The Factors of User Acceptance of News Feed Advertisement

With the rapid development of mobile e-commerce, the advent of news feed ads has been increasing. In view of users\u27 stereotypes about advertisements, how to improve user acceptance of news feed ads is a matter of great concern to mobile commerce operators. In the existing theoretical research, more discussions are start from the perspective of technology and channels. Based on the theory of perceived value, this study deeply analyzes the characteristics of news feed ads, and takes functional value perception, convenience value perception, prompt response value perception, trust value perception and social value perception as independent variables. Due to the variables, a user acceptance model was constructed, questionnaires were distributed and the assumptions were verified by regression analysis. The results show that perceived value theory can effectively explain the users\u27 willingness to accept ads on the mobile advertising side, of which, convenience value perception, functional value perception and social value perception have a greater impact on the willingness to accept, prompt response value perception followed, and the least impact is trust value perception

A new lookup model for multiple flow tables of open flow with implementation and optimization considerations

This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record.Open Flow has become the key standard for the southbound interface of software defined networking. The single flow table of Open Flow implementation can lead to fast storage space growth, and finally cause table-overflow, the multiple flow tables can address this problem and provide greater efficiency and flexibility. Through analyzing the potential deployment challenges of Open Flow, this paper proposes a new lookup model with implementation and optimization considerations for multiple flow tables in an Open Flow switch. With the developed lookup model, the original single flow table is split into multiple sub-flow tables, and the fields in each sub-flow table are further divided into several categories according to different field types. Preliminary simulation results demonstrate that the proposed solution can effectively reduce the storage space of flow tables

H-SOFT: a heuristic storage space optimisation algorithm for flow table of OpenFlow

PublishedThis is the peer reviewed version of the article, which has been published in final form at DOI 10.1002/cpe.3206. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.OpenFlow has become the key standard and technology for software defined networking, which has been widely adopted in various environments. However, the global deployment of OpenFlow encountered several issues, such as the increasing number of fields and complex structure of flow entries, making the size of flow table in OpenFlow switches explosively grows, which results in hardware implementation difficulty. To this end, this paper presents the modelling on the minimisation for storage space of flow table and proposes a Heuristic Storage space Optimisation algorithm for Flow Table (H-SOFT) to solve this optimisation problem. The H-SOFT algorithm degrades the complex and high-dimensional fields of a flow table into multiple flow tables with simple and low-dimensional fields based on the coexistence and conflict relationships among fields to release the unused storage space due to blank fields. Extensive simulation experiments demonstrate that the H-SOFT algorithm can effectively reduce the storage space of flow table. In particular, with frequent updates on flow entries, the storage space compression rate of flow table is stable and can achieve at ~70%. Moreover, in comparison with the optimal solution, the H-SOFT algorithm can achieve the similar compression rate with much lower execution time.National Natural Science Foundation of ChinaNational Program on Key Basic Research Project (973 Program)Strategic Priority Research Program of the Chinese Academy of SciencesNational High-Tech R&D Program of China (863 Program

Transitioning to UVM from VMM

This paper discusses the process of transitioning to a UVM design verification environment for current VMM users. Differences and parallels between the two verification methodologies are presented to show that updating to UVM is mostly a matter of learning a new DV syntax. Topics include UVM phases, agents, TLM ports, configuration, sequences, and register models. Best practices and reference resources are highlighted to make the transition from VMM to UVM as painless as possible

Printable and Versatile Superhydrophobic Paper via Scalable Nonsolvent Armor Strategy

Despite great scientific and industrial interest in waterproof cellulosic paper, its real world application is hindered by complicated and costly fabrication processes, limitations in scale-up production, and use of organic solvents. Furthermore, simultaneously achieving nonwetting properties and printability on paper surfaces still remains a technical and chemical challenge. Herein, we demonstrate a nonsolvent strategy for scalable and fast fabrication of waterproofing paper through in situ surface engineering with polysilsesquioxane nanorods (PSNR). Excellent superhydrophobicity is attained on the functionalized paper surface with water contact angle above 160˚. Notably, the engineered paper features outstanding printability and writability, as well as greatly enhanced strength and integrity upon prolonged exposure to water (tensile strength ≈ 9.0 MPa). Additionally, the PSNR concurrently armors paper-based printed items and artwork with waterproofing, self-cleaning and antimicrobial functionalities without compromising their appearance, readability and mechanical properties. We also demonstrate that the engineered paper holds the additional advantages of easy processing, low cost and mechanochemical robustness, which makes it particularly promising for real world applications

An Exploration of Phishing Information Sharing: A Heuristic-Systematic Approach

Phishing is an attempt to acquire sensitive information from a user by malicious means. The losses due to phishing have exceeded a trillion dollars globally. Social media has provided an alternate to sharing information about phishing online. However, very little attention has been paid to phishing information sharing on social media. In this paper, we explore the risk characteristics of phishing information on social media, and investigate its effect on people’s sharing of information regarding phishing. We address the research questions: (a) how do people decide which phishing information to share? (b) what aspects of phishing information are more or less consequential in influencing a user to share it? The findings suggest that the phishing messages that afford coping strategies, and come from users with higher credibility are likely to achieve higher level of sharing

Modulating Carrier Kinetics in BiVO4 Photoanodes through Molecular Co4O4 Cubane Layers

