Multi-scale graph capsule with influence attention for information cascades prediction

Information cascade size prediction is one of the primary challenges for understanding the diffusion of information. Traditional feature-based methods heavily rely on the quality of handcrafted features, requiring extensive domain knowledge and hard to generalize to new domains. Recently, inspired by the success of deep learning in computer vision and natural language processing, researchers have developed neural network-based approaches for tackling this problem. However, existing deep learning-based methods either focused on modeling the temporal characteristics of cascades but ignored the structural information or failed to take the order-scale and position-scale into consideration in modeling structures of information propagation. This paper proposed a novel graph neural network-based model, called MUCas, to learn the latent representations of cascade graphs from a multi-scale perspective, which can make full use of the direction-scale, high-order-scale, position-scale, and dynamic-scale of cascades via a newly designed MUlti-scale Graph Capsule Network (MUG-Caps) and the influence-attention mechanism. Extensive experiments conducted on two real-world data sets demonstrate that our MUCas significantly outperforms the state-of-the-art approaches.Computer Science

Modeling microscopic and macroscopic information diffusion for rumor detection

Researchers have exerted tremendous effort in designing ways to detect and identify rumors automatically. Traditional approaches focus on feature engineering, which requires extensive manual efforts and are difficult to generalize to different domains. Recently, deep learning solutions have emerged as the de facto methods which detect online rumors in an end-to-end manner. However, they still fail to fully capture the dissemination patterns of rumors. In this study, we propose a novel diffusion-based rumor detection model, called Macroscopic and Microscopic-aware Rumor Detection, to explore the full-scale diffusion patterns of information. It leverages graph neural networks to learn the macroscopic diffusion of rumor propagation and capture microscopic diffusion patterns using bidirectional recurrent neural networks while taking into account the user-time series. Moreover, it leverages knowledge distillation technique to create a more informative student model and further improve the model performance. Experiments conducted on two real-world data sets demonstrate that our method achieves significant accuracy improvements over the state-of-the-art baseline models on rumor detection.Computer Science

Gut Dysbiosis in Cutaneous T-Cell Lymphoma Is Characterized by Shifts in Relative Abundances of Specific Bacterial Taxa and Decreased Diversity in More Advanced Disease

Background Cutaneous T-cell lymphoma (CTCL) patients often suffer from recurrent skin infections and profound immune dysregulation in advanced disease. The gut microbiome has been recognized to influence cancers and cutaneous conditions; however, it has not yet been studied in CTCL.ObjectivesTo investigate the gut microbiome in patients with CTCL and in healthy controls.MethodsA case-control study was conducted between January 2019 and November 2020 at Northwestern’s busy multidisciplinary CTCL clinic (Chicago, Illinois, USA) utilizing 16S ribosomal RNA gene amplicon sequencing and bioinformatics analyses to characterize the microbiota present in fecal samples of CTCL patients (n = 38) and age-matched healthy controls (n = 13) from the same geographical region.ResultsGut microbial α-diversity trended lower in patients with CTCL and was significantly lower in patients with advanced CTCL relative to controls (P = 0.015). No differences in β-diversity were identified. Specific taxa were significantly reduced in patient samples; significance was determined using adjusted P-values (q-values) that accounted for a false discovery rate threshold of 0.05. Significantly reduced taxa in patient samples included the phylum Actinobacteria (q = 0.0002), classes Coriobacteriia (q = 0.002) and Actinobacteria (q = 0.03), order Coriobacteriales (q = 0.003), and genus Anaerotruncus (q = 0.01). The families Eggerthellaceae (q = 0.0007) and Lactobacillaceae (q = 0.02) were significantly reduced in patients with high skin disease burden.ConclusionsGut dysbiosis can be seen in patients with CTCL compared to healthy controls and is pronounced in more advanced CTCL. The taxonomic shifts associated with CTCL are similar to those previously reported in atopic dermatitis and opposite those of psoriasis, suggesting microbial parallels to the immune profile and skin barrier differences between these conditions. These findings may suggest new microbial disease biomarkers and reveal a new angle for intervention

