Fire Performance of Steel Reinforced Concrete (SRC) Structures

AbstractThis paper summarizes some of the recent research published on steel reinforced concrete (SRC) structures under or after exposure to fire. The contents include: 1) Fire resistance and post-fire behavior of SRC columns; 2) Fire performance of SRC column to beam joints, by adopting a loading sequence including initial loading, heating, cooling and post-fire loading; 3) Fire resistance and post-fire behavior of SRC composite frames

Analysis of concrete-filled stainless steel tubular columns under combined fire and loading

[EN] In fire scenarios, concrete-filled stainless steel tubular (CFSST) columns undergo initial loading at ambient temperature, loading during the heating phase as the fire develops, loading during the cooling phase as the fire dies out and continual loading after the fire. CFSST columns may fail some points during this process under combined fire and loading. In this paper, the failure modes and corresponding working mechanism of CFSST columns subjected to an entire loading and fire history are investigated. Sequentially coupled thermal-stress analyses in ABAQUS are employed to establish the temperature field and structural response of the CFSST column. To improve the precision of the finite element (FE) model, the influence of moisture on the thermal conductivity and specific heat of concrete during both the heating and cooling phases is considered using subroutines. Existing fire and post-fire test data of CFSST columns are used to validate the FE models. Comparisons between predicted and test results confirm that the accuracy of the FE models is acceptable; the FE models are then extended to simulate a typical CFSST column subjected to the entire loading and fire history. The behaviour of the CFSST column is explained by analysis of the temperature distribution, load versus axial deformation curves and failure response.The research reported in the paper is part of the Project 51308539 supported by the National Natural Science Foundation of China. The financial support is highly appreciated.Tan, Q.; Gardner, L.; Han, L.; Song, D. (2018). Analysis of concrete-filled stainless steel tubular columns under combined fire and loading. En Proceedings of the 12th International Conference on Advances in Steel-Concrete Composite Structures. ASCCS 2018. Editorial Universitat Politècnica de València. 825-833. https://doi.org/10.4995/ASCCS2018.2018.7206OCS82583

BotMoE: Twitter Bot Detection with Community-Aware Mixtures of Modal-Specific Experts

Twitter bot detection has become a crucial task in efforts to combat online misinformation, mitigate election interference, and curb malicious propaganda. However, advanced Twitter bots often attempt to mimic the characteristics of genuine users through feature manipulation and disguise themselves to fit in diverse user communities, posing challenges for existing Twitter bot detection models. To this end, we propose BotMoE, a Twitter bot detection framework that jointly utilizes multiple user information modalities (metadata, textual content, network structure) to improve the detection of deceptive bots. Furthermore, BotMoE incorporates a community-aware Mixture-of-Experts (MoE) layer to improve domain generalization and adapt to different Twitter communities. Specifically, BotMoE constructs modal-specific encoders for metadata features, textual content, and graphical structure, which jointly model Twitter users from three modal-specific perspectives. We then employ a community-aware MoE layer to automatically assign users to different communities and leverage the corresponding expert networks. Finally, user representations from metadata, text, and graph perspectives are fused with an expert fusion layer, combining all three modalities while measuring the consistency of user information. Extensive experiments demonstrate that BotMoE significantly advances the state-of-the-art on three Twitter bot detection benchmarks. Studies also confirm that BotMoE captures advanced and evasive bots, alleviates the reliance on training data, and better generalizes to new and previously unseen user communities.Comment: Accepted at SIGIR 202

Differences in diversity and community assembly processes between planktonic and benthic diatoms in the upper reach of the Jinsha River, China

Comparing spatio-temporal patterns between planktonic and benthic algae is helpful for understanding their associations and differences. However, such studies are still rare especially in large rivers. We used a dataset collected in the upper reach of the Jinsha River in different seasons to explore biodiversity and assembly processes of planktonic and benthic diatom assemblages. We found that planktonic and benthic diatoms presented different seasonal variation in species richness and community compositions. We also found evidence that planktonic and benthic diatoms were coupled in the summer. Planktonic diatom assemblages were mainly affected by spatial processes via directional spatial dispersal, especially in the summer. By comparison, benthic diatom assemblages were more affected by environmental processes. Our findings suggest that mass effect and species sorting paradigms explain the assembly processes of planktonic and benthic diatom assemblages, respectively, but the explanatory powers of these two paradigms vary seasonally. To effectively monitor and assess ecological conditions of large rivers, we recommend using benthic algae as a biotic indicator group as they had stronger correlations with environmental factors.Peer reviewe

