Are fathers a good substitute for mothers? Paternal care and growth rates in Shodagor children

Abstract Biparental care is a hallmark of human social organization, though paternal investment varies between and within societies. The facultative nature of paternal care in humans suggests males should invest when their care improves child survival and/or quality, though testing this prediction can be challenging because of the difficulties of empirically isolating paternal effects from those of other caregivers. Additionally, the broader context in which care is provided, vis-à-vis care from mothers and others, may lead to different child outcomes. Here, we examine the effects of paternal care on child growth among Shodagor fisher-traders, where fathers provide high levels of both additive and substitutive care, relative to mothers. We modeled seasonal z-scores and velocities for height, weight, and body mass index (BMI) outcomes using linear mixed models. Our evidence indicates that, as predicted, the context of paternal care is an important predictor of child outcomes. Results show that environmental seasonality and alloparental help contribute to a nuanced understanding of the impact of Shodagor paternal care on child physiology

Arctic air pollution: Challenges and opportunities for the next decade

The Arctic is a sentinel of global change. This region is influenced by multiple physical and socio-economic drivers and feedbacks, impacting both the natural and human environment. Air pollution is one such driver that impacts Arctic climate change, ecosystems and health but significant uncertainties still surround quantification of these effects. Arctic air pollution includes harmful trace gases (e.g. tropospheric ozone) and particles (e.g. black carbon, sulphate) and toxic substances (e.g. polycyclic aromatic hydrocarbons) that can be transported to the Arctic from emission sources located far outside the region, or emitted within the Arctic from activities including shipping, power production, and other industrial activities. This paper qualitatively summarizes the complex science issues motivating the creation of a new international initiative, PACES (air Pollution in the Arctic: Climate, Environment and Societies). Approaches for coordinated, international and interdisciplinary research on this topic are described with the goal to improve predictive capability via new understanding about sources, processes, feedbacks and impacts of Arctic air pollution. Overarching research actions are outlined, in which we describe our recommendations for 1) the development of trans-disciplinary approaches combining social and economic research with investigation of the chemical and physical aspects of Arctic air pollution; 2) increasing the quality and quantity of observations in the Arctic using long-term monitoring and intensive field studies, both at the surface and throughout the troposphere; and 3) developing improved predictive capability across a range of spatial and temporal scales

Retrospective model-based inference guides model-free credit assignment

An extensive reinforcement learning literature shows that organisms assign credit efficiently, even under conditions of state uncertainty. However, little is known about credit-assignment when state uncertainty is subsequently resolved. Here, we address this problem within the framework of an interaction between model-free (MF) and model-based (MB) control systems. We present and support experimentally a theory of MB retrospective-inference. Within this framework, a MB system resolves uncertainty that prevailed when actions were taken thus guiding an MF credit-assignment. Using a task in which there was initial uncertainty about the lotteries that were chosen, we found that when participants’ momentary uncertainty about which lottery had generated an outcome was resolved by provision of subsequent information, participants preferentially assigned credit within a MF system to the lottery they retrospectively inferred was responsible for this outcome. These findings extend our knowledge about the range of MB functions and the scope of system interactions

State of the Science: Salivary Biomarker Utilization for Stress Research

The use of salivary biomarkers for stress research is increasing based on the convenience of collection, affordability and scientific merit. This short review provides an overview of the state of the science of salivary biomarkers utilized in research related to stress. Methods: An integrative review was conducted. Results: The trend of utilizing salivary biomarkers in stress research was reviewed, specifically, focusing on the use of endocrine and inflammatory biomarkers incorporated in previous stress research. Then, a review of sampling procedures for salivary biomarkers and the analytic methods is provided. Finally, a discussion on the strengths and areas for improvement in the use of salivary biomarkers in stress research is included. Conclusion: Salivary biomarkers as an alternative to blood biomarkers are increasingly being recognized as a legitimate source for analyzing the stress response in humans

