Miracle-dz/UniFAR-FTUs huggingface dataset:
Privacy Vulnerability of Split Computing to Data-Free Model Inversion Attacks

Mobile edge devices see increased demands in deep neural networks (DNNs) inference while suffering from stringent constraints in computing resources. Split computing (SC) emerges as a popular approach to the issue by executing only initial layers on devices and offloading the remaining to the cloud. Prior works usually assume that SC offers privacy benefits as only intermediate features, instead of private data, are shared from devices to the cloud. In this work, we debunk this SC-induced privacy protection by (i) presenting a novel data-free model inversion method and (ii) demonstrating sample inversion where private data from devices can still be leaked with high fidelity from the shared feature even after tens of neural network layers. We propose Divide-and-Conquer Inversion (DCI) which partitions the given deep network into multiple shallow blocks and inverts each block with an inversion method. Additionally, cycle-consistency technique is introduced by re-directing the inverted results back to the model under attack in order to better supervise the training of the inversion modules. In contrast to prior art based on generative priors and computation-intensive optimization in deriving inverted samples, DCI removes the need for real device data and generative priors, and completes inversion with a single quick forward pass over inversion modules. For the first time, we scale data-free and sample-specific inversion to deep architectures and large datasets for both discriminative and generative networks. We perform model inversion attack to ResNet and RepVGG models on ImageNet and SNGAN on CelebA and recover the original input from intermediate features more than 40 layers deep into the network.
Leveraging QA Datasets to Improve Generative Data Augmentation

The ability of generative language models (GLMs) to generate text has improved considerably in the last few years, enabling their use for generative data augmentation. In this work, we propose CONDA, an approach to further improve GLM’s ability to generate synthetic data by reformulating data generation as context generation for a given question-answer (QA) pair and leveraging QA datasets for training context generators. Then, we cast downstream tasks into the same question answering format and adapt the fine-tuned context generators to the target task domain. Finally, we use the fine-tuned GLM to generate relevant contexts, which are in turn used as synthetic training data for their corresponding tasks. We perform extensive experiments on multiple classification datasets and demonstrate substantial improvements in performance for both few- and zero-shot settings. Our analysis reveals that QA datasets that require high-level reasoning abilities (e.g., abstractive and common-sense QA datasets) tend to give the best boost in performance in both few-shot and zero-shot settings.
Eigen Memory Trees

This work introduces the Eigen Memory Tree (EMT), a novel online memory model for sequential learning scenarios. EMTs store data at the leaves of a binary tree and route new samples through the structure using the principal components of previous experiences, facilitating efficient (logarithmic) access to relevant memories. We demonstrate that EMT outperforms existing online memory approaches, and provide a hybridized EMT-parametric algorithm that enjoys drastically improved performance over purely parametric methods with nearly no downsides. Our findings are validated using 206 datasets from the OpenML repository in both bounded and infinite memory budget situations.
The Richness-dependent Cluster Correlation Function: Early Sloan Digital Sky Survey Data

The cluster correlation function and its richness dependence are determined from 1108 clusters of galaxies—the largest sample of clusters studied so far—found in 379 deg2 of Sloan Digital Sky Survey early data. The results are compared with previous samples of optically and X-ray-selected clusters. The richness-dependent correlation function increases monotonically from an average correlation scale of ~12 h-1 Mpc for poor clusters to ~25 h-1 Mpc for the richer, more massive clusters with a mean separation of ~90 h-1 Mpc. X-ray-selected clusters suggest slightly stronger correlations than optically selected clusters (~2 σ). The results are compared with large-scale cosmological simulations. The observed richness-dependent cluster correlation function is well represented by the standard flat Λ-dominated cold dark matter (LCDM) model (Ωm ≃ 0.3, h ≃ 0.7) and is inconsistent with the considerably weaker correlations predicted by Ωm = 1 models. An analytic relation for the correlation scale versus cluster mean separation, r0-d, that best describes the observations and the LCDM prediction is r0 ≃ 2.6 (for d ≃ 20-90 h-1 Mpc). Data from the complete Sloan Digital Sky Survey, when available, will greatly enhance the accuracy of the results and allow a more precise determination of cosmological parameters.
On the localization properties of an RPWELL gas-avalanche detector

A study of the localization properties of a single-element Resistive Plate WELL (RPWELL) detector is presented. The detector comprises of a single-sided THick Gaseous Electron Multiplier (THGEM) coupled to a segmented readout anode through a doped silicate-glass plate of 1010 Ω⋅cm bulk resistivity. Operated in ambient \nech gas, the detector has been investigated with 150 GeV muons at CERN-SPS. Signals induced through the resistive plate on anode readout strips were recorded with APV25/SRS electronics. The experimental results are compared with that of Monte Carlo simulations. The effects of various physics phenomena on the position resolution are discussed. The measured position resolution in the present configuration is 0.28 mm RMS—compatible with the holes-pattern of the multiplier. Possible ways for improving the detector position resolution are suggested.
Modeling CO, CO2, and H2O Ice Abundances in the Envelopes of Young Stellar Objects in the Magellanic Clouds

