Sequential Effects in Judgements of Attractiveness: The Influences of Face Race and Sex

In perceptual decision-making, a person’s response on a given trial is influenced by their response on the immediately preceding trial. This sequential effect was initially demonstrated in psychophysical tasks, but has now been found in more complex, real-world judgements. The similarity of the current and previous stimuli determines the nature of the effect, with more similar items producing assimilation in judgements, while less similarity can cause a contrast effect. Previous research found assimilation in ratings of facial attractiveness, and here, we investigated whether this effect is influenced by the social categories of the faces presented. Over three experiments, participants rated the attractiveness of own- (White) and other-race (Chinese) faces of both sexes that appeared successively. Through blocking trials by race (Experiment 1), sex (Experiment 2), or both dimensions (Experiment 3), we could examine how sequential judgements were altered by the salience of different social categories in face sequences. For sequences that varied in sex alone, own-race faces showed significantly less opposite-sex assimilation (male and female faces perceived as dissimilar), while other-race faces showed equal assimilation for opposite- and same-sex sequences (male and female faces were not differentiated). For sequences that varied in race alone, categorisation by race resulted in no opposite-race assimilation for either sex of face (White and Chinese faces perceived as dissimilar). For sequences that varied in both race and sex, same-category assimilation was significantly greater than opposite-category. Our results suggest that the race of a face represents a superordinate category relative to sex. These findings demonstrate the importance of social categories when considering sequential judgements of faces, and also highlight a novel approach for investigating how multiple social dimensions interact during decision-making

Moisture transport by Atlantic tropical cyclones onto the North American continent

Tropical Cyclones (TCs) are an important source of freshwater for the North American continent. Many studies have tried to estimate this contribution by identifying TC-induced precipitation events, but few have explicitly diagnosed the moisture fluxes across continental boundaries. We design a set of attribution schemes to isolate the column-integrated moisture fluxes that are directly associated with TCs and to quantify the flux onto the North American Continent due to TCs. Averaged over the 2004–2012 hurricane seasons and integrated over the western, southern and eastern coasts of North America, the seven schemes attribute 7 to 18 % (mean 14 %) of total net onshore flux to Atlantic TCs. A reduced contribution of 10 % (range 9 to 11 %) was found for the 1980–2003 period, though only two schemes could be applied to this earlier period. Over the whole 1980–2012 period, a further 8 % (range 6 to 9 % from two schemes) was attributed to East Pacific TCs, resulting in a total TC contribution of 19 % (range 17 to 22 %) to the ocean-to-land moisture transport onto the North American continent between May and November. Analysis of the attribution uncertainties suggests that incorporating details of individual TC size and shape adds limited value to a fixed radius approach and TC positional errors in the ERA-Interim reanalysis do not affect the results significantly, but biases in peak wind speeds and TC sizes may lead to underestimates of moisture transport. The interannual variability does not appear to be strongly related to the El Nino-Southern Oscillation phenomenon

Dusty star forming galaxies at high redshift

The global star formation rate in high redshift galaxies, based on optical surveys, shows a strong peak at a redshift of z=1.5, which implies that we have already seen most of the formation. High redshift galaxies may, however, emit most of their energy at submillimeter wavelengths if they contain substantial amounts of dust. The dust would absorb the starlight and reradiate it as far-infrared light, which would be redshifted to the submillimeter range. Here we report a deep survey of two blank regions of sky performed at submillimeter wavelengths (450 and 850-micron). If the sources we detect in the 850-micron band are powered by star formation, then each must be converting more than 100 solar masses of gas per year into stars, which is larger than the maximum star formation rates inferred for most optically-selected galaxies. The total amount of high redshift star formation is essentially fixed by the level of background light, but where the peak occurs in redshift for the submillimeter is not yet established. However, the background light contribution from only the sources detected at 850-micron is already comparable to that from the optically-selected sources. Establishing the main epoch of star formation will therefore require a combination of optical and submillimeter studies.Comment: 10 pages + 2 Postscript figures, under embargo at Natur

