Men fear other men most: Gender specific brain activations in perceiving threat from dynamic faces and bodies. An fMRI study.

We report a functional magnetic resonance imaging experiment showing different activation patterns as a function of threatening signals from facial or bodily expressions and these differed between male and female participants as a function of male and female actors. Male observers showed a clear motor preparation response to threatening male body language

Keynote speakers : wearables for good

The Digital Catapult Centre brings together the UK’s brightest digital ideas, by programming targeted events for innovators. We also encourage serendipitous opportunities for startups and entrepreneurs to meet likeminded people through our programme of coffee mornings, digital breakfasts and meet ups. The Wearable Health: The Market Gap, part of our Digital Health Festival, looks at the innovative ways UK small businesses are using wearables to tackle health challenges, as well as the opportunities this growth market presents. With even conservative estimates predicting the wearables market to explode to hundreds of millions of units by 2025, we will discuss what businesses need to do next and the consumer pressures and fears they are already facing. We expect 80-100 people to attend the conference, including talks from key industry voices, award winning wearable organisations and tech pioneers trying to capitalise on this rapidly expanding market. Dr David Swann and Julia Meaton's keynote presentation describes project WAAA!, a 2015 UNICEF Wearable for Good Challenge finalist that seeks to reduce newborn mortality in low-resource settings through a low-cost wearable and APGAR education

Threat Prompts Defensive Brain Responses Independently of Attentional Control

Negative emotional signals are known to influence task performance, but so far, investigations have focused on how emotion interacts with perceptual processes by mobilizing attentional resources. The attention-independent effects of negative emotional signals are less well understood. Here, we show that threat signals trigger defensive responses independently of what observers pay attention to. Participants were scanned using functional magnetic resonance imaging while watching short video clips of threatening actions and performed either color or emotion judgments. Seeing threatening actions interfered with performance in both tasks. Amygdala activation reflected both stimulus and task conditions. In contrast, threat stimuli prompted a constant activity in a network underlying reflexive defensive behavior (periaqueductal gray, hypothalamus, and premotor cortex). Threat stimuli also disrupted ongoing behavior and provoked motor conflict in prefrontal regions during both tasks. The present results are consistent with the view that emotions trigger adaptive action tendencies independently of task setting

ACCEPTED MANUSCRIPT Bias in Markov Models of Disease

Abstract We examine bias in Markov models of diseases, including both chronic and infectious diseases. We consider two common types of Markov disease models: ones where disease progression changes by severity of disease, and ones where progression of disease changes in time or by age. We find sufficient conditions for bias to exist in models with aggregated transition probabilities when compared to models with state/time dependent transition probabilities. We also find that when aggregating data to compute transition probabilities, bias increases with the degree of data aggregation. We illustrate by examining bias in Markov models of Hepatitis C, Alzheimer's disease, and lung cancer using medical data and find that the bias is significant depending on the method used to aggregate the data. A key implication is that by not incorporating state/time dependent transition probabilities, studies that use Markov models of diseases may be significantly overestimating or underestimating disease progression. This could potentially result in incorrect recommendations from cost-effectiveness studies and incorrect disease burden forecasts

Expert Opinions: Current Pricing and Revenue Management Practice Across U.S. Industries

On May 18, 2006, the second annual Revenue Management and Price Optimization conference was held at the Georgia Institute of Technology. The theme of the conference was on how the Internet is changing traditional revenue management and pricing practices. The conference brought together experts and thought leaders from more than 30 companies; spanning airlines, hotels, car rentals, cruise lines, apartment rentals, aircraft manufacturing, retailing, distribution, e-mail marketing, on-line travel, logistics, sports, performing arts, software providers, and others. This paper summarizes the key discussions from this conference and synthesizes experts’ perspectives on near-term opportunities and challenges facing their industries

Exploring stakeholders\u27 perceptions of the acceptability, usability, and dissemination of the australian 24-hour movement guidelines for the early years

Background: Australian 24-Hour Movement Guidelines for the Early Years were recently developed. To maximize the uptake of the guidelines, perceptions of key stakeholders were sought. Methods: Thirty-five stakeholders (11% Aboriginal or Torres Strait Islander descent) participated in focus groups or key informant interviews. Stakeholders included parents of children aged 0-5 years, early childhood educators, and health and policy professionals, recruited using convenience and snowballing techniques. Focus groups and interviews were audio-recorded and transcribed verbatim. Data were analyzed inductively using thematic analysis. Results: There was general acceptance of the Movement Guidelines. The stakeholders suggested that the Guidelines were highly aspirational and needed to be carefully messaged, so parents did not feel guilty if their child was not meeting them. Stakeholders identified that the messaging needed to be culturally appropriate and visually appealing. Dissemination strategies differed depending on the stakeholder. Conclusion: Seeking stakeholder perceptions is an important process in the development of national Movement Guidelines. This study successfully examined stakeholders\u27 perceptions regarding the acceptability, usability, and dissemination of the Australian 24-Hour Movement Guidelines. Effective and innovative strategies for maximizing compliance and uptake of the Guidelines should be prioritized

Association of Simulated COVID-19 Vaccination and Nonpharmaceutical Interventions With Infections, Hospitalizations, and Mortality

