A Scalable Approach to Independent Vector Analysis by Shared Subspace Separation for Multi-Subject fMRI Analysis

[Abstract]: Joint blind source separation (JBSS) has wide applications in modeling latent structures across multiple related datasets. However, JBSS is computationally prohibitive with high-dimensional data, limiting the number of datasets that can be included in a tractable analysis. Furthermore, JBSS may not be effective if the data’s true latent dimensionality is not adequately modeled, where severe overparameterization may lead to poor separation and time performance. In this paper, we propose a scalable JBSS method by modeling and separating the “shared” subspace from the data. The shared subspace is defined as the subset of latent sources that exists across all datasets, represented by groups of sources that collectively form a low-rank structure. Our method first provides the efficient initialization of the independent vector analysis (IVA) with a multivariate Gaussian source prior (IVA-G) specifically designed to estimate the shared sources. Estimated sources are then evaluated regarding whether they are shared, upon which further JBSS is applied separately to the shared and non-shared sources. This provides an effective means to reduce the dimensionality of the problem, improving analyses with larger numbers of datasets. We apply our method to resting-state fMRI datasets, demonstrating that our method can achieve an excellent estimation performance with significantly reduced computational costs.The computational hardware used is part of the UMBC High Performance Computing Facility (HPCF), supported by the US NSF through the MRI and SCREMS programs (grants CNS-0821258, CNS-1228778, OAC-1726023, CNS-1920079, DMS-0821311), with additional substantial support from the University of Maryland, Baltimore County (UMBC). This work was supported by the grants NIH R01 MH118695, NIH R01 MH123610, and NIH R01 AG073949. Xunta de Galicia was supported by a postdoctoral grant No. ED481B 2022/012 and the Fulbright Program, sponsored by the US Department of State.Xunta de Galicia; ED481B 2022/01

From Adversarial Arms Race to Model-centric Evaluation: Motivating a Unified Automatic Robustness Evaluation Framework

Textual adversarial attacks can discover models' weaknesses by adding semantic-preserved but misleading perturbations to the inputs. The long-lasting adversarial attack-and-defense arms race in Natural Language Processing (NLP) is algorithm-centric, providing valuable techniques for automatic robustness evaluation. However, the existing practice of robustness evaluation may exhibit issues of incomprehensive evaluation, impractical evaluation protocol, and invalid adversarial samples. In this paper, we aim to set up a unified automatic robustness evaluation framework, shifting towards model-centric evaluation to further exploit the advantages of adversarial attacks. To address the above challenges, we first determine robustness evaluation dimensions based on model capabilities and specify the reasonable algorithm to generate adversarial samples for each dimension. Then we establish the evaluation protocol, including evaluation settings and metrics, under realistic demands. Finally, we use the perturbation degree of adversarial samples to control the sample validity. We implement a toolkit RobTest that realizes our automatic robustness evaluation framework. In our experiments, we conduct a robustness evaluation of RoBERTa models to demonstrate the effectiveness of our evaluation framework, and further show the rationality of each component in the framework. The code will be made public at \url{https://github.com/thunlp/RobTest}.Comment: Accepted to Findings of ACL 202

Field measurement of the erosion threshold of silty seabed in the intertidal flat of the Yellow River Delta with a newly-developed annular flume

Accurately measuring the critical shear stress is crucial for numerous applications, such as sediment transport modeling, erosion prediction, and the design of sustainable coastal engineering structures. However, developing reliable and precise in-situ measurement devices faces significant challenges due to the harsh and dynamic nature of aquatic environments. Factors like turbulence and waves introduce complexities that must be considered when designing and calibrating these devices. The newly developed Openable Underwater Carousel In-situ Flume (OUC-IF) was used to determine the critical shear stress (τc) and quantify erosion rates. Acoustic Doppler Velocimeter (ADV) was employed to measure 3D near-bottom velocities, which were then used to estimate and pre-calibrate bed shear stress (τ) applied on the seabed in the annular flume. Three computation methods of shear stress were evaluated: turbulent kinetic energy (TKE), direct covariance (COV), and log profile (LP). In-situ erosion experiments were conducted for the first time at two sites in the tidal flat of the Yellow River Delta (site 1 with a water depth of 1.32 m and site 2 with a water depth of 0.75 m). The critical shear stress was found to be 0.10 Pa at site 1 and 0.19 Pa at site 2, and the erosion rates of the sediments were successfully measured. The effect of wave-seabed interactions on erosion resistance was explored by theoretically estimating the wave-induced pore pressure of the seabed based on the observed data. The max liquefaction degree of the seabed at site 1 and site 2 was 0.035 and 0.057, respectively, and the average erosion coefficient Me was 2.63E-05 kg m-2s-1 at site 1 and 3.48E-05 kg m-2s-1 at site 2

