Regular exercise participation mediates the affective response to acute bouts of vigorous exercise

Physical inactivity is a leading factor associated with cardiovascular disease and a major contributor to the global burden of disease in developed countries. Subjective mood states associated with acute exercise are likely to influence future exercise adherence and warrant further investigation. The present study examined the effects of a single bout of vigorous exercise on mood and anxiety between individuals with substantially different exercise participation histories. Mood and anxiety were assessed one day before an exercise test (baseline), 5 minutes before (pre-test) and again 10 and 25 minutes post-exercise. Participants were 31 university students (16 males, 15 females; Age M = 20), with 16 participants reporting a history of regular exercise with the remaining 15 reporting to not exercise regularly. Each participant completed an incremental exercise test on a Monark cycle ergometer to volitional exhaustion. Regular exercisers reported significant post-exercise improvements in mood and reductions in state anxiety. By contrast, non-regular exercisers reported an initial decline in post-exercise mood and increased anxiety, followed by an improvement in mood and reduction in anxiety back to pre-exercise levels. Our findings suggest that previous exercise participation mediates affective responses to acute bouts of vigorous exercise. We suggest that to maximise positive mood changes following exercise, practitioners should carefully consider the individual’s exercise participation history before prescribing new regimes.

Facial expression recognition using facial movement features

Facial expression is an important channel for human communication and can be applied in many real applications. One critical step for facial expression recognition (FER) is to accurately extract emotional features. Current approaches on FER in static images have not fully considered and utilized the features of facial element and muscle movements, which represent static and dynamic, as well as geometric and appearance characteristics of facial expressions. This paper proposes an approach to solve this limitation using ‘salient’ distance features, which are obtained by extracting patch-based 3D Gabor features, selecting the ‘salient’ patches, and performing patch matching operations. The experimental results demonstrate high correct recognition rate (CRR), significant performance improvements due to the consideration of facial element and muscle movements, promising results under face registration errors, and fast processing time. The comparison with the state-of-the-art performance confirms that the proposed approach achieves the highest CRR on the JAFFE database and is among the top performers on the Cohn-Kanade (CK) database.

Capturing affective experiences using the SMS experience sampling (SMS-ES) method

This paper reports the feasibility and methodological considerations of using the Short Message System Experience Sampling (SMS-ES) Method, which is an experience sampling research method developed to assist researchers to collect repeat measures of consumers’ affective experiences. The method combines SMS with web-based technology in a simple yet effective way. It is described using a practical implementation study that collected consumers’ emotions in response to using mobile phones in everyday situations. The method is further evaluated in terms of the quality of data collected in the study, as well as against the methodological considerations for experience sampling studies. These two evaluations suggest that the SMS-ES Method is both a valid and reliable approach for collecting consumers’ affective experiences. Moreover, the method can be applied across a range of for-profit and not-for-profit contexts where researchers want to capture repeated measures of consumers’ affective experiences occurring over a period of time. The benefits of the method are discussed to assist researchers who wish to apply the SMS-ES Method in their own research designs.

Butterpaper, sweat & tears : the affective dimension of engaging students during the architectural critique

Considering how dominant a feature of architectural education the critique has been, and continues to be, little has been written about the affective dimension of engaging students during this key final stage of the design or documentation process. For most students, the critique is unlike any previous educational or life experience that they have ever confronted, and the abrupt change in the instructor’s role, from tutor to judge, can be disconcerting at a time when the student is feeling their most vulnerable. The fact that the period immediately leading up to the critique habitually entails not only a focused and sustained effort, but also sleepless nights of intensive work, further exacerbates this. The purpose of this paper is to recognise the affective phenomena influencing student engagement, during the critique. The participants of this research were second to fourth year architecture students at a major Australian university. Following the implementation of trials in alternative modes of critique in architectural design and technology studios, qualitative data was obtained from students, through questionnaires and interviews. Six indicators of engagement were investigated through this research: motivation and agency, transactional engagement with staff, transactional engagement with students, institutional support, active citizenship, and non-institutional support. This research confirms that affective phenomena play a significant role in the events of the critique; the relationship between instructor and student influences student engagement, as does the choreography and spatial planning of the critique environment; and these factors ultimately have an impact on the depth of student learning.

