Tweeting about emergency: A semantic network analysis of government organizations’ social media messaging during Hurricane Harvey

While social media like Twitter have been increasingly adopted by public-sector organizations, it remains less explored as to how government and emergency management (EM) organizations use these platforms to communicate with the public in response to emerging natural disasters. Extending the Situational Crisis Communication Theory (SCCT) to the realm of social media, this study examines the emerging semantic networks from 67 government and EM organizations’ official tweets during Hurricane Harvey over a three-week period. It identifies how multiple crisis response strategies—including instructing information, adjusting information, and bolstering—are constituted of different issues, actions, and organizational actors before, during, and immediately after the disaster event. Results suggest that government agencies use the strategy of instructing information predominantly before and during the disaster, whereas adjusting information and bolstering strategies are utilized more during post-disaster recovery. The study offers theoretical and practical implications of using a semantic network approach to studying organizational crisis responses

Organizational Disaster Communication Ecology: Examining Interagency Coordination on Social Media During the Onset of the COVID-19 Pandemic

Interagency coordination is crucial for effective multiagency disaster management. Viewing government and emergency management organizations as vital components of citizens’ disaster communication ecology, this study examines how a group of Texas-based public health departments and emergency management offices engaged in interagency coordination during different phases of the COVID-19 pandemic. By analyzing coronavirus-related agency tweets between early February and the end of August 2020, the study assesses two types of interagency coordination: (1) contentlevel coordination in the form of semantic similarity among the selected public agencies serving different jurisdictions and (2) relational-level coordination in terms of referencing common stakeholders through retweeting coronavirus-related information. Using a granular, four-stage construct of a crisis, results identify stage-based variation with regard to peer-to-peer and federal-to-local coordination. We conclude with theoretical and practical implications for communication ecology and disaster management

Experimental Investigation on Compressive Toughness of the PVA-Steel Hybrid Fiber Reinforced Cementitious Composites

In order to achieve the whole process control of crack formation of engineered cementitious composites (ECC) under loading and improve the mechanical properties of ECC, steel fibers are mixed into traditional ECC to get polyvinyl alcohol (PVA)-steel hybrid fiber reinforced cementitious composites (HyFRCC). And the key parameters to affect the HyFRCC performance are PVA fiber content, steel fiber content, and aspect ratio of steel fiber. In order to investigate the mechanical properties of PVA-steel HyFRCC such as the compressive toughness, 15 PVA-steel HyFRCC specimens with different volume fraction of steel fiber and PVA fiber, together with 1 non-fibrous cementitious composites specimen and 3 ECC specimens with PVA fibers only for comparison were designed and uniaxial compression tests were conducted. Furthermore, the effect of fiber content, fiber type and fiber geometrical characteristic on the compressive toughness of HyFRCC were analyzed. The results show that PVA fiber content, steel fiber content and aspect ratio of steel fiber have little impact on the uniaxial compressive strength of the PVA-steel HyFRCC, while the peak strain, compressive toughness and the post-peak ductility of PVA-steel HyFRCC are improved significantly due to fiber hybridization. The formation of large scale cracks of ECC specimens after post-peak loading is restrained effectively with the addition of steel fiber. The mixture of PVA and steel fiber has a remarkable effect on the improvement of ECC compression toughness and crack control. It indicates that the energy dissipation and damage control capacity of the structural component with PVA-steel HyFRCC under seismic loading will be enhanced

ASF-Net: Robust Video Deraining via Temporal Alignment and Online Adaptive Learning

In recent times, learning-based methods for video deraining have demonstrated commendable results. However, there are two critical challenges that these methods are yet to address: exploiting temporal correlations among adjacent frames and ensuring adaptability to unknown real-world scenarios. To overcome these challenges, we explore video deraining from a paradigm design perspective to learning strategy construction. Specifically, we propose a new computational paradigm, Alignment-Shift-Fusion Network (ASF-Net), which incorporates a temporal shift module. This module is novel to this field and provides deeper exploration of temporal information by facilitating the exchange of channel-level information within the feature space. To fully discharge the model's characterization capability, we further construct a LArge-scale RAiny video dataset (LARA) which also supports the development of this community. On the basis of the newly-constructed dataset, we explore the parameters learning process by developing an innovative re-degraded learning strategy. This strategy bridges the gap between synthetic and real-world scenes, resulting in stronger scene adaptability. Our proposed approach exhibits superior performance in three benchmarks and compelling visual quality in real-world scenarios, underscoring its efficacy. The code is available at https://github.com/vis-opt-group/ASF-Net

