PROTEUS two-dimensional Navier-Stokes computer code, version 1.0. Volume 2: User's guide

A new computer code was developed to solve the two-dimensional or axisymmetric, Reynolds averaged, unsteady compressible Navier-Stokes equations in strong conservation law form. The thin-layer or Euler equations may also be solved. Turbulence is modeled using an algebraic eddy viscosity model. The objective was to develop a code for aerospace applications that is easy to use and easy to modify. Code readability, modularity, and documentation were emphasized. The equations are written in nonorthogonal body-fitted coordinates, and solved by marching in time using a fully-coupled alternating direction-implicit procedure with generalized first- or second-order time differencing. All terms are linearized using second-order Taylor series. The boundary conditions are treated implicitly, and may be steady, unsteady, or spatially periodic. Simple Cartesian or polar grids may be generated internally by the program. More complex geometries require an externally generated computational coordinate system. The documentation is divided into three volumes. Volume 2 is the User's Guide, and describes the program's general features, the input and output, the procedure for setting up initial conditions, the computer resource requirements, the diagnostic messages that may be generated, the job control language used to run the program, and several test cases

PROTEUS two-dimensional Navier-Stokes computer code, version 1.0. Volume 1: Analysis description

A new computer code was developed to solve the two-dimensional or axisymmetric, Reynolds averaged, unsteady compressible Navier-Stokes equations in strong conservation law form. The thin-layer or Euler equations may also be solved. Turbulence is modeled using an algebraic eddy viscosity model. The objective was to develop a code for aerospace applications that is easy to use and easy to modify. Code readability, modularity, and documentation were emphasized. The equations are written in nonorthogonal body-fitted coordinates, and solved by marching in time using a fully-coupled alternating direction-implicit procedure with generalized first- or second-order time differencing. All terms are linearized using second-order Taylor series. The boundary conditions are treated implicitly, and may be steady, unsteady, or spatially periodic. Simple Cartesian or polar grids may be generated internally by the program. More complex geometries require an externally generated computational coordinate system. The documentation is divided into three volumes. Volume 1 is the Analysis Description, and describes in detail the governing equations, the turbulence model, the linearization of the equations and boundary conditions, the time and space differencing formulas, the ADI solution procedure, and the artificial viscosity models

PROTEUS two-dimensional Navier-Stokes computer code, version 1.0. Volume 3: Programmer's reference

A new computer code was developed to solve the 2-D or axisymmetric, Reynolds-averaged, unsteady compressible Navier-Stokes equations in strong conservation law form. The thin-layer or Euler equations may also be solved. Turbulence is modeled using an algebraic eddy viscosity model. The objective was to develop a code for aerospace applications that is easy to use and easy to modify. Code readability, modularity, and documentation were emphasized. The equations are written in nonorthogonal body-fitted coordinates, and solved by marching in time using a fully-coupled alternating-direction-implicit procedure with generalized first- or second-order time differencing. All terms are linearized using second-order Taylor series. The boundary conditions are treated implicitly, and may be steady, unsteady, or spatially periodic. Simple Cartesian or polar grids may be generated internally by the program. More complex geometries require an externally generated computational coordinate system. The documentation is divided into three volumes. Volume 3 is the Programmer's Reference, and describes the program structure, the FORTRAN variables stored in common blocks, and the details of each subprogram

Subtle perceptions of male sexual orientation influence occupational opportunities.

Theories linking the literatures on stereotyping and human resource management have proposed that individuals may enjoy greater success obtaining jobs congruent with stereotypes about their social categories or traits. Here, we explored such effects for a detectable, but not obvious, social group distinction: male sexual orientation. Bridging previous work on prejudice and occupational success with that on social perception, we found that perceivers rated gay and straight men as more suited to professions consistent with stereotypes about their groups (nurses, pediatricians, and English teachers vs. engineers, managers, surgeons, and math teachers) from mere photos of their faces. Notably, distinct evaluations of the gay and straight men emerged based on perceptions of their faces with no explicit indication of sexual orientation. Neither perceivers’ expertise with hiring decisions nor diagnostic information about the targets eliminated these biases, but encouraging fair decisions did contribute to partly ameliorating the differences. Mediation analysis further showed that perceptions of the targets’ sexual orientations and facial affect accounted for these effects. Individuals may therefore infer characteristics about individuals’ group memberships from their faces and use this information in a way that meaningfully influences evaluations of their suitability for particular jobs

Communicating Without the Face: Holistic Perception of Emotions of People With Facial Paralysis

People with facial paralysis (FP) report social difficulties, but some attempt to compensate by increasing expressivity in their bodies and voices. We examined perceivers’ emotion judgments of videos of people with FP to understand how they interpret the combination of an inexpressive face with an expressive body and voice. Results suggest perceivers form less favorable impressions of people with severe FP, but compensatory expression is effective in improving impressions. Perceivers seemed to form holistic impressions when rating happiness and possibly sadness. Findings have implications for basic emotion research and social functioning interventions for people with FP

