Are women better than men at multi-tasking?

Background: There seems to be a common belief that women are better in multi-tasking than men, but there is practically no scientific research on this topic. Here, we tested whether women have better multi-tasking skills than men.<p></p> Methods: In Experiment 1, we compared performance of 120 women and 120 men in a computer-based task-switching paradigm. In Experiment 2, we compared a different group of 47 women and 47 men on "paper-and-pencil" multi-tasking tests.<p></p> Results: In Experiment 1, both men and women performed more slowly when two tasks were rapidly interleaved than when the two tasks were performed separately. Importantly, this slow down was significantly larger in the male participants (Cohen’s d = 0.27). In an everyday multi-tasking scenario (Experiment 2), men and women did not differ significantly at solving simple arithmetic problems, searching for restaurants on a map, or answering general knowledge questions on the phone, but women were significantly better at devising strategies for locating a lost key (Cohen’s d = 0.49).<p></p> Conclusions: Women outperform men in these multi-tasking paradigms, but the near lack of empirical studies on gender differences in multitasking should caution against making strong generalisations. Instead, we hope that other researchers will aim to replicate and elaborate on our findings.<p></p&gt

Attentional biases for food stimuli in external eaters: Possible mechanism for stress-induced eating?

External eaters reportedly increase snack intake when stressed, which could be due to an attentional shift towards food stimuli. Attentional biases for food stimuli were tested in high and low external eaters in stress and control conditions, using a computerised Stroop. A significant interaction was observed between external eating group and condition for snack word bias. This suggested that low external eaters have a greater bias for snack words when unstressed and that stressed, high external eaters have a greater bias for snack words than stressed, low external eaters, which could contribute to stress-induced snack intake in high external eaters

Prediction of 24-hour milk yield and composition in dairy cows from a single part-day yield and sample

peer-reviewedTeagasc PublicationIrish Journal of Agricultural and Food Research | Volume 58: Issue 1 Prediction of 24-hour milk yield and composition in dairy cows from a single part-day yield and sample S. McParlandemail , B. Coughlan , B. Enright , M. O’Keeffe , R. O’Connor , L. Feeney and D.P. Berry DOI: https://doi.org/10.2478/ijafr-2019-0007 | Published online: 09 Aug 2019 PDF Abstract Article PDF References Recommendations Abstract The objective was to evaluate the accuracy of predicting 24-hour milk yield and composition from a single morning (AM) or evening (PM) milk weight and composition. A calibration dataset of 37,481 test-day records with both AM and PM yields and composition was used to generate the prediction equations; equations were validated using 4,644 test-day records. Prediction models were developed within stage of lactation and parity while accounting for the inter-milking time interval. The mean correlation between the predicted 24-hour yields and composition of milk, fat and protein and the respective actual values was 0.97 when based on just an AM milk yield and composition with a mean correlation of 0.95 when based on just a PM milk yield and composition. The regression of predicted 24-hour yield and composition on the respective actual values varied from 0.97 to 1.01 with the exception of 24-hour fat percentage predicted from a PM sample (1.06). A single AM sample is useful to predict 24-hour milk yield and composition when the milking interval is known

New Tests to Measure Individual Differences in Matching and Labelling Facial Expressions of Emotion, and Their Association with Ability to Recognise Vocal Emotions and Facial Identity

Although good tests are available for diagnosing clinical impairments in face expression processing, there is a lack of strong tests for assessing "individual differences"--that is, differences in ability between individuals within the typical, nonclinical, range. Here, we develop two new tests, one for expression perception (an odd-man-out matching task in which participants select which one of three faces displays a different expression) and one additionally requiring explicit identification of the emotion (a labelling task in which participants select one of six verbal labels). We demonstrate validity (careful check of individual items, large inversion effects, independence from nonverbal IQ, convergent validity with a previous labelling task), reliability (Cronbach's alphas of.77 and.76 respectively), and wide individual differences across the typical population. We then demonstrate the usefulness of the tests by addressing theoretical questions regarding the structure of face processing, specifically the extent to which the following processes are common or distinct: (a) perceptual matching and explicit labelling of expression (modest correlation between matching and labelling supported partial independence); (b) judgement of expressions from faces and voices (results argued labelling tasks tap into a multi-modal system, while matching tasks tap distinct perceptual processes); and (c) expression and identity processing (results argued for a common first step of perceptual processing for expression and identity).This research was supported by the Australian Research Council (http://www.arc.gov.au/) grant DP110100850 to RP and EM and the Australian Research Council Centre of Excellence for Cognition and its Disorders (CE110001021) http://www.ccd.edu.au. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Degradation and breakdown characteristics of thin MgO dielectric layers

