687 research outputs found

    Focus on bowel and bladder-control anxiety

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    Most people can remember a time when they have been desperate to use the toilet and found one just in the nick of time. But imagine having this experience routinely, every time you went out. This kind of experience can create a tendency to experience unhelpful thoughts like “I need to get out of here or I will wet myself” and a general preoccupation with being incontinent. This is what happens to people who have bowel and/or bladder-control anxiety (BBCA). Their worst fear is that they will be incontinent in a public place. We have conducted one of the first detailed studies of bowel and bladder-control anxiety, which was published 2014, by our team at University College London. This preliminary study of 140 people with BBCA anxiety found that there was an equal split between people who mainly had concerns about bowel control (~40%) and bladder control (~40%), with a smaller proportion having concerns about both (20%). Fifty percent had actually had at least one episode of incontinence in public ‘since school age,’ so it may be that people begin to believe that a future occurrence of being incontinent in public is more likely. BBCA fears tended to develop in people in their mid to late 20s and the majority of sufferers (75%) were women. A majority of the respondents also reported experiencing panic attacks (78%). One particularly striking finding from our research was the tendency of people to believe that being incontinent in public was very shameful and disgusting. They believed that other people would be unforgiving and unwilling to help them. While it may be natural to associated body waste with disgust, and losing control with shame, it was the level of shame and disgust that was noticeable. Many people indicated that being incontinent in public was the most shameful thing that could happen to someone; that it made them a disgusting person. Our experience of treating patients with BBCA suggests that they often respond well to cognitive therapy. For other patients who have high levels of shame and beliefs about self-disgust, additional techniques might also be useful. One of our aims is to develop a more complete understanding of the condition, which will enable us to devise more effective treatments. We hope that our studies will provide the basis for future research to develop more effective treatment for a set of symptoms that has been neglected for too long

    Identification of a narrow post-ovulatory window of vulnerability to distressing involuntary memories in healthy women

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    Psychological disorders characterised by intrusive memories are more prevalent in women than men. The biological, social and cognitive processes underlying this gender-difference have yet to be fully elucidated. Some evidence suggests that (fluctuations in) ovarian hormone levels are responsible for altered sensitivity to emotional stimuli during certain phases in the menstrual-cycle and this may form the basis of a specific vulnerability to psychological disorders in women. The post-ovulatory (luteal) phase has been identified as a period of particular vulnerability to the development of Post-Traumatic Stress Disorder (PTSD). Using an experimental model of PTSD, we examine whether differences are detectable between discrete phases in the menstrual-cycle in the experience of intrusive memories. Women (18-35 years-old) in one of three tightly-defined periods within the menstrual cycle – mid-follicular (n=15), early-luteal (n=15) and late-luteal (n=11) - provided saliva samples for ovarian-hormone assay and watched a distressing film. Subsequent intrusive memories, assessed using a daily online-diary, occurred significantly more frequently in the early-luteal group compared to mid-follicular and late-luteal groups. Intrusion frequency was negatively correlated with the estradiol-to-progesterone ratio, but not estradiol or progesterone alone, suggesting that the interactive effect of low estradiol and high progesterone at encoding contributes to the observed effect. Our results support the need for further research in a clinical context with naturally-cycling women who experience a traumatic event, since assessment of days-since-last-menses and ovarian hormone levels may help to identify those at greatest risk of developing re-experiencing symptoms akin to those seen in psychological disorder such as depression and PTSD

    The role of self-compassion and self-criticism in binge eating behaviour

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    Self-criticism and low self-compassion are implicated in the development and maintenance of binge eating. However, the association between these self-attitudes and binge eating symptoms remains unclear. Women with symptoms of Bulimia Nervosa (BN) or Binge Eating Disorder (BED) were randomised to either a self-compassion (n = 30) or self-critical rumination (n = 30) strategy following a negative mood induction. Responses to food cues (cue reactivity and affect) and calorie consumption in a ‘taste test’ were assessed. The self-compassion strategy was associated with a greater improvement in positive and negative affect following the negative mood induction. Despite the differential effects on mood, self-compassion and self-critical rumination led to similar self-reported food cravings and physiological reactivity to cues. However, participants in the self-compassion condition consumed significantly fewer calories, rated the consumed food as less pleasurable, and reported less desire to continue eating. The findings suggest that therapeutic strategies for cultivating self-compassion are associated with improved food-related self-regulation in the context of negative mood

    Processing of GPS Data using Accuracy Enhancement Techniques for Sag Monitoring Device

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    The paper describes an experimental set up used to collect GPS data in real time. The effect of weather of particular location is also considered in the paper. The major problems in GPS measurements may be due to tall buildings, high mountains, overhead foliage etc. The positioning data provided directly by the satellites are subject to variety of error sources such as thermal noise, tropospheric delays, multipath error, ephemeris errors, satellite clock errors and ionospheric delays before they are processed into position and time solution in the GPS receiver. The paper discusses DSP techniques such as Bad Data identification and modification and Kalman filter used to enhance the accuracy of GPS altitude measurements. Results obtained demonstrate that Kalman filter after Bad Data identification and modification technique significantly reduced the errors in GPS altitude measurements

    Breastfeeding experience differentially impacts recognition of happiness and anger in mothers

