China’s market economy, shadow banking and the frequency of growth slowdown

The activity of the Shadow Banks in China has been the subject of considerable interest in recent years. Total shadow banking lending has reached over 60% of GDP and has grown faster than regular bank lending. It has been argued that unregulated shadow banking has fuelled a credit boom that poses a risk to the stability of the financial system. This paper estimates a model of the Chinese economy using a DSGE framework that accommodates a banking sector that isolates the effects of lending to the private sector including shadow bank lending. A refinement of the model allows for bank lending including lending by the shadow banks to affect the credit premium on private investment. The main finding is that while financial shocks are significant, it is real shocks that dominate. The model is used to simulate the frequency of growth slowdowns in China and concludes that these are more likely to be driven by real sector shocks rather than financial sector, including shadow bank shocks. This paper differs from other applications in its use of indirect inference to test the fitted model against a threeequation VAR of inflation, output gap and interest rate

Phellinus linteus sensitises apoptosis induced by doxorubicin in prostate cancer

It has been demonstrated that the Phellinus linteus (PL) mushroom, which mainly consists of polysaccharides, possesses antitumour activity. The mechanisms of PL against malignant growth remain unknown. The anticancer drug doxorubicin (Dox) has been shown to induce apoptosis via initiating a caspase cascade. In this investigation, we tested the effect of PL on Dox-induced apoptosis in prostate cancer LNCaP cells. We showed that PL or Dox, at relatively low doses, does not induce apoptosis in the cells. However, combination treatment with low doses of PL and Dox results in a synergistic effect on the induction of apoptosis. In this apoptotic process, caspases 8, 3 and BID are cleaved, and the addition of caspase inhibitor z-VADfmk completely blocks apoptosis. In addition, JNK is activated in response to PL or the combination treatment in LNCaP cells. The suppression of JNK partially inhibits the induction of apoptosis elicited by the co-treatment. These findings indicate that PL has a synergistic effect with Dox to activate caspases in prostate cancer LNCaP cells. Our study also suggests that PL has therapeutic potential to augment the magnitude of apoptosis induced by antiprostate cancer drugs

In Situ Observations during Chemical Vapor Deposition of Hexagonal Boron Nitride on Polycrystalline Copper.

Using a combination of complementary in situ X-ray photoelectron spectroscopy and X-ray diffraction, we study the fundamental mechanisms underlying the chemical vapor deposition (CVD) of hexagonal boron nitride (h-BN) on polycrystalline Cu. The nucleation and growth of h-BN layers is found to occur isothermally, i.e., at constant elevated temperature, on the Cu surface during exposure to borazine. A Cu lattice expansion during borazine exposure and B precipitation from Cu upon cooling highlight that B is incorporated into the Cu bulk, i.e., that growth is not just surface-mediated. On this basis we suggest that B is taken up in the Cu catalyst while N is not (by relative amounts), indicating element-specific feeding mechanisms including the bulk of the catalyst. We further show that oxygen intercalation readily occurs under as-grown h-BN during ambient air exposure, as is common in further processing, and that this negatively affects the stability of h-BN on the catalyst. For extended air exposure Cu oxidation is observed, and upon re-heating in vacuum an oxygen-mediated disintegration of the h-BN film via volatile boron oxides occurs. Importantly, this disintegration is catalyst mediated, i.e., occurs at the catalyst/h-BN interface and depends on the level of oxygen fed to this interface. In turn, however, deliberate feeding of oxygen during h-BN deposition can positively affect control over film morphology. We discuss the implications of these observations in the context of corrosion protection and relate them to challenges in process integration and heterostructure CVD.P.R.K. acknowledges funding from the Cambridge Commonwealth Trust and the Lindemann Trust Fellowship. R.S.W. acknowledges a research fellowship from St. John’s College, Cambridge. S.H. acknowledges funding from ERC grant InsituNANO (no. 279342), EPSRC under grant GRAPHTED (project reference EP/K016636/1), Grant EP/H047565/1 and EU FP7 Work Programme under grant GRAFOL (project reference 285275). The European Synchrotron Radiation Facility (ESRF) is acknowledged for provision of synchrotron radiation and assistance in using beamline BM20/ROBL. We acknowledge Helmholtz-Zentrum-Berlin Electron storage ring BESSY II for synchrotron radiation at the ISISS beamline and continuous support of our experiments.This is the final version. It was first published by ACS at http://pubs.acs.org/doi/abs/10.1021/cm502603

Potential Bands of Sentinel-2A Satellite for Classification Problems in Precision Agriculture

Various indices are used for assessing vegetation and soil properties in satellite remote sensing applications. Some indices, such as normalized difference vegetation index (NDVI) and normalized difference water index (NDWI), are capable of simply differentiating crop vitality and water stress. Nowadays, remote sensing capabilities with high spectral, spatial and temporal resolution are available to analyse classification problems in precision agriculture. Many challenges in precision agriculture can be addressed by supervised classification, such as crop type classification, disease and stress (e.g., grass, water and nitrogen) monitoring. Instead of performing classification based on designated indices, this paper explores direct classification using different bands information as features. Land cover classification by using the recently launched Sentinel-2A image is adopted as a case study to validate our method. Four approaches of featured band selection are compared to classify five classes (crop, tree, soil, water and road) with the support vector machines (SVMs) algorithm, where the first approach utilizes traditional empirical indices as features and the latter three approaches adopt specific bands (red, near infrared and short wave infrared) related to indices, specific bands after ranking by mutual information (MI), and full bands of on board sensors as features, respectively. It is shown that a better classification performance can be achieved by directly using the selected bands after MI ranking compared with the one using empirical indices and specific bands related to indices, while the use of all 13 bands can marginally improve the classification accuracy than MI based one. Therefore, it is recommended that this approach can be applied for specific Sentinel-2A image classification problems in precision agriculture