Imputation strategies for missing binary outcomes in cluster randomized trials

<p>Abstract</p> <p>Background</p> <p>Attrition, which leads to missing data, is a common problem in cluster randomized trials (CRTs), where groups of patients rather than individuals are randomized. Standard multiple imputation (MI) strategies may not be appropriate to impute missing data from CRTs since they assume independent data. In this paper, under the assumption of missing completely at random and covariate dependent missing, we compared six MI strategies which account for the intra-cluster correlation for missing binary outcomes in CRTs with the standard imputation strategies and complete case analysis approach using a simulation study.</p> <p>Method</p> <p>We considered three within-cluster and three across-cluster MI strategies for missing binary outcomes in CRTs. The three within-cluster MI strategies are logistic regression method, propensity score method, and Markov chain Monte Carlo (MCMC) method, which apply standard MI strategies within each cluster. The three across-cluster MI strategies are propensity score method, random-effects (RE) logistic regression approach, and logistic regression with cluster as a fixed effect. Based on the community hypertension assessment trial (CHAT) which has complete data, we designed a simulation study to investigate the performance of above MI strategies.</p> <p>Results</p> <p>The estimated treatment effect and its 95% confidence interval (CI) from generalized estimating equations (GEE) model based on the CHAT complete dataset are 1.14 (0.76 1.70). When 30% of binary outcome are missing completely at random, a simulation study shows that the estimated treatment effects and the corresponding 95% CIs from GEE model are 1.15 (0.76 1.75) if complete case analysis is used, 1.12 (0.72 1.73) if within-cluster MCMC method is used, 1.21 (0.80 1.81) if across-cluster RE logistic regression is used, and 1.16 (0.82 1.64) if standard logistic regression which does not account for clustering is used.</p> <p>Conclusion</p> <p>When the percentage of missing data is low or intra-cluster correlation coefficient is small, different approaches for handling missing binary outcome data generate quite similar results. When the percentage of missing data is large, standard MI strategies, which do not take into account the intra-cluster correlation, underestimate the variance of the treatment effect. Within-cluster and across-cluster MI strategies (except for random-effects logistic regression MI strategy), which take the intra-cluster correlation into account, seem to be more appropriate to handle the missing outcome from CRTs. Under the same imputation strategy and percentage of missingness, the estimates of the treatment effect from GEE and RE logistic regression models are similar.</p

Accelerating Discovery for Complex Neurological and Behavioral Disorders Through Systems Genetics and Integrative Genomics in the Laboratory Mouse

Recent advances in systems genetics and integrative functional genomics have greatly improved the study of complex neurological and behavioral traits. The methods developed for the integrated characterization of new, high-resolution mouse genetic reference populations and systems genetics enable behavioral geneticists an unprecedented opportunity to address questions of the molecular basis of neurological and psychiatric disorders and their comorbidities. Integrative genomics augment these strategies by enabling rapid informatics-assisted candidate gene prioritization, cross-species translation, and mechanistic comparison across related disorders from a wealth of existing data in mouse and other model organisms. Ultimately, through these complementary approaches, finding the mechanisms and sources of genetic variation underlying complex neurobehavioral disease related traits is becoming tractable. Furthermore, these methods enable categorization of neurobehavioral disorders through their underlying biological basis. Together, these model organism-based approaches can lead to a refinement of diagnostic categories and targeted treatment of neurological and psychiatric disease

Mini-laparoscopic versus laparoscopic approach to appendectomy

BACKGROUND: The purpose of this clinical study is to evaluate the feasibility of using 2-mm laparoscopic instruments to perform an appendectomy in patients with clinically suspected acute appendicitis and compare the outcome of this mini-laparoscopic or "needlescopic" approach to the conventional laparoscopic appendectomy. METHODS: Two groups of patients undergoing appendectomy over 24 months were studied. In the first group, needlescopic appendectomy was performed in 15 patients by surgeons specializing in advanced laparoscopy. These patients were compared with the second or control group that included 21 consecutive patients who underwent laparoscopic appendectomy. We compared the patients' demographic data, operative findings, complications, postoperative pain medicine requirements, length of hospital stay, and recovery variables. Differences were considered statistically significant at a p-value < 0.05. RESULTS: Patient demographics, history of previous abdominal surgery, and operative findings were similar in both groups. There was no conversion to open appendectomy in either group. No postoperative morbidity or mortality occurred in either group. The needlescopic group had a significantly shorter mean operative time (p = 0.02), reduced postoperative narcotics requirements (p = 0.05), shorter hospital stay (p = 0.04), and quicker return to work (p = 0.03) when compared with the laparoscopic group. CONCLUSIONS: We conclude that the needlescopic technique is a safe and effective approach to appendectomy. When performed by experienced laparoscopic surgeons, the needlescopic technique results in significantly shorter postoperative convalescence and a prompt recovery

