Intravitreal tolerance of a new perfluorocarbon vitreous replacement, Multifluor APF-144

OBJECTIVE: To evaluate the intravitreal tolerance of a new perfluorocarbon vitreous replacement, Multifluor APF-144 (perfluorotetramethylcyclohexane). DESIGN: Ten New Zealand albino rabbits (one eye from each) underwent vitrectomy. The vitreous was replaced in five eyes with Multifluor APF-144 and in five eyes with saline (control group). OUTCOME MEASURES: Appearance on indirect ophthalmoscopy, electroretinography recordings before and 2, 4 and 8 weeks after vitrectomy, findings on electron and light microscopy at 8 weeks. RESULTS: Endophthalmitis did not develop in any of the eyes. There was no significant change in electroretinography values for the experimental eyes after vitrectomy. No evidence of retinal toxicity was found on light or electron microscopic examination. CONCLUSIONS: Multifluor APF-144 shows promise as a short-term postoperative retinal tamponading agent.     

Oil Spill Cleanup from Sea Water by Sorbent Materials

Three sorbents were compared in order to determine their potential for oil spill cleanup. Polypropylene nonwoven web, rice hull, and bagasse with two different particle sizes were evaluated in terms of oil sorption capacities and oil recovery efficiencies. Polypropylene can sorb almost 7 to 9 times its weight from different oils. Bagasse, 18 to 45 mesh size, follows polypropylene as the second sorbent in oil spill cleanup. Bagasse, 14 to 18 mesh size, and rice hull have comparable oil sorption capacities, which are lower than those of the two former sorbents. It was found that oil viscosity plays an important role in oil sorption by sorbents. All adsorbents used in this work could remove the oil from the surface of the water preferentially.     

A novel approach to predict shear strength of tilted angle connectors using artificial intelligence techniques

Shear connectors play a prominent role in the design of steel-concrete composite systems. The behavior of shear connectors is generally determined through conducting push-out tests. However, these tests are costly and require plenty of time. As an alternative approach, soft computing (SC) can be used to eliminate the need for conducting push-out tests. This study aims to investigate the application of artificial intelligence (AI) techniques, as sub-branches of SC methods, in the behavior prediction of an innovative type of C-shaped shear connectors, called Tilted Angle Connectors. For this purpose, several push-out tests are conducted on these connectors and the required data for the AI models are collected. Then, an adaptive neuro-fuzzy inference system (ANFIS) is developed to identify the most influencing parameters on the shear strength of the tilted angle connectors. Totally, six different models are created based on the ANFIS results. Finally, AI techniques such as an artificial neural network (ANN), an extreme learning machine (ELM), and another ANFIS are employed to predict the shear strength of the connectors in each of the six models. The results of the paper show that slip is the most influential factor in the shear strength of tilted connectors and after that, the inclination angle is the most effective one. Moreover, it is deducted that considering only four parameters in the predictive models is enough to have a very accurate prediction. It is also demonstrated that ELM needs less time and it can reach slightly better performance indices than those of ANN and ANFIS.

     

Transport of Gellan Gum Microbeads in Soil Columns of Various Grain Size Distributions

The transport of gellan gum microbeads as potential cell carriers was investigated in horizontal columns packed with different grain size classes of gravel (2–16 mm) and sand (0.25–2 mm). A suspension of microbeads was pulsed into each column for 6 h, followed by injection of water for 42 h. In general, the total amount of microbeads travelling across a given section of the column increased with injection time but decreased towards the column outlet, varying as a direct function of grain size. The results of this study demonstrate the feasibility of the transport of gellan gum microbeads through medium sand to medium gravel across distances up to 110 cm.     

Design of explicit model predictive control for constrained linear systems with disturbances

On-line model predictive control approaches require the online solution of an optimization problem. In contrast, the explicit model predictive control moves major part of computation offline. Therefore, eMPC enables one to implement a MPC in real time for wide range of fast systems. The eMPC approach requires the exact system model and results a piecewise affine control law defined on a polyhedral partition in the state space. As an important limitation, disturbances may reduce performance of the explicit model predictive control. This paper presents efficient approach for handling the problem of using eMPC for constrained systems with disturbances. It proposes an approach to improve performance of the closed loop system by designing a suitable state and disturbance estimator. Conditions for observability of the disturbances are considered and it is depicted that applying the disturbance’s estimation leads to rejection of the response error. It is also shown that the proposed approach prevents the reduction of feasible space. Simulation results illustrate the advantages of this approach.     

