Microfabricated Biomaterials for Engineering 3D Tissues

Mimicking natural tissue structure is crucial for engineered tissues with intended applications ranging from regenerative medicine to biorobotics. Native tissues are highly organized at the microscale, thus making these natural characteristics an integral part of creating effective biomimetic tissue structures. There exists a growing appreciation that the incorporation of similar highly organized microscale structures in tissue engineering may yield a remedy for problems ranging from vascularization to cell function control/determination. In this review, we highlight the recent progress in the field of microscale tissue engineering and discuss the use of various biomaterials for generating engineered tissue structures with microscale features. In particular, we will discuss the use of microscale approaches to engineer the architecture of scaffolds, generate artificial vasculature, and control cellular orientation and differentiation. In addition, the emergence of microfabricated tissue units and the modular assembly to emulate hierarchical tissues will be discussed.     

Evaluation of the shifting of the line of sight and higher order aberrations of eyes with keratoconus after corneal cross-linking

Aim

To evaluate changes in the coordinates of the line of sight (LoS) and higher order aberrations (HOAs) of eyes with keratoconus, following corneal cross-linking (CXL).

Perceptual quality‐based image communication service framework for wireless sensor networks

Wireless multimedia sensor networks (WMSNs) have an increasing variety of multimedia‐based applications including image and video transmission. In these types of applications, multimedia sensor nodes should ideally maximize perceptual quality and minimize energy expenditures in communication. For the required perceptual quality to be obtained, quality‐aware routing is a key research area in WMSNs. However, mapping the system parameters to the end user's perceptual quality‐of‐service measures is a challenging task because of incomplete identification metrics. Unfortunately, unless disputable assumptions and simplifications are made, optimal routing algorithm is not tractable. In this paper, we propose a novel image transmission framework to optimize both perceptual quality and energy expenditure in WMSNs. Our framework aims to provide acceptable perceptual quality at the end user by using an analytical distortion prediction model that is able to predict the image distortion resulting from any given error pattern. The innovation of the proposed scheme lies in the combined use of a content‐aware packet prioritization with an energy‐aware and quality‐aware routing protocol, named as image quality‐aware routing. Additionally, it does not only propose an energy‐efficient route selection policy but also manages the network load according to the energy residues of nodes, thus leading to a great energy economy. The results reveal that the framework is capable of identifying true metrics for mapping required image quality to network parameters. Copyright © 2011 John Wiley & Sons, Ltd.     

Effect of compression on the performance of a HT-PEM fuel cell

This paper shows by thorough electrochemical investigation that (1) the performances of high-temperature polymer electrolyte fuel cell membrane electrode assemblies of three suppliers are differently affected by compressive forces. (2) Membrane thickness reduction by compressive pressure takes place less than expected. (3) A contact pressure cycling experiment is a useful tool to distinguish the impact of compression on the contact resistances bipolar plate/gas diffusion layer (GDL) and GDL/catalytic layer. A detailed visual insight into the structural effects of compressive forces on membrane and gas diffusion electrode (GDE) is obtained by micro-computed X-ray tomography (μ-CT). μ-CT imaging confirms that membrane and GDEs undergo severe mechanical stress resulting in performance differences. Irreversible GDL deformation behavior and pinhole formation by GDL fiber penetration into the membrane could be observed.     

Energy recovery of biogas from juice wastewater through a short high temperature PEMFC stack

In this work, bio-hydrogen has been obtained from real industrial fruit juice wastewater using a dark fermentative process. The composition of the bio-hydrogen gas was 55% of hydrogen, 45% approx. of CO₂ and less than 1 ppm of CO. The bio-hydrogen yield was about 1.3 L per L of wastewater (1.4 mol H₂/mol hexose). The gas stream obtained in the dark fermentative process was directly fed, without any purification step, to a short PEMFC stack with composite PBI based membranes, with 2 wt.% of TiO₂, to operate at high temperature (100–200 °C). The performance of the stack was compared with the stack fed with pure hydrogen. Thus, the effect of operating at different temperatures and the use of air instead of O₂ as oxidant were tested. It was observed that a small drop of performance was reached when the stack was running with the bio-hydrogen due to the lower content of hydrogen in the stream, similar to the effect when the stack run with air instead of pure oxygen. Preliminary durability tests were also performed and showed that this bio-hydrogen can be fed directly to this type of technology without degradation processes under our operation conditions. It can be said that the composite PBI-based PEM fuel cell tolerated quite good the presence of 45% of CO₂ and traces of CO in the feed stream, overall at high temperature.     