Massive young stellar objects (MYSOs) in the Magellanic Clouds show infrared absorption features corresponding to significant abundances of CO, CO2, and H2O ice along the line of sight, with the relative abundances of these ices differing between the Magellanic Clouds and the Milky Way. CO ice is not detected toward sources in the Small Magellanic Cloud, and upper limits put its relative abundance well below sources in the Large Magellanic Cloud and the Milky Way. We use our gas-grain chemical code MAGICKAL, with multiple grain sizes and grain temperatures, and further expand it with a treatment for increased interstellar radiation field intensity to model the elevated dust temperatures observed in the MCs. We also adjust the elemental abundances used in the chemical models, guided by observations of H ii regions in these metal-poor satellite galaxies. With a grid of models, we are able to reproduce the relative ice fractions observed in MC MYSOs, indicating that metal depletion and elevated grain temperature are important drivers of the MYSO envelope ice composition. Magellanic Cloud elemental abundances have a subgalactic C/O ratio, increasing H2O ice abundances relative to the other ices; elevated grain temperatures favor CO2 production over H2O and CO. The observed shortfall in CO in the Small Magellanic Cloud can be explained by a combination of reduced carbon abundance and increased grain temperatures. The models indicate that a large variation in radiation field strength is required to match the range of observed LMC abundances. CH3OH abundance is found to be enhanced in low-metallicity models, providing seed material for complex organic molecule formation in the Magellanic Clouds.
Musical Meter Induces Interbrain Synchronization during Interpersonal Coordination

Abstract Music induces people to coordinate with one another. Here, we conduct two experiments to examine the underlying mechanism of the interbrain synchronization (IBS) that is induced by interpersonal coordination when people are exposed to musical beat and meter. In experiment 1, brain signals at the frontal cortex were recorded simultaneously from two participants of a dyad by using functional near-infrared spectroscopy (fNIRS) hyperscanning, while each tapped their fingers to aural feedback from their partner (coordination task) or from themselves (independence task) with and without the musical meter. The results showed enhanced IBS at the left-middle frontal cortex in case of the coordination task with musical beat and meter. The IBS was significantly correlated with the participants performance in terms of coordination. In experiment 2, we further examined the IBS while the participants coordinated their behaviors in various metrical contexts, such as strong and weak meters (i.e., high/low loudness of acoustically accenting beats). The results showed that strong meters elicited higher IBS at the middle frontal cortex than weak meters. These findings reveal that the musical beat and meter can affect brain-to-brain coupling in action coordination between people, and provide insights into the interbrain mechanism underlying the effects of music on cooperation.
Neural encoding of novel social networks: evidence that perceivers prioritize others’ centrality

Abstract Knowledge of someone’s friendships can powerfully impact how one interacts with them. Previous research suggests that information about others’ real-world social network positions—e.g. how well-connected they are (centrality), ‘degrees of separation’ (relative social distance)—is spontaneously encoded when encountering familiar individuals. However, many types of information covary with where someone sits in a social network. For instance, strangers’ face-based trait impressions are associated with their social network centrality, and social distance and centrality are inherently intertwined with familiarity, interpersonal similarity and memories. To disentangle the encoding of the social network position from other social information, participants learned a novel social network in which the social network position was decoupled from other factors and then saw each person’s image during functional magnetic resonance imaging scanning. Using representational similarity analysis, we found that social network centrality was robustly encoded in regions associated with visual attention and mentalizing. Thus, even when considering a social network in which one is not included and where centrality is unlinked from perceptual and experience-based features to which it is inextricably tied in naturalistic contexts, the brain encodes information about others’ importance in that network, likely shaping future perceptions of and interactions with those individuals.
Stable Outcomes of Generic Games in Extensive Form

We apply Mertens' dedinition of stability for a game in strategic form to a game in extensive form with perfect recall. We prove that if payoffs are generic then the outcomes of stable sets of equilibria defined via homological essentiality by Mertens coincide with those defined via homotopic essentiality. This implies that for such games various definitions of stability in terms of perturbations of players' strategies as in Mertens or best-reply correspondences as in Govindan and Wilson yield the same outcomes. A corollary yields a computational test that usually suffices to identify the stable outcomes of such a game.
A submillimetre survey of the star formation history of radio galaxies

