Human and machine recognition of dynamic and static facial expressions: prototypicality, ambiguity, and complexity

A growing body of research suggests that movement aids facial expression recognition. However, less is known about the conditions under which the dynamic advantage occurs. The aim of this research was to test emotion recognition in static and dynamic facial expressions, thereby exploring the role of three featural parameters (prototypicality, ambiguity, and complexity) in human and machine analysis. In two studies, facial expression videos and corresponding images depicting the peak of the target and non-target emotion were presented to human observers and the machine classifier (FACET). Results revealed higher recognition rates for dynamic stimuli compared to non-target images. Such benefit disappeared in the context of target-emotion images which were similarly well (or even better) recognised than videos, and more prototypical, less ambiguous, and more complex in appearance than non-target images. While prototypicality and ambiguity exerted more predictive power in machine performance, complexity was more indicative of human emotion recognition. Interestingly, recognition performance by the machine was found to be superior to humans for both target and non-target images. Together, the findings point towards a compensatory role of dynamic information, particularly when static-based stimuli lack relevant features of the target emotion. Implications for research using automatic facial expression analysis (AFEA) are discussed

The mimetic politics of lone-wolf terrorism

Written at a time of crisis in the project of social and political modernity, Fyodor Dostoevsky’s 1864 novel Notes from Underground offers an intriguing parallel for the twenty-first century lone-wolf; it portrays an abject, outcast, spiteful unnamed anti-hero boiling with rage, bitter with resentment and on the verge of radicalisation. A Girardian reading of the poetic truths contained in Dostoevsky’s work is able to provide important keys to explain the contemporary transformation from ‘fourth-wave’ religious terrorism to ‘fifth-wave’ lone-wolf terrorism. Such a reading argues that it is mimetic rivalry – rather than much-trumpeted forms of religious violence or cultural differences – that fuels the triangular relation between governments, terrorists and civilian victims at heart of terrorist acts. This approach is further able to blend social inquiry with an account of the individual, in fact anthropological, conditions of lone-wolf terrorism by tracing the globalisation of resentment and the individualisation of violence to the hyper-mimeticism characterising the globalisation of late modernity. Finally, a mimetic reading of ‘fifth-wave’ terrorism accounts for the turbulence of a global politics in which victimhood and scapegoating no longer have the ability to stabilise social order and warns against a future where violence proliferates and escalates unchecked

Automated data analysis to rapidly derive and communicate ecological insights from satellite-tag data: A case study of reintroduced red kites

Analysis of satellite-telemetry data mostly occurs long after it has been collected, due to the time and effort needed to collate and interpret such material. Such delayed reporting does reduce the usefulness of such data for nature conservation when timely information about animal movements is required. To counter this problem we present a novel approach which combines automated analysis of satellite-telemetry data with rapid communication of insights derived from such data. A relatively simple algorithm (comprising speed of movement and turning angle calculated from fixes), allowed instantaneous detection of excursions away from settlement areas and automated calculation of home ranges on the remaining data Automating the detection of both excursions and home range calculations enabled us to disseminate ecological insights from satellite-tag data instantaneously through a dedicated web portal to inform conservationists and wider audiences. We recommend automated analysis, interpretation and communication of satellite tag and other ecological data to advance nature conservation research and practice

A simplified method to measure choroidal thickness using adaptive compensation in enhanced depth imaging optical coherence tomography