Measurement of the Atmospheric Muon Spectrum from 20 to 3000 GeV

The absolute muon flux between 20 GeV and 3000 GeV is measured with the L3 magnetic muon spectrometer for zenith angles ranging from 0 degree to 58 degree. Due to the large exposure of about 150 m2 sr d, and the excellent momentum resolution of the L3 muon chambers, a precision of 2.3 % at 150 GeV in the vertical direction is achieved. The ratio of positive to negative muons is studied between 20 GeV and 500 GeV, and the average vertical muon charge ratio is found to be 1.285 +- 0.003 (stat.) +- 0.019 (syst.).Comment: Total 32 pages, 9Figure

Administration of helper-dependent adenoviral vectors and sequential delivery of different vector serotype for long-term liver-directed gene transfer in baboons

The efficiency of first-generation adenoviral vectors as gene delivery tools is often limited by the short duration of transgene expression, which can be related to immune responses and to toxic effects of viral proteins. In addition, readministration is usually ineffective unless the animals are immunocompromised or a different adenovirus serotype is used. Recently, adenoviral vectors devoid of all viral coding sequences (helper-dependent or gutless vectors) have been developed to avoid expression of viral proteins. In mice, liver-directed gene transfer with AdSTK109, a helper-dependent adenoviral (Ad) vector containing the human α1-antitrypsin (hAAT) gene, resulted in sustained expression for longer than 10 months with negligible toxicity to the liver. In the present report, we have examined the duration of expression of AdSTK109 in the liver of baboons and compared it to first- generation vectors expressing hAAT. Transgene expression was limited to approximately 3-5 months with the first-generation vectors. In contrast, administration of AdSTK109 resulted in transgene expression for longer than a year in two of three baboons. We have also investigated the feasibility of circumventing the humoral response to the virus by sequential administration of vectors of different serotypes. We found that the ineffectiveness of readministration due to the humoral response to an Ad5 first-generation vector was overcome by use of an Ad2-based vector expressing hAAT. These data suggest that long-term expression of transgenes should be possible by combining the reduced immunogenicity and toxicity of helper-dependent vectors with sequential delivery of vectors of different serotypes

Bimeron clusters in chiral antiferromagnets

A magnetic bimeron is an in-plane topological counterpart of a magnetic skyrmion. Despite the topological equivalence, their statics and dynamics could be distinct, making them attractive from the perspectives of both physics and spintronic applications. In this work, we demonstrate the stabilization of bimeron solitons and clusters in the antiferromagnetic (AFM) thin film with interfacial Dzyaloshinskii–Moriya interaction (DMI). Bimerons demonstrate high current-driven mobility as generic AFM solitons, while featuring anisotropic and relativistic dynamics excited by currents with in-plane and out-of-plane polarizations, respectively. Moreover, these spin textures can absorb other bimeron solitons or clusters along the translational direction to acquire a wide range of Néel topological numbers. The clustering involves the rearrangement of topological structures, and gives rise to remarkable changes in static and dynamical properties. The merits of AFM bimeron clusters reveal a potential path to unify multibit data creation, transmission, storage, and even topology-based computation within the same material system, and may stimulate spintronic devices enabling innovative paradigms of data manipulations

