Empathy and emotion recognition in people with autism, first-degree relatives, and controls

Empathy is the lens through which we view others' emotion expressions, and respond to them. In this study, empathy and facial emotion recognition were investigated in adults with autism spectrum conditions (ASC; N=314), parents of a child with ASC (N=297) and IQ-matched controls (N=184). Participants completed a self-report measure of empathy (the Empathy Quotient [EQ]) and a modified version of the Karolinska Directed Emotional Faces Task (KDEF) using an online test interface. Results showed that mean scores on the EQ were significantly lower in fathers (p<0.05) but not mothers (p>0.05) of children with ASC compared to controls, whilst both males and females with ASC obtained significantly lower EQ scores (p<0.001) than controls. On the KDEF, statistical analyses revealed poorer overall performance by adults with ASC (p<0.001) compared to the control group. When the 6 distinct basic emotions were analysed separately, the ASC group showed impaired performance across five out of six expressions (happy, sad, angry, afraid and disgusted). Parents of a child with ASC were not significantly worse than controls at recognising any of the basic emotions, after controlling for age and non-verbal IQ (all p>0.05). Finally, results indicated significant differences between males and females with ASC for emotion recognition performance (p<0.05) but not for self-reported empathy (p>0.05). These findings suggest that self-reported empathy deficits in fathers of autistic probands are part of the 'broader autism phenotype'. This study also reports new findings of sex differences amongst people with ASC in emotion recognition, as well as replicating previous work demonstrating empathy difficulties in adults with ASC. The use of empathy measures as quantitative endophenotypes for ASC is discussed.

Revenue-neutral tax policy under price uncertainty

The firm's response to revenue-neutral taxation is investigated under price uncertainty. Revenue-neutral policies adjust simultaneously the marginal tax rate and the level of exemptions while keeping expected tax receipts constant. Nonincreasing absolute risk aversion is sufficient to sign the firm's response: a reduction in the marginal rate causes the firm to contract output. Implications are established for the equilibrium level of treasury receipts.

Revenue-neutral tax policies under price uncertainty: reply

In their comment on my 1990 article, Yeh, Suwanakul, and Mai extend my analysis-which focused attention exclusively on firm output-to allow for simultaneous endogeneity of price, aggregate output, and numbers of firms. They show that, with downward- sloping demand, industry output adjusts positively to revenue-neutral changes in the marginal rate of taxation. This result is significant for two reasons. First, we are more often interested in predictions about aggregate phenomena than we are in predictions about individual firms. Indeed, firm-level predictions are frequently irrefutable since firm data are often unavailable. Second, the authors derive their result under a set of conditions that appear to be more general than those invoked in my 1990 article. In particular, they circumvent the need to invoke specific assumptions about the nature of firms' aversions toward risk. I consider this a useful extension and I appreciate the careful scrutiny of my paper.

Inferring the biggest and best: a measurement model for applying recognition to evoke consideration sets and judge between multiple alternatives

It has long been supposed that preference judgments between sets of to-be-considered possibilities are made by means of initially winnowing down the most promising-looking alternatives to form smaller “consideration sets” (Howard, 1963; Wright & Barbour, 1977). In preference choices with >2 options, it is standard to assume that a “consideration set”, based upon some simple criterion, is established to reduce the options available. Inferential judgments, in contrast, have more frequently been investigated in situations in which only two possibilities need to be considered (e.g., which of these two cities is the larger?) Proponents of the “fast and frugal” approach to decision-making suggest that such judgments are also made on the basis of limited, simple criteria. For example, if only one of two cities is recognized and the task is to judge which city has the larger population, the recognition heuristic states that the recognized city should be selected. A multinomial processing tree model is outlined which provides the basis for estimating the extent to which recognition is used as a criterion in establishing a consideration set for inferential judgments between three possible options.

Recognition of "difference" in Shari'a: a feminist scrutiny through the lens of substantive equality

The paper looks at the works of notable Islamic feminists to examine whether Islam can be reconciled with a substantive approach to gender equality. Located within contemporary feminist debates related to gender equality, it considers the Qur’anic verses related to two controversial areas of Shari’a law, namely, duty of obedience and polygamy, to explore how Islamic scriptures perceive ‘difference’ and its implications for substantive equality-based legal reforms in a Muslim society.