The Long Noncoding RNA MALAT1 Induces Tolerogenic Dendritic Cells and Regulatory T Cells via miR155/Dendritic Cell-Specific Intercellular Adhesion Molecule-3 Grabbing Nonintegrin/IL10 Axis

By shaping T cell immunity, tolerogenic dendritic cells (tDCs) play critical roles in the induction of immune tolerance after transplantation. However, the role of long noncoding RNAs (lncRNAs) in the function and immune tolerance of dendritic cells (DCs) is largely unknown. Here, we found that the lncRNA MALAT1 is upregulated in the infiltrating cells of tolerized mice with cardiac allografts and activated DCs. Functionally, MALAT1 overexpression favored a switch in DCs toward a tolerant phenotype. Mechanistically, ectopic MALAT1 promoted dendritic cell-specific intercellular adhesion molecule-3 grabbing nonintegrin (DC-SIGN) expression by functioning as an miR155 sponge, which is essential for the tolerogenic maintenance of DCs and the DC-SIGN-positive subset with more potent tolerogenic ability. The adoptive transfer of MALAT1-overexpressing DCs promoted cardiac allograft survival and protected from the development of experimental autoimmune myocarditis, accompanied with increasing antigen-specific regulatory T cells. Therefore, overexpressed MALAT1 induces tDCs and immune tolerance in heart transplantation and autoimmune disease by the miRNA-155/DC-SIGH/IL10 axis. This study highlights that the lncRNA MALAT1 is a novel tolerance regulator in immunity that has important implications in settings in which tDCs are preferred

Administration of Interleukin-35-Conditioned Autologous Tolerogenic Dendritic Cells Prolong Allograft Survival After Heart Transplantation

Background/Aims: IL-35, a powerful suppressor of inflammation and autoimmunity, is primarily secreted by regulatory T cells (Tregs) and can, in turn, promote Treg differentiation. However, the precise effect of IL-35 on dendritic cells (DCs) remains to be clarified. Methods: In this study, we investigated the expression of IL-35 in DCs after stimulation with LPS utilizing enzyme linked immunosorbent assay(ELISA), quantitative real-time reverse transcriptase polymerase chain reaction (qRT-PCR) and western blotting, and the influence of IL-35 on the maturation and function of DCs by mixed lymphocyte reaction assay and flow cytometry. We further examined the regulation of IL-35 in DCs by the microRNA let-7i (let-7i) via transfected with let-7i mimic, inhibitor or suppressor of cytokine signalling 1 (SOCS1) siRNA. IL-35-overexpressing DCs were transfused into BALB/c recipients with C57BL/6 heart transplantations to verify the role of immune tolerance in transplantation. Results: The results showed that IL-35 expression was significantly up-regulated following lipopolysaccharide (LPS)-induced DC maturation. Overexpression of IL-35 suppressed DC maturation, promoted the secretion of anti-inflammatory cytokines, and subsequently affected the balance between Treg and Th17 cells. IL-35 expression in DCs was regulated by let-7i, which targets SOCS1. The transfusion of IL-35-transfected DCs induced Treg generation in mice and prolonged cardiac allograft survival. Conclusion: Our data demonstrated that IL-35 induces tolerogenic DCs which are capable of alleviating allograft rejection. Clinical application of IL-35-treated DCs might be a promising approach for eliciting cardiac allograft immune tolerance

Deep Learning Method Based on Spectral Characteristic Rein-Forcement for the Extraction of Winter Wheat Planting Area in Complex Agricultural Landscapes

Winter wheat is one of the most important food crops in the world. Remote sensing technology can be used to obtain the spatial distribution and planting area of winter wheat in a timely and accurate manner, which is of great significance for agricultural management. Influenced by the growth conditions of winter wheat, the planting structures of the northern and southern regions differ significantly. Therefore, in this study, the spectral and phenological characteristics of winter wheat were analyzed in detail, and four red-edge vegetation indices (NDVI, NDRE, SRre, and CIred-edge) were included after band analysis to enhance the ability of the characteristics to extract winter wheat. These indices were combined with a deep convolutional neural network (CNN) model to achieve intelligent extraction of the winter wheat planting area in a countable number of complex agricultural landscapes. Using this method, GF-6 WFV and Sentinel-2A remote sensing data were used to obtain full coverage of the region to evaluate the geographical environment differences. This spectral characteristic enhancement method combined with a CNN could extract the winter wheat data well for both data sources, with average overall accuracies of 94.01 and 93.03%, respectively. This study proposes a method for fast and accurate extraction of winter wheat in complex agricultural landscapes that can provide decision support for national and local intelligent agricultural construction. Thus, our study has important application value and practical significance

