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.

Recognition, assessment and treatment of social anxiety disorder: summary of NICE guidance

Social anxiety disorder is one of the most persistent and common of the anxiety disorders, with lifetime prevalence rates in Europe of 6.7% (range 3.9-13.7%).1 It often coexists with depression, substance use disorder, generalised anxiety disorder, panic disorder, and post-traumatic stress disorder.2 It can severely impair a person’s daily functioning by impeding the formation of relationships, reducing quality of life, and negatively affecting performance at work or school. Despite this, and the fact that effective treatments exist, only about half of people with this condition seek treatment, many after waiting 10-15 years.3 Although about 40% of those who develop the condition in childhood or adolescence recover before adulthood,4 for many the disorder persists into adulthood, with the chance of spontaneous recovery then limited compared with other mental health problems. This article summarises the most recent recommendations from the National Institute for Health and Care Excellence (NICE) on recognising, assessing, and treating social anxiety disorder in children, young people, and adults.5

Emulation of chiral hydrogenation catalysts by adsorbtion of small molecules onto Ni surfaces

Adsorption of small molecules on the Ni{111} and NiO{111} surfaces is investigated under UHV and elevated pressures (~10-1 mbar) of hydrogen and water. The molecules considered are chosen for their relevance to understanding the mechanism of enantioselective hydrogenation on Raney Nickel modified by chiral molecules. Adsorption of water onto, and its subsequent reaction with, oxygen-covered Ni{111} is dependent on the initial atomic oxygen coverage. An OH species (O1s binding energy 531.5eV), oriented perpendicular to the surface, forms at atomic oxygen coverages <0.25ML. The reaction does not consume all the adsorbed oxygen for coverages ≥0.12ML. The p(2×2) atomic oxygen uperstructure is unreactive, while an OH species is formed on the p(√3×√3) superstructure at binding energy 530.9eV. L-alanine is adsorbed on Ni{111} as a model chiral modifier molecule. At low coverages, alanine forms a presumed tridentate alaninate species for coverages ≥0.11ML at 250K. A minority, bidentate zwitterionic species forms at coverages >0.11ML, but was not observed at 300K. Saturation occurs at 0.25ML. At high alanine coverages (≥0.19ML) and H2 pressure (≥1×10-2 mbar), the tridentate L-alaninate converts to bidentate zwitterionic L-alanine at 300K. Thermal evolution of L-alanine on Ni{111} under varying hydrogen pressures is examined. Adsorption of L-alanine onto hydroxylated NiO{111} at 300K in UHV, mimicking a catalyst surface under aqueous conditions, yields the tridentate alaninate which is immune to the effects of elevated hydrogen pressure. Exposing the L-alanine/Ni{111} adsorption system to water (≤10-1 mbar) oxidises the surface and recreates the L-alanine/hydroxylated NiO{111} system. Pyruvic acid on Ni{111} is examined as a model for hydrogenation substrate adsorption. Behaviour is coverage dependent and several conformations are possible at low coverages (≤0.1ML). Annealing at coverages <0.2ML causes a condensation reaction, releasing water onto the surface. High coverages do not condense and a saturation coverage of ~0.35ML is found.

Microbial Recognition Via Toll-Like Receptor-Dependent and -Independent Pathways Determines the Cytokine Response of Murine Dendritic Cell Subsets to CD40 Triggering

