Analysis of Test Specimens for Cohesive Near-Bond Failure of Fiber-Reinforced Polymer-Plated Concrete

The failure mechanisms of reinforced concrete (RC) members change due to the application of externally bonded fiber-reinforced polymer reinforcement. Although an extensive literature is available describing the failure mechanisms of poststrengthened flexural systems, brittle failure modes caused by bond failure, such as midspan debonding and end peeling, need to be further investigated in order to identify and quantify the fracture processes that result in bond failure. Simplified experimental tests have been designed to idealize the bond between the laminate and the RC member. However, it is unclear how the simplified test results can be related to the actual flexural debonding failures. This paper investigates and compares two bond failure tests: a simplified test (or simple shear test) and a recently proposed shear/normal test. After discussing the characteristics of both tests and how they relate to the midspan debonding and end peeling failures, the shear/normal test is studied in more detail using a nonlinear finite-element fracture mechanics program. The program accounts for cohesive localized and distributed concrete crack damage and is capable of describing the geometrical discontinuities that induce different brittle failure mechanisms. The numerical results compare well with available experimental data and help explain the crack formation and propagation pattern up to specimen failure. Parametric studies are presented to elucidate the influence of different material parameters on the failure mechanisms.     

Constraint Lingo: towards high‐level constraint programming

Logic programming requires that the programmer convert a problem into a set of constraints based on predicates. Choosing the predicates and introducing appropriate constraints can be intricate and error prone. If the problem domain is structured enough, we can let the programmer express the problem in terms of more abstract, higher‐level constraints. A compiler can then convert the higher‐level program into a logic‐programming formalism. The compiler writer can experiment with alternative low‐level representations of the higher‐level constraints in order to achieve a high‐quality translation. The programmer can then take advantage of both a reduction in complexity and an improvement in runtime speed for all problems within the domain. We apply this analysis to the domain of tabular constraint‐satisfaction problems. Examples of such problems include logic puzzles solvable on a hatch grid and combinatorial problems such as graph coloring and independent sets. The proper abstractions for these problems are rows, columns, entries, and their interactions. We present a higher‐level language, Constraint Lingo, dedicated to problems in this domain. We also describe how we translate programs from Constraint Lingo into lower‐level logic formalisms such as the logic of propositional schemata. These translations require that we choose among competing lower‐level representations in order to produce efficient results. The overall effectiveness of our approach depends on the appropriateness of Constraint Lingo, our ability to translate Constraint Lingo programs into high‐quality representations in logic formalisms, and the efficiency with which logic engines can compute answer sets. We comment on our computational experience with these tools in solving both graph problems and logic puzzles. Copyright © 2004 John Wiley & Sons, Ltd.     

Decentralized adaptive recurrent neural control structure

This paper presents a novel decentralized variable structure neural control approach for large-scale uncertain systems, which is developed using recurrent high-order neural networks (RHONN). It is assumed that each subsystem belongs to a class of block-controllable nonlinear systems whose vector fields includes interconnection terms, which are bounded by nonlinear functions. A decentralized RHONN structure and the respective learning law are proposed in order to approximate online the dynamical behavior of each nonlinear subsystem. The control law, which is able to regulate and to track the desired reference signals, is designed using the well-known variable structure theory. The stability of the whole system is analyzed via the Lyapunov methodology. The applicability of the proposed decentralized identification and control algorithm is illustrated via simulations as applied to an interconnected double inverted pendulum.     

Design and structural applications of stress-crack width relations in fibre reinforced concrete

The stress-crack width relationship has been shown to be the key to an understanding of fracture propagation in and mechanical behaviour in tension of fibre reinforced concrete materials and structures. A model is derived for the stress-crack width relationship for randomly oriented short fibre composites which takes hybrid fibre systems and possible fibre rupture into account. It is shown how this stress-crack width relationship can be included in a structural model for the prediction of crack widths in reinforced concrete structures. With this combination of models a rational design tool for the design of composite materials and structures has been established. It is shown how different fibre systems can be tested for structural applicability and how combined material and structural optimization can take place.     