We present the results of the first major systematic submillimetre survey of radio galaxies spanning the redshift range 1 2.5, and the average submillimetre luminosity rises at a rate ∝(1+z)3 out to z≃4. Moreover, our extensive sample allows us to argue that this behaviour is not driven by underlying correlations with other radio galaxy properties such as radio power, radio spectral index, or radio source size/age. Although radio selection may introduce other more subtle biases, the redshift distribution of our detected objects is in fact consistent with the most recent estimates of the redshift distribution of comparably bright submillimetre sources discovered in blank field surveys. The evolution of submillimetre luminosity found here for radio galaxies may thus be representative of massive ellipticals in general.
Variations on Debris Disks. IV. An Improved Analytical Model for Collisional Cascades

We derive a new analytical model for the evolution of a collisional cascade in a thin annulus around a single central star. In this model, rmax the size of the largest object changes with time, , with 0.1–0.2. Compared to standard models where rmax is constant in time, this evolution results in a more rapid decline of Md, the total mass of solids in the annulus, and Ld, the luminosity of small particles in the annulus: and . We demonstrate that the analytical model provides an excellent match to a comprehensive suite of numerical coagulation simulations for annuli at 1 au and at 25 au. If the evolution of real debris disks follows the predictions of the analytical or numerical models, the observed luminosities for evolved stars require up to a factor of two more mass than predicted by previous analytical models.
Yin and yang regulation of stress granules by Caprin-1

Significance Stress granules (SGs) are membraneless organelles regulating many vital biochemical processes. G3BP1 plays a critical role in regulating SG dynamics through its interaction with Caprin-1 and USP10. The crystal structures of the NTF2L domain of G3BP1 in complex with the G3BP1-interacting motif (GIM) of Caprin-1 and USP10 showed that both GIMs interact with the same pocket of G3BP1. Both GIMs suppressed the liquid–liquid phase separation (LLPS) of G3BP1, suggesting that Caprin-1 facilitates SG formation via other mechanisms. The C-terminal domain underwent spontaneous LLPS and promoted SG formation, whereas the N-terminal domain and GIM of Caprin-1 suppressed LLPS and SG formation. We propose that Caprin-1 regulates SG dynamics by a “yin and yang” mechanism of its N- and C-terminal domains.
Intrinsic alignment of redMaPPer clusters: cluster shape-matter density correlation

We measure the alignment of the shapes of galaxy clusters, as traced by their satellite distributions, with the matter density field using the public redMaPPer catalogue based on Sloan Digital Sky Survey–Data Release 8 (SDSS-DR8), which contains 26 111 clusters up to z ∼ 0.6. The clusters are split into nine redshift and richness samples; in each of them, we detect a positive alignment, showing that clusters point towards density peaks. We interpret the measurements within the tidal alignment paradigm, allowing for a richness and redshift dependence. The intrinsic alignment (IA) amplitude at the pivot redshift z = 0.3 and pivot richness λ = 30 is AgenIA=12.6+1.5−1.2 AIAgen=12.6−1.2+1.5 . We obtain tentative evidence that the signal increases towards higher richness and lower redshift. Our measurements agree well with results of maxBCG clusters and with dark-matter-only simulations. Comparing our results to the IA measurements of luminous red galaxies, we find that the IA amplitude of galaxy clusters forms a smooth extension towards higher mass. This suggests that these systems share a common alignment mechanism, which can be exploited to improve our physical understanding of IA.
Studying 21cm power spectrum with one-point statistics

The redshifted 21cm line signal from neutral hydrogens is a promising tool to probe the cosmic dawn and the epoch of reionization (EoR). Ongoing and future low-frequency radio experiments are expected to detect its fluctuations, especially through the power spectrum. In this paper, we give a physical interpretation of the time evolution of the power spectrum of the 21cm brightness temperature fluctuations, which can be decomposed into dark matter density, spin temperature and neutral fraction of hydrogen fluctuations. From the one-point statistics of the fluctuations, such as variance and skewness, we find that the peaks and dips in the time evolution are deeply related to X-ray heating of the intergalactic gas, which controls the spin temperature. We suggest the skewness of the brightness temperature distribution is a key observable to identify the onset of X-ray heating.
The zCOSMOS redshift survey : Influence of luminosity, mass and environment on the galaxy merger rate

