Enhancement of a body area network to support smart health monitoring at the digital home

The deployment of home-based smart health services requires effective and reliable systems for personal and environmental data management. ooperation between Home Area Networks (HAN) and Body Area Networks (BAN) can provide smart systems with ad hoc reasoning information to support health care. This paper details the implementation of an architecture that integrates BAN, HAN and intelligent agents to manage physiological and environmental data to proactively detect risk situations at the digital home. The system monitors dynamic situations and timely adjusts its behavior to detect user risks concerning to health. Thus, this work provides a reasoning framework to infer appropriate solutions in cases of health risk episodes. Proposed smart health monitoring approach integrates complex reasoning according to home environment, user profile and physiological parameters defined by a scalable ontology. As a result, health care demands can be detected to activate adequate internal mechanisms and report public health services for requested actions.

The specificity of emotion inferences as a function of emotional contextual support

Research on emotion inferences has shown that readers include a representation of the main character's emotional state in their mental representations of the text. We examined the specificity of emotion representations as a function of the emotion content of short narratives, in terms of the quantity and quality of emotion components included in the narratives, based on the GRID instrument (Fontaine et al., 2013). In a self-paced reading task, target sentences that only moderately matched the emotional context were read faster than target sentences that strongly matched the emotional context of the narratives. In a “makes sense” judgment task, we showed that this result was not driven by a mapping difficulty and, in a memory task, we provided some evidence that these effects reflected integration processes. We suggest that readers can integrate specific emotions into their mental representations, but only if provided with the appropriate emotional contextual support.

Dynamic facial expressions evoke distinct activation in the face perception network:a connectivity analysis study

Very little is known about the neural structures involved in the perception of realistic dynamic facial expressions. In the present study, a unique set of naturalistic dynamic facial emotional expressions was created. Through fMRI and connectivity analysis, a dynamic face perception network was identified, which is demonstrated to extend Haxby et al.'s [Haxby, J. V., Hoffman, E. A., & Gobbini, M. I. The distributed human neural system for face perception. Trends in Cognitive Science, 4, 223–233, 2000] distributed neural system for face perception. This network includes early visual regions, such as the inferior occipital gyrus, which is identified as insensitive to motion or affect but sensitive to the visual stimulus, the STS, identified as specifically sensitive to motion, and the amygdala, recruited to process affect. Measures of effective connectivity between these regions revealed that dynamic facial stimuli were associated with specific increases in connectivity between early visual regions, such as the inferior occipital gyrus and the STS, along with coupling between the STS and the amygdala, as well as the inferior frontal gyrus. These findings support the presence of a distributed network of cortical regions that mediate the perception of different dynamic facial expressions.

Competence–Based Support of Interaction between Business Network Members

In a complicated business network finding a supplier can be a very time consuming task. The technology of competence management is aimed to support such kind of tasks. The paper presents an approach to support interaction between business network members based on such technologies as competence management and knowledge management. The conceptual models of the context-driven competence management system and production network member competence profile are described. The usage of the competence management system is illustrated via an example from automotive industry.

Driving licensing renewal policy using neural network-based probabilistic decision support system

This paper investigates neural network-based probabilistic decision support system to assess drivers' knowledge for the objective of developing a renewal policy of driving licences. The probabilistic model correlates drivers' demographic data to their results in a simulated written driving exam (SWDE). The probabilistic decision support system classifies drivers' into two groups of passing and failing a SWDE. Knowledge assessment of drivers within a probabilistic framework allows quantifying and incorporating uncertainty information into the decision-making system. The results obtained in a Jordanian case study indicate that the performance of the probabilistic decision support systems is more reliable than conventional deterministic decision support systems. Implications of the proposed probabilistic decision support systems on the renewing of the driving licences decision and the possibility of including extra assessment methods are discussed.