IMPORTANCE Vaccination against SARS-CoV-2 has the potential to significantly reduce transmission and COVID-19 morbidity and mortality. The relative importance of vaccination strategies and nonpharmaceutical interventions (NPIs) is not well understood. OBJECTIVE To assess the association of simulated COVID-19 vaccine efficacy and coverage scenarios with and without NPIs with infections, hospitalizations, and deaths. DESIGN, SETTING, AND PARTICIPANTS An established agent-based decision analytical model was used to simulate COVID-19 transmission and progression from March 24, 2020, to September 23, 2021. The model simulated COVID-19 spread in North Carolina, a US state of 10.5 million people. A network of 1 017 720 agents was constructed from US Census data to represent the statewide population. EXPOSURES Scenarios of vaccine efficacy (50% and 90%), vaccine coverage (25%, 50%, and 75% at the end of a 6-month distribution period), and NPIs (reduced mobility, school closings, and use of face masks) maintained and removed during vaccine distribution. MAIN OUTCOMES AND MEASURES Risks of infection from the start of vaccine distribution and risk differences comparing scenarios. Outcome means and SDs were calculated across replications. RESULTS In the worst-case vaccination scenario (50% efficacy, 25%coverage), a mean (SD) of 2 231 134 (117 867) new infections occurred after vaccination began with NPIs removed, and a mean (SD) of 799 949 (60 279) new infections occurred with NPIs maintained during 11 months. In contrast, in the best-case scenario (90% efficacy, 75%coverage), a mean (SD) of 527 409 (40 637) new infections occurred with NPIs removed and a mean (SD) of 450 575 (32 716) new infections occurred with NPIs maintained. With NPIs removed, lower efficacy (50%) and higher coverage (75%) reduced infection risk by a greater magnitude than higher efficacy (90%) and lower coverage (25%) compared with theworst-case scenario (mean [SD] absolute risk reduction, 13%[1%] and 8%[1%], respectively). CONCLUSIONS AND RELEVANCE Simulation outcomes suggest that removing NPIs while vaccines are distributed may result in substantial increases in infections, hospitalizations, and deaths. Furthermore, as NPIs are removed, higher vaccination coverage with less efficacious vaccines can contribute to a larger reduction in risk of SARS-CoV-2 infection compared with more efficacious vaccines at lower coverage. These findings highlight the need for well-resourced and coordinated efforts to achieve high vaccine coverage and continued adherence to NPIs before many prepandemic activities can be resumed

Use of Modeling to Inform Decision Making in North Carolina during the COVID-19 Pandemic: A Qualitative Study

Background. The COVID-19 pandemic has popularized computer-based decision-support models, which are commonly used to inform decision making amidst complexity. Understanding what organizational decision makers prefer from these models is needed to inform model development during this and future crises. Methods. We recruited and interviewed decision makers from North Carolina across 9 sectors to understand organizational decision-making processes during the first year of the COVID-19 pandemic (N = 44). For this study, we identified and analyzed a subset of responses from interviewees (n = 19) who reported using modeling to inform decision making. We used conventional content analysis to analyze themes from this convenience sample with respect to the source of models and their applications, the value of modeling and recommended applications, and hesitancies toward the use of models. Results. Models were used to compare trends in disease spread across localities, estimate the effects of social distancing policies, and allocate scarce resources, with some interviewees depending on multiple models. Decision makers desired more granular models, capable of projecting disease spread within subpopulations and estimating where local outbreaks could occur, and incorporating a broad set of outcomes, such as social well-being. Hesitancies to the use of modeling included doubts that models could reflect nuances of human behavior, concerns about the quality of data used in models, and the limited amount of modeling specific to the local context. Conclusions. Decision makers perceived modeling as valuable for informing organizational decisions yet described varied ability and willingness to use models for this purpose. These data present an opportunity to educate organizational decision makers on the merits of decision-support modeling and to inform modeling teams on how to build more responsive models that address the needs of organizational decision makers.HighlightsOrganizations from a diversity of sectors across North Carolina (including public health, education, business, government, religion, and public safety) have used decision-support modeling to inform decision making during COVID-19.Decision makers wish for models to project the spread of disease, especially at the local level (e.g., individual cities and counties), and to help estimate the outcomes of policies.Some organizational decision makers are hesitant to use modeling to inform their decisions, stemming from doubts that models could reflect nuances of human behavior, concerns about the accuracy and precision of data used in models, and the limited amount of modeling available at the local level

Risk Factors for Seizures Among Young Children Monitored With Continuous Electroencephalography in Intensive Care Unit: A Retrospective Study

Objective: cEEG is an emerging technology for which there are no clear guidelines for patient selection or length of monitoring. The purpose of this study was to identify subgroups of pediatric patients with high incidence of seizures.Study Design: We conducted a retrospective study on 517 children monitored by cEEG in the intensive care unit (ICU) of a children's hospital. The children were stratified using an age threshold selection method. Using regression modeling, we analyzed significant risk factors for increased seizure risk in younger and older children. Using two alternative correction procedures, we also considered a relevant comparison group to mitigate selection bias and to provide a perspective for our findings.Results: We discovered an approximate risk threshold of 14 months: below this threshold, the seizure risk increases dramatically. The older children had an overall seizure rate of 18%, and previous seizures were the only significant risk factor. In contrast, the younger children had an overall seizure rate of 45%, and the seizures were significantly associated with hypoxic-ischemic encephalopathy (HIE; p = 0.007), intracranial hemorrhage (ICH; p = 0.005), and central nervous system (CNS) infection (p = 0.02). Children with HIE, ICH, or CNS infection accounted for 61% of all seizure patients diagnosed through cEEG under 14 months.Conclusions: An extremely high incidence of seizures prevails among critically ill children under 14 months, particularly those with HIE, ICH, or CNS infection