Detecting Spoilers in Movie Reviews with External Movie Knowledge and User Networks

Online movie review platforms are providing crowdsourced feedback for the film industry and the general public, while spoiler reviews greatly compromise user experience. Although preliminary research efforts were made to automatically identify spoilers, they merely focus on the review content itself, while robust spoiler detection requires putting the review into the context of facts and knowledge regarding movies, user behavior on film review platforms, and more. In light of these challenges, we first curate a large-scale network-based spoiler detection dataset LCS and a comprehensive and up-to-date movie knowledge base UKM. We then propose MVSD, a novel Multi-View Spoiler Detection framework that takes into account the external knowledge about movies and user activities on movie review platforms. Specifically, MVSD constructs three interconnecting heterogeneous information networks to model diverse data sources and their multi-view attributes, while we design and employ a novel heterogeneous graph neural network architecture for spoiler detection as node-level classification. Extensive experiments demonstrate that MVSD advances the state-of-the-art on two spoiler detection datasets, while the introduction of external knowledge and user interactions help ground robust spoiler detection. Our data and code are available at https://github.com/Arthur-Heng/Spoiler-DetectionComment: EMNLP 202

HOFA: Twitter Bot Detection with Homophily-Oriented Augmentation and Frequency Adaptive Attention

Twitter bot detection has become an increasingly important and challenging task to combat online misinformation, facilitate social content moderation, and safeguard the integrity of social platforms. Though existing graph-based Twitter bot detection methods achieved state-of-the-art performance, they are all based on the homophily assumption, which assumes users with the same label are more likely to be connected, making it easy for Twitter bots to disguise themselves by following a large number of genuine users. To address this issue, we proposed HOFA, a novel graph-based Twitter bot detection framework that combats the heterophilous disguise challenge with a homophily-oriented graph augmentation module (Homo-Aug) and a frequency adaptive attention module (FaAt). Specifically, the Homo-Aug extracts user representations and computes a k-NN graph using an MLP and improves Twitter's homophily by injecting the k-NN graph. For the FaAt, we propose an attention mechanism that adaptively serves as a low-pass filter along a homophilic edge and a high-pass filter along a heterophilic edge, preventing user features from being over-smoothed by their neighborhood. We also introduce a weight guidance loss to guide the frequency adaptive attention module. Our experiments demonstrate that HOFA achieves state-of-the-art performance on three widely-acknowledged Twitter bot detection benchmarks, which significantly outperforms vanilla graph-based bot detection techniques and strong heterophilic baselines. Furthermore, extensive studies confirm the effectiveness of our Homo-Aug and FaAt module, and HOFA's ability to demystify the heterophilous disguise challenge.Comment: 11 pages, 7 figure

Three new shuttle vectors for heterologous expression in Zymomonas mobilis

Background: Zymomonas mobilis , as a novel platform for bio-ethanol production, has been attractedmore attention and it is very important to construct vectors for the efficient expression of foreign genes in this bacterium. Results: Three shuttle vectors (pSUZM1, pSUZM2 and pSUZM3)were first constructedwith the origins of replication from the chromosome and two native plasmids (pZZM401 and pZZM402) of Z. mobilis ZM4, respectively. The three shuttle vectorswere stable in Z. mobilis ZM4 and have 3, 32 and 27 copies, respectively. The promoter Ppdc (a), from the pyruvate decarboxylase gene,was cloned into the shuttle vectors, generating the expression vectors pSUZM1(2, 3)a. The codon-optimized glucoamylase gene from Aspergillus awamori combined with the signal peptide sequence from the alkaline phosphatase gene of Z. mobilis was cloned into pSUZM1(2, 3)a, resulting in the plasmids pSUZM1a-GA, pSUZM2a-GA and pSUZM3a-GA, respectively. After transforming these plasmids into Z. mobilis ZM4, the host was endowed with glucoamylase activity for starch hydrolysis. Both pSUZM2a-GA and pSUZM3a-GA were more efficient at producing glucoamylase than pSUZM1a-GA. Conclusions: These results indicated that these expression vectors are useful tools for gene expression in Z. mobilis and this could provide a solid foundation for further studies of heterologous gene expression in Z. mobilis

