AI Hyperrealism: Why AI Faces Are Perceived as More Real Than Human Ones

Recent evidence shows that AI-generated faces are now indistinguishable from human faces. However, algorithms are trained disproportionately on White faces, and thus White AI faces may appear especially realistic. In Experiment 1 (N = 124 adults), alongside our reanalysis of previously published data, we showed that White AI faces are judged as human more often than actual human faces-a phenomenon we term AI hyperrealism. Paradoxically, people who made the most errors in this task were the most confident (a Dunning-Kruger effect). In Experiment 2 (N = 610 adults), we used face-space theory and participant qualitative reports to identify key facial attributes that distinguish AI from human faces but were misinterpreted by participants, leading to AI hyperrealism. However, the attributes permitted high accuracy using machine learning. These findings illustrate how psychological theory can inform understanding of AI outputs and provide direction for debiasing AI algorithms, thereby promoting the ethical use of AI

AI Hyperrealism : Why AI Faces Are Perceived as More Real Than Human Ones

Acknowledgment We thank Sophie J. Nightingale and Hany Farid for providing open access to their stimuli and data. Funding This research is supported by the Australian Government through the Australian Research Council’s Discovery Projects funding scheme (Project No. DP220101026), a TRANSFORM Career Development Fellowship to A. Dawel from the Australian National University College of Health and Medicine, and an Experimental Psychology Society Small Grant to C. A. M. Sutherland. The funders had no role in developing or conducting this research.Peer reviewe

Faint galaxy population in clusters: X-ray emission, cD halos and projection effects

We analyze samples of nearby clusters taken from the Abell catalog and the X-ray Sample of Bright Clusters(De Grandi et al 1999) including a wide range of X-ray luminosities.Using the usually adopted background subtraction procedures, we find that galaxies in clusters selected by means of their X-ray emission show a flat luminosity function (faint end slope $\alpha \simeq -1.1$) consistent with that derived for galaxies in the field and groups. By contrast, the sample of Abell clusters that do not have an X-ray counterpart shows a galaxy luminosity function with a steep faint end ($\alpha \simeq -1.6$). We investigate the possibility that cD halos could be formed by the disruption of galaxies in rich relaxed clusters that show an apparently flat faint end galaxy luminosity function (Lopez-Cruz et al 1997). We find that clusters dominated by a central cD galaxy (Bautz-Morgan classes I and II) show the same systematic trend: X-ray selected clusters have flatter faint end slopes than those clusters with no detected X-ray emission. Thus, it is likely the X-ray selection and not the cluster domination by central galaxies what correlates with background decontamination estimates of the galaxy luminosity function. Moreover, no significant correlation between X-ray luminosity and the galaxy LF faint end slope is found. These results do not support a scenario where flat faint end slopes are a consequence of cD formation via the disruption of faint galaxies. We argue that the clusters without X-ray emission are strongly affected by projection effects which give rise to spurious faint end slopes estimated using background subtraction procedures (Valotto et al 2001).Comment: Accepted for publication in ApJ (vol. 601

Individualization as driving force of clustering phenomena in humans

One of the most intriguing dynamics in biological systems is the emergence of clustering, the self-organization into separated agglomerations of individuals. Several theories have been developed to explain clustering in, for instance, multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of fish, and animal herds. A persistent puzzle, however, is clustering of opinions in human populations. The puzzle is particularly pressing if opinions vary continuously, such as the degree to which citizens are in favor of or against a vaccination program. Existing opinion formation models suggest that "monoculture" is unavoidable in the long run, unless subsets of the population are perfectly separated from each other. Yet, social diversity is a robust empirical phenomenon, although perfect separation is hardly possible in an increasingly connected world. Considering randomness did not overcome the theoretical shortcomings so far. Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture, while larger noise disrupts opinion clusters and results in rampant individualism without any social structure. Our solution of the puzzle builds on recent empirical research, combining the integrative tendencies of social influence with the disintegrative effects of individualization. A key element of the new computational model is an adaptive kind of noise. We conduct simulation experiments to demonstrate that with this kind of noise, a third phase besides individualism and monoculture becomes possible, characterized by the formation of metastable clusters with diversity between and consensus within clusters. When clusters are small, individualization tendencies are too weak to prohibit a fusion of clusters. When clusters grow too large, however, individualization increases in strength, which promotes their splitting.Comment: 12 pages, 4 figure

