StyleID: Identity Disentanglement for Anonymizing Faces

Privacy of machine learning models is one of the remaining challenges that hinder the broad adoption of Artificial Intelligent (AI). This paper considers this problem in the context of image datasets containing faces. Anonymization of such datasets is becoming increasingly important due to their central role in the training of autonomous cars, for example, and the vast amount of data generated by surveillance systems. While most prior work de-identifies facial images by modifying identity features in pixel space, we instead project the image onto the latent space of a Generative Adversarial Network (GAN) model, find the features that provide the biggest identity disentanglement, and then manipulate these features in latent space, pixel space, or both. The main contribution of the paper is the design of a feature-preserving anonymization framework, StyleID, which protects the individuals' identity, while preserving as many characteristics of the original faces in the image dataset as possible. As part of the contribution, we present a novel disentanglement metric, three complementing disentanglement methods, and new insights into identity disentanglement. StyleID provides tunable privacy, has low computational complexity, and is shown to outperform current state-of-the-art solutions.Comment: Accepted to Privacy Enhancing Technologies Symposium (PETS), July 2023. Will appear in Proceedings on Privacy Enhancing Technologies (PoPETs), volume 1, 2023. 15 pages including references and appendix, 16 figures, 5 table

Carbon monoxide in the solar atmosphere I. Numerical method and two-dimensional models

The radiation hydrodynamic code CO5BOLD has been supplemented with the time-dependent treatment of chemical reaction networks. Advection of particle densities due to the hydrodynamic flow field is also included. The radiative transfer is treated frequency-independently, i.e. grey, so far. The upgraded code has been applied to two-dimensional simulations of carbon monoxide (CO) in the non-magnetic solar photosphere and low chromosphere. For this purpose a reaction network has been constructed, taking into account the reactions which are most important for the formation and dissociation of CO under the physical conditions of the solar atmosphere. The network has been strongly reduced to 27 reactions, involving the chemical species H, H2, C, O, CO, CH, OH, and a representative metal. The resulting CO number density is highest in the cool regions of the reversed granulation pattern at mid-photospheric heights and decreases strongly above. There, the CO abundance stays close to a value of 8.3 on the usual logarithmic abundance scale with [H]=12 but is reduced in hot shock waves which are a ubiquitous phenomenon of the model atmosphere. For comparison, the corresponding equilibrium densities have been calculated, based on the reaction network but also under assumption of instantaneous chemical equilibrium by applying the Rybicki & Hummer (RH) code by Uitenbroek (2001). Owing to the short chemical timescales, the assumption holds for a large fraction of the atmosphere, in particular the photosphere. In contrast, the CO number density deviates strongly from the corresponding equilibrium value in the vicinity of chromospheric shock waves. Simulations with altered reaction network clearly show that the formation channel via hydroxide (OH) is the most important one under the conditions of the solar atmosphere.Comment: 15 pages, 6 figures, final version will contain online materia

AnonFACES: Anonymizing Faces Adjusted to Constraints on Efficacy and Security

Image data analysis techniques such as facial recognition can threaten individuals’ privacy. Whereas privacy risks often can be reduced by adding noise to the data, this approach reduces the utility of the images. For this reason, image de-identification techniques typically replace directly identifying features (e.g., faces, car number plates) present in the data with synthesized features, while still preserving other non-identifying features. As of today, existing techniques mostly focus on improving the naturalness of the generated synthesized images, without quantifying their impact on privacy. In this paper, we propose the first methodology and system design to quantify, improve, and tune the privacy-utility trade-off, while simultaneously also improving the naturalness of the generated images. The system design is broken down into three components that address separate but complementing challenges. This includes a two-step cluster analysis component to extract low-dimensional feature vectors representing the images (embedding) and to cluster the images into fixed-sized clusters. While the importance of good clustering mostly has been neglected in previous work, we find that our novel approach of using low-dimensional feature vectors can improve the privacy-utility trade-off by better clustering similar images. The use of these embeddings has been found particularly useful when wanting to ensure high naturalness and utility of the synthetically generated images. By combining improved clustering and incorporating StyleGAN, a state-of-the-art Generative Neural Network, into our solution, we produce more realistic synthesized faces than prior works, while also better preserving properties such as age, gender, skin tone, or even emotional expressions. Finally, our iterative tuning method exploits non-linear relations between privacy and utility to identify good privacy-utility trade-offs. We note that an example benefit of these improvements is that our solution allows car manufacturers to train their autonomous vehicles while complying with privacy laws

