Recommender System-Based Diffusion Inferring for Open Social Networks

Open social network (OSN) plays a more significant role in information propagation through the rapid developing of information technology. Since information diffusion is an essential process happens in OSN, it has been studied in many studies. Several models have been proposed to infer the diffusion process and reproduce diffusion network. However, these methods have two critical problems: 1) ignoring the effects of user social characteristics and 2) inaccuracy resulted from calculating the influence of different features independently. To address these limitations, a diffusion inferring method based on a recommender system (DIM-SPTF) was proposed. The DIM-SPTF method considers the propagation process between the users as the recommendation process of information and employs a recommender system to infer the propagation relationship. Through determining the propagation relations among all users in the observed topic data set, an information diffusion network can be finally obtained. Experimental results show that DIM-SPTF leads to improvements in performance compared with the state-of-the-art methods

Operation and evaluation of digitalized retail electricity markets under low-carbon transition: recent advances and challenges

With the growth of electricity consumers purchasing green energy and the development of digital energy trading platforms, the role of digitalized retail electricity markets in the low-carbon transition of electric energy systems is becoming increasingly crucial. In this circumstance, the research work on retail electricity markets needs to be further analyzed and expanded, which would facilitate the efficient decision-making of both market players and policymakers. First, this paper introduces the latest developments in the retail electricity market under low-carbon energy transition and analyzes the limitations of the existing research works. Second, from three aspects of power trading strategy, retail pricing methodology, and market risk management, it provides an overview of the existing operation and mechanism design strategies of the retail electricity market; then, it provides a systematic introduction to the evaluation system and monitoring methodology of electricity markets, which is not sufficient for the current digitalized retail electricity markets. Finally, the issues regarding operation evaluation and platform optimization of the current digitalized retail electricity market are summarized, and the research topics worth further investigations are recommended

Psychometric Properties of the Chinese Version of the Perceived Stress Scale in Policewomen

BACKGROUND: The 10-item Perceived Stress Scale (PSS-10) is one of most widely used instruments to measure a global level of perceived stress in a range of clinical and research settings. This study was conducted to examine the psychometric properties of the Simplified Chinese version of the PSS-10 in policewomen. METHODOLOGY: A total of 240 policewomen were recruited in this study. The Simplified Chinese versions of the PSS-10, the Beck Depression Inventory Revised (BDI-II), and the Beck Anxiety Inventory (BAI) were administered to all participants, and 36 of the participants were re-tested two weeks after the initial testing. PRINCIPAL FINDINGS: The overall Cronbach's alpha was 0.86, and the test-retest reliability coefficient was 0.68. Exploratory Factor Analysis (EFA) yielded 2 factors with eigenvalues of 4.76 and 1.48, accounting for 62.41% of variance. Factor 1 consisted of 6 items representing "negative feelings"; whereas Factor 2 consisted of 4 items representing "positive feelings". The item loadings ranged from 0.72 to 0.83. The Confirmatory factor analysis (CFA) indicated a very good fit of this two-factor model to this sample. The PSS-10 significantly correlated with both BDI-II and BAI, indicating an acceptable concurrent validity. CONCLUSIONS: The Simplified Chinese version of the PSS-10 demonstrated adequate psychometric properties for evaluating stress levels. The results support its use among the Chinese population

Hydrothermal Synthesis, Microstructure and Photoluminescence of Eu3+-Doped Mixed Rare Earth Nano-Orthophosphates

Eu3+-doped mixed rare earth orthophosphates (rare earth = La, Y, Gd) have been prepared by hydrothermal technology, whose crystal phase and microstructure both vary with the molar ratio of the mixed rare earth ions. For LaxY1–xPO4: Eu3+, the ion radius distinction between the La3+ and Y3+ is so large that only La0.9Y0.1PO4: Eu3+ shows the pure monoclinic phase. For LaxGd1–xPO4: Eu3+ system, with the increase in the La content, the crystal phase structure of the product changes from the hexagonal phase to the monoclinic phase and the microstructure of them changes from the nanorods to nanowires. Similarly, YxGd1–xPO4: Eu3+, Y0.1Gd0.9PO4: Eu3+ and Y0.5Gd0.5PO4: Eu3+ samples present the pure hexagonal phase and nanorods microstructure, while Y0.9Gd0.1PO4: Eu3+ exhibits the tetragonal phase and nanocubic micromorphology. The photoluminescence behaviors of Eu3+ in these hosts are strongly related to the nature of the host (composition, crystal phase and microstructure)

Household, community, sub-national and country-level predictors of primary cooking fuel switching in nine countries from the PURE study

Introduction. Switchingfrom polluting (e.g. wood, crop waste, coal)to clean (e.g. gas, electricity) cooking fuels can reduce household air pollution exposures and climate-forcing emissions.While studies have evaluated specific interventions and assessed fuel-switching in repeated cross-sectional surveys, the role of different multilevel factors in household fuel switching, outside of interventions and across diverse community settings, is not well understood. Methods.We examined longitudinal survey data from 24 172 households in 177 rural communities across nine countries within the Prospective Urban and Rural Epidemiology study.We assessed household-level primary cooking fuel switching during a median of 10 years offollow up (∼2005–2015).We used hierarchical logistic regression models to examine the relative importance of household, community, sub-national and national-level factors contributing to primary fuel switching. Results. One-half of study households(12 369)reported changing their primary cookingfuels between baseline andfollow up surveys. Of these, 61% (7582) switchedfrom polluting (wood, dung, agricultural waste, charcoal, coal, kerosene)to clean (gas, electricity)fuels, 26% (3109)switched between different polluting fuels, 10% (1164)switched from clean to polluting fuels and 3% (522)switched between different clean fuels