Molecular recognition between functionalized gold nanoparticles and healable, supramolecular polymer blends – a route to property enhancement

A new, healable, supramolecular nanocomposite material has been developed and evaluated. The material comprises a blend of three components: a pyrene-functionalized polyamide, a polydiimide and pyrenefunctionalized gold nanoparticles (P-AuNPs). The polymeric components interact by forming well-defined p–p stacked complexes between p-electron rich pyrenyl residues and p-electron deficient polydiimide residues. Solution studies in the mixed solvent chloroform–hexafluoroisopropanol (6 : 1, v/v) show that mixing the three components (each of which is soluble in isolation), results in the precipitation of a supramolecular, polymer nanocomposite network. The precipitate thus formed can be re-dissolved on heating, with the thermoreversible dissolution/precipitation procedure repeatable over at least 5 cycles. Robust, self-supporting composite films containing up to 15 wt% P-AuNPs could be cast from 2,2,2- trichloroethanol. Addition of as little as 1.25 wt% P-AuNPs resulted in significantly enhanced mechanical properties compared to the supramolecular blend without nanoparticles. The nanocomposites showed a linear increase in both tensile moduli and ultimate tensile strength with increasing P-AuNP content. All compositions up to 10 wt% P-AuNPs exhibited essentially quantitative healing efficiencies. Control experiments on an analogous nanocomposite material containing dodecylamine-functionalized AuNPs (5 wt%) exhibited a tensile modulus approximately half that of the corresponding nanocomposite that incorporated 5 wt% pyrene functionalized-AuNPs, clearly demonstrating the importance of the designed interactions between the gold filler and the supramolecular polymer matrix.

Achievement motivation and memory: achievement goals differentially influence immediate and delayed remember–know recognition memory

Little research has been conducted on achievement motivation and memory and, more specifically, on achievement goals and memory. In the present research, the authors conducted two experiments designed to examine the influence of mastery-approach and performance-approach goals on immediate and delayed remember–know recognition memory. The experiments revealed differential effects for achievement goals over time: Performance-approach goals showed higher correct remember responding on an immediate recognition test, whereas mastery-approach goals showed higher correct remember responding on a delayed recognition test. Achievement goals had no influence on overall recognition memory and no consistent influence on know responding across experiments. These findings indicate that it is important to consider quality, not just quantity, in both motivation and memory, when studying relations between these constructs. (PsycINFO Database Record (c) 2012 APA, all rights reserved)(journal abstract)

Anion recognition and transport properties of sulfamide-, phosphoric triamide- and thiophosphoric triamide-based receptors

Studies of sulfamide, phosphoric triamide and thiophosphoric triamidebased organocatalysts show that the phosphorus containing systems are effective new hydrogen bonding motifs for the recognition and transport of anions.

The effects of distraction on metacognition and metacognition on distraction: evidence from recognition memory

The effects of auditory distraction in memory tasks have been examined to date with procedures that minimize participants’ control over their own memory processes. Surprisingly little attention has been paid to metacognitive control factors which might affect memory performance. In this study, we investigate the effects of auditory distraction on metacognitive control of memory, examining the effects of auditory distraction in recognition tasks utilizing the metacognitive framework of Koriat and Goldsmith (1996), to determine whether strategic regulation of memory accuracy is impacted by auditory distraction. Results replicated previous findings in showing that auditory distraction impairs memory performance in tasks minimizing participants’ metacognitive control (forced-report test). However, the results revealed also that when metacognitive control is allowed (free-report tests), auditory distraction impacts upon a range of metacognitive indices. In the present study, auditory distraction undermined accuracy of metacognitive monitoring (resolution), reduced confidence in responses provided and, correspondingly, increased participants’ propensity to withhold responses in free-report recognition. Crucially, changes in metacognitive processes were related to impairment in free-report recognition performance, as the use of the ‘don’t know’ option under distraction led to a reduction in the number of correct responses volunteered in free-report tests. Overall, the present results show how auditory distraction exerts its influence on memory performance via both memory and metamemory processes.

Type 2 diabetes and impaired glucose tolerance are associated with word memory source monitoring recollection deficits but not simple recognition familiarity deficits following water, low glycaemic load, and high glycaemic load breakfasts.

Isolated source monitoring recollection deficits indicate that abnormalities in glucose metabolism are not detrimental for global episodic memory processes. This enhances our understanding of how metabolic disorders are associated with memory impairments.

A unified approach to the recognition of complex actions from sequences of zone-crossings

We present a method for the recognition of complex actions. Our method combines automatic learning of simple actions and manual definition of complex actions in a single grammar. Contrary to the general trend in complex action recognition that consists in dividing recognition into two stages, our method performs recognition of simple and complex actions in a unified way. This is performed by encoding simple action HMMs within the stochastic grammar that models complex actions. This unified approach enables a more effective influence of the higher activity layers into the recognition of simple actions which leads to a substantial improvement in the classification of complex actions. We consider the recognition of complex actions based on person transits between areas in the scene. As input, our method receives crossings of tracks along a set of zones which are derived using unsupervised learning of the movement patterns of the objects in the scene. We evaluate our method on a large dataset showing normal, suspicious and threat behaviour on a parking lot. Experiments show an improvement of ~ 30% in the recognition of both high-level scenarios and their composing simple actions with respect to a two-stage approach. Experiments with synthetic noise simulating the most common tracking failures show that our method only experiences a limited decrease in performance when moderate amounts of noise are added.

