Regulating the proper carbon-aware intervention policy is one of the keys to emission alleviation in the distribution network, whose basis lies in effectively attributing the emission responsibility using emission factors. This paper establishes the distribution locational marginal emission (DLME) to calculate the marginal change of emission from the marginal change of both active and reactive load demand for incentivizing carbon alleviation. It first formulates the day-head distribution network scheduling model based on the second-order cone program (SOCP). The emission propagation and responsibility are analyzed from demand to supply to system emission. Considering the complex and implicit mapping of the SOCP-based scheduling model, the implicit theorem is leveraged to exploit the optimal condition of SOCP. The corresponding SOCP-based implicit derivation approach is proposed to calculate the DLMEs effectively in a model-based way. Comprehensive numerical studies are conducted to verify the superiority of the proposed method by comparing its calculation efficacy to the conventional marginal estimation approach, assessing its effectiveness in carbon alleviation with comparison to the average emission factors, and evaluating its carbon alleviation ability of reactive DLME.

Background and aimTo conduct meta-analyses of all published studies on various aspects of association between vitamin D and tuberculosis (TB).MethodsPubMed and Web of Knowledge were searched for all properly controlled studies on vitamin D and TB. Pooled odds ratio, mean difference or standardized mean difference, and its corresponding 95% confidence interval were calculated with the Cochrane Review Manager 5.3.ResultsA significantly lower vitamin D level was found in TB patients vs controls; vitamin D deficiency (VDD) was associated with an increased risk of TB, although such an association was lacking in the African population and in the human immunodeficiency virus-infected African population. A significantly lower vitamin D level was found in human immunodeficiency virus-TB-coinfected African patients receiving antiretroviral treatment who developed TB-associated immune reconstitution inflammatory syndrome vs those who did not develop TB-associated immune reconstitution inflammatory syndrome. VDD was associated with an increased risk of developing active TB in those subjects with latent TB infection and with an increased risk of tuberculin skin test conversion/TB infection conversion, and the trend toward a lower vitamin D level in active TB patients vs latent TB infection subjects did not reach statistical significance, indicating that VDD was more likely a risk factor than a consequence of TB. This concept was further strengthened by our result that anti-TB treatment did not affect vitamin D level in TB patients receiving the treatment.ConclusionOur analyses revealed an association between vitamin D and TB. VDD is more likely a risk factor for TB than its consequence. More studies are needed to determine whether vitamin D supplementation is beneficial to TB prevention and treatment.

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The electric vehicle (EV) market has been growing rapidly around the world. With large scale deployment of EVs in power systems, both the grid and EV owners will benefit if the flexible demand of EV charging is properly managed through the electricity market. When EV charging demand is considerable in a grid, it will impact spot prices in the electricity market and consequently influence the charging scheduling itself. The interaction between the spot prices and the EV demand needs to be considered in the EV charging scheduling, otherwise it will lead to a higher charging cost. A day-ahead EV charging scheduling based on an aggregative game model is proposed in this paper. The impacts of the EV demand on the electricity prices are formulated with the game model in the scheduling considering possible actions of other EVs. The existence and uniqueness of the pure strategy Nash equilibrium are proved for the game. An optimization method is developed to calculate the equilibrium of the game model through quadratic programming. The optimal scheduling of the individual EV controller considering the actions of other EVs in the game is developed with the EV driving pattern distribution. Case studies with the proposed game model were carried out using real world driving data from the Danish National Travel Surveys. The impacts of the EV driving patterns and price forecasts on the EV demand with the proposed game model were also analysed. Index Terms-Aggregative game model, day-ahead market, electric vehicles (EVs), game theory, Nash equilibrium. NOMENCLATURE A. Indices and Sets: t, τ Index of time intervals. T Set of time intervals for planning. v, v , v , i, φ Index of electric vehicles (EVs). V Set of EVs in the game. Φ Set of EVs with driving pattern realizations according to the driving pattern distribution of set V. δ Cardinality of set T .