Predicting Autism From Infant Characteristics: A Systematic Review

A literature review was conducted of 73 articles to explore 12-month-old characteristics in infants that predicted later diagnosis with autism (ASD). Articles were reviewed if they discussed ASD, infants with siblings diagnosed with autism (high-risk) and/or infants later diagnosed with autism without known family history of ASD (low risk). Articles were not reviewed if the participants were 36 months or older at the start of the study. More factors were identified that discriminate characteristics associated with later ASD diagnosis in infants between 12-24 months compared to characteristics of infants below 12 months. Characteristics of infants under 12 months that were associated with later autism diagnosis include social behaviors, communication behaviors, eye gaze, abnormal movements, and auditory brainstem responses

Looking for discrete UV absorption features in the early-type eclipsing binaries μ1 Scorpii and AO Cassiopeiae

A search for discrete absorption components in the ultraviolet spectra of the early-type binaries μ1 Scorpii and AO Cassiopeiae has been undertaken by analyzing material secured with the International Ultraviolet Explorer satellite during an exclusively assigned interval of nearly 50 hr. While the spectra of μ1 Sco definitely do not show the presence of such lines, the spectra of AO Cas do confirm them and permit us to draw some conclusions about where they may be formed.Facultad de Ciencias Astronómicas y Geofísica

Looking for discrete UV absorption features in the early-type eclipsing binaries μ1 Scorpii and AO Cassiopeiae

A search for discrete absorption components in the ultraviolet spectra of the early-type binaries μ1 Scorpii and AO Cassiopeiae has been undertaken by analyzing material secured with the International Ultraviolet Explorer satellite during an exclusively assigned interval of nearly 50 hr. While the spectra of μ1 Sco definitely do not show the presence of such lines, the spectra of AO Cas do confirm them and permit us to draw some conclusions about where they may be formed.Facultad de Ciencias Astronómicas y Geofísica

Development of a risk classification model in early pregnancy to screen for suboptimal postnatal mother-to-infant bonding:A prospective cohort study

BACKGROUND: Previous studies identified demographic, reproduction-related and psychosocial correlates of suboptimal mother-to-infant bonding. Their joint informative value was still unknown. This study aimed to develop a multivariable model to screen early in pregnancy for suboptimal postnatal mother-to-infant bonding and to transform it into a risk classification model. METHODS: Prospective cohort study conducted at 116 midwifery centers between 2010-2014. 634 women reported on the Mother-to-Infant Bonding questionnaire in 2015-2016. A broad range of determinants before 13 weeks of gestation were considered. Missing data were described, analyzed and imputed by multiple imputation. Multivariable logistic regression with backward elimination was used to develop a screening model. The explained variance, the Area Under the Curve of the final model were calculated and a Hosmer and Lemeshow test performed. Finally, we designed a risk classification model. RESULTS: The prevalence of suboptimal mother-to-infant bonding was 11%. The estimated probability of suboptimal mother-to-infant can be calculated: P(MIBS≥4) = 1/(1+exp(-(-4.391+(parity× 0.519)+(Adult attachment avoidance score× 0.040))). The explained variance was 14% and the Area Under the Curve was 0.750 (95%CI 0.690-0.809). The Hosmer and Lemeshow test had a p-value of 0.21. This resulted in a risk classification model. CONCLUSION: Parity and adult attachment avoidance were the strongest independent determinants. Higher parity and higher levels of adult attachment avoidance are associated with an increased risk of suboptimal mother-to-infant bonding. The model and risk classification model should be externally validated and optimized before use in daily practice. Future research should include an external validation study, a study into the additional value of non-included determinants and finally a study on the impact and feasibility of the screening model

Calculation of the average Green's function of electrons in a stochastic medium via higher-dimensional bosonization

The disorder averaged single-particle Green's function of electrons subject to a time-dependent random potential with long-range spatial correlations is calculated by means of bosonization in arbitrary dimensions. For static disorder our method is equivalent with conventional perturbation theory based on the lowest order Born approximation. For dynamic disorder, however, we obtain a new non-perturbative expression for the average Green's function. Bosonization also provides a solid microscopic basis for the description of the quantum dynamics of an interacting many-body system via an effective stochastic model with Gaussian probability distribution.Comment: RevTex, no figure