ReadingAct RGB-D action dataset and human action recognition from local features

For general home monitoring, a system should automatically interpret people’s actions. The system should be non-intrusive, and able to deal with a cluttered background, and loose clothes. An approach based on spatio-temporal local features and a Bag-of-Words (BoW) model is proposed for single-person action recognition from combined intensity and depth images. To restore the temporal structure lost in the traditional BoW method, a dynamic time alignment technique with temporal binning is applied in this work, which has not been previously implemented in the literature for human action recognition on depth imagery. A novel human action dataset with depth data has been created using two Microsoft Kinect sensors. The ReadingAct dataset contains 20 subjects and 19 actions for a total of 2340 videos. To investigate the effect of using depth images and the proposed method, testing was conducted on three depth datasets, and the proposed method was compared to traditional Bag-of-Words methods. Results showed that the proposed method improves recognition accuracy when adding depth to the conventional intensity data, and has advantages when dealing with long actions.

Is it me? Self-recognition bias across sensory modalities and its relationship to autistic traits

Background Atypical self-processing is an emerging theme in autism research, suggested by lower self-reference effect in memory, and atypical neural responses to visual self-representations. Most research on physical self-processing in autism uses visual stimuli. However, the self is a multimodal construct, and therefore, it is essential to test self-recognition in other sensory modalities as well. Self-recognition in the auditory modality remains relatively unexplored and has not been tested in relation to autism and related traits. This study investigates self-recognition in auditory and visual domain in the general population and tests if it is associated with autistic traits. Methods Thirty-nine neurotypical adults participated in a two-part study. In the first session, individual participant’s voice was recorded and face was photographed and morphed respectively with voices and faces from unfamiliar identities. In the second session, participants performed a ‘self-identification’ task, classifying each morph as ‘self’ voice (or face) or an ‘other’ voice (or face). All participants also completed the Autism Spectrum Quotient (AQ). For each sensory modality, slope of the self-recognition curve was used as individual self-recognition metric. These two self-recognition metrics were tested for association between each other, and with autistic traits. Results Fifty percent ‘self’ response was reached for a higher percentage of self in the auditory domain compared to the visual domain (t = 3.142; P < 0.01). No significant correlation was noted between self-recognition bias across sensory modalities (τ = −0.165, P = 0.204). Higher recognition bias for self-voice was observed in individuals higher in autistic traits (τ AQ = 0.301, P = 0.008). No such correlation was observed between recognition bias for self-face and autistic traits (τ AQ = −0.020, P = 0.438). Conclusions Our data shows that recognition bias for physical self-representation is not related across sensory modalities. Further, individuals with higher autistic traits were better able to discriminate self from other voices, but this relation was not observed with self-face. A narrow self-other overlap in the auditory domain seen in individuals with high autistic traits could arise due to enhanced perceptual processing of auditory stimuli often observed in individuals with autism.

Massive Open Online Courses and sustainability

Massive Open Online Courses (MOOCs) have become very popular among learners millions of users from around the world registered with leading platforms. There are hundreds of universities (and other organizations) offering MOOCs. However, sustainability of MOOCs is a pressing concern as MOOCs incur up front creation costs, maintenance costs to keep content relevant and on-going support costs to provide facilitation while a course is being run. At present, charging a fee for certification (for example Coursera Signature Track and FutureLearn Statement of Completion) seems a popular business model. In this paper, the authors discuss other possible business models and their pros and cons. Some business models discussed here are: Freemium model – providing content freely but charging for premium services such as course support, tutoring and proctored exams. Sponsorships – courses can be created in collaboration with industry where industry sponsorships are used to cover the costs of course production and offering. For example Teaching Computing course was offered by the University of East Anglia on the FutureLearn platform with the sponsorship from British Telecom while the UK Government sponsored the course Introduction to Cyber Security offered by the Open University on FutureLearn. Initiatives and Grants – The government, EU commission or corporations could commission the creation of courses through grants and initiatives according to the skills gap identified for the economy. For example, the UK Government’s National Cyber Security Programme has supported a course on Cyber Security. Similar initiatives could also provide funding to support relevant course development and offering. Donations – Free software, Wikipedia and early OER initiatives such as the MIT OpenCourseware accept donations from the public and this could well be used as a business model where learners could contribute (if they wish) to the maintenance and facilitation of a course. Merchandise – selling merchandise could also bring revenue to MOOCs. As many participants do not seek formal recognition (European Commission, 2014) for their completion of a MOOC, merchandise that presents their achievement in a playful way could well be attractive for them. Sale of supplementary material –supplementary course material in the form of an online or physical book or similar could be sold with the revenue being reinvested in the course delivery. Selective advertising – courses could have advertisements relevant to learners Data sharing – though a controversial topic, sharing learner data with relevant employers or similar could be another revenue model for MOOCs. Follow on events – the courses could lead to follow on summer schools, courses or other real-life or online events that are paid-for in which case a percentage of the revenue could be passed on to the MOOC for its upkeep. Though these models are all possible ways of generating revenue for MOOCs, some are more controversial and sensitive than others. Nevertheless unless appropriate business models are identified the sustainability of MOOCs would be problematic.