Weldability and liquation cracking behavior of ZhS6U superalloy during electron-beam welding

The weldability of the ZhS6U nickel-based superalloy, which is prone to solidification cracking during electron-beam welding(EBW) repair processes, was investigated. The effects of two different pre-weld heat-treatment cycles on the final microstructure before and after welding were examined. Welds were made on flat coupons using an EBW machine, and the two heat-treatment cycles were designed to reduce γ′ liquation before welding. Microstructural features were also examined by optical and scanning electron microscopy. The results showed that the change in the morphology and size of the γ′ precipitates in the pre-weld heat-treatment cycles changed the ability of the superalloy to release the tensile stresses caused by the matrix phase cooling after EBW. The high hardness in the welded coupons subjected to the first heat-treatment cycle resulted in greater resistance to stress release by the base alloy, and the concentration of stress in the base metal caused liquation cracks in the heat-affected zone and solidification cracks in the weld area.     

A self-similar local neuro-fuzzy model for short-term demand forecasting

This paper proposes a selfsimilar local neurofuzzy （SSLNF） model with mutual informati onbased input selection algorithm for the shortterm electricity demand forecasting. The proposed self similar model is composed of a number of local models, each being a local linear neurofuzzy （LLNF） model, and their associated validity functions and can be interpreted itself as an LLNF model. The proposed model is trained by a nested local liner model tree （NLOLIMOT） learning algorithm which partitions the input space into axisorthogonal subdomains and then fits an LLNF model and its associated validity function on each subdomain. Furthermore, the proposed approach allows different input spaces for rule premises （validity functions） and consequents （local models）. This appealing property is employed to assign the candidate input variables （i.e., previous load and temperature） which influence shortterm electricity demand in linear and nonlinear ways to local models and validity functions, respectively. Numerical results from shortterm load forecasting in the New England in 2002 demonstrated the accuracy of the SSLNF model for the STLF applications.     

Reference to the best explanation

This paper shows that two questions productively overlap: first, in virtue of what does an agent infer one hypothesis rather than another? Second, in virtue of what does an agent refer to one natural kind rather than another? Peter Lipton (2004) answers the first question by articulating the model of inference to the best explanation. Lipton’s answer to the first question is appropriated as an answer to the second.     

Critical role of TRAF3 in the Toll-like receptor-dependent and -independent antiviral response

Type I interferon (IFN) production is a critical component of the innate defence against viral infections. Viral products induce strong type I IFN responses through the activation of Toll-like receptors (TLRs) and intracellular cytoplasmic receptors such as protein kinase R (PKR). Here we demonstrate that cells lacking TRAF3, a member of the TNF receptor-associated factor family, are defective in type I IFN responses activated by several different TLRs. Furthermore, we show that TRAF3 associates with the TLR adaptors TRIF and IRAK1, as well as downstream IRF3/7 kinases TBK1 and IKK-epsilon, suggesting that TRAF3 serves as a critical link between TLR adaptors and downstream regulatory kinases important for IRF activation. In addition to TLR stimulation, we also show that TRAF3-deficient fibroblasts are defective in their type I IFN response to direct infection with vesicular stomatitis virus, indicating that TRAF3 is also an important component of TLR-independent viral recognition pathways. Our data demonstrate that TRAF3 is a major regulator of type I IFN production and the innate antiviral response.