In mobile SCTP, a mobile terminal has two or more network interfaces and vertical handover occurs when it moves from one network to another. The delay due to the handover process and the slow-start ...phase of SCTP's congestion control after handover cause substantial performance degradation. If the mobile node goes back and forth frequently, excessive handovers occur and data transmission quality deteriorates. In order to provide the required level of QoS for on-going application, the frequency of handovers should be kept minimized. In this paper, we propose a transport layer handover mechanism using the mobile SCTP. We take the QoS requirements of application as the major criterion in deciding path switching. In our mechanism, the mobile node in overlapping area does not perform handover if the current network metrics satisfy the QoS requirements of on-going application. Both analytic evaluation and simulation results show that the proposed mechanism significantly improves the throughput by suppressing unnecessary handovers. Our research results can also be applied to distributed mobile sensor networks.
In location-based social network platforms, the point-of-interest(POI) recommendation is an essential function to serve users. The existing POI recommendation algorithms are rarely able to fully ...integrate various factors affecting the POI recommendation and cannot make dynamic recommendations to users over time. To address this issue, POI recommendation based on a multiple bipartite graph network model (MBR) is proposed. To reduce the overall complexity of the recommendation algorithm, we propose a clustering algorithm based on graph model, which determines the center of user clustering in the established user graph. An algorithm for finding the sparsest subgraph is built to cluster users who have social friendships or check in at similar POI, which significantly excludes more dissimilar users and makes the final recommendation more effective, as well as reducing the algorithm’s complexity. To make more accurate recommendations to users, a large heterogeneous network of six weighted bipartite graphs is built based on the user clustering to describe the relations between users’ social relationships, geographical locations of POI, and temporal information. The original Large-scale Information Network Embedding (LINE) model is too complex to be adopted for the learning of vertex embedding, thus it is optimized by negative sampling and Alias sampling methods and are fused with bipartite graphs, which accelerates the training speed. Finally, simulation experiments are conducted with the Gowalla dataset to verify the MBR algorithm, and the results show that the algorithm outperforms another three recommendation algorithms in terms of time awareness.
Location-based social networks (LBSN) is a new type of heterogeneous information network (HIN). The check-in data usually has the characteristics of a large amount of data and high sparsity. It is a ...problem worth studying how to effectively discover its complex community structure and accurately recommend it to users. Most HIN-based recommendation methods rely on path-based similarity, which cannot fully mine latent structure features of LBSN users and items. This paper proposes a meta-path-aware common clustering recommendation method MPNMF (meta-path-aware non-negative matrix factorization), based on non-negative matrix tri-factorization. By establishing the objective function based on non-negative matrix tri-factorization and second-order meta-path method, LBSN users and points of interest are integrated with their multi-dimensional heterogeneous relationships. The interrelated user clusters and interest point clusters can be obtained, effectively alleviating the influence of data sparsity. To solve the initial value problem of the model, this method uses the spectral cluster method, which provides a good initial value for the construction of the prediction model. It improves the operational efficiency of the model and the precision of model recommendations. Experiments on the real LBSN datasets show that the proposed method has a high recommendation precision and recall.
CEO compensation stickiness represents an important indicator to measure the effectiveness of compensation contracts. This study uses CEO career experience data and compensation stickiness data from ...Shanghai and Shenzhen A-share listed companies from 2015 to 2020 to investigate the compensation contracts’ effectiveness of CEOs with diverse career experiences. The findings are as follows: 1) Compensation stickiness is more pronounced for CEOs with diverse career experiences. According to the mechanism test, these CEOs with diverse career experiences can obtain compensation incentives by reducing corporate uncertainty perception and improving total factor productivity. This approach leads to increased compensation stickiness and the effectiveness of compensation contracts. CEOs with diverse career experiences may receive excess compensation by raising agency costs, which intensifies compensation stickiness and weakens the effectiveness of compensation contracts. 2) Compensation stickiness of CEOs with diverse career experiences is more significant in companies with lower investor protection, which brings about less effective compensation contracts. In contrast, in companies with higher diversification, the compensation stickiness of CEOs with diverse career experiences is more significant, which delivers more effective compensation contracts. The conclusions deepen the research of CEO compensation contracts and provide a helpful reference for CEO compensation management practices.
Cross-domain interaction in social networks and mobile applications is rapidly expanding. The demand for accessing data across multiple domains from different applications is growing. Establishing ...robust authorization and access control mechanisms within trusted domains has become a critical foundation for data security. Despite advancements in the field of identity authentication and cross-domain access, challenges persist in various application domain transition scenarios, including cumbersome and inefficient processes, and the potential for authority misuse by malicious actors in decentralized environments. To mitigate these limitations, we propose a blockchain-based scheme that leverages consensus mechanisms to enable "one-time authentication, multidomain authorization." This scheme enhances security attributes and performance in several key aspects. First, we developed a primary-secondary chain model compatible with multiple trusted domains, where the primary chain records user authentication and authorization information, and the secondary chain logs domain-specific user identity registration information. Nodes within the primary and secondary chains reach a rapid consensus on authentication outcomes through an improved consensus algorithm. Building on this model, we devised a certificateless cross-domain identity authentication method, rendering the authentication and authorization processes more secure and efficient. Additionally, to address the issue of centralized user authority, an optimized chameleon hash function was designed to facilitate identity revocation within a multicentric environment. Furthermore, security analyses and simulation validations were conducted to assess the performance of the proposed scheme. Compared to existing approaches, our scheme demonstrates reduced computational and communication overhead, substantiating its efficacy in streamlining cross-domain interactions.