MgO has been suggested as a possible high-k dielectric for future complementary metal-oxide semiconductor processes. In this work, the time dependent dielectric breakdown (TDDB) characteristics of 20 nm MgO films are discussed. Stress induced leakage current measurements indicate that the low measured Weibull slopes of the TDDB distributions for both n-type and p-type devices cannot be attributed to a lower trap generation rate than for SiO2. This suggests that much fewer defects are required to trigger breakdown in MgO under voltage stress than is the case for SiO2 or other metal-oxide dielectrics. This in turn explains the progressive nature of the breakdown in these films which is observed both in this work and elsewhere. The reason fewer defects are required is attributed to the morphology of the films

Energy-Aware Cloud Management through Progressive SLA Specification

Novel energy-aware cloud management methods dynamically reallocate computation across geographically distributed data centers to leverage regional electricity price and temperature differences. As a result, a managed VM may suffer occasional downtimes. Current cloud providers only offer high availability VMs, without enough flexibility to apply such energy-aware management. In this paper we show how to analyse past traces of dynamic cloud management actions based on electricity prices and temperatures to estimate VM availability and price values. We propose a novel SLA specification approach for offering VMs with different availability and price values guaranteed over multiple SLAs to enable flexible energy-aware cloud management. We determine the optimal number of such SLAs as well as their availability and price guaranteed values. We evaluate our approach in a user SLA selection simulation using Wikipedia and Grid'5000 workloads. The results show higher customer conversion and 39% average energy savings per VM.Comment: 14 pages, conferenc

A minimum thickness gate valve with integrated ion optics for mass spectrometry

A minimum thickness gate valve design for mass spectrometry is described in detail. The ion optics required to transmit ions from the source to the ICR cell are integrated into the design to minimize fringe field effects on the ions as they travel through the gate valve. The total thickness of the complete gate valve assembly is 1.03 in. (26.2 mm) with a maximum fringe field distance of 0.065 in. (1.7 mm). The gate valve is able to maintain a vacuum of <10−10 mbar at the ICR cell when the source is vented to atmosphere and the estimated ion transfer efficiency is >95%

Timing is Everything: PTTH Mediated DHR4 Nucleocytoplasmic Trafficking Sets the Tempo of Drosophila Steroid Production

During development, multicellular organisms must become sexually mature in order to reproduce. The developmental timing of this transition is controlled by pulses of steroid hormones, but how these pulses are generated have remained unclear? A recent paper shows that in Drosophila larvae, nucleocytoplasmic trafficking of DHR4, a nuclear receptor, in response to prothoracicotropic hormone signaling, is critical for producing the correct temporal pulses of steroid hormones that coordinate the juvenile–adult transition

Entanglement in a molecular three-qubit system

We study the entanglement properties of a molecular three-qubit system described by the Heisenberg spin Hamiltonian with anisotropic exchange interactions and including an external magnetic field. The system exhibits first order quantum phase transitions by tuning two parameters, $x$ and $y$, of the Hamiltonian to specific values. The three-qubit chain is open ended so that there are two types of pairwise entanglement : nearest-neighbour (n.n.) and next-nearest-neighbour (n.n.n.). We calculate the ground and thermal state concurrences, quantifying pairwise entanglement, as a function of the parameters $x$, $y$ and the temperature $T$. The entanglement threshold and gap temperatures are also determined as a function of the anisotropy parameter $x$. The results obtained are of relevance in understanding the entanglement features of the recently engineered molecular $Cr_{7}Ni$-$Cu^{2+}$-$Cr_{7}Ni$ complex which serves as a three-qubit system at sufficiently low temperatures.Comment: 9 pages, 13 figures, revtex

Predicting the U.S. Airline Operating Profitability using Machine Learning Algorithms

With the increasing competition and cost pressures, the U.S. airline industry has explored methods to reduce operating costs and diversify revenue sources for improving financial performance. Understanding the influence of operating revenues and expenses on airline profitability is imperative for the long term growth of the airlines and continued generation of profits. This study examined the cost and revenue data of the U.S. major airlines from the Department of Transportation’s Bureau of Transportation Statistics Form 41 reports between 2009 and 2018. Using SAS Enterprise Miner software, researchers used variables representing revenue and expenses from these data to develop and test predictive models for airline profit generation. Decision trees and linear regression methods were used for two identical datasets one with monetary values and the other with percentage values to identify the best predictor of airline profitability. From this study, decision tree models appeared to be better predictors of profitability for major airlines. Using the decision model, transport-related revenue and expenses which are incidentals to the air transportation services performed by airlines were found to be the two most influential factors in predicting the U. S. airlines’ profitability