Maxillary distraction osteogenesis in Pfeiffer's syndrome: urgent ocular protection by gradual midfacial skeletal advancement

Distraction osteogenesis is increasingly recognised as a potentially useful technique to achieve the co-ordinated augmentation of craniofacial skeletal and soft tissue. A case is presented where bilateral maxillary distraction was successfully used to advance the midface in the treatment of recurrent ocular dislocation, in a 10-month-old boy with Pfeiffer's syndrome.     

Rational Design of Programmable Monodisperse Semi-Synthetic Protein Nanomaterials Containing Engineered Disulfide Functionality**

The reversible nature of disulfide functionality has been exploited to design intelligent materials such as nanocapsules, micelles, vesicles, inorganic nanoparticles, peptide and nucleic acid nanodevices. Herein, we report a new chemical methodology for the construction redox-sensitive protein assemblies using monodisperse facially amphiphilic protein-dendron bioconjugates. The disulfide functionality is strategically placed between the dendron and protein domains. The custom designed bioconjugates self-assembled into nanoscopic objects of a defined size dictated by the nature of dendron domain. The stimuli-responsive behavior of the protein assemblies is demonstrated using a suitable redox trigger.     

Effect of intake air oxygen enrichment for improving engine performance and emissions control in diesel engine

Stringent emission regulations and health awareness about air pollution have led researchers to find alternative means of minimising emissions in diesel engines. In this article, the influence of oxygen enrichment is discussed to determine the effect on diesel engine performance, emission characteristics and combustion characteristics. Normal diesel and oxygen-enriched diesel are used in this experiment. The increase in oxygen concentration led to complete combustion, producing higher thermal efficiency and low harmful emissions. From the results, it is noted that oxygen-enriched diesel fuel showed reduction of CO, HC and smoke emissions, while NOx emission increased.

Abbreviations/Nomenclature DI: direct injection; NOx: oxides of nitrogen; O₂: oxygen; HC: hydrocarbon; PM: particulate matters; CO: carbon monoxide; CO₂: carbon dioxide     

Enhancement of uniform temperature distribution during casting solidification by methoding process

The main purpose of this study was to adapt proper methoding models to improve the cast ability and reduce the defects in casting. According to many researchers, 90% of the defects in casting are due to the wrong design of gating and riser systems and 10% due to casting defects. Here we are improving the runner and riser placement through methoding process. In the present work, to validate the advantages of methoding, we have selected casting model with and without methoding, temperature distribution over various positions have been analysed and it is found that casting model with methoding provides uniform temperature distribution.     

Image reconstruction using interval simulated annealing in electrical impedance tomography

Electrical impedance tomography (EIT) is an imaging technique that attempts to reconstruct the impedance distribution inside an object from the impedance between electrodes placed on the object surface. The EIT reconstruction problem can be approached as a nonlinear nonconvex optimization problem in which one tries to maximize the matching between a simulated impedance problem and the observed data. This nonlinear optimization problem is often ill-posed, and not very suited to methods that evaluate derivatives of the objective function. It may be approached by simulated annealing (SA), but at a large computational cost due to the expensive evaluation process of the objective function, which involves a full simulation of the impedance problem at each iteration. A variation of SA is proposed in which the objective function is evaluated only partially, while ensuring boundaries on the behavior of the modified algorithm.     

A Universal Chemical Method for Rational Design of Protein-Based Nanoreactors**

Self-assembly of a monomeric protease to form a multi-subunit protein complex “proteasome” enables targeted protein degradation in living cells. Naturally occurring proteasomes serve as an inspiration and blueprint for the design of artificial protein-based nanoreactors. Here we disclose a general chemical strategy for the design of proteasome-like nanoreactors. Micelle-assisted protein labeling (MAPLab) technology along with the N-terminal bioconjugation strategy is utilized for the synthesis of a well-defined monodisperse self-assembling semi-synthetic protease. The designed protein is programmed to self-assemble into a proteasome-like nanostructure which preserves the functional properties of native protease.     