Toward a Generalizable Framework of Disturbance Ecology Through Crowdsourced Science

© 2021 Graham, Averill, Bond-Lamberty, Knelman, Krause, Peralta, Shade, Smith, Cheng, Fanin, Freund, Garcia, Gibbons, Van Goethem, Guebila, Kemppinen, Nowicki, Pausas, Reed, Rocca, Sengupta, Sihi, Simonin, Słowiński, Spawn, Sutherland, Tonkin, Wisnoski, Zipper and Contributor Consortium.Disturbances fundamentally alter ecosystem functions, yet predicting their impacts remains a key scientific challenge. While the study of disturbances is ubiquitous across many ecological disciplines, there is no agreed-upon, cross-disciplinary foundation for discussing or quantifying the complexity of disturbances, and no consistent terminology or methodologies exist. This inconsistency presents an increasingly urgent challenge due to accelerating global change and the threat of interacting disturbances that can destabilize ecosystem responses. By harvesting the expertise of an interdisciplinary cohort of contributors spanning 42 institutions across 15 countries, we identified an essential limitation in disturbance ecology: the word ‘disturbance’ is used interchangeably to refer to both the events that cause, and the consequences of, ecological change, despite fundamental distinctions between the two meanings. In response, we developed a generalizable framework of ecosystem disturbances, providing a well-defined lexicon for understanding disturbances across perspectives and scales. The framework results from ideas that resonate across multiple scientific disciplines and provides a baseline standard to compare disturbances across fields. This framework can be supplemented by discipline-specific variables to provide maximum benefit to both inter- and intra-disciplinary research. To support future syntheses and meta-analyses of disturbance research, we also encourage researchers to be explicit in how they define disturbance drivers and impacts, and we recommend minimum reporting standards that are applicable regardless of scale. Finally, we discuss the primary factors we considered when developing a baseline framework and propose four future directions to advance our interdisciplinary understanding of disturbances and their social-ecological impacts: integrating across ecological scales, understanding disturbance interactions, establishing baselines and trajectories, and developing process-based models and ecological forecasting initiatives. Our experience through this process motivates us to encourage the wider scientific community to continue to explore new approaches for leveraging Open Science principles in generating creative and multidisciplinary ideas.This research was supported by the U.S. Department of Energy (DOE), Office of Biological and Environmental Research (BER), as part of Subsurface Biogeochemical Research Program’s Scientific Focus Area (SFA) at the Pacific Northwest National Laboratory (PNNL). PNNL is operated for DOE by Battelle under contract DE-AC06-76RLO 1830

Do clusters contain a large population of dwarf galaxies?

We analyze systematic effects in the determination of the galaxy luminosity function in clusters using a deep mock catalogue constructed from a numerical simulation of a hierarchical universe. The results indicate a strong tendency to derive a rising faint end (\alpha \lsim -1.5) in clusters selected in two dimensions, using a galaxy catalogue constructed with a universal flat luminosity function with $\alpha \simeq -1.0$. This is due to the projection effects inherent in catalogues of clusters constructed using 2 dimensional data. Many of the clusters found in 2d have no significant 3d counterparts, and most suffer from massive background contamination that cannot be corrected for by subtracting random offset fields. The luminosity function of high surface brightness galaxies in the field and within small groups follows a Schechter function with a fairly flat faint end slope, $n(L)\propto L^{\alpha}$ with $\alpha = -0.9$ to -1.2. On the contrary, observational studies of clusters constructed using Abell, EDCC and APM catalogues are systematically found to have steeper luminosity functions with $\alpha = -1.4$ to -2.0. This may be attributed to projection effects rather than a dominant population of high surface brightness dwarf galaxies (M\gsim M^*+2) in clusters. It should be straighforward to confirm our results by measuring redshifts of these faint cluster galaxies.Comment: 23 pages, 7 Postscript figures TeX, accepted for publication in the Astrophysical Journal, e-mail:[email protected] http://iate.oac.uncor.edu/cv.htm

