A pattern recognition-based approach for phylogenetic network construction with constrained recombination

The tree representation of evolutionary relationship oversimplifies the view of the process of evolution as it cannot take into account the events such as horizontal gene transfer, hybridization, homoplasy and genetic recombination. Several algorithms exist for constructing phylogenetic networks which result from events such as horizontal gene transfer, hybridization and homoplasy. Very little work has been published on the algorithmic detail of phylogenetic networks with constrained recombination. The problem of minimizing the number of recombinations in a phylogenetic network, constructed using binary DNA sequences, is NP-hard. In this paper, we propose a pattern recognition-based O(n²) time approach for constructing the phylogenetic network, where n is the number of nodes or sequences in the input data. The network is constructed with the restriction that no two cycles in the network share a common node.     

Preparation and properties of poly(ethylene oxide) star polymers

Poly(ethylene oxide) (PEO) star polymers were prepared by anionic polymerization of methacryloyl chloride and glyceryl trimethacrylate with sec‐butyllithium in cyclohexane. The ensuing polymers were grafted with poly(ethylene glycol) of molecular weight 400. The final product was washed with methylene chloride and analyzed with infrared spectroscopy, differential scanning calorimetry, and thermogravimetry. Star polymers of PEO were also prepared by anionic polymerization of glycidol with sec‐butyllithium in cyclohexane. The initiator was chosen so as to yield a polymer of 10,000 molecular weight. The resulting polymers were analyzed by nuclear magnetic resonance, infrared spectroscopy, and thermogravimetry. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 87: 322–327, 2003     

Efficient compression and network adaptive video coding for distributed video surveillance

The availability of cheap network based video cameras and the prevalence of wireless networks has lead to a major thrust towards deployment of large scale Distributed Video Surveillance (DVS) systems. This has opened up an important area of research to deal with the issues involved in DVS system for efficient collection and transmission of large scale video streams from the cameras at the guarded sites, to the end users in possibly constrained network conditions. In this paper, we propose a framework based on content-based video classification and scalable compression scheme to provide a robust bandwidth efficient video transmission for DVS. The scheme builds on a Discrete Wavelet Transform (DWT) based Color-Set Partitioning for Hierarchical Trees (CSPIHT) coding to obtain a scalable bitstream. Wavelet domain segmentation and compression assists in development of a DVS architecture. The architecture includes a novel module for dynamic allocation of Network bandwidth based on the current available resources and constraints. Different frame constituents are optimally coded based on their relative significance, perceptual quality, and available estimate of network bandwidth. Experimental result over different video sequences and simulations for Network conditions demonstrate the efficient performance of the approach.     

OS-Guard: on-site signature based framework for multimedia surveillance data management

This paper presents OS-Guard(On-Site Guard), a novel on-site signature based framework for multimedia surveillance data management. One of the major concerns in widespread deployment of multimedia surveillance systems is the enormous amount of data collected from multiple media streams that need to be communicated, observed and stored for crime alerts and forensic analysis. This necessitates investigating efficient data management techniques to solve this problem. This work aims to tackle this problem, motivated by the following observation, more data does not mean more information. OS-Guard is a novel framework that attempts to collect informative data and filter out non-informative data on-site, thus taking a step towards solving the data management problem. In the framework, both audio and video cues are utilized by extracting features from the incoming data stream and the resultant real valued feature data is binarized for efficient storage and processing. A feature selection process based on association rule mining selects discriminant features. A short representative sample of the whole database is generated using a novel reservoir sampling algorithm that is stored onsite and used with an support vector machine to classify an important event. Initial experiments for a Bank ATM monitoring scenario demonstrates promising results.     