Radiotherapy exposure directly damages the uterus and causes pregnancy loss

Female cancer survivors are significantly more likely to experience infertility than the general population. It is well established that chemotherapy and radiotherapy can damage the ovary and compromise fertility, yet the ability of cancer treatments to induce uterine damage, and the underlying mechanisms, have been understudied. Here, we show that in mice total-body γ-irradiation (TBI) induced extensive DNA damage and apoptosis in uterine cells. We then transferred healthy donor embryos into ovariectomized adolescent female mice that were previously exposed to TBI to study the impacts of radiotherapy on the uterus independent from effects to ovarian endocrine function. Following TBI, embryo attachment and implantation were unaffected, but fetal resorption was evident at midgestation in 100% of dams, suggesting failed placental development. Consistent with this hypothesis, TBI impaired the decidual response in mice and primary human endometrial stromal cells. TBI also caused uterine artery endothelial dysfunction, likely preventing adequate blood vessel remodeling in early pregnancy. Notably, when pro-apoptotic protein Puma-deficient (Puma–/–) mice were exposed to TBI, apoptosis within the uterus was prevented, and decidualization, vascular function, and pregnancy were restored, identifying PUMA-mediated apoptosis as a key mechanism. Collectively, these data show that TBI damages the uterus and compromises pregnancy success, suggesting that optimal fertility preservation during radiotherapy may require protection of both the ovaries and uterus. In this regard, inhibition of PUMA may represent a potential fertility preservation strategy.Meaghan J. Griffiths, Sarah A. Marshall, Fiona L. Cousins, Lauren R. Alesi, Jordan Higgins, Saranya Giridharan, Urooza C. Sarma, Ellen Menkhorst, Wei Zhou, Alison S. Care, Jacqueline F. Donoghue, Sarah J. Holdsworth-Carson, Peter A.W. Rogers, Evdokia Dimitriadis, Caroline E. Gargett, Sarah A. Robertson, Amy L. Winship, and Karla J. Hut

Galaxy Clusters Associated with Short GRBs. II. Predictions for the Rate of Short GRBs in Field and Cluster Early-Type Galaxies

We determine the relative rates of short GRBs in cluster and field early-type galaxies as a function of the age probability distribution of their progenitors, P(\tau) \propto \tau^n. This analysis takes advantage of the difference in the growth of stellar mass in clusters and in the field, which arises from the combined effects of the galaxy stellar mass function, the early-type fraction, and the dependence of star formation history on mass and environment. This approach complements the use of the early- to late-type host galaxy ratio, with the added benefit that the star formation histories of early-type galaxies are simpler than those of late-type galaxies, and any systematic differences between progenitors in early- and late-type galaxies are removed. We find that the ratio varies from R(cluster)/R(field) ~ 0.5 for n = -2 to ~ 3 for n = 2. Current observations indicate a ratio of about 2, corresponding to n ~ 0 - 1. This is similar to the value inferred from the ratio of short GRBs in early- and late-type hosts, but it differs from the value of n ~ -1 for NS binaries in the Milky Way. We stress that this general approach can be easily modified with improved knowledge of the effects of environment and mass on the build-up of stellar mass, as well as the effect of globular clusters on the short GRB rate. It can also be used to assess the age distribution of Type Ia supernova progenitors.Comment: ApJ accepted versio

The performance of the jet trigger for the ATLAS detector during 2011 data taking

The performance of the jet trigger for the ATLAS detector at the LHC during the 2011 data taking period is described. During 2011 the LHC provided proton–proton collisions with a centre-of-mass energy of 7 TeV and heavy ion collisions with a 2.76 TeV per nucleon–nucleon collision energy. The ATLAS trigger is a three level system designed to reduce the rate of events from the 40 MHz nominal maximum bunch crossing rate to the approximate 400 Hz which can be written to offline storage. The ATLAS jet trigger is the primary means for the online selection of events containing jets. Events are accepted by the trigger if they contain one or more jets above some transverse energy threshold. During 2011 data taking the jet trigger was fully efficient for jets with transverse energy above 25 GeV for triggers seeded randomly at Level 1. For triggers which require a jet to be identified at each of the three trigger levels, full efficiency is reached for offline jets with transverse energy above 60 GeV. Jets reconstructed in the final trigger level and corresponding to offline jets with transverse energy greater than 60 GeV, are reconstructed with a resolution in transverse energy with respect to offline jets, of better than 4 % in the central region and better than 2.5 % in the forward direction