Comparative study of commercial building energy-efficiency retrofit policies in four pilot cities in China

The energy efficiency of existing commercial buildings is more challenging to regulate and improve than the energy efficiency of new constructions. In 2011 and 2012, the Chinese Government selected four cities- Shanghai, Tianjin, Shenzhen, and Chongqing- to implement pilot commercial building energy efficiency retrofit program. Based on site surveys and expert interviews in these pilot cities, this research conducted a comparative analysis on incentive policies of local city level. The analysis results show that policy designs of existing commercial buildings should be further improved. The aspects that influence the implementation effect in the future, such as subsidy level, installments, and business model promotion, should be specified in the policy clauses. Referring to the technical solution and cost-benefit in Chongqing, we found that lighting system is the most common retrofit objects while envelope system is the least common one. And the subsidy incentive is greatest for educational buildings, followed by office buildings. In the end, we further discussed the problems and obstacles in commercial building retrofit market, and provided a series of recommendations

Two-stage hybrid feature selection algorithms for diagnosing erythemato-squamous diseases

This paper proposes two-stage hybrid feature selection algorithms to build the stable and efficient diagnostic models where a new accuracy measure is introduced to assess the models. The two-stage hybrid algorithms adopt Support Vector Machines (SVM) as a classification tool, and the extended Sequential Forward Search (SFS), Sequential Forward Floating Search (SFFS), and Sequential Backward Floating Search (SBFS), respectively, as search strategies, and the generalized F-score (GF) to evaluate the importance of each feature. The new accuracy measure is used as the criterion to evaluated the performance of a temporary SVM to direct the feature selection algorithms. These hybrid methods combine the advantages of filters and wrappers to select the optimal feature subset from the original feature set to build the stable and efficient classifiers. To get the stable, statistical and optimal classifiers, we conduct 10-fold cross validation experiments in the first stage; then we merge the 10 selected feature subsets of the 10-cross validation experiments, respectively, as the new full feature set to do feature selection in the second stage for each algorithm. We repeat the each hybrid feature selection algorithm in the second stage on the one fold that has got the best result in the first stage. Experimental results show that our proposed two-stage hybrid feature selection algorithms can construct efficient diagnostic models which have got better accuracy than that built by the corresponding hybrid feature selection algorithms without the second stage feature selection procedures. Furthermore our methods have got better classification accuracy when compared with the available algorithms for diagnosing erythemato-squamous diseases

Reaction Mechanisms for Long-Life Rechargeable Zn/MnO 2 Batteries

Rechargeable aqueous Zn-ion batteries (ZIBs) are very promising for large-scale grid energy storage applications owing to their low cost, environmentally benign constituents, excellent safety, and relatively high energy density. Their usage, however, is largely hampered by the fast capacity fade. The complexity of the reactions has resulted in long-standing ambiguities of the chemical pathways of Zn/MnO 2 system. In this study, we find that both H + /Zn 2+ intercalation and conversion reactions occur at different voltages and that the rapid capacity fading can clearly be ascribed to the rate-limiting and irreversible conversion reactions at a lower voltage. By limiting the irreversible conversion reactions at â1.26 V, we successfully demonstrate ultrahigh power and long life that are superior to most of the reported ZIBs or even some lithium-ion batteries

Determining the Magnetic Field Orientation of Coronal Mass Ejections from Faraday Rotation

We describe a method to measure the magnetic field orientation of coronal mass ejections (CMEs) using Faraday rotation (FR). Two basic FR profiles, Gaussian-shaped with a single polarity or "N"-like with polarity reversals, are produced by a radio source occulted by a moving flux rope depending on its orientation. These curves are consistent with the Helios observations, providing evidence for the flux-rope geometry of CMEs. Many background radio sources can map CMEs in FR onto the sky. We demonstrate with a simple flux rope that the magnetic field orientation and helicity of the flux rope can be determined 2-3 days before it reaches Earth, which is of crucial importance for space weather forecasting. An FR calculation based on global magnetohydrodynamic (MHD) simulations of CMEs in a background heliosphere shows that FR mapping can also resolve a CME geometry curved back to the Sun. We discuss implementation of the method using data from the Mileura Widefield Array (MWA).Comment: 22 pages with 9 figures, accepted for publication in Astrophys.