Active Brownian Particles. From Individual to Collective Stochastic Dynamics

We review theoretical models of individual motility as well as collective dynamics and pattern formation of active particles. We focus on simple models of active dynamics with a particular emphasis on nonlinear and stochastic dynamics of such self-propelled entities in the framework of statistical mechanics. Examples of such active units in complex physico-chemical and biological systems are chemically powered nano-rods, localized patterns in reaction-diffusion system, motile cells or macroscopic animals. Based on the description of individual motion of point-like active particles by stochastic differential equations, we discuss different velocity-dependent friction functions, the impact of various types of fluctuations and calculate characteristic observables such as stationary velocity distributions or diffusion coefficients. Finally, we consider not only the free and confined individual active dynamics but also different types of interaction between active particles. The resulting collective dynamical behavior of large assemblies and aggregates of active units is discussed and an overview over some recent results on spatiotemporal pattern formation in such systems is given.Comment: 161 pages, Review, Eur Phys J Special-Topics, accepte

Organic residue analysis of Egyptian votive mummies and their research potential

YesVast numbers of votive mummies were produced in Egypt during the Late Pharaonic, Ptolemaic, and Roman periods. Although millions remain in situ, many were removed and have ultimately entered museum collections around the world. There they have often languished as uncomfortable reminders of antiquarian practices with little information available to enhance their value as artefacts worthy of conservation or display. A multi-disciplinary research project, based at the University of Manchester, is currently redressing these issues. One recent aspect of this work has been the characterization of natural products employed in the mummification of votive bundles. Using gas chromatography–mass spectrometry and the well-established biomarker approach, analysis of 24 samples from 17 mummy bundles has demonstrated the presence of oils/fats, natural waxes, petroleum products, resinous exudates, and essential oils. These results confirm the range of organic materials employed in embalming and augment our understanding of the treatment of votives. In this first systematic initiative of its kind, initial findings point to possible trends in body treatment practices in relation to chronology, geography, and changes in ideology which will be investigated as the study progresses. Detailed knowledge of the substances used on individual bundles has also served to enhance their value as display items and aid in their conservation.RCB is supported by a PhD studentship from the Art and Humanities Research Council (43019R00209). L.M. and S.A.W. are supported by a Leverhulme Trust Research Project Award (RPG-2013-143)

NFV, an HIV-1 protease inhibitor, induces growth arrest, reduced Akt signalling, apoptosis and docetaxel sensitisation in NSCLC cell lines

HIV-1 protease inhibitor (PI), nelfinavir (NFV) induced growth arrest and apoptosis of NCI-H460 and -H520, A549, EBC-1 and ABC-1 non-small-cell lung cancer (NSCLC) cells in association with upregulation of p21waf1, p27 kip1 and p53, and downregulation of Bcl-2 and matrix metalloproteinase (MMP)-2 proteins. We found that NFV blocked Akt signalling in these cells as measured by Akt kinase assay with glycogen synthase kinase-3α/β (GSK-3α/β) as a substrate. To explore the role of Akt signalling in NFV-mediated growth inhibition of NSCLC cells, we blocked this signal pathway by transfection of Akt small interfering RNA (siRNA) in these cells; transient transfection of Akt siRNA in NCI-H460 cells decreased the level of Bcl-2 protein and slowed their proliferation compared to the nonspecific siRNA-transfected cells. Conversely, forced-expression of Akt partially reversed NFV-mediated growth inhibition of these cells, suggesting that Akt may be a molecular target of NFV in NSCLC cells. Also, we found that inhibition of Akt signalling by NFV enhanced the ability of docetaxel to inhibit the growth of NCI-H460 and -H520 cells, as measured by MTT assay. Importantly, NFV slowed the proliferation and induced apoptosis of NCI-H460 cells present as tumour xenografts in nude mice without adverse systemic effects. Taken together, this family of compounds might be useful for the treatment of individuals with NSCLC