Role Stress, Emotional Exhaustion, and Job Satisfaction in the Hotel Industry: The Moderating Role of Supervisory Support

The purpose of this study is to investigate supervisory support as a moderator of the effects of role conflict and role ambiguity on emotional exhaustion and job satisfaction. This study also examines the moderating role of supervisory support on the relationship between emotional exhaustion and job satisfaction. Data were collected from a sample of frontline hotel employees in Northern Cyprus. The aforementioned relationships were tested based on hierarchical multiple regression analysis. The results demonstrate that supervisory support mitigates the impact of role conflict on emotional exhaustion and further reveal that supervisory support reduces the effect of emotional exhaustion on job satisfaction. There is no empirical support for the rest of the hypothesized relationships. Implications of the empirical results are discussed, and future research directions are offered.

A qualitative study of the emotional coping and support needs of children living with a parent with a brain injury

Primary objective: To examine emotional coping and support needs in children of persons with acquired brain injury, with a view to understanding what interventions would be helpful for these children. Design: The study was qualitative, using a thematic analysis approach. Methods and procedure: Six children between 9 and 18 years of age, six parents (three with ABI), and three support workers were interviewed either at home or at a support centre, using a semi-structured interview guide. Results: Children reported using a variety of adaptive and maladaptive emotional coping strategies, but were consistent in expressing a need for credible validation, i.e. sharing experiences with peers. The results are presented under four overarching themes: difficulties faced; emotions experienced; coping strategies; and reported support needs. Conclusions: The results reveal an interaction between the child’s experiences of complex loss that is difficult to acknowledge, emotional distancing between parent and child, and the children’s need for credible validation. All children expressed a desire for talking to peers in a similar situation to themselves, but had not had this opportunity. Interventions should set up such peer interaction to create credible validation for the specific distress suffered by this population.

A longitudinal qualitative exploration of healthcare and informal support needs among survivors of critical illness: the RELINQUISH protocol.

Introduction and background: Survival following critical illness is associated with a significant burden of physical, emotional and psychosocial morbidity. Recovery can be protracted and incomplete, with important and sustained effects upon everyday life, including family life, social participation and return to work. In stark contrast with other critically ill patient groups (eg, those following cardiothoracic surgery), there are comparatively few interventional studies of rehabilitation among the general intensive care unit patient population. This paper outlines the protocol for a sub study of the RECOVER study: a randomised controlled trial evaluating a complex intervention of enhanced ward-based rehabilitation for patients following discharge from intensive care. Methods and analysis: The RELINQUISH study is a nested longitudinal, qualitative study of family support and perceived healthcare needs among RECOVER participants at key stages of the recovery process and at up to 1 year following hospital discharge. Its central premise is that recovery is a dynamic process wherein patients’ needs evolve over time. RELINQUISH is novel in that we will incorporate two parallel strategies into our data analysis: (1) a pragmatic health services-oriented approach, using an a priori analytical construct, the ‘Timing it Right’ framework and (2) a constructivist grounded theory approach which allows the emergence of new themes and theoretical understandings from the data. We will subsequently use Qualitative Health Needs Assessment methodology to inform the development of timely and responsive healthcare interventions throughout the recovery process. Ethics and dissemination: The protocol has been approved by the Lothian Research Ethics Committee (protocol number HSRU011). The study has been added to the UK Clinical Research Network Database (study ID. 9986). The authors will disseminate the findings in peer reviewed publications and to relevant critical care stakeholder groups.

Participation Space Studies: a socio-technical exploration of activist and community groups’ use of online and offline spaces to support their work