Understanding the role and immobilization of molecular catalysts on photoelectrodes is essential to use their full potential for efficient solar fuel generation. Here, a CoII4O4 cubane with proven catalytic performance and an active H2O─Co2(OR)2─OH2 edge-site moiety is immobilized on BiVO4 photoanodes through a versatile layer-by-layer assembly strategy. This delivers a photocurrent of 3.3 mA cm−2 at 1.23 VRHE and prolonged stability. Tuning the thickness of the Co4O4 layer has remarkable effects on photocurrents, dynamic open circuit potentials, and charge carrier behavior. Comprehensive-time and frequency-dependent perturbation techniques are employed to investigate carrier kinetics in transient and pseudo-steady-state operando conditions. It is revealed that the Co4O4 layer can prolong carrier lifetime, unblock kinetic limitations at the interface by suppressing recombination, and enhance charge transfer. Additionally, its flexible roles are identified as passivation/hole trapping/catalytic layer at respective lower/moderate/higher potentials. These competing functions are under dynamic equilibrium, which fundamentally defines the observed photocurrent trends

Screening, identification, and mechanism analysis of starch-degrading bacteria during curing process in tobacco leaf

Tobacco, a vital economic crop, had its quality post-curing significantly influenced by starch content. Nonetheless, the existing process parameters during curing were inadequate to satisfy the starch degradation requirements. Microorganisms exhibit inherent advantages in starch degradation, offering significant potential in the tobacco curing process. Our study concentrated on the microbial populations on the surface of tobacco leaves and in the rhizosphere soil. A strain capable of starch degradation, designated as BS3, was successfully isolated and identified as Bacillus subtilis by phylogenetic tree analysis based on 16SrDNA sequence. The application of BS3 on tobacco significantly enhanced enzyme activity and accelerated starch degradation during the curing process. Furthermore, analyses of the metagenome, transcriptome, and metabolome indicated that the BS3 strain facilitated starch degradation by regulating surface microbiota composition and affecting genes related to starch hydrolyzed protein and key metabolites in tobacco leaves. This study offered new strategies for efficiently improving the quality of tobacco leaves

Cerebrospinal fluid oligoclonal bands in Chinese patients with multiple sclerosis: the prevalence and its association with clinical features

BackgroundCerebrospinal fluid oligoclonal band (CSF-OCB) is an established biomarker in diagnosing multiple sclerosis (MS), however, there are no nationwide data on CSF-OCB prevalence and its diagnostic performance in Chinese MS patients, especially in the virtue of common standard operation procedure (SOP).MethodsWith a consensus SOP and the same isoelectric focusing system, we conducted a nationwide multi-center study on OCB status in consecutively, and recruited 483 MS patients and 880 non-MS patients, including neuro-inflammatory diseases (NID, n = 595) and non-inflammatory neurological diseases (NIND, n=285). Using a standardized case report form (CRF) to collect the clinical, radiological, immunological, and CSF data, we explored the association of CSF-OCB positivity with patient characters and the diagnostic performance of CSF-OCB in Chinese MS patients. Prospective source data collection, and retrospective data acquisition and statistical data analysis were used.Findings369 (76.4%) MS patients were OCB-positive, while 109 NID patients (18.3%) and 6 NIND patients (2.1%) were OCB-positive, respectively. Time from symptom onset to diagnosis was significantly shorter in OCB-positive than that in OCB-negative MS patients (13.2 vs 23.7 months, P=0.020). The prevalence of CSF-OCB in Chinese MS patients was significantly higher in high-latitude regions (41°-50°N)(P=0.016), and at high altitudes (>1000m)(P=0.025). The diagnostic performance of CSF-OCB differentiating MS from non-MS patients yielded a sensitivity of 76%, a specificity of 87%.InterpretationThe nationwide prevalence of CSF-OCB was 76.4% in Chinese MS patients, and demonstrated a good diagnostic performance in differentiating MS from other CNS diseases. The CSF-OCB prevalence showed a correlation with high latitude and altitude in Chinese MS patients

Recent smell loss is the best predictor of COVID-19 among individuals with recent respiratory symptoms

In a preregistered, cross-sectional study we investigated whether olfactory loss is a reliable predictor of COVID-19 using a crowdsourced questionnaire in 23 languages to assess symptoms in individuals self-reporting recent respiratory illness. We quantified changes in chemosensory abilities during the course of the respiratory illness using 0-100 visual analog scales (VAS) for participants reporting a positive (C19+; n=4148) or negative (C19-; n=546) COVID-19 laboratory test outcome. Logistic regression models identified univariate and multivariate predictors of COVID-19 status and post-COVID-19 olfactory recovery. Both C19+ and C19- groups exhibited smell loss, but it was significantly larger in C19+ participants (mean±SD, C19+: -82.5±27.2 points; C19-: -59.8±37.7). Smell loss during illness was the best predictor of COVID-19 in both univariate and multivariate models (ROC AUC=0.72). Additional variables provide negligible model improvement. VAS ratings of smell loss were more predictive than binary chemosensory yes/no-questions or other cardinal symptoms (e.g., fever). Olfactory recovery within 40 days of respiratory symptom onset was reported for ~50% of participants and was best predicted by time since respiratory symptom onset. We find that quantified smell loss is the best predictor of COVID-19 amongst those with symptoms of respiratory illness. To aid clinicians and contact tracers in identifying individuals with a high likelihood of having COVID-19, we propose a novel 0-10 scale to screen for recent olfactory loss, the ODoR-19. We find that numeric ratings ≤2 indicate high odds of symptomatic COVID-19 (4<10). Once independently validated, this tool could be deployed when viral lab tests are impractical or unavailable