Dismissive and deceptive car dealerships create barriers to electric vehicle adoption at the point of sale

This study investigates the role of car dealerships in the electrification of passenger transport, namely their sales advice about the purchase and use of electric vehicles (EVs). Because most consumers do not have pre-existing knowledge of EVs, and current market conditions favour petrol and diesel vehicles, car dealership experiences may strongly influence EV purchasing decisions. Here we show that car dealerships pose a significant barrier at the point of sale due to a perceived lack of business case viability in relation to petrol and diesel vehicles. In 126 shopping experiences at 82 car dealerships across Denmark, Finland, Iceland, Norway, and Sweden, we find dealers were dismissive of EVs, misinformed shoppers on vehicle specifications, omitted EVs from the sales conversation and strongly oriented customers towards petrol and diesel vehicle options. Dealer’s technological orientation, willingness to sell, and displayed knowledge of EVs were the main contributors to likely purchase intentions. These findings combined with expert interviews suggest that government and industry signalling affect sales strategies and purchasing trends. Policy and business strategies that address barriers at the point of sale are needed to accelerate EV adoption

Impact of progressive global warming on the global-scale yield of maize and soybean

Global surface temperature is projected to warm over the coming decades, with regional differences expected in temperature change, rainfall and the frequency of extreme events. Temperature is a major determinant of crop growth and development, affecting planting date, growing season length and yield. We investigated the effects of increments of mean global temperature warming from 0.5 °C to 4 °C on soybean and maize development and yield, both globally and for the main producing countries, and simulated adaptation through changing planting date and variety. Increasing temperature resulted in reduced growing season lengths and ultimately reduced yields for both crops. The global yield for maize decreased as temperature increased, although the severity of the decrease was dependent on geographic region. Small temperature increases of 0.5 °C had no effect on soybean yield, although yield decreased as temperature increased. These negative effects, however, were partly compensated for by the implementation of adaptation strategies including planting earlier in the season and changing variety. The degree of compensation was dependent on geographical area and crop, with maize adaptation delaying the negative effects of temperature on yield, compared to soybean adaptation which increased yield in China, India and Korea DPR as well as delaying the effects in the remaining countries. The results of this paper indicate the degree to which farmer-controlled adaptation strategies can alleviate the negative impacts of increasing temperature on two major crop species

Different atmospheric moisture divergence responses to extreme and moderate El Niños

On seasonal and inter-annual time scales, vertically integrated moisture divergence provides a useful measure of the tropical atmospheric hydrological cycle. It reflects the combined dynamical and thermodynamical effects, and is not subject to the limitations that afflict observations of evaporation minus precipitation. An empirical orthogonal function (EOF) analysis of the tropical Pacific moisture divergence fields calculated from the ERA-Interim reanalysis reveals the dominant effects of the El Niño-Southern Oscillation (ENSO) on inter-annual time scales. Two EOFs are necessary to capture the ENSO signature, and regression relationships between their Principal Components and indices of equatorial Pacific sea surface temperature (SST) demonstrate that the transition from strong La Niña through to extreme El Niño events is not a linear one. The largest deviation from linearity is for the strongest El Niños, and we interpret that this arises at least partly because the EOF analysis cannot easily separate different patterns of responses that are not orthogonal to each other. To overcome the orthogonality constraints, a self-organizing map (SOM) analysis of the same moisture divergence fields was performed. The SOM analysis captures the range of responses to ENSO, including the distinction between the moderate and strong El Niños identified by the EOF analysis. The work demonstrates the potential for the application of SOM to large scale climatic analysis, by virtue of its easier interpretation, relaxation of orthogonality constraints and its versatility for serving as an alternative classification method. Both the EOF and SOM analyses suggest a classification of “moderate” and “extreme” El Niños by their differences in the magnitudes of the hydrological cycle responses, spatial patterns and evolutionary paths. Classification from the moisture divergence point of view shows consistency with results based on other physical variables such as SST