8d75949ccb9a8243651db0abf.