567 research outputs found
Human factors in forensic science: The cognitive mechanisms that underlie forensic feature-comparison expertise
After a decade of critique from leading scientific bodies, forensic science research is at a crossroads. Whilst emerging research has shown that some forensic feature-comparison disciplines are not foundationally valid, others are moving towards establishing reliability and validity. Forensic examiners in fingerprint, face and handwriting comparison disciplines have skills and knowledge that distinguish them from novices. Yet our understanding of the basis of this expertise is only beginning to emerge. In this paper, we review evidence on the psychological mechanisms contributing to forensic feature-comparison expertise, with a focus on one mechanism: statistical learning, or the ability to learn how often things occur in the environment. Research is beginning to emphasise the importance of statistical learning in forensic feature-comparison expertise. Ultimately, this research and broader cognitive science research has an important role to play in informing the development of training programs and selection tools for forensic feature-comparison examiners
Morphological Analysis of the Polarized Synchrotron Emission with WMAP and Planck
The bright polarized synchrotron emission, away from the Galactic plane,
originates mostly from filamentary structures. We implement a filament finder
algorithm which allows the detection of bright elongated structures in
polarized intensity maps. We analyse the sky at 23 and 30 GHz as observed
respectively by WMAP and Planck. We identify 19 filaments, 13 of which have
been previously observed. For each filament, we study the polarization
fraction, finding values typically larger than for the areas outside the
filaments, excluding the Galactic plane, and a fraction of about 30% is reached
in two filaments. We study the polarization spectral indices of the filaments,
and find a spectral index consistent with the values found in previous analysis
(about -3.1) for more diffuse regions. Decomposing the polarization signals
into the and families, we find that most of the filaments are detected
in , but not in . We then focus on understanding the statistical
properties of the diffuse regions of the synchrotron emission at 23 GHz. Using
Minkowski functionals and tensors, we analyse the non-Gaussianity and
statistical isotropy of the polarized intensity maps. For a sky coverage
corresponding to 80% of the fainter emission, and on scales smaller than 6
degrees (), the deviations from Gaussianity and isotropy are
significantly higher than 3. The level of deviation decreases for
smaller scales, however, it remains significantly high for the lowest analised
scale (). When 60% sky coverage is analysed, we find that the
deviations never exceed 3. Finally, we present a simple data-driven
model to generate non-Gaussian and anisotropic simulations of the synchrotron
polarized emission. The simulations are fitted in order to match the spectral
and statistical properties of the faintest 80% sky coverage of the data maps.Comment: 35 pages, 17 figure
One step closer to influenza vaccine inclusiveness
Flu virus infection is a common cause of acute respiratory illness, with the major incidence in pediatric age, high morbidity, and mortality. The flu vaccine is recommended for all people aged ≥6 months, unless specific contraindications are present. Younger and older age, pregnancy, chronic diseases like asthma, and immunodeficiency are risk factors for severe complications following flu infection. Thus, these categories represent the target for flu vaccine strategies in most countries. Inactivated influenza vaccine (IIV), recombinant influenza vaccine (RIV) or live‐attenuated influenza virus (LAIV) are currently available, with specific precautions and contraindications. We aim to resume the current indications for vaccines in the vulnerable populations to support flu vaccination inclusiveness, in anticipation of a “universal vaccine” strategy
Public attitudes towards the use of automatic facial recognition technology in criminal justice systems around the world
Automatic facial recognition technology (AFR) is increasingly used in criminal justice systems around the world, yet to date there has not been an international survey of public attitudes toward its use. In Study 1, we ran focus groups in the UK, Australia and China (countries at different stages of adopting AFR) and in Study 2 we collected data from over 3,000 participants in the UK, Australia and the USA using a questionnaire investigating attitudes towards AFR use in criminal justice systems. Our results showed that although overall participants were aligned in their attitudes and reasoning behind them, there were some key differences across countries. People in the USA were more accepting of tracking citizens, more accepting of private companies’ use of AFR, and less trusting of the police using AFR than people in the UK and Australia. Our results showed that support for the use of AFR depends greatly on what the technology is used for and who it is used by. We recommend vendors and users do more to explain AFR use, including details around accuracy and data protection. We also recommend that governments should set legal boundaries around the use of AFR in investigative and criminal justice settings
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