The contribution of major mergers to galaxy mass assembly along cosmic time is an important ingredient to the galaxy evolution scenario. We aim to measure the evolution of the merger rate for both luminosity/mass selected galaxy samples and investigate its dependence with the local environment. We use a sample of 10644 spectroscopically observed galaxies from the zCOSMOS redshift survey to identify pairs of galaxies destined to merge, using only pairs for which the velocity difference and projected separation of both components with a confirmed spectroscopic redshift indicate a high probability of merging. We have identified 263 spectroscopically confirmed pairs with r_p^{max} = 100 h^{-1} kpc. We find that the density of mergers depends on luminosity/mass, being higher for fainter/less massive galaxies, while the number of mergers a galaxy will experience does not depends significantly on its intrinsic luminosity but rather on its stellar mass. We find that the pair fraction and merger rate increase with local galaxy density, a property observed up to redshift z=1. We find that the dependence of the merger rate on the luminosity or mass of galaxies is already present up to redshifts z=1, and that the evolution of the volumetric merger rate of bright (massive) galaxies is relatively flat with redshift with a mean value of 3*10^{-4} (8*10^{-5} respectively) mergers h^3 Mpc^{-3} Gyr^{-1}. The dependence of the merger rate with environment indicates that dense environments favors major merger events as can be expected from the hierarchical scenario. The environment therefore has a direct impact in shapping-up the mass function and its evolution therefore plays an important role on the mass growth of galaxies along cosmic time.
Disentangled Capsule Routing for Fast Part-Object Relational Saliency

Recently, the Part-Object Relational (POR) saliency underpinned by the Capsule Network (CapsNet) has been demonstrated to be an effective modeling mechanism to improve the saliency detection accuracy. However, it is widely known that the current capsule routing operations have huge computational complexity, which seriously limited the usability of the POR saliency models in real-time applications. To this end, this paper takes an early step towards a fast POR saliency inference by proposing a novel disentangled part-object relational network. Concretely, we disentangle horizontal routing and vertical routing from the original omnidirectional capsule routing, thus generating Disentangled Capsule Routing (DCR). This mechanism enjoys two advantages. On one hand, DCR that disentangles orthogonal 1D (i.e., vertical and horizontal) routing greatly reduces parameters and routing complexity, resulting in much faster inference than omnidirectional 2D routing adopted by existing CapsNets. On the other hand, thanks to the light POR cues explored by DCR, we could conveniently integrate the part-object routing process to different feature layers in CNN, rather than just applying it to the small-scaled one as in previous works. This helps to increase saliency inference accuracy. Compared to previous POR saliency detectors, DPORTNet infers visual saliency $\left ({{5 \sim 9} }\right) \times $ faster, and is more accurate. DPORTNet is available under the open-source license at https://github.com/liuyi1989/DCR.
Immunohistochemical expression of immune check point protein PDL-1 in hepatocellular carcinoma denotes its prognostic significance and association with survival

ABSTRACT This study was designed to evaluate the immunohistochemical expression of programmed death ligand-1 (PD-L1) in tumor cells (TCs) and tumor-infiltrating immune cells (TICs) in hepatocellular carcinoma (HCC) and to correlate its expression with clinicopathological parameters. Seventy-two formalin-fixed paraffin-embedded blocks of HCC were collected. The data were collected from the patients’ records. The blocks were stained with hematoxylin and eosin. Additionally, they were immunostained with PD-L1. Membranous staining was considered positive expression including the entire membrane or part of it ± cytoplasmic staining, and the percentage of total cancer cells ≥ 5% was evaluated as positive staining for TCs. The TICs were considered positive if they expressed membranous ± cytoplasmic staining of PD-L1 ≥ 1%. Of the total cases, 34.7% expressed PD-L1 positively in TCs and 15.3% expressed PD-L1 positively in TICs. Significant associations were observed between PD-L1 expression in TCs and tumor grade, capsular and/or vascular invasion, tumor stage, nodal metastasis, and the expression of PD-L1 in paracancerous tissue. The cases that positively expressed PD-L1 exhibited reduced overall survival (OS). PD-L1 was expressed in HCC TCs and TICs. Its expression in TCs was associated with higher HCC grades, advanced stages, capsular and/or vascular invasion, and nodal metastasis, and cases that expressed PD-L1 displayed reduced OS. Therefore, PD-L1 might serve as a poor prognostic indicator and a tumor immunotherapy target.
Moral Foundations Partially Explain the Associations of Machiavellianism, Grandiose Narcissism, and Psychopathy With Homonegativity and Transnegativity

ABSTRACT People with antagonistic (or “dark”) personality traits (e.g., Machiavellianism, grandiose narcissism, and psychopathy) are reportedly more racist, sexist, and xenophobic than their non-antagonistic counterparts. In the present studies (N1 = 709; N2 = 267), we examined whether people with antagonistic personality traits are also more likely to express homonegative and transnegative attitudes, and, if so, whether this can be explained by their endorsement of the moral foundations. We found that people high in Machiavellianism, grandiose narcissism, and psychopathy are more likely to endorse homonegative and transnegative views. The associations of Machiavellianism and psychopathy with homonegativity and transnegativity were primarily explained by low endorsement of individualizing moral foundations (i.e., care and fairness), while the association of narcissism with these beliefs was primarily explained by high endorsement of the binding moral foundations (i.e., loyalty, authority, and purity). These findings provide insight into the types of people who harbor homonegative and transnegative attitudes, and how differences in moral foundations contribute to these associations.