Improving the prediction of page access by using semantically enhanced clustering

There are many parameters that may affect the navigation behaviour of web users. Prediction of the potential next page that may be visited by the web user is important, since this information can be used for prefetching or personalization of the page for that user. One of the successful methods for the determination of the next web page is to construct behaviour models of the users by clustering. The success of clustering is highly correlated with the similarity measure that is used for calculating the similarity among navigation sequences. This work proposes a new approach for determining the next web page by extending the standard clustering with the content-based semantic similarity method. Semantics of web-pages are represented as sets of concepts, and thus, user session are modelled as sequence of sets. As a result, session similarity is defined as an alignment of two sequences of sets. The success of the proposed method has been shown through applying it on real life web log data.     

Cross-document word matching for segmentation and retrieval of Ottoman divans

Motivated by the need for the automatic indexing and analysis of huge number of documents in Ottoman divan poetry, and for discovering new knowledge to preserve and make alive this heritage, in this study we propose a novel method for segmenting and retrieving words in Ottoman divans. Documents in Ottoman are difficult to segment into words without a prior knowledge of the word. In this study, using the idea that divans have multiple copies (versions) by different writers in different writing styles, and word segmentation in some of those versions may be relatively easier to achieve than in other versions, segmentation of the versions (which are difficult, if not impossible, with traditional techniques) is performed using information carried from the simpler version. One version of a document is used as the source dataset and the other version of the same document is used as the target dataset. Words in the source dataset are automatically extracted and used as queries to be spotted in the target dataset for detecting word boundaries. We present the idea of cross-document word matching for a novel task of segmenting historical documents into words. We propose a matching scheme based on possible combinations of sequence of sub-words. We improve the performance of simple features through considering the words in a context. The method is applied on two versions of Layla and Majnun divan by Fuzuli. The results show that, the proposed word-matching-based segmentation method is promising in finding the word boundaries and in retrieving the words across documents.     

Synthesis and characterization of 2‐hydroxyethylmethacrylate/2‐(3‐indol‐yl)ethylmethacrylamide‐based novel hydrogels as drug carrier with in vitro antibacterial properties

In this study, a new cationic monomer 2‐(3‐indol‐yl)ethylmethacrylamide (IEMA) derived from tryptamine was synthesized in a single step and characterized by Fourier transform infrared (FTIR), ¹H‐NMR, and ¹³C‐NMR. Then, one‐step preparation of novel poly[2‐hydroxyethylmethacrylate‐c‐2‐(3‐indol‐yl)ethylmethacrylamide], or p(HEMA‐c‐IEMA), copolymeric hydrogels has been performed successfully with IEMA and 2‐hydroxyethylmethacrylate (HEMA) as monomers using free radical aqueous polymerization. The hydrogels were characterized with scanning electron microscopy, FTIR, elemental analysis, thermogravimetric analysis, and texture profile analysis instruments. p(HEMA‐c‐IEMA) hydrogels were used for swelling, diffusion, drug release, and antibacterial activity studies. The drug‐release behavior of the hydrogels was determined as a function of time at 37 °C in pH 1.2 and 7.2. The swelling and drug‐release studies showed that an increased IEMA amount caused a higher increase in swelling and drug‐release values. Additionally, zero‐order, first‐order, and Higuchi equation kinetic models were applied to the drug‐release data, and the data fit well in the Higuchi model, and the Peppas power‐law model was applied to the release mechanism. Finally, the antibacterial activities of the hydrogels were screened against Gram‐positive bacteria (Bacillus cereus and Staphylococcus aureus) and Gram‐negative bacteria (Escherichia coli and Salmonella typhimurium). © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 45550.     

The subspace Gaussian mixture model—A structured model for speech recognition

We describe a new approach to speech recognition, in which all Hidden Markov Model (HMM) states share the same Gaussian Mixture Model (GMM) structure with the same number of Gaussians in each state. The model is defined by vectors associated with each state with a dimension of, say, 50, together with a global mapping from this vector space to the space of parameters of the GMM. This model appears to give better results than a conventional model, and the extra structure offers many new opportunities for modeling innovations while maintaining compatibility with most standard techniques.     

Enumerating Minimal Subset Feedback Vertex Sets

The Subset Feedback Vertex Set problem takes as input a pair (G,S), where G=(V,E) is a graph with weights on its vertices, and S?V. The task is to find a set of vertices of total minimum weight to be removed from G, such that in the remaining graph no cycle contains a vertex of S. We show that this problem can be solved in time O(1.8638 ⁿ ), where n=|V|. This is a consequence of the main result of this paper, namely that all minimal subset feedback vertex sets of a graph can be enumerated in time O(1.8638 ⁿ ).