Participation Space Studies explore eParticipation in the day-to-day activities of local, citizen-led groups, working to improve their communities. The focus is the relationship between activities and contexts. The concept of a participation space is introduced in order to reify online and offline contexts where people participate in democracy. Participation spaces include websites, blogs, email, social media presences, paper media, and physical spaces. They are understood as sociotechnical systems: assemblages of heterogeneous elements, with relevant histories and trajectories of development and use. This approach enables the parallel study of diverse spaces, on and offline. Participation spaces are investigated within three case studies, centred on interviews and participant observation. Each case concerns a community or activist group, in Scotland. The participation spaces are then modelled using a Socio-Technical Interaction Network (STIN) framework (Kling, McKim and King, 2003). The participation space concept effectively supports the parallel investigation of the diverse social and technical contexts of grassroots democracy and the relationship between the case-study groups and the technologies they use to support their work. Participants’ democratic participation is supported by online technologies, especially email, and they create online communities and networks around their goals. The studies illustrate the mutual shaping relationship between technology and democracy. Participants’ choice of technologies can be understood in spatial terms: boundaries, inhabitants, access, ownership, and cost. Participation spaces and infrastructures are used together and shared with other groups. Non-public online spaces, such as Facebook groups, are vital contexts for eParticipation; further, the majority of participants’ work is non-public, on and offline. It is informational, potentially invisible, work that supports public outputs. The groups involve people and influence events through emotional and symbolic impact, as well as rational argument. Images are powerful vehicles for this and digital images become an increasingly evident and important feature of participation spaces throughout the consecutively conducted case studies. Collaboration of diverse people via social media indicates that these spaces could be understood as boundary objects (Star and Griesemer, 1989). The Participation Space Studies draw from and contribute to eParticipation, social informatics, mediation, social shaping studies, and ethnographic studies of Internet use.

The Psychedelic State Induced By Ayahuasca Modulates The Activity And Connectivity Of The Default Mode Network.

The experiences induced by psychedelics share a wide variety of subjective features, related to the complex changes in perception and cognition induced by this class of drugs. A remarkable increase in introspection is at the core of these altered states of consciousness. Self-oriented mental activity has been consistently linked to the Default Mode Network (DMN), a set of brain regions more active during rest than during the execution of a goal-directed task. Here we used fMRI technique to inspect the DMN during the psychedelic state induced by Ayahuasca in ten experienced subjects. Ayahuasca is a potion traditionally used by Amazonian Amerindians composed by a mixture of compounds that increase monoaminergic transmission. In particular, we examined whether Ayahuasca changes the activity and connectivity of the DMN and the connection between the DMN and the task-positive network (TPN). Ayahuasca caused a significant decrease in activity through most parts of the DMN, including its most consistent hubs: the Posterior Cingulate Cortex (PCC)/Precuneus and the medial Prefrontal Cortex (mPFC). Functional connectivity within the PCC/Precuneus decreased after Ayahuasca intake. No significant change was observed in the DMN-TPN orthogonality. Altogether, our results support the notion that the altered state of consciousness induced by Ayahuasca, like those induced by psilocybin (another serotonergic psychedelic), meditation and sleep, is linked to the modulation of the activity and the connectivity of the DMN.

Teen Triple P: A universal approach to reducing risk factors for behavioural and emotional problems in adolescents at the transition to high school

Teen Triple P is a multilevel system of intervention that is designed to provide parents with specific strategies to promote the positive development of their teenage children as they make the transition into high school and through puberty. The program is based on a combination of education about the developmental needs of adolescents, skills training to improve communication and problem-solving, plus specific modules to deal with common problems encountered by parents and adolescents that can escalate into major conflict and violence. It is designed to increase the engagement of parents of adolescent and pre-adolescent children by providing them with easy access to evidencebased parenting advice and support. This paper presents data collected as part of a survey of over 1400 students in first year high school at 9 Brisbane schools. The survey instrument was constructed to obtain students' reports about behaviour which is known to be associated with their health and wellbeing, and also on the extent to which their parents promoted or discouraged such behaviour at home, at school, and in their social and recreational activities in the wider community. Selected data from the survey were extracted and presented to parents at a series of parenting seminars held at the schools to promote appropriate parenting of teenagers. The objectives were to provide parents with accurate data about teenagers' behaviour, and about teenagers' reports of how they perceived their parents' behaviour. Normative data on parent and teenager behaviour will be presented from the survey as well as psychometric data relating to the reliability and validity of this new measure. Implications of this strategy for increasing parent engagement in parenting programs that aim to reduce behavioural and emotional problems in adolescents will be discussed.