(Approximate) Uncertain Skylines

Given a set of points with uncertain locations, we consider the problem of computing the probability of each point lying on the skyline, that is, the probability that it is not dominated by any other input point. If each point’s uncertainty is described as a probability distribution over a discrete set of locations, we improve the best known exact solution. We also suggest why we believe our solution might be optimal. Next, we describe simple, near-linear time approximation algorithms for computing the probability of each point lying on the skyline. In addition, some of our methods can be adapted to construct data structures that can efficiently determine the probability of a query point lying on the skyline.     

Copper/copper oxide nanoparticles synthesis using Stachys lavandulifolia and its antibacterial activity

Nanoparticles of copper/cuprous oxide (Cu/Cu₂ O) were successfully synthesised by a green chemistry route. The synthesis process was carried out using an extract of Stachys lavandulifolia as both reducing and capping agents with a facile procedure. The nanoparticles were characterised by different techniques including X‐ray diffraction, indicating that the synthesised sample comprised both copper and cuprous oxide entity. The nanoparticles had a mean size of 80 nm and represented an impressive bactericidal effect on Pseudomonas aeruginosa.Inspec keywords: copper, copper compounds, nanoparticles, nanofabrication, nanomedicine, antibacterial activity, X‐ray diffractionOther keywords: nanoparticles synthesis, Stachys lavandulifolia, antibacterial activity, green chemistry route, reducing agents, capping agents, X‐ray diffraction, bactericidal effect, Pseudomonas aeruginosa, Cu‐Cu₂ O     

Dynamic estimation of the modeling error statistics in Diffuse Optical Tomography

Diffuse Optical Tomography (DOT) is a non-invasive imaging technique that suffers from a typical large-scale and ill-posed inverse problem with low spatial resolution. In DOT, the inverse problem is computationally intensive and decreasing the computation complexity and making it well-posed is the one of the most challenging research areas. More precisely, one of the well-known complexity reduction techniques is defined as applying modelling error originated from discretization of forward problem. Applying the discretization error in Bayesian inference has already been discussed; the method in which the likelihood is modified by an off-line prior density estimation. This paper implements a new method to enhance the modelling error approach using an iterative scheme to update statistical parameters of modelling discrepancy in DOT. The algorithm is very similar to Ensemble Kalman Filter. Moreover, the reconstruction process in the applied method is conducted by a small sample size rather than off-line method. Hence, the computation complexity is decreased and the algorithm converges in few iterations. The efficiency of the proposed method is illustrated by simulations.     

Access and service convergence over the mobile internet – A survey

Next generation heterogeneous wireless networks are expected to interwork with Internet Protocol (IP)-based infrastructures. Conventional network services operate like silos in that a specific set of services are offered over a specific type of access network. It is desirable for users to be able to roam between fixed and mobile networks that employ different access technologies. Therefore, mobility management with quality of service (QoS) support is of particular importance and one of the driving forces of convergence. Since service providers often provide more than one service to their subscribers, it is important to facilitate convergence of network charging architecture through a common charging framework. One of the main issues of IP-based convergence is security and privacy. This requires coordination of different security policies in diverse networks that have different security levels and capabilities. The business case for migration to an IP-based platform motivates operators to deliver more powerful services for customers as well as a better user experience. This paper provides an overview of converged mobile Internet architectures and their implications on QoS, charging/billing and security, as well as emerging business models for telecommunication services.     

Annotation-based access control for collaborative information spaces

Web 2.0 social platforms (e.g., Flickr, YouTube) and Collaborative Working Environments (e.g., Microsoft SharePoint, BSCW) provide Web-based collaborative information spaces which enable common users and/or professionals to work together and share their online resources. Most of these collaborative information spaces provide role-based or group-based, coarse-grained access control policies which cannot successfully cope with the requirements posed by massive and open collaboration. In this paper, we present an annotation-based access control (AnBAC) model supported by a Collaboration Vocabulary (CoVoc) as a more flexible and user-centric access control approach. Based on this, we developed two tools: Uncle-Share is a gadget that provides annotation-based access control and can be equipped with CoVoc for annotating collaborative relationships. Who-With-Whom uses CoVoc to visualize extended social networks in order to help users to select appropriate contacts to grant access to resources.