Advanced Computational Intelligence System for inverse aeronautical design optimisation

Abstract—Computational Intelligence Systems (CIS) is one of advanced softwares. CIS has been important position for solving single-objective / reverse / inverse and multi-objective design problems in engineering. The paper hybridise a CIS for optimisation with the concept of Nash-Equilibrium as an optimisation pre-conditioner to accelerate the optimisation process. The hybridised CIS (Hybrid Intelligence System) coupled to the Finite Element Analysis (FEA) tool and one type of Computer Aided Design(CAD) system; GiD is applied to solve an inverse engineering design problem; reconstruction of High Lift Systems (HLS). Numerical results obtained by the hybridised CIS are compared to the results obtained by the original CIS. The benefits of using the concept of Nash-Equilibrium are clearly demonstrated in terms of solution accuracy and optimisation efficiency.

Affect, attention, or anticipatory arousal? Human blink startle modulation in forward and backward affective conditioning

Affect modulates the blink startle reflex in the picture-viewing paradigm, however, the process responsible for reflex modulation during conditional stimuli (CSs) that have acquired valence through affective conditioning remains unclear. In Experiment 1, neutral shapes (CSs) and valenced or neutral pictures (USs) were paired in a forward (CS → US) manner. Pleasantness ratings supported affective learning of positive and negative valence. Post-acquisition, blink reflexes were larger during the pleasant and unpleasant CSs than during the neutral CS. Rather than affect, attention or anticipatory arousal were suggested as sources of startle modulation. Experiment 2 confirmed that affective learning in the picture–picture paradigm was not affected by whether the CS preceded the US. Pleasantness ratings and affective priming revealed similar extents of affective learning following forward, backward or simultaneous pairings of CSs and USs. Experiment 3 utilized a backward conditioning procedure (US → CS) to minimize effects of US anticipation. Again, blink reflexes were larger during CSs paired with valenced USs regardless of US valence implicating attention rather than anticipatory arousal or affect as the process modulating startle in this paradigm.

The contribution of leadership attributes to large scale, complex project success

Mismanagement of large-scale, complex projects has resulted in spectacular failures, cost overruns, time blowouts, and stakeholder dissatisfaction. We focus discussion on the interaction of key management and leadership attributes which facilitate leaders’ adaptive behaviors. These behaviors should in turn influence adaptive team member behavior, stakeholder engagement and successful project outcomes, outputs and impacts. An understanding of this type of management will benefit from a perspective based in managerial and organizational cognition. The research question we explore is whether successful leaders of large-scale complex projects have an internal process leading to a display of administrative, adaptive, and enabling behaviors that foster adaptive processes and enabling behaviors within their teams and with external stakeholders. At the core of the model we propose interactions of key attributes, namely cognitive flexibility, affect, and emotional intelligence. The result of these cognitive-affective attribute interactions is leadership leading to enhanced likelihood of complex project success.

A multi-level model of leadership in complex project management

Management (or perceived mismanagement) of large-scale, complex projects poses special problems and often results in spectacular failures, cost overruns, time blowouts and stakeholder dissatisfaction. While traditional project management responds with increasingly administrative constraints, we argue that leaders of such projects also need to display adaptive and enabling behaviours to foster adaptive processes, such as opportunity recognition, which requires an interaction of cognitive and affective processes of individual, project, and team leader attributes and behaviours. At the core of this model we propose is an interaction of cognitive flexibility, affect and emotional intelligence. The result of this interaction is enhanced leader opportunity recognition that, in turn, facilitates multilevel outcomes.

Person-environment fit: project leader-stakeholder relationships in a complex project environment

In this paper, we develop a conceptual model to explore the perceived complementary congruence between complex project leaders and the demands of the complex project environment to understand how leaders’ affective and behavioural performance at work might be impacted by this fit. We propose that complex project leaders high in emotional intelligence and cognitive flexibility should report a higher level of fit between themselves and the complex project environment. This abilities-demands measure of fit should then relate to affective and behavioural performance outcomes, such that leaders who perceive a higher level of fit should establish and maintain more effective, higher quality project stakeholder relationships than leaders who perceive a lower level of fit.