The effect of emotional and attentional processes on blink startle modulation and on electrodermal responses

Emotional accounts of startle modulation predict that startle is facilitated if elicited during aversive foreground stimuli. Attentional accounts hold that startle is enhanced if startle-eliciting stimulus and foreground stimulus are in the same modality. Visual and acoustic foreground stimuli and acoustic startle probes were employed in aversive differential conditioning and in a stimulus discrimination task. Differential conditioning was evident in electrodermal responses and blink latency shortening in both modalities, but effects on magnitude facilitation were found only for visual stimuli. In the discrimination task, skin conductance responses, blink latency shortening, and blink magnitude facilitation were larger during to-be-attended stimuli regardless of stimulus modality. The present results support the notion that attention and emotion can affect blink startle modulation during foreground stimuli.

White matter microstructure underlying default mode network connectivity in the human brain

Resting state functional magnetic resonance imaging (fMRI) reveals a distinct network of correlated brain function representing a default mode state of the human brain The underlying structural basis of this functional connectivity pattern is still widely unexplored We combined fractional anisotropy measures of fiber tract integrity derived from diffusion tensor imaging (DTI) and resting state fMRI data obtained at 3 Tesla from 20 healthy elderly subjects (56 to 83 years of age) to determine white matter microstructure e 7 underlying default mode connectivity We hypothesized that the functional connectivity between the posterior cingulate and hippocampus from resting state fMRI data Would be associated with the white matter microstructure in the cingulate bundle and fiber tracts connecting posterior cingulate gyrus With lateral temporal lobes, medial temporal lobes, and precuneus This was demonstrated at the p<0001 level using a voxel-based multivariate analysis of covariance (MANCOVA) approach In addition, we used a data-driven technique of joint independent component analysis (ICA) that uncovers spatial pattern that are linked across modalities. It revealed a pattern of white matter tracts including cingulate bundle and associated fiber tracts resembling the findings from the hypothesis-driven analysis and was linked to the pattern of default mode network (DMN) connectivity in the resting state fMRI data Out findings support the notion that the functional connectivity between the posterior cingulate and hippocampus and the functional connectivity across the entire DMN is based oil distinct pattern of anatomical connectivity within the cerebral white matter (C) 2009 Elsevier Inc All rights reserved

A decision support system to facilitate management of patients with acute gastrointestinal bleeding

Objective: To develop a model to predict the bleeding source and identify the cohort amongst patients with acute gastrointestinal bleeding (GIB) who require urgent intervention, including endoscopy. Patients with acute GIB, an unpredictable event, are most commonly evaluated and managed by non-gastroenterologists. Rapid and consistently reliable risk stratification of patients with acute GIB for urgent endoscopy may potentially improve outcomes amongst such patients by targeting scarce health-care resources to those who need it the most. Design and methods: Using ICD-9 codes for acute GIB, 189 patients with acute GIB and all. available data variables required to develop and test models were identified from a hospital medical records database. Data on 122 patients was utilized for development of the model and on 67 patients utilized to perform comparative analysis of the models. Clinical data such as presenting signs and symptoms, demographic data, presence of co-morbidities, laboratory data and corresponding endoscopic diagnosis and outcomes were collected. Clinical data and endoscopic diagnosis collected for each patient was utilized to retrospectively ascertain optimal management for each patient. Clinical presentations and corresponding treatment was utilized as training examples. Eight mathematical models including artificial neural network (ANN), support vector machine (SVM), k-nearest neighbor, linear discriminant analysis (LDA), shrunken centroid (SC), random forest (RF), logistic regression, and boosting were trained and tested. The performance of these models was compared using standard statistical analysis and ROC curves. Results: Overall the random forest model best predicted the source, need for resuscitation, and disposition with accuracies of approximately 80% or higher (accuracy for endoscopy was greater than 75%). The area under ROC curve for RF was greater than 0.85, indicating excellent performance by the random forest model Conclusion: While most mathematical models are effective as a decision support system for evaluation and management of patients with acute GIB, in our testing, the RF model consistently demonstrated the best performance. Amongst patients presenting with acute GIB, mathematical models may facilitate the identification of the source of GIB, need for intervention and allow optimization of care and healthcare resource allocation; these however require further validation. (c) 2007 Elsevier B.V. All rights reserved.