Impact of Genetic Polymorphisms on the Smoking-related Risk of Periodontal Disease: the Population-based Study SHIP

Periodontitis is a bacterial inflammatory disease leading to attachment loss with the consequence of tooth loss. There exists a multifactorial risk pattern including bacterial challenge, smoking, age, sex, diabetes, socio-economic and genetic factors. Smoking has the highest impact on the course of the disease modulated by all the other factors. Here, we report the relationship between smoking and the polymorphisms of genetic polymorphisms inflicted in the pathogenesis

Screening masses in quenched (2+1)d Yang-Mills theory: universality from dynamics?

We compute the spectrum of gluonic screening-masses in the $0^{++}$ channel of quenched 3d Yang-Mills theory near the phase-transition. Our finite-temperature lattice simulations are performed at scaling region, using state-of-art techniques for thermalization and spectroscopy, which allows for thorough data extrapolations to thermodynamic limit. Ratios among mass-excitations with the same quantum numbers on the gauge theory, 2d Ising and $\lambda\phi^{4}$ models are compared, resulting in a nice agreement with predictions from universality. In addition, a gauge-to-scalar mapping, previously employed to fit QCD Green's functions at deep IR, is verified to dynamically describe these universal spectroscopic patternsComment: 15 pages, 4 eps figures. Revised version, to appear in Nucl. Phys.

Variation in resistance to multiple pathogen species:anther-smuts of Silene uniflora

The occurrence of multiple pathogen species on a shared host species is unexpected when they exploit the same micro-niche within the host individual. One explanation for such observations is the presence of pathogen-specific resistances segregating within the host population into sites that are differentially occupied by the competing pathogens. This study used experimental inoculations to test whether specific resistances may contribute to the maintenance of two species of anther-smut fungi, Microbotryum silenes-inflatae and Microbotryum lagerheimii, in natural populations of Silene uniflora in England and Wales. Overall, resistance to the two pathogens was strongly positively correlated among host populations and to a lesser degree among host families within populations. A few instances of specific resistance were also observed and confirmed by replicated inoculations. The results suggest that selection for resistance to one pathogen may protect the host from the emergence via host shifts of related pathogen species, and conversely that co-occurrence of two species of pathogens may be dependent on the presence of host genotypes susceptible to both

A Call to Action on Prediabetes

Diabetes and prediabetes have become an epidemic in the United States. The keys to battling this public health challenge are effective screening and evidence-based interventions. Studies show that intensive lifestyle interventions, medications, and weight loss surgery can reduce or delay new-onset type 2 diabetes. This article reviews the steps clinicians can take to help patients stay ahead of this disease

Intrinsic ripples in graphene

The stability of two-dimensional (2D) layers and membranes is subject of a long standing theoretical debate. According to the so called Mermin-Wagner theorem, long wavelength fluctuations destroy the long-range order for 2D crystals. Similarly, 2D membranes embedded in a 3D space have a tendency to be crumpled. These dangerous fluctuations can, however, be suppressed by anharmonic coupling between bending and stretching modes making that a two-dimensional membrane can exist but should present strong height fluctuations. The discovery of graphene, the first truly 2D crystal and the recent experimental observation of ripples in freely hanging graphene makes these issues especially important. Beside the academic interest, understanding the mechanisms of stability of graphene is crucial for understanding electronic transport in this material that is attracting so much interest for its unusual Dirac spectrum and electronic properties. Here we address the nature of these height fluctuations by means of straightforward atomistic Monte Carlo simulations based on a very accurate many-body interatomic potential for carbon. We find that ripples spontaneously appear due to thermal fluctuations with a size distribution peaked around 70 \AA which is compatible with experimental findings (50-100 \AA) but not with the current understanding of stability of flexible membranes. This unexpected result seems to be due to the multiplicity of chemical bonding in carbon.Comment: 14 pages, 6 figure