Superior electrocatalytic activity of mesoporous Au film templated from diblock copolymer micelles

Mesoporous Au films consisting of a network of interconnected Au ligaments around ultra-large pores were found to exhibit a promising electrocatalytic activity towards sluggish reactions. Mesoporous Au films with pore sizes up to 25 nm were successfully fabricated using a polymeric micelle approach. A superior catalytic activity of the mesoporous Au films towards methanol oxidation was confirmed, which was thoroughly analyzed and compared with that of other Au materials. An intrinsic investigation on the high catalytic activity revealed that the superior performance of the as-prepared mesoporous Au film was related to its unique atomic structures around the mesopores with well-crystallized facets and several step/kink sites on the Au surfaces. These findings showcase a strategic and feasible design for preparing highly active Au-based catalysts that could be used as promising candidates in electrocatalytic applications.

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Next-Generation Grade and Survival Expression Biomarkers of Human Gliomas Based on Algorithmically Reconstructed Molecular Pathways

In gliomas, expression of certain marker genes is strongly associated with survival and tumor type and often exceeds histological assessments. Using a human interactome model, we algorithmically reconstructed 7494 new-type molecular pathways that are centered each on an individual protein. Each single-gene expression and gene-centric pathway activation was tested as a survival and tumor grade biomarker in gliomas and their diagnostic subgroups (IDH mutant or wild type, IDH mutant with 1p/19q co-deletion, MGMT promoter methylated or unmethylated), including the three major molecular subtypes of glioblastoma (proneural, mesenchymal, classical). We used three datasets from The Cancer Genome Atlas and the Chinese Glioma Genome Atlas, which in total include 527 glioblastoma and 1097 low grade glioma profiles. We identified 2724 such gene and 2418 pathway survival biomarkers out of total 17,717 genes and 7494 pathways analyzed. We then assessed tumor grade and molecular subtype biomarkers and with the threshold of AUC > 0.7 identified 1322/982 gene biomarkers and 472/537 pathway biomarkers. This suggests roughly two times greater efficacy of the reconstructed pathway approach compared to gene biomarkers. Thus, we conclude that activation levels of algorithmically reconstructed gene-centric pathways are a potent class of new-generation diagnostic and prognostic biomarkers for gliomas.     

Monochromatic and bichromatic ranked reverse boolean spatial keyword nearest neighbors search

Recently, Reverse k Nearest Neighbors (RkNN) queries, returning every answer for which the query is one of its k nearest neighbors, have been extensively studied on the database research community. But the RkNN query cannot retrieve spatio-textual objects which are described by their spatial location and a set of keywords. Therefore, researchers proposed a RSTkNN query to find these objects, taking both spatial and textual similarity into consideration. However, the RSTkNN query cannot control the size of answer set and to be sorted according to the degree of influence on the query. In this paper, we propose a new problem Ranked Reverse Boolean Spatial Keyword Nearest Neighbors query called Ranked-RBSKNN query, which considers both spatial similarity and textual relevance, and returns t answers with most degree of influence. We propose a separate index and a hybrid index to process such queries efficiently. Experimental results on different real-world and synthetic datasets show that our approaches achieve better performance.     

Green cell association for multimedia transmission in cognitive heterogeneous networks

With the introduction of low‐powered pico/femto‐base stations and relay nodes into the macro‐cell, recent heterogeneous networks provide an attractive approach for future wireless communication. Although it may achieve better coverage and higher capacity, several problems remain unsolved before practical deployment. For example, how to select the proper cell from neighbor low‐powered cells and then occupy the radio resource without interference on macro‐users is both important and challenging, especially for rigorous multimedia applications. The traditional cell access algorithms and quality‐control parameters such as delay or throughput no longer suit well in this complex environment. An effective approach should be pursued. In this paper, we investigate this interesting cell association problem and propose a complete green resolution on the basis of thorough discussions about the multimedia transmission under these concerns. Cognitive radio is introduced to share spectrum between macro‐cell and low‐powered cells while securing the transmission of authorized macro‐users. We also bring forth the concept of ‘interference balance’ to better manage the overall interference and energy consumption in the network. Restless bandit model is formulated on the basis of channel state, data rate, interference control, and the carefully chosen intra‐refreshing rate for multimedia traffic. Then the cell association scheme is designed to be efficient and practical because of the simple index property of our model output. Simulation results have proven the performance of our proposed resolution compared with existing algorithms on interference constraint, multimedia distortion, and overall network energy consumption balance. Copyright © 2013 John Wiley & Sons, Ltd.