Spatial memory deficits following stimulation of hippocampal 5-HT1B receptors in the rat

The authors review the principles of reconstructive surgery for lower limb salvage after severe lower limb trauma to determine factors that have been used as decision-making criteria for limb salvage or amputation in severe lower extremity injuries and the methods of reconstruction and their outcome. The use of scoring systems and their value in acute decision making (primary amputation or limb salvage) are described. Soft-tissue reconstructive techniques, with emphasis on the use of flaps and the importance of selecting the best technique and time for the reconstruction are reviewed. Skeletal reconstructive techniques are described, including available options and currently held views on indications and use of the best contemporary methods. It is essential for the physician to make a good initial decision on the need for primary amputation or limb salvage. A multidisciplinary approach is fundamental to successful salvage.     

Improved genetic algorithm for channel allocation with channel borrowing in mobile computing

This paper exploits the potential of the Genetic Algorithm to solve the cellular resource allocation problem. When a blocked host is to be allocated to a borrowable channel, a crucial decision is which neighboring cell to choose to borrow a channel. It is an optimization problem and the genetic algorithm is efficiently applied to handle this. The Genetic Algorithm, for this particular problem, is improved by introducing a new genetic operator, named pluck, that incorporates a problem-specific knowledge in population generation and leads to a better channel utilization by reducing the average blocked hosts. The pluck operator makes the crucial decision of when and which cell to borrow with the future consideration that the borrowing should not lead the network to chaos. It makes a channel borrowing decision that minimizes the number of blocked hosts and improves the long-term performance of the network. Efficacy of the proposed method has been evaluated by experimentation.     

Interaction of nonylphenol and hepatic CYP1A in rats

Both estradiol and nonylphenol (NP) inhibited hepatic microsomal 7-ethoxyresorufin O-deethylase (EROD) activity of beta-naphthoflavone-treated rats. Enzyme kinetic analyses (Lineweaver-Burk plots) using different estradiol and NP concentrations with graded increases in the concentrations of the substrate, ethoxyresorufin, showed that the inhibition was of a competitive nature at all concentrations of estradiol or NP used. Thus, the mechanism by which NP inhibits EROD activity is similar to that of estradiol. NP, however, was much less potent than estradiol. Young rats treated in vivo with 80 mg/kg body weight of NP demonstrated a slight but significant decrease in their hepatic microsomal EROD activity and CYP1A protein as measured by western blot analysis. In addition, treatment with NP led to a decrease in the steady-state levels of hepatic CYP1A mRNA in rats, suggesting that NP acted at the pre-translational level. The competitive nature of inhibition by NP on hepatic microsomal EROD activity indirectly suggests that this compound is a possible substrate of the CYP1A enzyme. Furthermore, NP had a moderate modulating effect on the expression of CYP1A in rat liver.     

VPR-Bench: An Open-Source Visual Place Recognition Evaluation Framework with Quantifiable Viewpoint and Appearance Change

International Journal of Computer Vision - Visual place recognition (VPR) is the process of recognising a previously visited place using visual information, often under varying appearance...     

ANDES: efficient evaluation of NOT-twig queries in relational databases

Despite a large body of work on XPath query processing in relational environment, systematic study of queries containing not-predicates have received little attention in the literature. Particularly, several xml supports of industrial-strength commercial rdbms fail to efficiently evaluate such queries. In this paper, we present an efficient and novel strategy to evaluate not -twig queries in a tree-unaware relational environment. not -twig queries are XPath queries with ancestor–descendant and parent–child axis and contain one or more not-predicates. We propose a novel Dewey-based encoding scheme called Andes (ANcestor Dewey-based Encoding Scheme), which enables us to efficiently filter out elements satisfying a not-predicate by comparing their ancestor group identifiers. In this approach, a set of elements under the same common ancestor at a specific level in the xml tree is assigned same ancestor group identifier. Based on this scheme, we propose a novel sql translation algorithm for not-twig query evaluation. Experiments carried out confirm that our proposed approach built on top of an off-the-shelf commercial rdbms significantly outperforms state-of-the-art relational and native approaches. We also explore the query plans selected by a commercial relational optimizer to evaluate our translated queries in different input cardinality. Such exploration further validates the performance benefits of Andes.     