A Profile-Based Novel Framework for Detecting EDoS Attacks in the Cloud Environment

The future of information technology mainly depends upon cloud computing. Hence security in cloud computing is highly essential for the consumers as well as the service providers of the particular cloud environment. There are many security threats are challenging the current cloud environment. One of the important security threat ever in cloud environment is considered to be the Distributed Denial of Service (DDoS) attack. Where cloud is of greater benefit in terms of providing on-demand services, a certain kind of attack named as Economic Denial of Sustainability (EDoS) occurs in pay per use payment model. Due to the occurrence of this attack the consumers are forced to pay additional amount for the services offered. EDoS attacks are similar to that of DDoS attacks Which is classified as-attacks associated with bandwidth consuming, application targeted attacks and the exhaustion of the connection layer. The main objective of the proposed work is to design a profile-based novel framework for maximizing the detection of various types of EDoS attacks. During this process, the proposed framework consisting Feature Classification (FC) algorithm ensures that false positives and negatives along with bandwidth and memory consumption are highly minimized. The proposed algorithm allows only the limited resources for allocation to the available virtual machines which increases the chances of the detecting the attack and preventing the misuse propagation of resources. The accuracy and efficiency of this approach is proven to be higher with lesser computational complexity when compare to the existing approaches.

     

Dynamic selection of classifiers—A comprehensive review

This work presents a literature review of multiple classifier systems based on the dynamic selection of classifiers. First, it briefly reviews some basic concepts and definitions related to such a classification approach and then it presents the state of the art organized according to a proposed taxonomy. In addition, a two-step analysis is applied to the results of the main methods reported in the literature, considering different classification problems. The first step is based on statistical analyses of the significance of these results. The idea is to figure out the problems for which a significant contribution can be observed in terms of classification performance by using a dynamic selection approach. The second step, based on data complexity measures, is used to investigate whether or not a relation exists between the possible performance contribution and the complexity of the classification problem. From this comprehensive study, we observed that, for some classification problems, the performance contribution of the dynamic selection approach is statistically significant when compared to that of a single-based classifier. In addition, we found evidence of a relation between the observed performance contribution and the complexity of the classification problem. These observations allow us to suggest, from the classification problem complexity, that further work should be done to predict whether or not to use a dynamic selection approach.     

Fusion of feature sets and classifiers for facial expression recognition

This paper presents a novel method for facial expression recognition that employs the combination of two different feature sets in an ensemble approach. A pool of base support vector machine classifiers is created using Gabor filters and Local Binary Patterns. Then a multi-objective genetic algorithm is used to search for the best ensemble using as objective functions the minimization of both the error rate and the size of the ensemble. Experimental results on JAFFE and Cohn-Kanade databases have shown the efficiency of the proposed strategy in finding powerful ensembles, which improves the recognition rates between 5% and 10% over conventional approaches that employ single feature sets and single classifiers.     

Derivatives of biomacromolecules as stabilizers of aqueous alumina suspensions

The stabilization of alumina suspensions is key to the development of high‐performance materials for the ceramic industry, which has motivated extensive research into synthetic polymers used as stabilizers. In this study, mimosa tannin extract and a chitosan derivative, that is, macromolecules obtained from renewable resources, are shown to be promising to replace synthetic polymers, yielding less viscous suspensions with smaller particles and greater fluidity, that is, more homogeneous suspensions that may lead to better‐quality products. The functional groups of tannin present in mimosa extract and N,N,N‐trimethylchitosan (TMC) are capable of establishing interactions with the alumina surface, thus leading to repulsion between the particles mainly due to steric and electrosteric mechanisms, respectively. The stabilization of the suspension induced by either TMC or mimosa tannin was confirmed by a considerable decrease in viscosity and average particle size, in comparison with alumina suspensions without stabilizing agents. The viscosity/average particle size decreased by 49/84% and 52/87% for suspensions with TMC and mimosa tannin, respectively. In addition, the increase in the absolute zeta potential upon addition of either TMC or mimosa tannin extract, especially at high pHs, points to an increased stability of the suspension. The feasibility of using derivatives of macromolecules from renewable sources to stabilize aqueous alumina suspensions was therefore demonstrated. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2010