Comparative Study on the Degradation of Two Self-Polishing Antifouling Coating Systems with Copper-Based Antifouling Agents

The degradation processes of two self-polishing antifouling coatings containing copper-based agents (CuSCN and Cu2O) in 3.5% NaCl solution and the protection effect of the coating systems were studied by electrochemical impedance spectroscopy (EIS), Fourier transform infrared spectroscopy (FTIR) and scanning electron microscope (SEM/EDS) methods. The results demonstrate that after immersion for 1525 d at room temperature, the two coating systems still have very good protection property for the 5083 Al alloy substrate, manifesting by the high value of the low-frequency impedance. Alternate high and low temperature immersion test (45 °C 12 h + 25 °C 12 h) leads to serious damage to the antifouling topcoat, and the failure is mainly manifested by many micro-pores and micro-cracks. Because the CuSCN antifouling agent particle has bigger diameter and slightly higher solubility than that of Cu2O agent, the micro-pores established after the agents dissolved and released during the hydrolysis process of the antifouling coating are relatively larger, which results in more decrease in the impedance and a worse protective property of the coating system for the substrate

Insights into the photocatalytic ozonation over Ag2O-ZnO@g-C3N4 composite: Cooperative structure, degradation performance, and synergistic mechanisms

In this work, Ag2O and ZnO modified g-C3N4 (Ag2O-ZnO@CNx) catalysts were fabricated by a simple precipitation-reflux method and employed for visible-light-driven photocatalytic ozonation process towards oxalic acid (OA) degradation. A series of characterizations such as XRD, TEM, XPS, UV-vis DRS, PL, Mott- Schottky were conducted to investigate the impact of loading Ag2O-ZnO on the microstructure and catalytic properties of catalysts. It was noteworthy that the mesoporous and backbone structure did not perceptibly change after doping Ag2O-ZnO to g-C3N4. Moreover, the separation of photogenerated e h+ pairs, the mobility of e transfer, and the photocatalytic ozonation performance were improved with the increase in doping amount of g-C3N4. Amongst, the [email protected] achieved 83.43% of OA removal efficiency and the highest k value (0.0311 min 1), showing an excellent synergistic effect (synergy index η = 10.37) in this coupling system. Moreover, the [email protected] exhibited satisfactory reusability for multiple consecutive cycles (≥5). Through the radical scavenger experiments and ESR spectra, the reactive species including h+, e , O2¿ , 1O2 and ¿OH were verified to play an important role in PhOx system. Accordingly, an empirical kinetic model was established to predict OA concentration with the given operational parameters. The synergistic mechanism of OA degradation in the PhOx system was also proposed. Overall, the results presented a new insight into the application of PhOx process in water treatment

Paternal and maternal exposures to adverse childhood experiences and spontaneous fetal loss: a nationwide cross-sectional analysis

Abstract Background Adverse childhood experiences (ACEs) might be associated with maternal spontaneous fetal loss, while evidence among Chinese population is limited. This study aims to explore the associations of adverse childhood experiences (ACEs) among women and their spouses with the risk of spontaneous abortion and stillbirth. Method Data were from the China Health and Retirement Longitudinal Study (CHARLS) 2014 survey. ACEs were categorized into intra-familial ACEs and extra-familial ACEs. The associations of maternal and paternal ACEs with women’s history of spontaneous abortion and stillbirth were investigated by logistic regression. Results 7,742 women were included with 9.05% and 2.47% experiencing at least one spontaneous abortion or stillbirth, respectively. Women exposed to 2, 3, and ≥ 4 ACEs were at significantly higher odds of spontaneous abortion, with adjusted odds ratios (ORs) of 1.52 (95% [CI, Confidence Interval] 1.10–2.10), 1.50 (95% CI 1.07–2.09) and 1.68 (95% CI 1.21–2.32), respectively. A significant association between ≥ 4 maternal intra-familial ACEs and stillbirth (OR 2.23, 95% CI 1.12–4.42) was also revealed. Furthermore, paternal exposures to 3 and ≥ 4 overall ACEs were significantly associated with their wives’ history of spontaneous abortion, with adjusted ORs of 1.81 (95% CI 1.01–3.26) and 1.83 (95% CI 1.03–3.25), respectively. Conclusion Both maternal and paternal ACEs were associated with spontaneous abortion, and potential mediators might need to be considered to further explore impacts of maternal and paternal ACEs on maternal reproductive health