Dendritic cells (DC) can produce Th-polarizing cytokines and direct the class of the adaptive immune response. Microbial stimuli, cytokines, chemokines, and T cell-derived signals all have been shown to trigger cytokine synthesis by DC, but it remains unclear whether these signals are functionally equivalent and whether they determine the nature of the cytokine produced or simply initiate a preprogrammed pattern of cytokine production, which may be DC subtype specific. Here, we demonstrate that microbial and T cell-derived stimuli can synergize to induce production of high levels of IL-12 p70 or IL-10 by individual murine DC subsets but that the choice of cytokine is dictated by the microbial pattern recognition receptor engaged. We show that bacterial components such as CpG-containing DNA or extracts from Mycobacterium tuberculosis predispose CD8alpha(+) and CD8alpha(-)CD4(-) DC to make IL-12 p70. In contrast, exposure of CD8alpha(+), CD4(+) and CD8alpha(-)CD4(-) DC to heat-killed yeasts leads to production of IL-10. In both cases, secretion of high levels of cytokine requires a second signal from T cells, which can be replaced by CD40 ligand. Consistent with their differential effects on cytokine production, extracts from M. tuberculosis promote IL-12 production primarily via Toll-like receptor 2 and an MyD88-dependent pathway, whereas heat-killed yeasts activate DC via a Toll-like receptor 2-, MyD88-, and Toll/IL-1R domain containing protein-independent pathway. These results show that T cell feedback amplifies innate signals for cytokine production by DC and suggest that pattern recognition rather than ontogeny determines the production of cytokines by individual DC subsets.

EU free movement law and the legal recognition of same-sex relationships: the case for mutual recognition

This article seeks to examine the cross-border legal recognition of same-sex relationships in the EU. Although the Member States maintain an exclusive competence in the field of family law and, thus, it is up to them to determine whether they will provide a legal status to same-sex couples within their territory, they need to exercise their powers in that field in a way that does not violate EU law. This, it is suggested, requires that Member States mutually recognize the legal status of same-sex couples and do not treat same-sex couples worse than opposite-sex couples, if the basis of the differentiation is, merely, the (homosexual) sexual orientation of the two spouses/partners. Nonetheless, the current legal framework does not make it clear that Member States are under such an obligation. The main argument of the article, therefore, is that the EU must adopt a more hands-on approach towards this issue.

Morphology of polymer networks formed in the chiral and non chiral phases of an anti-ferroelectric liquid crystal

We introduced photo-polymer networks into the various liquid crystalline phases of the antiferroelectric liquid crystal AS612 and studied the effects of these networks by measuring the temperature dependence of the Bragg wavelengths selectively reflected. After polymerization, the decrease in Bragg wavelengths with respect to the original values is consistent with a shorter helical pitch due to polymer network shrinkage. Also, by removing the liquid crystalline material, we are able to image the residual polymer network using scanning electron microscopy and polarized light microscopy. The polymer strands are a few microns thick and the networks show both chiral and non-chiral features.

Elucidating the structure of chiral molecules by using amplified vibrational circular dichroism: from theory to experimental realization

Recent experimental observations of enhanced vibrational circular dichroism (VCD) in molecular systems with low-lying electronically excited states suggest interesting new applications of VCD spectroscopy. The theory describing VCD enhancement through vibronic coupling schemes was derived by Nafie in 1983, but only recently experimental evidence of VCD amplification has demonstrated the extent to which this effect can be exploited as a structure elucidation tool to probe local structure. In this Concept paper, we give an overview of the physics behind vibrational circular dichroism, in particular the equations governing the VCD amplification effect, and review the latest experimental developments with a prospective view on the application of amplified VCD to locally probe biomolecular structure.

Stereochemistry and thermal stability of tartaric acid on the intrinsically chiral Cu{531} surface

Intrinsically chiral metal surfaces provide enantiospecific reaction environments without the need of coadsorbed modifiers. Amongst the intrinsically chiral copper surfaces, Cu{531} has the smallest unit cell and the highest density of chiral sites. XPS, NEXAFS and TPD were employed to investigate the adsorption and decomposition behaviour of the two chiral enantiomers of tartaric acid on this surface. The results obtained from XPS and NEXAFS show that at saturation coverage both enantiomers of tartaric acid adsorb in a μ4 configuration through the two carboxylic groups,which are rotatedwith respect to each other by 90°±≈15°within the surface plane. At intermediate coverage the R,R enantiomer adopts a similar configuration, but the S,S enantiomer is different and shows a high degree of dissociation. Growth of multilayers is observed at high exposures when the sample is kept at below 370 K. TPD experiments show that multilayers desorb between 390 K and 470 K and decomposition of the chemisorbed layer occurs between 470 K and 600 K. The desorption spectra support a two-step decomposition mechanism with a O_C_C_O or HO–HC_CH–OH intermediate that leads to production of CO2 and CO. Enantiomeric differences are observed in the desorption features related to the decomposition of the chemisorbed layer.