Supplementary Material to “Distributed Consensus-based Weight Design for Cooperative Spectrum Sensing”

Abstract—This material is a supplement to the paper “Distributed Consensus-based Weight Design for Cooperative Spectrum Sensing”. Section 1 offers related literature review on cooperative spectrum sensing and consensus algorithms. Section 2 presents related notations and models of the consensus-based graph theory. Section 3 offers further analysis of the proposed spectrum sensing scheme including detection threshold settings and convergence properties in terms of detection performance. Section 4 presents the proofs for the convergence of the proposed consensus algorithm, and discusses the convergence of the proposed algorithm under random link failure network models. Section 5 shows additional simulation results

Effects of active galactic nucleus feedback on cold gas depletion and quenching of central galaxies

NSCWe investigate the influence of active galactic nucleus (AGN) feedback on the galaxy cold gas content and its connection to galaxy quenching in three hydrodynamical simulations of Illustris, IllustrisTNG, and SIMBA. By comparing to the observed atomic and molecular neutral hydrogen measurements for central galaxies, we find that Illustris overpredicts the cold gas masses in star-forming galaxies and significantly underpredicts them for quenched galaxies. IllustrisTNG performs better in this comparison than Illustris, but quenched galaxies retain too much cold gas compared with observations. SIMBA shows good agreement with observations, by depleting the global cold gas reservoir for quenched galaxies. We find that the discrepancies in IllustrisTNG are caused by its weak kinetic AGN feedback that only redistributes the cold gas from the inner disks to the outer regions and reduces the inner cold gas densities. It agrees with observations much better when only the cold gas within the stellar disk is considered to infer the star formation rates. From dependences of the cold gas reservoir on the black hole mass and Eddington ratio, we find that the cumulative energy release during the black hole growth is the dominant reason for the cold gas depletion and thus the galaxy quenching. We further measure the central stellar surface density within 1 kpc (Σ1) for the high-resolution run of IllustrisTNG and find a tight correlation between Σ1 and black hole mass. It suggests that the observed decreasing trend of cold gas mass with Σ1 is also a reflection of the black hole growth.N/

IKKbeta Deficiency in Myeloid Cells Ameliorates Alzheimer's Disease-Related Symptoms and Pathology

Alzheimer's disease (AD) is characterized by extracellular amyloid-beta (Abeta) deposits and microglia-dominated inflammatory activation. Innate immune signaling controls microglial inflammatory activities and Abeta clearance. However, studies examining innate immunity in Abeta pathology and neuronal degeneration have produced conflicting results. In this study, we investigated the pathogenic role of innate immunity in AD by ablating a key signaling molecule, IKKbeta, specifically in the myeloid cells of TgCRND8 APP-transgenic mice. Deficiency of IKKbeta in myeloid cells, especially microglia, simultaneously reduced inflammatory activation and Abeta load in the brain and these effects were associated with reduction of cognitive deficits and preservation of synaptic structure proteins. IKKbeta deficiency enhanced microglial recruitment to Abeta deposits and facilitated Abeta internalization, perhaps by inhibiting TGF-beta-SMAD2/3 signaling, but did not affect Abeta production and efflux. Therefore, inhibition of IKKbeta signaling in myeloid cells improves cognitive functions in AD mice by reducing inflammatory activation and enhancing Abeta clearance. These results contribute to a better understanding of AD pathogenesis and could offer a new therapeutic option for delaying AD progression

RNF115/BCA2 E3 Ubiquitin Ligase Promotes Breast Cancer Cell Proliferation through Targeting p21Waf1/Cip1 for Ubiquitin-Mediated Degradation

AbstractThe E3 ubiquitin ligase RING finger protein 115 (RNF115), also known as breast cancer-associated gene 2 (BCA2), has previously been reported to be overexpressed in estrogen receptor α (ERα)-positive breast tumors and to promote breast cell proliferation; however, its mechanism is unknown. In this study, we demonstrated that silencing of BCA2 by small interfering RNAs (siRNAs) in two ERα-positive breast cancer cell lines, MCF-7 and T47D, decreases cell proliferation and increases the protein levels of the cyclin-dependent kinase inhibitor p21Waf/Cip1. The protein stability of p21 was negatively regulated by BCA2. BCA2 directly interacts with p21 and promotes p21 ubiquitination and proteasomal degradation. Knockdown of p21 partially rescues the cell growth arrest induced by the BCA2 siRNA. These results suggest that BCA2 promotes ERα-positive breast cancer cell proliferation at least partially through downregulating the expression of p21