Capturing the interplay between risk perception and social media posting to support risk response and decision making

This research aims to capture the interplay between risk perception and social media posting through a case study of COVID-19 in Wuhan to support risk response and decision making. Dividing users on SinaWeibo into the government, the media, the public, and other users, we address two main research questions: Whose posting affects risk perception and vice versa? How do different categories of social media users’ posts affect risk perception and vice versa? We use Granger causality analysis and impulse response functions to answer the research questions. The results show that from one perspective, the government and the media on Sina Weibo play critical roles in forming and affecting risk perceptions. From another perspective, risk perception promotes the posting of the media and the public on Sina Weibo. Since government’s posting and media’s posting can significantly enhance the public’s perceptions of risk issues, the government and the media must remain vigilant to provide credible risk-related information

Temporal, spatial, and socioeconomic dynamics in social media thematic emphases during Typhoon Mangkhut

Disaster-related social media data often consist of several themes, and each theme allows people to understand and communicate from a certain perspective. It is necessary to take into consideration the dynamics of thematic emphases on social media in order to understand the nature of such data and to use them appropriately. This paper proposes a framework to analyze the temporal, spatial, and socioeconomic disparities in thematic emphases on social media during Typhoon Mangkhut. First, the themes were identified through a latent Dirichlet allocation model during Typhoon Mangkhut. Then, we adopted a quantitative method of indexing the themes to represent the dynamics of the thematic emphases. Spearman correlation analyses between the index and eight socioeconomic variables were conducted to identify the socioeconomic disparities in thematic emphases. The main research findings are revealing. From the perspective of time evolution, Theme 1 (general response) and Theme 2 (urban transportation) hold the principal position throughout the disaster. In the early hours of the disaster, Theme 3 (typhoon status and impact) was the most popular theme, but its popularity fell sharply soon after. From the perspective of spatial distribution, people in severely affected areas were more concerned about urban transportation (Theme 2), while people in moderately affected areas were more concerned about typhoon status and impact (Theme 3) and animals and humorous news (Theme 4). The results of the correlation analyses show that there are differences in thematic emphases across disparate socioeconomic groups. Women preferred to post about typhoon status and impact (Theme 3) and animals and humorous news (Theme 4), while people with higher income paid less attention to these two themes during Typhoon Mangkhut. These findings can help government agencies and other stakeholders address public needs effectively and accurately in disaster responses

A Knowledge-Constrained Role-Based Access Control model for protecting patient privacy in hospital information systems

Current access control mechanisms of the hospital information system can hardly identify the real access intention of system users. A relaxed access control increases the risk of compromise of patient privacy. To reduce unnecessary access of patient information by hospital staff, this paper proposes a Knowledge-Constrained Role-Based Access Control (KCRBAC)model in which a variety of medical domain knowledge is considered in access control. Based on the proposed Purpose Tree and knowledge-involved algorithms, the model can dynamically define the boundary of access to the patient information according to the context, which helps protect patient privacy by controlling access. Compared with the Role-Based Access Control model, KC-RBAC can effectively protectpatient information according to the results of the experiments

Neural Dependencies Emerging from Learning Massive Categories

This work presents two astonishing findings on neural networks learned for large-scale image classification. 1) Given a well-trained model, the logits predicted for some category can be directly obtained by linearly combining the predictions of a few other categories, which we call \textbf{neural dependency}. 2) Neural dependencies exist not only within a single model, but even between two independently learned models, regardless of their architectures. Towards a theoretical analysis of such phenomena, we demonstrate that identifying neural dependencies is equivalent to solving the Covariance Lasso (CovLasso) regression problem proposed in this paper. Through investigating the properties of the problem solution, we confirm that neural dependency is guaranteed by a redundant logit covariance matrix, which condition is easily met given massive categories, and that neural dependency is highly sparse, implying that one category correlates to only a few others. We further empirically show the potential of neural dependencies in understanding internal data correlations, generalizing models to unseen categories, and improving model robustness with a dependency-derived regularizer. Code for this work will be made publicly available

Integrated Sensing and Communications: Recent Advances and Ten Open Challenges

It is anticipated that integrated sensing and communications (ISAC) would be one of the key enablers of next-generation wireless networks (such as beyond 5G (B5G) and 6G) for supporting a variety of emerging applications. In this paper, we provide a comprehensive review of the recent advances in ISAC systems, with a particular focus on their foundations, system design, networking aspects and ISAC applications. Furthermore, we discuss the corresponding open questions of the above that emerged in each issue. Hence, we commence with the information theory of sensing and communications (S$\&$C), followed by the information-theoretic limits of ISAC systems by shedding light on the fundamental performance metrics. Next, we discuss their clock synchronization and phase offset problems, the associated Pareto-optimal signaling strategies, as well as the associated super-resolution ISAC system design. Moreover, we envision that ISAC ushers in a paradigm shift for the future cellular networks relying on network sensing, transforming the classic cellular architecture, cross-layer resource management methods, and transmission protocols. In ISAC applications, we further highlight the security and privacy issues of wireless sensing. Finally, we close by studying the recent advances in a representative ISAC use case, namely the multi-object multi-task (MOMT) recognition problem using wireless signals.Comment: 26 pages, 22 figures, resubmitted to IEEE Journal. Appreciation for the outstanding contributions of coauthors in the paper