2-DOF vibratory gyroscope fabricated by SU-8 based UV-LIGA process

This paper reports fabrication of 2-DOF vibratory gyroscope using SU-8 based UV-LIGA process. The device structure is designed to be symmetrical in order to match the resonance frequencies of drive and sense mode oscillators and also to minimize their relative temperature dependent drift. The overall arrangement is such that the two vibration modes do not affect each other and therefore, mechanical decoupling is achieved which helps in minimizing bias drift. The design is optimized to be compatible with the UV-LIGA process having 10 μm thick electroformed nickel as structural layer. Photolithography to create 11 μm thick SU-8 molds for electroforming sacrificial copper and structural nickel layer is optimized using multiple exposure technique that ensures near vertical side walls. Since the highly cross-linked SU-8 remaining after development is difficult to remove reliably from high aspect ratio structures without damage or alteration to the electroformed metals, a 2.45 GHz MW plasma etching process is developed with CF₄/O₂ mixes. The fabricated device is checked for off-plane misalignment between the stationary and movable comb fingers using white light interferometry and it is found to be almost negligible. Also, the prototype device is characterized for amplitude and phase spectral responses using Polytec MSA-500 Micro System Analyzer. The drive and sense mode resonance frequencies are observed at 7.3 and 7.1 kHz respectively against the mode matched designed frequency of 7.5 kHz.     

Pruning deep convolutional neural networks for efficient edge computing in condition assessment of infrastructures

Health monitoring of civil infrastructures is a key application of Internet of things (IoT), while edge computing is an important component of IoT. In this context, swarms of autonomous inspection robots, which can replace current manual inspections, are examples of edge devices. Incorporation of pretrained deep learning algorithms into these robots for autonomous damage detection is a challenging problem since these devices are typically limited in computing and memory resources. This study introduces a solution based on network pruning using Taylor expansion to utilize pretrained deep convolutional neural networks for efficient edge computing and incorporation into inspection robots. Results from comprehensive experiments on two pretrained networks (i.e., VGG16 and ResNet18) and two types of prevalent surface defects (i.e., crack and corrosion) are presented and discussed in detail with respect to performance, memory demands, and the inference time for damage detection. It is shown that the proposed approach significantly enhances resource efficiency without decreasing damage detection performance.     

Chemopreventive Effect of Different Ratios of Fish Oil and Corn Oil in Experimental Colon Carcinogenesis

n-3 Polyunsaturated fatty acids (PUFA) have a chemopreventive effect while n-6 PUFA promote carcinogenesis. The effect of these essential fatty acids may be related to oxidative stress. Therefore, the study was designed to evaluate the effect of different ratios of fish oil (FO) and corn oil (CO) in the prevention of colon cancer. Male Wistar rats were divided into control, dimethylhydrazine dihydrochloride (DMH) treated, FO + CO (1:1) and FO + CO (2.5:1). All the groups, except the control received a weekly injection of DMH for 4 weeks. The animals were sacrificed either 48 h later (initiation phase) or kept for 16 weeks (post initiation phase). DMH treatment in the initiation phase animals showed mild to moderate inflammation, decreased ROS and TrxR activity, increased antioxidants, apoptosis and ACF multiplicity. The post initiation study showed severe inflammation with hyperplasia, increased ACF multiplicity and ROS levels, a decrease in antioxidants and apoptosis. The FO + CO (1:1) treated animals showed severe inflammation, a decrease in ROS, an increase in antioxidants and apoptosis in the initiation phase. FO + CO (1:1) in the post initiation phase and FO + CO (2.5:1) in the initiation showed mild inflammation, increased ROS, apoptosis and decreased antioxidants. There was a decrease in ACF multiplicity and ROS levels, increased antioxidants and apoptosis in the post initiation phase study. The present study suggests that FO has a dose- and time-dependent chemopreventive effect in colon cancer mediated through oxidative stress and apoptosis.     

Management of Multipurpose Multireservoir Using Fuzzy Interactive Method

In this paper a fuzzy interactive method is proposed for efficient management of multipurpose multireservoir problems. The proposed method provides an option to decision maker (DM) to work in an interactive manner to achieve the conflicting objectives as close to their desired values as is practically feasible. In each iteration, fuzzy membership functions of various objectives are framed and combined into a single objective using the product operator. The single objective nonlinear optimization model thus framed in each iteration is numerically solved using genetic algorithm. The solution provides the values of the objectives which can be actually achieved keeping in view their aspired values as provided by DM. At the end of each iteration, DM has the option to modify the aspired values of one or more objectives keeping in view the results obtained by the algorithm thus far. The algorithm is stopped when DM feels satisfied with the results. The working of the proposed method has been demonstrated on the mathematical model of a realistic multipurpose multireservoir system taken from literature.