There's no contest: Human sex differences are sexually selected

The official published version can be accessed from the link below - Copyright © Cambridge University Press 2009An evolutionary psychological perspective drawing on sexual selection theory can better explain sex differences in aggression and violence than can social constructionist theories. Moreover, there is accumulating evidence that, in accordance with predictions derived from sexual selection theory, men modulate their willingness to engage in risky and violent confrontations in response to cues to fitness variance and future prospects

Predicting Alcohol Concentration during Beer Fermentation Using Ultrasonic Measurements and Machine Learning

Beer fermentation is typically monitored by periodic sampling and off-line analysis. In-line sensors would remove the need for time-consuming manual operation and provide real-time evaluation of the fermenting media. This work uses a low-cost ultrasonic sensor combined with machine learning to predict the alcohol concentration during beer fermentation. The highest ac-curacy model (R2=0.952, MAE=0.265, MSE=0.136) used a transmission-based ultrasonic sensing technique along with the measured temperature. However, the second most accurate model (R2=0.948, MAE=0.283, MSE=0.146) used a reflection-based technique without the temperature. Both the reflection-based technique and the omission of the temperature data are novel to this research and demonstrate the potential for a non-invasive sensor to monitor beer fermentation

Domain Adaptation and Federated Learning for Ultrasonic Monitoring of Beer Fermentation

Beer fermentation processes are traditionally monitored through sampling and off-line wort density measurements. In-line and on-line sensors would provide real-time data on the fermentation progress whilst minimising human involvement, enabling identification of lagging fermentations or prediction of ethanol production end points. Ultrasonic sensors have previously been used for in-line and on-line fermentation monitoring and are increasingly being combined with machine learning models to interpret the sensor measurements. However, fermentation processes typically last many days and so impose a significant time investment to collect data from a sufficient number of batches for machine learning model training. This expenditure of effort must be multiplied if different fermentation processes must be monitored, such as varying formulations in craft breweries. In this work, three methodologies are evaluated to use previously collected ultrasonic sensor data from laboratory scale fermentations to improve machine learning model accuracy on an industrial scale fermentation process. These methodologies include training models on both domains simultaneously, training models in a federated learning strategy to preserve data privacy, and fine-tuning the best performing models on the industrial scale data. All methodologies provided increased prediction accuracy compared with training based solely on the industrial fermentation data. The federated learning methodology performed best, achieving higher accuracy for 14 out of 16 machine learning tasks compared with the base case model

A review of ultrasonic sensing and machine learning methods to monitor industrial processes

Supervised machine learning techniques are increasingly being combined with ultrasonic sensor measurements owing to their strong performance. These techniques also offer advantages over calibration procedures of more complex fitting, improved generalisation, reduced development time, ability for continuous retraining, and the correlation of sensor data to important process information. However, their implementation requires expertise to extract and select appropriate features from the sensor measurements as model inputs, select the type of machine learning algorithm to use, and find a suitable set of model hyperparameters. The aim of this article is to facilitate implementation of machine learning techniques in combination with ultrasonic measurements for in-line and on-line monitoring of industrial processes and other similar applications. The article first reviews the use of ultrasonic sensors for monitoring processes, before reviewing the combination of ultrasonic measurements and machine learning. We include literature from other sectors such as structural health monitoring. This review covers feature extraction, feature selection, algorithm choice, hyperparameter selection, data augmentation, domain adaptation, semi-supervised learning and machine learning interpretability. Finally, recommendations for applying machine learning to the reviewed processes are made

Cross-cultural effects of color, but not morphological masculinity, on perceived attractiveness of men's faces

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2012 ElsevierMuch attractiveness research has focused on face shape. The role of masculinity (which for adults is thought to be a relatively stable shape cue to developmental testosterone levels) in male facial attractiveness has been examined, with mixed results. Recent work on the perception of skin color (a more variable cue to current health status) indicates that increased skin redness, yellowness, and lightness enhance apparent health. It has been suggested that stable cues such as masculinity may be less important to attractiveness judgments than short-term, more variable health cues. We examined associations between male facial attractiveness, masculinity, and skin color in African and Caucasian populations. Masculinity was not found to be associated with attractiveness in either ethnic group. However, skin color was found to be an important predictor of attractiveness judgments, particularly for own-ethnicity faces. Our results suggest that more plastic health cues, such as skin color, are more important than developmental cues such as masculinity. Further, unfamiliarity with natural skin color variation in other ethnic groups may limit observers' ability to utilize these color cues

