Surface modification of polyurethane via creating a biocompatible superhydrophilic nanostructured layer: role of surface chemistry and structure

Advanced surface modification approaches of biomaterials alongside the advent of sophisticated analytical techniques have provided a great opportunity to understand how the physicochemical characteristics of materials determine cell–surface dynamics at molecular and atomic scale. However, there are still many contradictory reports, which are mainly due to inadequate information about the role of the two parameters of surface chemistry and structure and their synergistic effect as an adequate predictor of biological performance. Here, surface parameters were altered by grafting of poly ethylene glycol (PEG) on polyurethane (PU) surfaces through a superhydrophilic modification method. In this study, surface modification of PU films by PEG thin layer via grafting technique and TiO2 nanoparticle entrapment in the brush polymers was investigated. The surface modification led to a reduction in protein adsorption and bacterial attachment by 8.7 times and 71% respectively with no cytotoxicity effect on HeLa cells. It was also observed that when PU surface became superhydrophilic the bacterial adhesion becomes independent of bacterium type. In general, it was observed that the impact of topographical changes on the biocompatibility and biofilm formation becomes significantly more profound than that of the surface chemistry alteration.     

Microstructural Evolution,Powder Characteristics,Compaction Behavior and Sinterability of Al 6061–B<Subscript>4</Subscript>C Composites as a Function of Reinforcement Content and Milling Times

Al 6061_100–x–x wt % B₄C (x = 0, 5, 10, 20, 30 and 40) composites, prepared by mechanical alloying and compacted at room temperature, have been used for the present investigation. The effects of B₄C content and milling time on the powder morphology, powder particle size, and other powder characteristics such as the apparent density, tap density, flow rate, cohesiveness, and hausner ratio are systematically investigated. The steady state of milling process is determined by observing the correlation between apparent densities and milling time explained by the morphological evolution of the powder particles during the milling process. The Hausner ratio (HR), estimated to evaluate friction between the particles, decreases with an increase in milling duration and B₄C content due to the changes in morphology and hardness of the powders. The compressibility behavior of post-compacts as a function of compaction pressure and the B₄C content was analyzed by using several linear and non-linear powder compaction equations. The linear Panelli and Ambrozio Filho, and non-linear Van Der Zwan and Siskens equations give the highest regression coefficients. The results are explained in terms of the plastic deformation capacity and plastic deformation coefficient of the powders, which are influenced by the hardness and the morphology of the powder. After compaction, the supersolidus liquid phase sintering was performed at various temperatures (585, 610 and 630°C) under high purity nitrogen atmosphere. The results revealed that the sinterability was degraded by increasing the reinforcement content, particularly above 10 wt % B₄C. Neutron radiography measurements conducted on the rolled composite sheet have revealed the uniform distribution of B₄C particles in the composite.     

Boost-wise pre-loaded mixture of experts for classification tasks

A modified version of Boosted Mixture of Experts (BME) is presented in this paper. While previous related works, namely BME, attempt to improve the performance by incorporating complementary features of a hybrid combining framework, they have some drawback. Analyzing the problems of previous approaches has suggested several modifications that have led us to propose a new method called Boost-wise Pre-loaded Mixture of Experts (BPME). We present a modification in pre-loading (initialization) procedure of ME, which addresses previous problems and overcomes them by employing a two-stage pre-loading procedure. In this approach, both the error and confidence measures are used as the difficulty criteria in boost-wise partitioning of problem space.

     

AutoRWN: automatic construction and training of random weight networks using competitive swarm of agents

Neural Computing and Applications - Random Weight Networks have been extensively used in many applications in the last decade because it has many strong features such as fast learning and good...     

OVRP_GELS: solving open vehicle routing problem using the gravitational emulation local search algorithm

In open vehicle routing problem (OVRP), after delivering service to the last customer, the vehicle does not necessarily return to the initial depot. This type of problem originally defined about thirty years ago and still is an open issue. In real life, the OVRP is similar to the delivering newspapers and consignments. The problem of service delivering to a set of customers is a particular open VRP with an identical fleet for transporting vehicles that do not necessarily return to the initial depot. Contractors which are not the employee of the delivery company use their own vehicles and do not return to the depot. Solving the OVRP means to optimize the number of vehicles, the traveling distance and the traveling time of a vehicle. In time, several algorithms such as tabu search, deterministic annealing and neighborhood search were used for solving the OVRP. In this paper, a new combinatorial algorithm named OVRP_GELS based on gravitational emulation local search algorithm for solving the OVRP is proposed. We also used record-to-record algorithm to improve the results of the GELS. Several numerical experiments show a good performance of the proposed method for solving the OVRP when compared with existing techniques.

     

Embedding cycles and paths on solid grid graphs

Despite many algorithms for embedding graphs on unbounded grids, only a few results on embedding graphs on restricted grids have been published. In this paper, we study the problem of embedding paths and cycles on solid grid graphs. We show that a cycle of length k is unit-length embeddable on a solid grid graph G if k is an even integer between four and the length of the longest cycle of G. In addition, our result shows that a path of length k is unit-length embeddable on G, between its two given vertices s and t, if \(k\le L\) and \(k\equiv L (\mathrm{mod}\ 2)\), in which L is the length of the longest path between s and t. Our presented two algorithms show that such embeddings can be found in linear time for cycles and quadratic time for paths, with respect to the size of graph G. In the case of rectangular grid graphs, the running time of the algorithms can be improved to O(k) and O\((k^2)\), respectively. In addition, we extend our results to \(m\times n\times o\) 3D grids. A application of our result is in the interconnection network mapping in parallel processing.     

A state-based approach to integration testing based on UML models

Correct functioning of object-oriented software depends upon the successful integration of classes. While individual classes may function correctly, several new faults can arise when these classes are integrated together. In this paper, we present a technique to enhance testing of interactions among modal classes. The technique combines UML collaboration diagrams and statecharts to automatically generate an intermediate test model, called SCOTEM (State COllaboration TEst Model). The SCOTEM is then used to generate valid test paths. We also define various coverage criteria to generate test paths from the SCOTEM model. In order to assess our technique, we have developed a tool and applied it to a case study to investigate its fault detection capability. The results show that the proposed technique effectively detects all the seeded integration faults when complying with the most demanding adequacy criterion and still achieves reasonably good results for less expensive adequacy criteria.     

Resource provisioning for cloud applications: a 3-D,provident and flexible approach

The scalability feature of cloud computing attracts application service providers (ASPs) to use cloud application hosting. In cloud environments, resources can be dynamically provisioned on demand for ASPs. Autonomic resource provisioning for the purpose of preventing resources over-provisioning or under-provisioning is a widely investigated topic in cloud environments. There has been proposed a lot of resource-aware and/or service-level agreement (SLA)-aware solutions to handle this problem. However, intelligence solutions such as exploring the hidden knowledge on the Web users’ behavior are more effective in cost efficiency. Most importantly, with considering cloud service diversity, solutions should be flexible and customizable to fulfill ASPs’ requirements. Therefore, lack of a flexible resource provisioning mechanism is strongly felt. In this paper, we proposed an autonomic resource provisioning mechanism with resource-aware, SLA-aware, and user behavior-aware features, which is called three-dimensional mechanism. The proposed mechanism used radial basis function neural network in order to provide providence and flexibility features. The experimental results showed that the proposed mechanism reduces the cost while guarantees the quality of service.     

Periodic unsteady flows of a non-Newtonian fluid

Summary Exact analytic solutions for the flow of non-Newtonian fluid generated by periodic oscillations of a rigid plate are discussed. Some interesting flows caused by certain special oscillations are also obtained.