Longitudinal Variations in Physiochemical Conditions and Their Consequent Effect on Phytoplankton Functional Diversity Within a Subtropical System of Cascade Reservoirs

The social and environmental impacts of large dams are quantifiable and have been well documented, while small dams have often been presumed to be less environmentally damaging than large dams. The purpose of this study was to analyze longitudinal gradients in environmental, hydrodynamic variables and their impact on phytoplankton function, within a cascade of four reservoirs (XuanMiaoGuan, XMG; TianFuMiao, TFM; XiBeiKou, XBK; ShangJiaHe, SJH) and one reservoir bay (Huangbohe Bay, HBH), located from upstream to downstream in the Huangbo River, Hubei Province, China. Our results showed that water temperature, total nitrogen, and soluble silicate increased along the cascade reservoir system, while the concentration of dissolved oxygen and total phosphorus decreased. We identified 16 phytoplankton functional groups, and the predominant groups, including D (Synedra and Stephanodiscus hantzschii), E (Dinobryon divergens), Lo (Dinoflagellate: Peridinium bipes and Peridiniopsis), X2 (Chroomona), and Y (Cryptomonas), changed longitudinally from up to down in the cascade reservoirs. The number of dominant functional groups increased along the longitudinal gradient, indicating that the function of the phytoplankton community was more stable. Functional group D was the dominant phytoplankton functional group among the four reservoirs, and Lo group was dominant except SJH. The phytoplankton functional groups in the HBH have been completely changed due to the backwater jacking of the main stream of the Yangtze River. Euphotic depth, suspended solids, and nutrients were apparently the key factors driving variations in phytoplankton functional groups among the reservoirs. Notably, the patterns we observed were not all consistent with the cascading reservoir continuum concept (CRCC) that typically characterizes large rivers. Thus, our findings contribute to the further theoretical development of the CRCC, which may not apply widely to all cascade systems

CO-CHANGES I: IRAM 30m CO Observations of Molecular Gas in the Sombrero Galaxy

Molecular gas plays a critical role in explaining the quiescence of star formation (SF) in massive isolated spiral galaxies, which could be a result of either the low molecular gas content and/or the low SF efficiency. We present IRAM 30m observations of the CO lines in the Sombrero galaxy (NGC~4594), the most massive spiral at $d\lesssim30\rm~Mpc$. We detect at least one of the three CO lines covered by our observations in all 13 observed positions located at the galactic nucleus and along a $\sim25\rm~kpc$-diameter dusty ring. The total extrapolated molecular gas mass of the galaxy is $M_{\rm H_2}\approx4\times10^{8}\rm~M_\odot$. The measured maximum CO gas rotation velocity of $\approx379\rm~km~s^{-1}$ suggests that NGC~4594 locates in a dark matter halo with a mass $M_{\rm200}\gtrsim10^{13}\rm~M_\odot$. Comparing to other galaxy samples, NGC~4594 is extremely gas poor and SF inactive, but the SF efficiency is apparently not inconsistent with that predicted by the Kennicutt-Schmidt law, so there is no evidence of enhanced SF quenching in this extremely massive spiral with a huge bulge. We also calculate the predicted gas supply rate from various sources to replenish the cold gas consumed in SF, and find that the galaxy must experienced a starburst stage at high redshift, then the leftover or recycled gas provides SF fuels to maintain the gradual growth of the galactic disk at a gentle rate.Comment: 21 pages, 13 figures, accepted for publication in MNRA