A composite approach for modeling deformation behaviors of thermoplastic polyurethane considering soft-hard domains transformation

Thermoplastic polyurethane elastomers (TPUs) are the most used engineering thermoplastics combining the properties for both elastomers and glassy materials. TPUs have good physical and mechanical properties, excellent chemical and abrasion resistances. Compared with typical thermoset rubbers, TPUs are easier to be processed and recycled. However, the deformation behaviors of TPUs are very complex due to their nonlinear, hysteresis, rate and temperature dependences, and softening properties. Therefore, development of a constitutive model with microstructure considerations is important for predicting the deformation behavior of TPUs under mechanical loading as well as during forming processes such as rolling and stretching. In this work, TPUs were taken as a two-phase material consisting of both hard and soft phases corresponding to their hard and soft domains. A new composite constitutive model for stress-strain response of TPUs was proposed taking into account the microstructure of TPUs as well as its evolution (hard to soft phase transformation) induced by deformation. Excellent agreement between model predictions and experimental results for the loading-unloading behaviors of two TPUs with different hard and soft segment contents confirmed the efficacy of our proposed composite constitutive model.     

A new fuzzy logic approach for reliable communications in wireless underground sensor networks

Wireless Networks - Nowadays, the exploitation of Wireless Underground Sensor Networks (WUSNs) remains challenging because of the attenuation of wireless underground communications. This issue...     

Identification of Abundant and Functional dodecaRNAs (doRNAs) Derived from Ribosomal RNA

Using a modified RNA-sequencing (RNA-seq) approach, we discovered a new family of unusually short RNAs mapping to ribosomal RNA 5.8S, which we named dodecaRNAs (doRNAs), according to the number of core nucleotides (12 nt) their members contain. Using a new quantitative detection method that we developed, we confirmed our RNA-seq data and determined that the minimal core doRNA sequence and its 13-nt variant C-doRNA (doRNA with a 5′ Cytosine) are the two most abundant doRNAs, which, together, may outnumber microRNAs. The C-doRNA/doRNA ratio is stable within species but differed between species. doRNA and C-doRNA are mainly cytoplasmic and interact with heterogeneous nuclear ribonucleoproteins (hnRNP) A0, A1 and A2B1, but not Argonaute 2. Reporter gene activity assays suggest that C-doRNA may function as a regulator of Annexin II receptor (AXIIR) expression. doRNAs are differentially expressed in prostate cancer cells/tissues and may control cell migration. These findings suggest that unusually short RNAs may be more abundant and important than previously thought.     

A randomized clustering of anonymous wireless ad hoc networks with an application to the initialization problem

The Distributed Mobility-Adaptive Clustering (DMAC) due to Basagni partitions the nodes of a mobile ad hoc network into clusters, thus giving the network a hierarchical organization. This algorithm supports the mobility of the nodes, even during the cluster formation. The main feature of DMAC is that in a weighted network (in which two or more nodes cannot have the same weight), nodes have to choose the clusterheads taking into account only the node weight, i.e. the mobility when a node weight is the inverse of its speed. In our approach many nodes may have the same speed and hence the same weight. We assume that nodes have no identities and the number of nodes, say n, is the only known parameter of the network. After the randomized clustering, we show that the initialization problem can be solved in a multi-hop ad hoc wireless network of n stations in O(k ^1/2log ^1/2 k)+D _b −1+O(log (max (P _i )+log ²max (P _i )) broadcast rounds with high probability, where k is the number of clusters, D _b is the blocking diameter and max (P _i ), 1≤i≤k, is the maximum number of nodes in a cluster. Thus the initialization protocol presented here uses less broadcast rounds than the one in Ravelemanana (IEEE Trans. Parallel Distributed Syst. 18(1):17–28 2007).     

A scheme for detecting every single target molecule with surface-enhanced Raman spectroscopy

Surface-enhanced Raman spectroscopy (SERS) is now a well-established technique for the detection, under appropriate conditions, of single molecules (SM) adsorbed on metallic nanostructures. However, because of the large variations of the SERS enhancement factor on the surface, only molecules located at the positions of highest enhancement, so-called hot-spots, can be detected at the single-molecule level. As a result, in all SM-SERS studies so far only a small fraction, typically less than 1%, of molecules are actually observed. This complicates the analysis of such experiments and means that trace detection via SERS can in principle still be vastly improved. Here we propose a simple scheme, based on selective adsorption of the target analyte at the SERS hot-spots only, that allows in principle detection of every single target molecule in solution. We moreover provide a general experimental methodology, based on the comparison between average and maximum (single molecule) SERS enhancement factors, to verify the efficiency of our approach. The concepts and tools introduced in this work can readily be applied to other SERS systems aiming for detection of every single target molecule.