Anomalous dependence of the c-axis polarized Fe B1g_{1g} phonon mode with Fe and Se concentrations in Fe1+y_{1+y}Te1−x_{1-x}Sex_x

We report an investigation of the lattice dynamical properties in a range of Fe$_{1+y}$Te$_{1-x}$Se$_{x}$ compounds, with special emphasis on the c-axis polarized vibration of Fe with B$_{1g}$ symmetry, a Raman active mode common to all families of Fe-based superconductors. We have carried out a systematic study of the temperature dependence of this phonon mode as a function of Se $x$ and excess Fe $y$ concentrations. In parent compound Fe$_{1+y}$Te, we observe an unconventional broadening of the phonon between room temperature and magnetic ordering temperature $T_N$. The situation smoothly evolves towards a regular anharmonic behavior as Te is substituted for Se and long range magnetic order is replaced by superconductivity. Irrespective to Se contents, excess Fe is shown to provide an additional damping channel for the B$_{1g}$ phonon at low temperatures. We performed Density Functional Theory (DFT) ab-initio calculations within the local density approximation (LDA) to calcuate the phonon frequencies including magnetic polarization and Fe non-stoichiometry in the Virtual Crystal Approximation (VCA). We obtained a good agreement with the measured phonon frequencies in the Fe-deficient samples, while the effects of Fe excess are poorly reproduced. This may be due to excess Fe-induced local magnetism and low energy magnetic fluctuations that can not be treated accurately within these approaches. As recently revealed by neutron scattering and $\mu$-SR studies, these phenomena occur in the temperature range where anomalous decay of the B$_{1g}$ phonon is observed, and suggests a peculiar coupling of this mode with local moments and spin fluctuations in Fe$_{1+y}$Te$_{1-x}$Se$_{x}$

Nucleus pulposus phenotypic markers to determine stem cell differentiation : fact or fiction?

Progress in mesenchymal stem cell (MSC) based therapies for nucleus pulposus (NP) regeneration are hampered by a lack of understanding and consensus of the normal NP cell phenotype. Despite the recent consensus paper on NP markers, there is still a need to further validate proposed markers. This study aimed to determine whether an NP phenotypic profile could be identified within a large population of mature NP samples. qRT-PCR was conducted to assess mRNA expression of 13 genes within human non-degenerate articular chondrocytes (AC) (n=10) and NP cells extracted from patients across a spectrum of histological degeneration grades (n=71). qRT-PCR results were used to select NP marker candidates for protein expression analysis. Differential expression at mRNA between AC and non-degenerate NP cells was only observed for Paired Box Protein 1 (PAX1) and Forkhead box F1 (FOXF1). In contrast no other previously suggested markers displayed differential expression between non-degenerate NP and AC at mRNA level. PAX1 and FOXF1 protein expression was significantly higher in the NP compared to annulus fibrosus (AF), cartilaginous endplate (CEP) and AC. In contrast Laminin-5 (LAM-332), Keratin-19 (KRT-19) and Hypoxia Inducible Factor 1 alpha (HIF1α) showed no differential expression in NP cells compared with AC cells. A marker which exclusively differentiates NP cells from AF and AC cells remains to be identified, raising the question: is the NP a heterogeneous population of cells? Or does the natural biological variation during IVD development, degeneration state and even the life cycle of cells make finding one definitive marker impossible