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• Aggregation and cooperation among peers will expand beyond prosumers in microgrids. • Growth in IoT and metering infrastructure is empowering end-use consumers. • Methodology allows aggregated consumers to schedule load and share energy. • Application demonstrates a significant cost reduction while assuring fairness. • Offers a novel cost-sharing strategy guided by cost minimization and Nash bargaining. End-use consumers (peers) are being empowered to aggregate for direct demand-side participation through load scheduling and energy sharing. This is the result of the growth of Internet of Things (IoT) enabled loads, availability of advanced metering infrastructure, and the move towards real-time (RT) pricing of electricity. Peer-to-peer (P2P) cooperation has received significant interest in recent years, though the focus of this growing body of research is on modeling prosumer behavior in microgrids. Hence, there is a need for new methodologies to examine empowerment of all end-use consumers (not limited to prosumers) to form aggregations and develop fair rules of cooperation to reduce cost. This paper offers an optimization based methodology to address the above need for power systems. It minimizes the total cost and considers fairness using a Nash bargaining approach. Since cost and fairness are often in conflict, trade-off strategies are also presented. The model to asses fairness is nonlinear. Hence, it is transformed into a second order cone program (SOCP) and solved using GUROBI software version 7.5.2. The methodology is implemented on a sample 5-bus network, built using price and demand data from one of the load zones of Pennsylvania, New Jersey, and Maryland (PJM) power network in the United States. It is shown that two aggregations of peers participating in the sample network can reduce their total cost by 14.17% and 22.7%, while maintaining fairness. Concluding remarks highlight some of the limitations of the methodology. [ABSTRACT FROM AUTHOR]

Abstract: Four decades ago, argued that spatial autocorrelation (i.e., local distance and configuration effects) and distance decay (i.e., global distance effects) intermingle in the estimation of spatial interaction model specifications. Today, massive computer power available with a desktop PC offers the necessary resources to account for these spatial autocorrelation effects within spatial interaction. Simple gravity model respecifications have been analyzed by and by . These results have been extended to a doubly-constrained gravity model respecification by . This paper summarizes results from a further refinement of this doubly-constrained respecification, namely differentiating within and between areal unit flows. In doing so, an eigenfunction-based spatial filter description of spatial autocorrelation is constructed, which lends itself to visualization of analytical spatial autocorrelation components. Results are illustrated with the 2000 journey-to-work dataset for the extended state of Pennsylvania, USA. [Copyright &y& Elsevier]

Daily ambient aerosol samples were taken in Pittsburgh, Pennsylvania from the summer 2001 to the winter 2002 as part of the Pittsburgh Air Quality Study (PAQS). The study measured PM2.5 mass by the Federal Reference Method (FRM) and the PM2.5 chemical composition by a variety of filter-based and continuous instruments. This paper examines the mass balance between the FRM-measured mass and the sum of the aerosol chemical components. For the 7-month study period, the average FRM-measured mass is 11% greater than the sum of the mass of the aerosol chemical components. This mass balance discrepancy varies seasonally, with the average FRM-measured mass 17% greater than the sum of the chemical components for the summer months, with discrepancies as large as 30% during certain periods. Meanwhile, the FRM-measured mass was at or slightly below the sum of the chemical components for the winter months.The mass balance discrepancy and its seasonal shift cannot be explained by measurement uncertainty; instead the discrepancy is due to combination of retained aerosol water on the conditioned FRM filters and volatilization losses. The relative importance of these different effects varies with aerosol composition and causes the observed seasonal variation in the mass balance. The contribution of the aerosol water to the FRM-measured mass is estimated using continuous measurements of aerosol water at the site; volatilization losses are estimated from other filter-based instruments. Water contributes 16% of the FRM mass in the summer, and 8% of the FRM mass in the winter; it also appears responsible for episodes where the FRM-measured mass is significantly greater than the sum of components. Retention of water is greatest during acidic conditions, which commonly occur during the summer months. Volatilization losses are estimated at 5% of the FRM mass during the summer, and 9% for the winter. Volatilization losses appear to be most significant on days dominated by organic aerosol, or winter days with relatively high nitrate concentration. Accounting for the effects of water and volatilization losses closes the mass balance between the FRM and the sum of the chemical components, providing insight into the FRM measurements. [Copyright &y& Elsevier]

The article presents news and information related to dermatology. It states that the twelve dermatological residents will compete in December 1974 for the Fifth Henry W. Stelwagon Prize presented by the College of Physicians of Philadelphia to "the resident who shall be adjudged to give the most outstanding paper" at the annual meeting of the American Academy of Dermatology. The Stelwagon Prize stems from an endowment bequeathed to the College of Physicians of Philadelphia by Henry Weightman Stelwagon, who was the first teacher of Dermatology at Jefferson Medical College, Philadelphia, Pennsylvania.