Combining 3D and 2D for less constrained periocular recognition

Periocular recognition has recently become an active topic in biometrics. Typically it uses 2D image data of the periocular region. This paper is the first description of combining 3D shape structure with 2D texture. A simple and effective technique using iterative closest point (ICP) was applied for 3D periocular region matching. It proved its strength for relatively unconstrained eye region capture, and does not require any training. Local binary patterns (LBP) were applied for 2D image based periocular matching. The two modalities were combined at the score-level. This approach was evaluated using the Bosphorus 3D face database, which contains large variations in facial expressions, head poses and occlusions. The rank-1 accuracy achieved from the 3D data (80%) was better than that for 2D (58%), and the best accuracy (83%) was achieved by fusing the two types of data. This suggests that significant improvements to periocular recognition systems could be achieved using the 3D structure information that is now available from small and inexpensive sensors.

University teaching: recognition and reward

Teaching in universities has increased in importance in recent years which, in part, is a consequence of the change in funding of universities from block grants to student tuition fees. Various initiatives have been made which serve to raise the profile of teaching and give it greater recognition. It is also important that teaching is recognised even more fully and widely, and crucially that it is rewarded accordingly. We propose a mechanism for recognising and rewarding university teaching that is based on a review process that is supported by documented evidence whose outcomes can be fed into performance and development reviews, and used to inform decisions about reward and promotion, as well as the review of probationary status where appropriate.

On fusion for multispectral iris recognition

Multispectral iris recognition uses information from multiple bands of the electromagnetic spectrum to better represent certain physiological characteristics of the iris texture and enhance obtained recognition accuracy. This paper addresses the questions of single versus cross spectral performance and compares score-level fusion accuracy for different feature types, combining different wavelengths to overcome limitations in less constrained recording environments. Further it is investigated whether Doddington's “goats” (users who are particularly difficult to recognize) in one spectrum also extend to other spectra. Focusing on the question of feature stability at different wavelengths, this work uses manual ground truth segmentation, avoiding bias by segmentation impact. Experiments on the public UTIRIS multispectral iris dataset using 4 feature extraction techniques reveal a significant enhancement when combining NIR + Red for 2-channel and NIR + Red + Blue for 3-channel fusion, across different feature types. Selective feature-level fusion is investigated and shown to improve overall and especially cross-spectral performance without increasing the overall length of the iris code.

Segmentation-level fusion for iris recognition

This paper investigates the potential of fusion at normalisation/segmentation level prior to feature extraction. While there are several biometric fusion methods at data/feature level, score level and rank/decision level combining raw biometric signals, scores, or ranks/decisions, this type of fusion is still in its infancy. However, the increasing demand to allow for more relaxed and less invasive recording conditions, especially for on-the-move iris recognition, suggests to further investigate fusion at this very low level. This paper focuses on the approach of multi-segmentation fusion for iris biometric systems investigating the benefit of combining the segmentation result of multiple normalisation algorithms, using four methods from two different public iris toolkits (USIT, OSIRIS) on the public CASIA and IITD iris datasets. Evaluations based on recognition accuracy and ground truth segmentation data indicate high sensitivity with regards to the type of errors made by segmentation algorithms.

Designing care bundle documentation to support the recognition and treatment of acute kidney injury: a route to quality improvement

The chapter describes development of care bundle documentation, through an iterative, user-centred design process, to support the recognition and treatment of acute kidney injury (AKI). The chapter details stages of user and stakeholder consultation, employed to develop a design response that was sensitive to user experience and need, culminating in simulation testing of a near final prototype. The development of supplementary awareness-raising materials, relating to the main care bundle tool is also discussed. This information design response to a complex clinical decision-making process is contrasted to other approaches to promoting AKI care. The need for different but related approaches to the working tool itself and the tool’s communication are discussed. More general recommendations are made for the development of communication tools to support complex clinical processes.