Network Design through Graph Neural Networks: Identifying Challenges and Improving Performance

Graph Neural Network (GNN) research has produced strategies to modify a graph's edges using gradients from a trained GNN, with the goal of network design. However, the factors which govern gradient-based editing are understudied, obscuring why edges are chosen and if edits are grounded in an edge's importance. Thus, we begin by analyzing the gradient computation in previous works, elucidating the factors that influence edits and highlighting the potential over-reliance on structural properties. Specifically, we find that edges can achieve high gradients due to structural biases, rather than importance, leading to erroneous edits when the factors are unrelated to the design task. To improve editing, we propose ORE, an iterative editing method that (a) edits the highest scoring edges and (b) re-embeds the edited graph to refresh gradients, leading to less biased edge choices. We empirically study ORE through a set of proposed design tasks, each with an external validation method, demonstrating that ORE improves upon previous methods by up to 50%

On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks

Research on GNNs has highlighted a relationship between high homophily (i.e., the tendency for nodes of a similar class to connect) and strong predictive performance in node classification. However, recent research has found the relationship to be more nuanced, demonstrating that even simple GNNs can learn in certain heterophilous settings. To bridge the gap between these findings, we revisit the assumptions made in previous works and identify that datasets are often treated as having a constant homophily level across nodes. To align closer to real-world datasets, we theoretically and empirically study the performance of GNNs when the local homophily level of a node deviates at test-time from the global homophily level of its graph. To aid our theoretical analysis, we introduce a new parameter to the preferential attachment model commonly used in homophily analysis to enable the control of local homophily levels in generated graphs, enabling a systematic empirical study on how local homophily can impact performance. We additionally perform a granular analysis on a number of real-world datasets with varying global homophily levels. Across our theoretical and empirical results, we find that (a)~ GNNs can fail to generalize to test nodes that deviate from the global homophily of a graph, (b)~ high local homophily does not necessarily confer high performance for a node, and (c)~ GNN models designed to handle heterophily are able to perform better across varying heterophily ranges irrespective of the dataset's global homophily. These findings point towards a GNN's over-reliance on the global homophily used for training and motivates the need to design GNNs that can better generalize across large local homophily ranges

Studying the [OIII]λ\lambda5007A emission-line width in a sample of ∼\sim80 local active galaxies: A surrogate for σ⋆\sigma_{\star}?

For a sample of $\sim$80 local ($0.02 \leq z \leq 0.1$) Seyfert-1 galaxies with high-quality long-slit Keck spectra and spatially-resolved stellar-velocity dispersion ($\sigma_{\star}$) measurements, we study the profile of the [OIII]$\lambda$5007A emission line to test the validity of using its width as a surrogate for $\sigma_{\star}$. Such an approach has often been used in the literature, since it is difficult to measure $\sigma_{\star}$ for type-1 active galactic nuclei (AGNs) due to the AGN continuum outshining the stellar-absorption lines. Fitting the [OIII] line with a single Gaussian or Gauss-Hermite polynomials overestimates $\sigma_{\star}$ by 50-100%. When line asymmetries from non-gravitational gas motion are excluded in a double Gaussian fit, the average ratio between the core [OIII] width ($\sigma_{\rm {[OIII],D}}$) and $\sigma_{\star}$ is $\sim$1, but with individual data points off by up to a factor of two. The resulting black-hole-mass-$\sigma_{\rm {[OIII],D}}$ relation scatters around that of quiescent galaxies and reverberation-mapped AGNs. However, a direct comparison between $\sigma_{\star}$ and $\sigma_{\rm {[OIII],D}}$ shows no close correlation, only that both quantities have the same range, average and standard deviation, probably because they feel the same gravitational potential. The large scatter is likely due to the fact that line profiles are a luminosity-weighted average, dependent on the light distribution and underlying kinematic field. Within the range probed by our sample (80-260 km s$^{-1}$), our results strongly caution against the use of [OIII] width as a surrogate for $\sigma_{\star}$ on an individual basis. Even though our sample consists of radio-quiet AGNs, FIRST radio-detected objects have, on average, a $\sim$10% larger [OIII] core width.Comment: 15 pages, 10 figures, 6 tables. Accepted for publication in the Monthly Notices of the Royal Astronomical Societ

The effect of an autologous cellular gel-matrix integrated implant system on wound healing

<p>Abstract</p> <p>Background</p> <p>This manuscript reports the production and preclinical studies to examine the tolerance and efficacy of an autologous cellular gel-matrix integrated implant system (IIS) aimed to treat full-thickness skin lesions.</p> <p>Methods</p> <p>The best concentration of fibrinogen and thrombin was experimentally determined by employing 28 formula ratios of thrombin and fibrinogen and checking clot formation and apparent stability. IIS was formed by integrating skin cells by means of the <it>in situ </it>gelification of fibrin into a porous crosslinked scaffold composed of chitosan, gelatin and hyaluronic acid. The <it>in vitro </it>cell proliferation within the IIS was examined by the MTT assay and PCNA expression. An experimental rabbit model consisting of six circular lesions was utilized to test each of the components of the IIS. Then, the IIS was utilized in an animal model to cover a 35% body surface full thickness lesion.</p> <p>Results</p> <p>The preclinical assays in rabbits demonstrated that the IIS was well tolerated and also that IIS-treated rabbit with lesions of 35% of their body surface, exhibited a better survival rate (p = 0,06).</p> <p>Conclusion</p> <p>IIS should be further studied as a new wound dressing which shows promising properties, being the most remarkable its good biological tolerance and cell growth promotion properties.</p

The Lick AGN Monitoring Project 2016 : dynamical modeling of velocity-resolved Hβ lags in luminous Seyfert galaxies

K.H. acknowledges support from STFC grant ST/R000824/1.We have modeled the velocity-resolved reverberation response of the Hβ broad emission line in nine Seyfert 1 galaxies from the Lick Active Galactic Nucleus (AGN) Monitoring Project 2016 sample, drawing inferences on the geometry and structure of the low-ionization broad-line region (BLR) and the mass of the central supermassive black hole. Overall, we find that the Hβ BLR is generally a thick disk viewed at low to moderate inclination angles. We combine our sample with prior studies and investigate line-profile shape dependence, such as log10(FWHM/σ), on BLR structure and kinematics and search for any BLR luminosity-dependent trends. We find marginal evidence for an anticorrelation between the profile shape of the broad Hβ emission line and the Eddington ratio, when using the rms spectrum. However, we do not find any luminosity-dependent trends, and conclude that AGNs have diverse BLR structure and kinematics, consistent with the hypothesis of transient AGN/BLR conditions rather than systematic trends.Publisher PDFPeer reviewe