Balancing the popularity bias of object similarities for personalised recommendation

Network-based similarity measures have found wide applications in recommendation algorithms and made signicant contributions for uncovering users' potential interests. However, existing measures are generally biased in terms of popularity, that the popular objects tend to have more common neighbours with others and thus are considered more similar to others. Such popularity bias of similarity quantification will result in the biased recommendations, with either poor accuracy or poor diversity. Based on the bipartite network modelling of the user-object interactions, this paper firstly calculates the expected number of common neighbours of two objects with given popularities in random networks. A Balanced Common Neighbour similarity index is accordingly developed by removing the random-driven common neighbours, estimated as the expected number, from the total number. Recommendation experiments in three data sets show that balancing the popularity bias in a certain degree can significantly improve the recommendations' accuracy and diversity simultaneously

Streptococcus suis Sequence Type 7 Outbreak, Sichuan, China

An outbreak of Streptococcus suis serotype 2 emerged in the summer of 2005 in Sichuan Province, and sporadic infections occurred in 4 additional provinces of China. In total, 99 S. suis strains were isolated and analyzed in this study: 88 isolates from human patients and 11 from diseased pigs. We defined 98 of 99 isolates as pulse type I by using pulsed-field gel electrophoresis analysis of SmaI-digested chromosomal DNA. Furthermore, multilocus sequence typing classified 97 of 98 members of the pulse type I in the same sequence type (ST), ST-7. Isolates of ST-7 were more toxic to peripheral blood mononuclear cells than ST-1 strains. S. suis ST-7, the causative agent, was a single-locus variant of ST-1 with increased virulence. These findings strongly suggest that ST-7 is an emerging, highly virulent S. suis clone that caused the largest S. suis outbreak ever described

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

The Effect of Muscle-Regulatory Factor Genes and Satellite Cell Response to Recombinant Hsp70 Protein on Megalobrama amblycephala Skeletal Muscle

Hsp70 (70-kDa heat shock protein) plays a key regulatory role in muscle development. In order to evaluate whether recombinant Hsp70 protein (rMaHsp70) of M. amblycephala could affect muscle growth by inducing the expression of Myogenin (MyoG), Myogenic Differentiation Antigen (MyoD), Myogenic factor 5 (Myf5), myogenic regulatory factor 4 (MRF4) and myostatin (MSTN) in muscle, Hsp70 was injected intraperitoneally (IP) at two concentrations: 1.0 mg/mL and 3.4 mg/mL. The mRNA and protein levels of the transcription factor Pax-7 and the protein Hsp70 initially increased, then as concentration levels of injected recombinant M. amblycephala Hsp70 protein rMaHsp70 further increased, the protein Hsp70 decreased. In order to investigate the relationship between muscle hyperplasia, hypertrophy and satellite cell growth following rMaHsp70 administration, the number of satellite cells were analyzed and revealed that the numbers of satellite cells in low concentration group (1 mg/mL) was predominantly higher than in the other concentration groups in both red and white muscle. These results suggest that low concentrations of rMaHsp70 could decrease muscle-related gene expression and increase the number of satellite cells. Our research will be helpful in adapting Hsp70 as a feed additive to enhance M. amblycephala growth

Molecular Characterization and Possible Immune Function of Two Members of Interleukin Family from Trachinotus ovatus

Interleukins (ILs) are a group of cytokines which play a core regulatory role in the immune system. In the present study, two members of the IL family, IL7 and IL8, were detected in Trachinotus ovatus. IL7 and IL8 cDNAs of T. ovatus consist of a 492 bp and 300 bp ORF (open reading frame) encoding a polypeptide of 163 and 99 amino acids, respectively. Multiple sequence alignment revealed that IL7 and IL8 contain characteristic arrangements of several conserved cysteine residues, which in T. ovatus are in positions 20, 57, 67, 105, 140, 152 and 35, 37, 61, 78, respectively. The phylogenetic tree showed that all ILs fell into four categories. Moreover, IL7 and IL8 mRNA of T. ovatus were constitutively expressed at different levels in all examined tissues, except muscle. Transcripts of IL7 were mainly expressed in liver, intestine, kidney, stomach, and fin, while transcripts of IL8 were highly detected in the eye, liver, kidney, and intestine of healthy fish. After Photobacterium damselae innoculation, mRNA levels of IL7 were higher than IL8 in the spleen and intestine, however, mRNA expression levels of IL7 were lower than IL8 in kidney 3 h post-injection. These results suggest that the two IL molecules play an important role in the inflammatory response of T. ovatus