A framework for analysing system intelligence of the building control system: a study of the integrated building management system

The lack of satisfactory consensus for characterizing the system intelligence and structured analytical decision models has inhibited the developers and practitioners to understand and configure optimum intelligent building systems in a fully informed manner. So far, little research has been conducted in this aspect. This research is designed to identify the key intelligent indicators, and develop analytical models for computing the system intelligence score of smart building system in the intelligent building. The integrated building management system (IBMS) was used as an illustrative example to present a framework. The models presented in this study applied the system intelligence theory, and the conceptual analytical framework. A total of 16 key intelligent indicators were first identified from a general survey. Then, two multi-criteria decision making (MCDM) approaches, the analytic hierarchy process (AHP) and analytic network process (ANP), were employed to develop the system intelligence analytical models. Top intelligence indicators of IBMS include: self-diagnostic of operation deviations; adaptive limiting control algorithm; and, year-round time schedule performance. The developed conceptual framework was then transformed to the practical model. The effectiveness of the practical model was evaluated by means of expert validation. The main contribution of this research is to promote understanding of the intelligent indicators, and to set the foundation for a systemic framework that provide developers and building stakeholders a consolidated inclusive tool for the system intelligence evaluation of the proposed components design configurations.

The role of anxiety and perspective-taking strategy on affective empathic responses

Empathy is an important pro-social behaviour critical to a positive clientetherapist relationship. Therapist anxiety has been linked to reduced ability to empathise and lower client satisfaction with therapy. However, the nature of the relationship between anxiety and empathy is currently unclear. The current study investigated the effect of experimentally-induced anxiety on empathic responses elicited during three different perspective-taking tasks. Perspective-taking was manipulated within-subjects with all participants (N¼ 52) completing imagine-self, imagine-other and objective conditions. A threat of shock manipulation was used to vary anxiety between-subjects. Participants in the threat of shock condition reported higher levels of anxiety during the experiment and lower levels of empathyrelated distress for the targets than participants in the control condition. Perspective-taking was associated with higher levels of empathy-related distress and concern compared to the objective condition. The present results suggest that perspective-taking can to a large extent mitigate the influence of heightened anxiety on an individual’s ability to empathise.

The effects of verbal instruction on affective and expectancy learning

The current research assessed the effects of verbal instruction on affective and expectancy learning during repeated contingency reversals (Experiment 1 and during extinction (Experiment 2) in a picture–picture paradigm. Affective and expectancy learning displayed contingency reversal and extinction, but changes were slower for affective learning. Instructions facilitated reversal and extinction of expectancy learning but did not impact on affective learning. These findings suggest a differential susceptibility of affective and expectancy learning to verbal instruction and question previous reports that verbal instructions can accelerate the extinction of non-prepared fear learning in humans.

No evidence for subliminal affective priming with emotional facial expression primes

The present study investigated whether facial expressions of emotion presented outside consciousness awareness will elicit evaluative responses as assessed in affective priming. Participants were asked to evaluate pleasant and unpleasant target words that were preceded by masked or unmasked schematic (Experiment 1) or photographic faces (Experiments 1 and 2) with happy or angry expressions. They were either required to perform the target evaluation only or to perform the target evaluation and to name the emotion expressed by the face prime. Prime-target interval was 300 ms in Experiment 1 and 80 ms in Experiment 2. Naming performance confirmed the effectiveness of the masking procedure. Affective priming was evident after unmasked primes in tasks that required naming of the facial expressions for schematic and photographic faces and after unmasked primes in tasks that did not require naming for photographic faces. No affective priming was found after masked primes. The present study failed to provide evidence for affective priming with masked face primes, however, it indicates that voluntary attention to the primes enhances affective priming.

Improved facial expression recognition via uni-hyperplane classification

Large margin learning approaches, such as support vector machines (SVM), have been successfully applied to numerous classification tasks, especially for automatic facial expression recognition. The risk of such approaches however, is their sensitivity to large margin losses due to the influence from noisy training examples and outliers which is a common problem in the area of affective computing (i.e., manual coding at the frame level is tedious so coarse labels are normally assigned). In this paper, we leverage the relaxation of the parallel-hyperplanes constraint and propose the use of modified correlation filters (MCF). The MCF is similar in spirit to SVMs and correlation filters, but with the key difference of optimizing only a single hyperplane. We demonstrate the superiority of MCF over current techniques on a battery of experiments.