295 research outputs found
Automaticity in the Recognition of Nonverbal Emotional Vocalizations
The ability to perceive the emotions of others is crucial for everyday social interactions. Important aspects of visual socioemotional processing, such as the recognition of facial expressions, are known to depend on largely automatic mechanisms. However, whether and how properties of automaticity extend to the auditory domain remains poorly understood. Here we ask if nonverbal auditory emotion recognition is a controlled deliberate or an automatic efficient process, using vocalizations such as laughter, crying, and screams. In a between-subjects design (N = 112), and covering eight emotions (four positive), we determined whether emotion recognition accuracy (a) is improved when participants actively deliberate about their responses (compared with when they respond as fast as possible) and (b) is impaired when they respond under low and high levels of cognitive load (concurrent task involving memorizing sequences of six or eight digits, respectively). Response latencies were also measured. Mixed-effects models revealed that recognition accuracy was high across emotions, and only minimally affected by deliberation and cognitive load; the benefits of deliberation and costs of cognitive load were significant mostly for positive emotions, notably amusement/laughter, and smaller or absent for negative ones; response latencies did not suffer under low or high cognitive load; and high recognition accuracy (approximately 90%) could be reached within 500 ms after the stimulus onset, with performance exceeding chance-level already between 300 and 360 ms. These findings indicate that key features of automaticity, namely fast and efficient/effortless processing, might be a modality-independent component of emotion recognition
Primate modularity and evolution: first anatomical network analysis of primate head and neck musculoskeletal system
Network theory is increasingly being used to study morphological modularity and integration. Anatomical network analysis (AnNA) is a framework for quantitatively characterizing the topological organization of anatomical structures and providing an operational way to compare structural integration and modularity. Here we apply AnNA for the first time to study the macroevolution of the musculoskeletal system of the head and neck in primates and their closest living relatives, paying special attention to the evolution of structures associated with facial and vocal communication. We show that well-defined left and right facial modules are plesiomorphic for primates, while anthropoids consistently have asymmetrical facial modules that include structures of both sides, a change likely related to the ability to display more complex, asymmetrical facial expressions. However, no clear trends in network organization were found regarding the evolution of structures related to speech. Remarkably, the increase in the number of head and neck muscles – and thus of musculoskeletal structures – in human evolution led to a decrease in network density and complexity in humans
Anatomical Network Comparison of Human Upper and Lower, Newborn and Adult, and Normal and Abnormal Limbs, with Notes on Development, Pathology and Limb Serial Homology vs. Homoplasy
How do the various anatomical parts (modules) of the animal body evolve into very different integrated forms (integration) yet still function properly without decreasing the individual's survival? This long-standing question remains unanswered for multiple reasons, including lack of consensus about conceptual definitions and approaches, as well as a reasonable bias toward the study of hard tissues over soft tissues. A major difficulty concerns the non-trivial technical hurdles of addressing this problem, specifically the lack of quantitative tools to quantify and compare variation across multiple disparate anatomical parts and tissue types. In this paper we apply for the first time a powerful new quantitative tool, Anatomical Network Analysis (AnNA), to examine and compare in detail the musculoskeletal modularity and integration of normal and abnormal human upper and lower limbs. In contrast to other morphological methods, the strength of AnNA is that it allows efficient and direct empirical comparisons among body parts with even vastly different architectures (e.g. upper and lower limbs) and diverse or complex tissue composition (e.g. bones, cartilages and muscles), by quantifying the spatial organization of these parts-their topological patterns relative to each other-using tools borrowed from network theory. Our results reveal similarities between the skeletal networks of the normal newborn/adult upper limb vs. lower limb, with exception to the shoulder vs. pelvis. However, when muscles are included, the overall musculoskeletal network organization of the upper limb is strikingly different from that of the lower limb, particularly that of the more proximal structures of each limb. Importantly, the obtained data provide further evidence to be added to the vast amount of paleontological, gross anatomical, developmental, molecular and embryological data recently obtained that contradicts the long-standing dogma that the upper and lower limbs are serial homologues. In addition, the AnNA of the limbs of a trisomy 18 human fetus strongly supports Pere Alberch's ill-named "logic of monsters" hypothesis, and contradicts the commonly accepted idea that birth defects often lead to lower integration (i.e. more parcellation) of anatomical structures
Percepção de adolescentes infratoras submetidas à ação socioeducativa sobre assistência à saúde
The anti-adherence effect of Lippia sidoides Cham: extract against microorganisms of dental biofilm
DETECTION OF INTESTINAL PARASITES IN THE ENVIRONMENTS OF A PUBLIC SCHOOL IN THE TOWN OF DIAMANTINA , MINAS GERAIS STATE, BRAZIL
Incorporation of ceramic waste into binary and ternary soil-cement formulations for the production of solid bricks
A New Fluorescence-Based Method Identifies Protein Phosphatases Regulating Lipid Droplet Metabolism
In virtually every cell, neutral lipids are stored in cytoplasmic structures called lipid droplets (LDs) and also referred to as lipid bodies or lipid particles. We developed a rapid high-throughput assay based on the recovery of quenched BODIPY-fluorescence that allows to quantify lipid droplets. The method was validated by monitoring lipid droplet turnover during growth of a yeast culture and by screening a group of strains deleted in genes known to be involved in lipid metabolism. In both tests, the fluorimetric assay showed high sensitivity and good agreement with previously reported data using microscopy. We used this method for high-throughput identification of protein phosphatases involved in lipid droplet metabolism. From 65 yeast knockout strains encoding protein phosphatases and its regulatory subunits, 13 strains revealed to have abnormal levels of lipid droplets, 10 of them having high lipid droplet content. Strains deleted for type I protein phosphatases and related regulators (ppz2, gac1, bni4), type 2A phosphatase and its related regulator (pph21 and sap185), type 2C protein phosphatases (ptc1, ptc4, ptc7) and dual phosphatases (pps1, msg5) were catalogued as high-lipid droplet content strains. Only reg1, a targeting subunit of the type 1 phosphatase Glc7p, and members of the nutrient-sensitive TOR pathway (sit4 and the regulatory subunit sap190) were catalogued as low-lipid droplet content strains, which were studied further. We show that Snf1, the homologue of the mammalian AMP-activated kinase, is constitutively phosphorylated (hyperactive) in sit4 and sap190 strains leading to a reduction of acetyl-CoA carboxylase activity. In conclusion, our fast and highly sensitive method permitted us to catalogue protein phosphatases involved in the regulation of LD metabolism and present evidence indicating that the TOR pathway and the SNF1/AMPK pathway are connected through the Sit4p-Sap190p pair in the control of lipid droplet biogenesis
Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set
We report a measurement of the bottom-strange meson mixing phase \beta_s
using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays
in which the quark-flavor content of the bottom-strange meson is identified at
production. This measurement uses the full data set of proton-antiproton
collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment
at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity.
We report confidence regions in the two-dimensional space of \beta_s and the
B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2,
-1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in
agreement with the standard model expectation. Assuming the standard model
value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +-
0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +-
0.009 (syst) ps, which are consistent and competitive with determinations by
other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012
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