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    Breastfeeding is a dynamic biological and social process based on hormonal regulation involving oxytocin. While there is much work on the role of breastfeeding in infant development and on the role of oxytocin in socio-emotional functioning in adults, little is known about how breastfeeding impacts emotion perception during motherhood. We therefore examined whether breastfeeding influences emotion recognition in mothers. Using a dynamic emotion recognition task, we found that longer durations of exclusive breastfeeding were associated with faster recognition of happiness, providing evidence for a facilitation of processing positive facial expressions. In addition, we found that greater amounts of breastfed meals per day were associated with slower recognition of anger. Our findings are in line with current views of oxytocin function and support accounts that view maternal behaviour as tuned to prosocial responsiveness, by showing that vital elements of maternal care can facilitate the rapid responding to affiliative stimuli by reducing importance of threatening stimuli

    Transfer: Cross Modality Knowledge Transfer using Adversarial Networks -- A Study on Gesture Recognition

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    Knowledge transfer across sensing technology is a novel concept that has been recently explored in many application domains, including gesture-based human computer interaction. The main aim is to gather semantic or data driven information from a source technology to classify / recognize instances of unseen classes in the target technology. The primary challenge is the significant difference in dimensionality and distribution of feature sets between the source and the target technologies. In this paper, we propose TRANSFER, a generic framework for knowledge transfer between a source and a target technology. TRANSFER uses a language-based representation of a hand gesture, which captures a temporal combination of concepts such as handshape, location, and movement that are semantically related to the meaning of a word. By utilizing a pre-specified syntactic structure and tokenizer, TRANSFER segments a hand gesture into tokens and identifies individual components using a token recognizer. The tokenizer in this language-based recognition system abstracts the low-level technology-specific characteristics to the machine interface, enabling the design of a discriminator that learns technology-invariant features essential for recognition of gestures in both source and target technologies. We demonstrate the usage of TRANSFER for three different scenarios: a) transferring knowledge across technology by learning gesture models from video and recognizing gestures using WiFi, b) transferring knowledge from video to accelerometer, and d) transferring knowledge from accelerometer to WiFi signals

    Mindfulness, Acceptance and Defusion Strategies in Smokers: a Systematic Review of Laboratory Studies

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    The psychological flexibility model (PFM) provides a framework for understanding and treating behavioural dysregulation in addictions. Rather than modulating the intensity of subjective experience, interventions based on, or consistent with, the PFM (PFM interventions) seek to alter the individual’s relationship to internal states, such as craving, negative affect and drug-related thoughts, using mindfulness, acceptance and related strategies. Experimental (non-clinical) studies in smokers have examined the effects of specific isolated strategies informed by or consistent with the PFM (PFM strategies). Here, we systematically review these studies and determine the extent to which they conform to methodological standards indicative of high levels of internal validity. Eligible studies were identified through electronic database searches and assessed for the presence of specific methodological features. Provisional aggregate effect sizes were determined depending on availability of data. Of 1499 screened publications, 12 met the criteria. All examined aspects of private subjective experience relevant to abstinence (craving n = 12; negative affect n = 10), demonstrating effects favouring PFM strategies relative to inactive control conditions. However, only six assessed outcome domains consistent with the PFM and provided no consistent evidence favouring PFM strategies. Overall, most studies had methodological limitations. As such, high-quality experimental studies continue to be needed to improve our understanding of necessary and/or sufficient constituents of PFM-guided smoking cessation interventions. Recommendations for future research are discussed

    Merging Deep Learning with Expert Knowledge for Seizure Onset Zone localization from rs-fMRI in Pediatric Pharmaco Resistant Epilepsy

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    Surgical disconnection of Seizure Onset Zones (SOZs) at an early age is an effective treatment for Pharmaco-Resistant Epilepsy (PRE). Pre-surgical localization of SOZs with intra-cranial EEG (iEEG) requires safe and effective depth electrode placement. Resting-state functional Magnetic Resonance Imaging (rs-fMRI) combined with signal decoupling using independent component (IC) analysis has shown promising SOZ localization capability that guides iEEG lead placement. However, SOZ ICs identification requires manual expert sorting of 100s of ICs per patient by the surgical team which limits the reproducibility and availability of this pre-surgical screening. Automated approaches for SOZ IC identification using rs-fMRI may use deep learning (DL) that encodes intricacies of brain networks from scarcely available pediatric data but has low precision, or shallow learning (SL) expert rule-based inference approaches that are incapable of encoding the full spectrum of spatial features. This paper proposes DeepXSOZ that exploits the synergy between DL based spatial feature and SL based expert knowledge encoding to overcome performance drawbacks of these strategies applied in isolation. DeepXSOZ is an expert-in-the-loop IC sorting technique that a) can be configured to either significantly reduce expert sorting workload or operate with high sensitivity based on expertise of the surgical team and b) can potentially enable the usage of rs-fMRI as a low cost outpatient pre-surgical screening tool. Comparison with state-of-art on 52 children with PRE shows that DeepXSOZ achieves sensitivity of 89.79%, precision of 93.6% and accuracy of 84.6%, and reduces sorting effort by 6.7-fold. Knowledge level ablation studies show a pathway towards maximizing patient outcomes while optimizing the machine-expert collaboration for various scenarios.Comment: This paper is currently under review in IEEE Journa
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