10.1371/journal.pone.0096661PLoS ONE95-POLN

Tracking the Expression of Annoyance in Call Centers

Machine learning researchers have dealt with the identification of emo- tional cues from speech since it is research domain showing a large number of po- tential applications. Many acoustic parameters have been analyzed when searching for cues to identify emotional categories. Then classical classifiers and also out- standing computational approaches have been developed. Experiments have been carried out mainly over induced emotions, even if recently research is shifting to work over spontaneous emotions. In such a framework, it is worth mentioning that the expression of spontaneous emotions depends on cultural factors, on the particu- lar individual and also on the specific situation. In this work, we were interested in the emotional shifts during conversation. In particular we were aimed to track the annoyance shifts appearing in phone conversations to complaint services. To this end we analyzed a set of audio files showing different ways to express annoyance. The call center operators found disappointment, impotence or anger as expression of annoyance. However, our experiments showed that variations of parameters derived from intensity combined with some spectral information and suprasegmental fea- tures are very robust for each speaker and annoyance rate. The work also discussed the annotation problem arising when dealing with human labelling of subjective events. In this work we proposed an extended rating scale in order to include anno- tators disagreements. Our frame classification results validated the chosen annota- tion procedure. Experimental results also showed that shifts in customer annoyance rates could be potentially tracked during phone callsSpanish Mineco under grant TIN2014- 54288-C4-4-R H2020 EU under Empathic RIA action number 769872

Identification of blood-based molecular signatures for prediction of response and relapse in schizophrenia patients

The current inability of psychiatric medicine to objectively select the most appropriate treatment or to predict imminent relapse are major factors contributing to the severity and clinical burden of schizophrenia. We have previously used multiplexed immunoassays to show that schizophrenia patients have a distinctive molecular signature in serum compared with healthy control subjects. In the present study, we used the same approach to measure biomarkers in a population of 77 schizophrenia patients who were followed up over 25 months with four aims: (1) to identify molecules associated with symptom severity in antipsychotic naive and unmedicated patients, (2) to determine biomarker signatures that could predict response over a 6-week treatment period, (3) to identify molecular panels that could predict the time to relapse in a cross-sectional population of patients in remission and (4) to investigate how the biological relapse signature changed throughout the treatment course. This led to identification of molecular signatures that could predict symptom improvement over the first 6 weeks of treatment as well as predict time to relapse in a subset of 18 patients who experienced recurrence of symptoms. This study provides the groundwork for the development of novel objective clinical tests that can help psychiatrists in the clinical management of schizophrenia

Host Immune Response to Mosquito-Transmitted Chikungunya Virus Differs from That Elicited by Needle Inoculated Virus

Mosquito-borne diseases are a worldwide public health threat. Mosquitoes transmit viruses or parasites during feeding, along with salivary proteins that modulate host responses to facilitate both blood feeding and pathogen transmission. Understanding these earliest events in mosquito transmission of arboviruses by mosquitoes is essential for development and assessment of rational vaccine and treatment strategies. In this report, we compared host immune responses to chikungunya virus (CHIKV) transmission by (1) mosquito bite, or (2) by needle inoculation.Differential cytokine expression was measured using quantitative real-time RT-PCR, at sites of uninfected mosquito bites, CHIKV-infected mosquito bites, and needle-inoculated CHIKV. Both uninfected and CHIKV infected mosquitoes polarized host cytokine response to a TH2 profile. Compared to uninfected mosquito bites, expression of IL-4 induced by CHIKV-infected mosquitoes were 150 fold and 527.1 fold higher at 3 hours post feeding (hpf) and 6 hpf, respectively. A significant suppression of TH1 cytokines and TLR-3 was also observed. These significant differences may result from variation in the composition of uninfected and CHIKV-infected mosquito saliva. Needle injected CHIKV induced a robust interferon-gamma, no detectable IL-4, and a significant up-regulation of TLR-3.This report describes the first analysis of cutaneous cytokines in mice bitten by CHIKV-infected mosquitoes. Our data demonstrate contrasting immune activation in the response to CHIKV infection by mosquito bite or needle inoculation. The significant role of mosquito saliva in these earliest events of CHIKV transmission and infection are highlighted

Molecular Epidemiology of Glanders, Pakistan

We collected epidemiologic and molecular data from Burkholderia mallei isolates from equines in Punjab, Pakistan from 1999 through 2007. We show that recent outbreaks are genetically distinct from available whole genome sequences and that these genotypes are persistent and ubiquitous in Punjab, probably due to human-mediated movement of equines