Circadian clock relies on a transcription and translation feedback loop (TTFL). Two transcription factors, i.e. Bmal1 and Clock, activate the transcription of Period (Per) and Cryptochrome (Cry), ...which inhibit their own transcription when accumulated to a critical concentration. NAD+-dependent deacylase Sirt1 deacetylates Bmal1 and Per2 to regulate circadian rhythms. Sirt6 interacts with Bmal1 to regulate clock-controlled gene (CCG) expression by local chromatin remodeling. Whether Sirt6 directly modify clock components is elusive. Here, we found that loss of Sirt6 jeopardizes circadian phase. At molecular level, Sirt6 interacts with and deacetylates Per2, thus preventing its proteasomal degradation. These data highlight an important function of Sirt6 in the direct regulation of TTFL and circadian rhythms.
•SIRT6 deficiency affects cell-autonomous clocks.•SIRT6 interacts with PER2 and regulates its acetylation.•SIRT6-mediated deacetylation prevents PER2 degradation.
SaPLIγ is a natural phospholipase A2 (PLA2) inhibitor, isolated from Sinonatrix annularis, that has been demonstrated to protect against envenomation by other venomous snakes. As snake venom PLA2s ...and mammalian secretory PLA2s are similar, saPLIγ is thought to have potential to alleviate inflammatory reactions in which PLA2s act as a key enzyme for arachidonic acid release. The aim of this study was to investigate the anti-inflammatory effects and mechanisms of action of saPLIγ in an animal model of carrageenan-induced acute inflammation. The results indicated that saPLIγ inhibited PLA2 subtypes extensively, especially IIA-PLA2, in a dose-dependent manner. Paw swelling in mice was reduced markedly by intraperitoneal saPLIγ 2.5 mg/kg, and the effect was significantly better than observed with dexamethasone at the same dose. Lower neutrophil infiltration and tissue edema was observed in the paws of saPLIγ-treated mice. Additionally, carrageenan-induced cyclooxygenase-2 (COX-2) and pro-inflammatory cytokines (TNFα and IL-1β) were also significantly down-regulated by saPLIγ in a dose-dependent manner. These results suggested that saPLIγ had effective anti-inflammatory effects in vivo, and these were produced by blocking mammalian IB, IIA, V and X sPLA2 subtypes.
•SaPLIγ, a PLA2 inhibitor isolated from S. annularis, showed good inhibitory effect on mammalian inflammation..•SaPLIγ was extensive inhibitive to PLA2 subtypes, especially to IIA-PLA2 in dose-effect manner.•SaPLIγ showed a better effect than dexamethasone in preventing paw swelling and neutrophil infiltration.•Cyclooxygenase-2 (COX-2) and pro-inflammatory cytokines (TNFα, IL-1β) expression were significantly down-regulated by saPLIγ.
The gamma-type inhibitor of snake venom phospholipase A2 (PLIγ) is expressed extensively in livers of both venomous and non-venomous snakes. It is not clear why PLIγs from different snake species ...possess diverse activities. To obtain high activity PLIγs and interpret the sequence-function relationships, we used DNA shuffling to hybridize the PLIγs of Sinonatrix annularis (saPLIγ) and Elaphe carinata (ecPLIγ). Chimera PLIγs (cPLIγ) of ∼550 bp were obtained by a series of gene manipulations including DNase I digestion, primer-free PCR, and PCR amplification with PLIγs primer pair. After successful insertion of cPLIγs into pCANTAB5e phage vector, the transformed TG1 strain of Esherichia coli was achieved. The cPLIγ phage library was produced and panned in a five-pace snake venom-coated immune tube. Three high affinity cPLIγ isoforms survived two rounds of panning. Prokaryote expression by the pET28c vector was employed for production of the three cPLIγs and the two parental PLIγs. These all showed anti-hemorrhage activity with cPLIγ 2 demonstrating superior inhibition to the parent PLIγs. Sequence alignment showed that the three kinds of cPLIγ were produced by gene splicing of S. annularis and E. carinata at different sites. Primary sequence changes brought regional changes in secondary and tertiary structure, which may explain the differences in PLIγ activity.
•PLIγ can neutralize snake venom PLA2s, and is regarded as a promising antivenom candidate.•DNA shuffling and phage surface display is an effective way for PLIγ directed evolution.•The chimera PLIγ 2 showed even superior anti-hemorrhage activity than the parent PLIγs.•The α-helix of 150–155aa was believed to be correlative to the activity of PLIγ.
Abstract
Most of the detection methods against DDoS attacks are based on periodic detection, which leads to high communication overhead, untimely detection, and slow attack response. This paper ...proposes a passive abnormality detection approach. First, we record the two flow-table characteristics of the regular switches. Then, based on dynamic threshold method and Grubbs outlier test method, we make a determination of abnormal switches. This method reduces the amount of data duplication and regular traffic collection. Moreover, we use Support Vector Machine (SVM) algorithm to evaluate the performance of the passive anomaly detection method. The experiment results show a better performance than active period DDoS attack detection approaches.
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