TADPOL: A 1.3 mm Survey of Dust Polarization in Star-forming Cores and Regions

We present {\lambda}1.3 mm CARMA observations of dust polarization toward 30 star-forming cores and 8 star-forming regions from the TADPOL survey. We show maps of all sources, and compare the ~2.5" resolution TADPOL maps with ~20" resolution polarization maps from single-dish submillimeter telescopes. Here we do not attempt to interpret the detailed B-field morphology of each object. Rather, we use average B-field orientations to derive conclusions in a statistical sense from the ensemble of sources, bearing in mind that these average orientations can be quite uncertain. We discuss three main findings: (1) A subset of the sources have consistent magnetic field (B-field) orientations between large (~20") and small (~2.5") scales. Those same sources also tend to have higher fractional polarizations than the sources with inconsistent large-to-small-scale fields. We interpret this to mean that in at least some cases B-fields play a role in regulating the infall of material all the way down to the ~1000 AU scales of protostellar envelopes. (2) Outflows appear to be randomly aligned with B-fields; although, in sources with low polarization fractions there is a hint that outflows are preferentially perpendicular to small-scale B-fields, which suggests that in these sources the fields have been wrapped up by envelope rotation. (3) Finally, even at ~2.5" resolution we see the so-called "polarization hole" effect, where the fractional polarization drops significantly near the total intensity peak. All data are publicly available in the electronic edition of this article.Comment: 53 pages, 37 figures -- main body (13 pp., 3 figures), source maps (32 pp., 34 figures), source descriptions (8 pp.). Accepted by the Astrophysical Journal Supplemen

Molecular Gas in the z=1.2 Ultraluminous Merger GOODS J123634.53+621241.3

We report the detection of CO(2-1) emission from the z=1.2 ultraluminous infrared galaxy (ULIRG) GOODS J123634.53+621241.3 (also known as the sub-millimeter galaxy GN26). These observations represent the first discovery of high-redshift CO emission using the new Combined Array for Research in Millimeter-Wave Astronomy (CARMA). Of all high-redshift (z>1) galaxies within the GOODS-North field, this source has the largest far-infrared (FIR) flux observed in the Spitzer 70um and 160um bands. The CO redshift confirms the optical identification of the source, and the bright CO(2-1) line suggests the presence of a large molecular gas reservoir of about 7x10^10 M(sun). The infrared-to-CO luminosity ratio of L(IR)/L'(CO) = 80+/-30 L(sun) (K Km/s pc^2)^-1 is slightly smaller than the average ratio found in local ULIRGs and high-redshift sub-millimeter galaxies. The short star-formation time scale of about 70 Myr is consistent with a starburst associated with the merger event and is much shorter than the time scales for spiral galaxies and estimates made for high-redshift galaxies selected on the basis of their B-z and z-K colors.Comment: Accepted for publication in ApJ Letter

Female economic dependence and the morality of promiscuity

This article is made available through the Brunel Open Access Publishing Fund. Copyright @ The Author(s) 2014.In environments in which female economic dependence on a male mate is higher, male parental investment is more essential. In such environments, therefore, both sexes should value paternity certainty more and thus object more to promiscuity (because promiscuity undermines paternity certainty). We tested this theory of anti-promiscuity morality in two studies (N = 656 and N = 4,626) using U.S. samples. In both, we examined whether opposition to promiscuity was higher among people who perceived greater female economic dependence in their social network. In Study 2, we also tested whether economic indicators of female economic dependence (e.g., female income, welfare availability) predicted anti-promiscuity morality at the state level. Results from both studies supported the proposed theory. At the individual level, perceived female economic dependence explained significant variance in anti-promiscuity morality, even after controlling for variance explained by age, sex, religiosity, political conservatism, and the anti-promiscuity views of geographical neighbors. At the state level, median female income was strongly negatively related to anti-promiscuity morality and this relationship was fully mediated by perceived female economic dependence. These results were consistent with the view that anti-promiscuity beliefs may function to promote paternity certainty in circumstances where male parental investment is particularly important

Menstrual cycle phase does not predict political conservatism

Recent authors have reported a relationship between women's fertility status, as indexed by menstrual cycle phase, and conservatism in moral, social and political values. We conducted a survey to test for the existence of a relationship between menstrual cycle day and conservatism. 2213 women reporting regular menstrual cycles provided data about their political views. Of these women, 2208 provided information about their cycle date, 1260 provided additional evidence of reliability in self-reported cycle date, and of these, 750 also indicated an absence of hormonal disruptors such as recent hormonal contraception use, breastfeeding or pregnancy. Cycle day was used to estimate day-specific fertility rate (probability of conception); political conservatism was measured via direct self-report and via responses to the "Moral Foundations” questionnaire. We also recorded relationship status, which has been reported to interact with menstrual cycle phase in determining political preferences. We found no evidence of a relationship between estimated cyclical fertility changes and conservatism, and no evidence of an interaction between relationship status and cyclical fertility in determining political attitudes. Our findings were robust to multiple inclusion/exclusion criteria and to different methods of estimating fertility and measuring conservatism. In summary, the relationship between cycle-linked reproductive parameters and conservatism may be weaker or less reliable than previously thought

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy