Linear birefringence and optical activity are two common optical polarization effects present in biological tissue, and determination of these properties has useful biomedical applications. However, ...measurement and unique interpretation of these parameters in tissue is hindered by strong multiple scattering effects and by the fact that these and other polarization effects are often present simultaneously. We have investigated the efficacy of a Mueller matrix decomposition methodology to extract the individual intrinsic polarimetry characteristics (linear retardance
and optical rotation
, in particular) from a multiply scattering medium exhibiting simultaneous linear birefringence and optical activity. In the experimental studies, a photoelastic modulation polarimeter was used to record Mueller matrices from polyacrylamide phantoms having strain-induced birefringence, sucrose-induced optical activity, and polystyrene microspheres-induced scattering. Decomposition of the Mueller matrices recorded in the forward detection geometry from these phantoms with controlled polarization properties yielded reasonable estimates for
and
parameters. The confounding effects of scattering, the propagation path of multiple scattered photons, and detection geometry on the estimated values for
and
were further investigated using polarization-sensitive Monte Carlo simulations. The results show that in the forward detection geometry, the effects of scattering induced linear retardance and diattenuation are weak, and the decomposition of the Mueller matrix can retrieve the intrinsic values for
and
with reasonable accuracy. The ability of this approach to extract the individual intrinsic polarimetry characteristics should prove valuable in diagnostic photomedicine, for example, in quantifying the small optical rotations due to the presence of glucose in tissue and for monitoring changes in tissue birefringence as a signature of tissue abnormality.
Right-wing authoritarianism (RWA) has shown inconsistent results as a predictor of beliefs in conspiracy theories (CTs). The present investigation attempted to clarify these results by separating ...anti-establishment CTs, which challenge the existing social order, from pro-establishment CTs, which seek to justify and reinforce it against external threats. In two MTurk samples (N = 294, 200), RWA correlated strongly with pro-establishment CTs but weakly with anti-establishment CTs. Regression analyses suggest that after controlling for exposure to the CTs, this gap in the predictive power of RWA can be explained by differences in attitudes toward their alleged perpetrators, highlighting the importance of intergroup attitudes as an important driver of CT endorsement.
Research on the psychology of conspiracy theories has shown recent steps towards a standardization of measures. The present article seeks to continue that trend by presenting the Flexible Inventory ...of Conspiracy Suspicions (FICS), a questionnaire template that can be adapted to measure suspicions of a conspiracy around nearly any topic of public interest. Compared to conspiracy belief measures that ask about specific theories on a given topic, the FICS is worded in such a way as to provide relatively stable validity across time and cultural context. Using a hybrid approach incorporating classical test theory and Rasch scaling, three questionnaire studies on Mechanical Turk demonstrate the validity of the FICS in measuring conspiracy suspicions regarding 9/11, vaccine safety, and US elections, with good psychometric properties in most situations. However, the utility of the FICS is limited in the case of climate change due to the existence of two opposing conspiracy theories that share essentially no common assumptions (‘climate change is a hoax’ vs. ‘there is a conspiracy to make people believe that climate change is a hoax’). The results indicate that the FICS is a reliable and valid measure of conspiracy suspicions within certain parameters, and suggest a three‐level model that differentiates general conspiracist ideation, relatively vague conspiracy suspicions, and relatively specific conspiracy beliefs.
HIDDEN IN PLAIN SIGHT BANSAL, PRATIMA; KIM, ANNA; WOOD, MICHAEL O.
The Academy of Management review,
04/2018, Volume:
43, Issue:
2
Journal Article
Peer reviewed
Open access
The organizational attention literature has an epistemological bias, in that it explains how and why organizations notice issues. The ontological or real attributes of the issues are largely ignored, ...subordinated, or confounded with this epistemological orientation. In this article we argue that organizations sometimes miss issues, not only because of attentional failures but also because of the temporal and spatial scale of the underlying processes related to the issues. Some processes are of such large or small scale they escape organizational attention. We argue that large-scale processes, such as those related to climate change, require broad attentional extent, whereas small-scale processes, such as those related to local variations in poverty, require fine attentional grain. This work aims to shed light on the relatively underexplored question of why some issues are not noticed, with important implications for both theory and practice.
"Conspiracy theory" is widely acknowledged to be a loaded term. Politicians use it to mock and dismiss allegations against them, while philosophers and political scientists warn that it could be used ...as a rhetorical weapon to pathologize dissent. In two empirical studies conducted on Amazon Mechanical Turk, I present an initial examination of whether this concern is justified. In Experiment 1, 150 participants judged a list of historical and speculative theories to be no less likely when they were labeled "conspiracy theories" than when they were labeled "ideas." In Experiment 2 (N = 802), participants who read a news article about fictitious "corruption allegations" endorsed those allegations no more than participants who saw them labeled "conspiracy theories." The lack of an effect of the conspiracy-theory label in both experiments was unexpected and may be due to a romanticized image of conspiracy theories in popular media or a dilution of the term to include mundane speculation regarding corruption and political intrigue.
Assessing the presence and abundance of birds is important for monitoring specific species as well as overall ecosystem health. Many birds are most readily detected by their sounds, and thus, passive ...acoustic monitoring is highly appropriate. Yet acoustic monitoring is often held back by practical limitations such as the need for manual configuration, reliance on example sound libraries, low accuracy, low robustness, and limited ability to generalise to novel acoustic conditions.
Here, we report outcomes from a collaborative data challenge. We present new acoustic monitoring datasets, summarise the machine learning techniques proposed by challenge teams, conduct detailed performance evaluation, and discuss how such approaches to detection can be integrated into remote monitoring projects.
Multiple methods were able to attain performance of around 88% area under the receiver operating characteristic (ROC) curve (AUC), much higher performance than previous general‐purpose methods.
With modern machine learning, including deep learning, general‐purpose acoustic bird detection can achieve very high retrieval rates in remote monitoring data, with no manual recalibration, and no pretraining of the detector for the target species or the acoustic conditions in the target environment.
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