Seasonality of aerosol optical properties in the Arctic

Given the sensitivity of the Arctic climate to short-lived climate forcers, long-term in situ surface measurements of aerosol parameters are useful in gaining insight into the magnitude and variability of these climate forcings. Seasonality of aerosol optical properties – including the aerosol light-scattering coefficient, absorption coefficient, single-scattering albedo, scattering Ångström exponent, and asymmetry parameter – are presented for six monitoring sites throughout the Arctic: Alert, Canada; Barrow, USA; Pallas, Finland; Summit, Greenland; Tiksi, Russia; and Zeppelin Mountain, Ny-Ålesund, Svalbard, Norway. Results show annual variability in all parameters, though the seasonality of each aerosol optical property varies from site to site. There is a large diversity in magnitude and variability of scattering coefficient at all sites, reflecting differences in aerosol source, transport, and removal at different locations throughout the Arctic. Of the Arctic sites, the highest annual mean scattering coefficient is measured at Tiksi (12.47&thinsp;Mm−1), and the lowest annual mean scattering coefficient is measured at Summit (1.74&thinsp;Mm−1). At most sites, aerosol absorption peaks in the winter and spring, and has a minimum throughout the Arctic in the summer, indicative of the Arctic haze phenomenon; however, nuanced variations in seasonalities suggest that this phenomenon is not identically observed in all regions of the Arctic. The highest annual mean absorption coefficient is measured at Pallas (0.48&thinsp;Mm−1), and Summit has the lowest annual mean absorption coefficient (0.12&thinsp;Mm−1). At the Arctic monitoring stations analyzed here, mean annual single-scattering albedo ranges from 0.909 (at Pallas) to 0.960 (at Barrow), the mean annual scattering Ångström exponent ranges from 1.04 (at Barrow) to 1.80 (at Summit), and the mean asymmetry parameter ranges from 0.57 (at Alert) to 0.75 (at Summit). Systematic variability of aerosol optical properties in the Arctic supports the notion that the sites presented here measure a variety of aerosol populations, which also experience different removal mechanisms. A robust conclusion from the seasonal cycles presented is that the Arctic cannot be treated as one common and uniform environment but rather is a region with ample spatiotemporal variability in aerosols. This notion is important in considering the design or aerosol monitoring networks in the region and is important for informing climate models to better represent short-lived aerosol climate forcers in order to yield more accurate climate predictions for the Arctic.</p

Identifying component modules

A computer-based system for modelling component dependencies and identifying component modules is presented. A variation of the Dependency Structure Matrix (DSM) representation was used to model component dependencies. The system utilises a two-stage approach towards facilitating the identification of a hierarchical modular structure. The first stage calculates a value for a clustering criterion that may be used to group component dependencies together. A Genetic Algorithm is described to optimise the order of the components within the DSM with the focus of minimising the value of the clustering criterion to identify the most significant component groupings (modules) within the product structure. The second stage utilises a 'Module Strength Indicator' (MSI) function to determine a value representative of the degree of modularity of the component groupings. The application of this function to the DSM produces a 'Module Structure Matrix' (MSM) depicting the relative modularity of available component groupings within it. The approach enabled the identification of hierarchical modularity in the product structure without the requirement for any additional domain specific knowledge within the system. The system supports design by providing mechanisms to explicitly represent and utilise component and dependency knowledge to facilitate the nontrivial task of determining near-optimal component modules and representing product modularity

Real-time measurements in optical metrology

Methods as well as recording materials for real-time measurements were discussed. Electrooptical crystals can be used for nearly realtime contactless measuring techniques. The BSO was found appropriate for real-time holographic interferometry, contour line display and for deformation, displacement and vibration analysis. Furthermore, for real-time speckle photography the BSO was found to be very useful. For noise and vibration analysis of oscillating objects such as rotating car tyres, gearing boxes, turbines blades, a vibrometer based on Doppler shift measuring principles was found to be useful, leading to an amplitude and frequency analysis. For the analyse of rotating objects an image derotator is frequently used for compensation of the rotation. In optical metrology real-time methods will be useful for the engineer in future

Effects Of Length, Complexity, And Grammatical Correctness On Stuttering In Spanish-Speaking Preschool Children

Purpose: To explore the effects of utterance length, syntactic complexity, and grammatical correctness on stuttering in the spontaneous speech of young, monolingual Spanish-speaking children. Method: Spontaneous speech samples of 11 monolingual Spanish-speaking children who stuttered, ages 35 to 70 months, were examined. Mean number of syllables, total number of clauses, utterance complexity (i.e., containing no clauses, simple clauses, or subordinate and/or conjoined clauses), and grammatical correctness (i.e., the presence or absence of morphological and syntactical errors) in stuttered and fluent utterances were compared. Results: Findings revealed that stuttered utterances in Spanish tended to be longer and more often grammatically incorrect, and contain more clauses, including more subordinate and/or conjoined clauses. However, when controlling for the interrelatedness of syllable number and clause number and complexity, only utterance length and grammatical incorrectness were significant predictors of stuttering in the spontaneous speech of these Spanish-speaking children. Use of complex utterances did not appear to contribute to the prediction of stuttering when controlling for utterance length. Conclusions: Results from the present study were consistent with many earlier reports of English-speaking children. Both length and grammatical factors appear to affect stuttering in Spanish-speaking children. Grammatical errors, however, served as the greatest predictor of stuttering.Communication Sciences and Disorder