Thin Slice Judgments in the Clinical Context

Clinicians make a variety of judgments about their clients, from judging personality traits to making diagnoses, and a variety of methods are available to do so, ranging from observations to structured interviews. A large body of work demonstrates that from a brief glimpse of another’s nonverbal behavior, a variety of traits and inner states can be accurately perceived. Additionally, from these thin slices of behavior, even future outcomes can be predicted with some accuracy. Certain clinical disorders such as Parkinson’s disease and facial paralysis disrupt nonverbal behavior and may impair clinicians’ ability to make accurate judgments. In certain contexts, personality disorders, anxiety, depression, suicide attempts and outcomes can be detected from others’ nonverbal behavior. Additionally, thin slices can predict psychological adjustment to divorce, bereavement, sexual abuse, and well-being throughout life. Thus, for certain traits and disorders, judgments from a thin slice could provide a complementary tool for the clinician’s toolbox.Keywords: person perception, psychological disorders, nonverbal behavior, accurac

Multifaceted determinants for achieving glycemic control the international diabetes management practice study (IDMPS)

OBJECTIVE - The International Diabetes Mellitus Practice Study is a 5-year survey documenting changes in diabetes treatment practice in developing regions. RESEARCH DESIGN AND METHODS - Logistic regression analysis was used to identify factors for achieving A1C <7% in 11,799 patients (1,898 type 1 diabetic and 9,901 type 2 diabetic) recruited by 937 physicians from 17 countries in Eastern Europe (n = 3,519), Asia (n = 5,888), Latin America (n = 2,116), and Africa (n = 276). RESULTS - Twenty-two percent of type 1 diabetic and 36% of type 2 diabetic patients never had A1C measurements. In those with values for A1C, blood pressure, and LDL cholesterol, 7.5% of type 1 diabetic (n = 696) and 3.6% of type 2 diabetic (n = 3,896) patients attained all three recommended targets (blood pressure < 130/80 mmHg, LDL cholesterol <100 mg/dl, and A1C <7%). Self-monitoring of blood glucose was the only predictor for achieving the A1C goal in type 1 diabetes (odds ratios: Asia 2.24, Latin America 3.55, and Eastern Europe 2.42). In type 2 diabetes, short disease duration (Asia 0.97, Latin America 0.97, and Eastern Europe 0.82) and treatment with few oral glucose-lowering drugs (Asia 0.64, Latin America 0.76, and Eastern Europe 0.62) were predictors. Other region-specific factors included lack of microvascular complications and old age in Latin America and Asia; health insurance coverage and specialist care in Latin America; lack of obesity and self-adjustment of insulin dosages in Asia; and training by a diabetes educator, self-monitoring of blood glucose in patients who self-adjusted insulin, and lack of macrovascular complications in Eastern Europe. CONCLUSIONS - In developing countries, factors pertinent to patients, doctors, and health care systems all impact on glycemic control.Facultad de Ciencias Médica

Genuine Personality Recognition from Highly Constrained Face Images

People are able to accurately estimate personality traits, merely on the basis of \u201cpassport\u201d-style neutral faces and, thus, cues must exist that allow for such estimation. However, up&nbsp;to date, there has been little progress in identifying the form and location of these cues. In this paper we address the problem of inferring true personality traits in highly constrained images using state of art machine learning techniques, in particular, deep networks and class activation maps analysis. The novelty of our work consists in that, differently from the vast majority of the current and past approaches (that refer to the problem of consensus personality rating prediction) we predict the genuine personality based on highly constrained images: the target\u2019s are self ratings on a validated personality inventory and we restrict to passport-like photos, in which so-called controllable cues are minimized. Our results show that self-reported personality traits can be accurately evaluated from facial features. A preliminar analysis on the features activation maps shows promising results for a deeper understanding on relevant facial cues for traits estimation

Not so black and white: Memory for ambiguous group members.

Exponential increases in multiracial identities, expected over the next century, create a conundrum for perceivers accustomed to classifying people as their own- or other-race. The current research examines how perceivers resolve this dilemma with regard to the own-race bias. The authors hypothesized that perceivers are not motivated to include ambiguous-race individuals in the in-group and therefore have some difficulty remembering these individuals. Both racially ambiguous and other-race faces were misremembered more often than own-race faces (Study 1), though memory for ambiguous faces was improved among perceivers motivated to include biracial individuals in the in-group (Study 2). Racial labels assigned to racially ambiguous faces determined memory for these faces, suggesting that uncertainty provides the motivational context for discounting ambiguous faces in memory (Study 3). Finally, an inclusion motivation fostered cognitive associations between racially ambiguous faces and the in-group. Moreover, the extent to which perceivers associated racially ambiguous faces with the in-group predicted memory for ambiguous faces and accounted for the impact of motivation on memory (Study 4). Thus, memory for biracial individuals seems to involve a flexible person construal process shaped by motivational factors

The Rationality of Prejudices

We model an -player repeated prisoner's dilemma in which players are given traits (e.g., height, age, wealth) which, we assume, affect their behavior. The relationship between traits and behavior is unknown to other players. We then analyze the performance of “prejudiced” strategies—strategies that draw inferences based on the observation of some or all of these traits, and extrapolate the inferred behavior to other carriers of these traits. Such prejudiced strategies have the advantage of learning rapidly, and hence of being well adapted to rapidly changing conditions that might result, for example, from high migration or birth rates. We find that they perform remarkably well, and even systematically outperform both Tit-For-Tat and ALLD when the population changes rapidly