First-principles investigation of F-functionalized ZGNR/AGNR for nanoscale interconnect applications

Journal of Computational Electronics - Zigzag and armchair graphene nanoribbons (ZGNR and AGNR) have been investigated using the density functional theory (DFT) and nonequilibrium Green’s...     

Enhancement of electromechanical properties of natural rubber by adding barium titanate filler: An electro-mechanical study

Natural rubber is one of the most potential electro-active polymers for sensors, actuators, and energy harvesting applications. Enhancing the characteristic properties of polymers by reinforcing with fillers that possess multifunctional attributes have attracted considerable attention. In the present study, barium titanate reinforced natural rubber composite is prepared by using two-roll mill mixing. Afterwards, mechanical, electrical, and electromechanical properties of the composites are extensively analyzed by reinforcing different amounts of barium titanate into the matrix of natural rubber. The fabricated dielectric composite shows excellent properties such as high dielectric constant, low dielectric losses, high dielectric breakdown strength, and extreme stretchability. It is observed that as the filler loading reaches the value of 11 parts per hundred rubber (phr), maximum agglomeration of the particles occurs. Maximum stretchability and highest ratio of dielectric constant to elastic modulus are obtained at 8 phr of barium titanate fillers and at the loading, a maximum actuation strain of 11.24% is achieved. This study provides a simple, economical, and effective method for preparing enhanced mechanical, electrical, and electromechanical properties of natural rubber composites, facilitating the wide applications of dielectric materials as actuators and generators.     

Distributed probabilistic inferencing in sensor networks using variational approximation

This paper considers the problem of distributed inferencing in a sensor network. It particularly explores the probabilistic inferencing problem in the context of a distributed Boltzmann machine-based framework for monitoring the network. The paper offers a variational mean-field approach to develop communication-efficient local algorithm for variational inferencing in distributed environments (VIDE). It compares the performance of the proposed approximate variational technique with respect to the exact and centralized techniques. It shows that the VIDE offers a much more communication-efficient solution at very little cost in terms of the accuracy. It also offers experimental results in order to substantiate the scalability of the proposed algorithm.     

An Architectural Framework for Accurate Characterization of Network Traffic

In networks carrying large volume of traffic, accurate traffic characterization is necessary for understanding the dynamics and patterns of network resource usage. Previous approaches to flow characterization are based on random sampling of the packets (e.g., Cisco's NetFlow) or inferring characteristics solely based on long lived flows (LLFs) or on lossy data structures (e.g., bloom filters, hash tables). However, none of these approaches takes into account the heavy-tailed nature of the Internet traffic and separates the estimation algorithm from the flow measurement architecture.In this paper, we propose an alternate approach to traffic characterization by closely linking the flow measurement architecture with the estimation algorithm. Our measurement framework stores complete information related to short lived flows (SLFs) while collecting partial information related to LLFs. For real-time separation of LLFs and SLFs, we propose a novel algorithm based on typical sequences from Information theory. The distribution (pdf) and sample space of the underlying traffic is estimated using the non-parametric Parzen window technique and likelihood function defined over the Coupon collector problem. We validate the accuracy and performance of our estimation technique using traffic traces from the internal LAN in our laboratory and from National Library for Applied Network Research (NLANR).     

Reliable before-fabrication forecasting of MEMS piezoresistive pressure sensor: mathematical modelling and numerical simulation

Microsystem Technologies - Micro-mechanical systems (MEMS) based piezoresistive pressure sensors have significant importance in several pressure sensor devices in real world, i.e., aviation, IoT...