Antibacterial activity of teicoplanin against Clostridium difficile

The in vitro inhibitory action of teicoplanin, vancomycin, metronidazole and clindamycin against clinical isolates of Clostridium difficile was investigated. Minimum inhibitory concentrations (MICs) were determined using E test. Teicoplanin (MIC range 0.023-0.75 microgram/ml), vancomycin (MIC range 0.5-3 micrograms/ml) and metronidazole (MIC range 0.19-1 microgram/ml) were all very active against the isolates examined. No resistant strains of C. difficile to those three antimicrobial agents were observed, whereas resistance to clindamycin was found in 39.5% of the tested strains. Teicoplanin was about 4-times more potent than vancomycin. It appears to be a more promising antimicrobial for treatment of C. difficile enteric disease.     

Handling class imbalance problem in software maintainability prediction: an empirical investigation

As the complexity of software systems is increasing; software maintenance is becoming a challenge for software practitioners. The prediction of classes that require high maintainability effort is of utmost necessity to develop cost-effective and high-quality software. In research of software engineering predictive modeling, various software maintainability prediction (SMP) models are evolved to forecast maintainability. To develop a maintainability prediction model, software practitioners may come across situations in which classes or modules requiring high maintainability effort are far less than those requiring low maintainability effort. This condition gives rise to a class imbalance problem (CIP). In this situation, the minority classes’ prediction, i.e., the classes demanding high maintainability effort, is a challenge. Therefore, in this direction, this study investigates three techniques for handling the CIP on ten open-source software to predict software maintainability. This empirical investigation supports the use of resampling with replacement technique (RR) for treating CIP and develop useful models for SMP.     

A two‐phase harmony search algorithm for continuous optimization

Harmony search (HS) algorithm is inspired by the music improvisation process in which a musician searches for the best harmony and continues to polish the harmony to improve its aesthetics. The efficiency of evolutionary algorithms depends on the extent of balance between diversification and intensification during the course of the search. An ideal evolutionary algorithm must have efficient exploration in the beginning and enhanced exploitation toward the end. In this paper, a two‐phase harmony search (TPHS) algorithm is proposed that attempts to strike a balance between exploration and exploitation by concentrating on diversification in the first phase using catastrophic mutation and then switches to intensification using local search in the second phase. The performance of TPHS is analyzed and compared with 4 state‐of‐the‐art HS variants on all the 30 IEEE CEC 2014 benchmark functions. The numerical results demonstrate the superiority of the proposed TPHS algorithm in terms of accuracy, particularly on multimodal functions when compared with other state‐of‐the‐art HS variants; further comparison with state‐of‐the‐art evolutionary algorithms reveals excellent performance of TPHS on composition functions. Composition functions are combined, rotated, shifted, and biased version of other unimodal and multimodal test functions and mimic the difficulties of real search spaces by providing a massive number of local optima and different shapes for different regions of the search space. The performance of the TPHS algorithm is also evaluated on a real‐life problem from the field of computer vision called camera calibration problem, ie, a 12‐dimensional highly nonlinear optimization problem with several local optima.     

Structural and optical properties of sol gel derived Cu2ZnSnS4 nanoparticles

The spherical Cu₂ZnSnS₄ nanoparticles with the average diameters (～8–10 nm) have been synthesized by sol gel method. The effects of solvents and reaction temperatures on the properties of the as-synthesized nanoparticles were investigated. The X-ray diffraction shows as grown Cu₂ZnSnS₄ nanoparticles exhibit kesterite crystal structure along preferential orientation (1 1 2) plane. The crystalline nature of nanoparticles was improved in ethylene glycol solvent with the increase in reaction temperature. Rietveld refinement study was performed and structural parameters were determined for the Cu₂ZnSnS₄ nanoparticles. The Raman spectra show the main characteristic peak of A₁ vibrational mode which confirmed the formation of Cu₂ZnSnS₄ phase in all the samples. Scanning electron micrographs depict the irregular aggregate formation of nanoparticles in methanol solvent and uniformly distributed aggregates of nanoparticles with ethylene glycol solvent. Transmission electron microscopy results show the synthesis of polycrystalline porous nanostructures and uniform spherical nanoparticles in methanol and ethylene glycol solvents respectively at the temperature of 250 °C. UV–vis absorption spectra indicated the broad absorption in visible range and the band gap of the nanoparticles was found to 1.38 and 1.45 eV which is suitable for absorbing the solar radiation. The obtained results revealed ethylene glycol as a suitable solvent and 250 °C as the favorable synthesis temperature.     

Secure data aggregation in wireless sensor networks using homomorphic encryption

In a Wireless Sensor Network (WSN), aggregation exploits the correlation between spatially and temporally proximate sensor data to reduce the total data volume to be transmitted to the sink. Mobile agents (MAs) fit into this paradigm, and data can be aggregated and collected by an MA from different sensor nodes using context specific codes. The MA-based data collection suffers due to large size of a typical WSN and is prone to security problems. In this article, homomorphic encryption in a clustered WSN has been proposed for secure and efficient data collection using MAs. The nodes keep encrypted data that are given to an MA for data aggregation tasks. The MA performs all the data aggregation operations upon encrypted data as it migrates between nodes in a tree-like structure in which the nodes are leafs and the cluster head is the root of the tree. It returns and deposits the encrypted aggregated data to the cluster head after traversing through all the intra cluster nodes over a shortest path route. The homomorphic encryption and aggregation processing in encrypted domain makes the data collection process secure. Simulation results confirm the effectiveness of the proposed secure data aggregation mechanism. In addition to security, MA-based mechanism leads to lesser delay and bandwidth requirements.     

A Low Profile Ultra-Wideband Antenna Design with Reconfigurable Notch-Bands for Wideband and Narrowband Applications

Wireless Personal Communications - A novel low profile ultra-wideband antenna design has been presented in this work, that offers switchable band-notch characteristics suitable for both wideband...     

Improving the Local Search Ability of Spider Monkey Optimization Algorithm Using Quadratic Approximation for Unconstrained Optimization

Spider monkey optimization (SMO) algorithm, which simulates the food searching behavior of a swarm of spider monkeys, is a new addition to the class of swarm intelligent techniques for solving unconstrained optimization problems. The purpose of this article is to study the performance of SMO after incorporating quadratic approximation (QA) operator in it. The proposed version is named as QA‐based spider monkey optimization (QASMO). An experimental study has been carried out to check the validity and applicability of QASMO. For validation purpose, the performance of QASMO is tested over a benchmark set of 46 scalable and nonscalable problems, and results are compared with the original SMO algorithm. In order to test the applicability of the proposed algorithm in solving real‐life optimization problems, one of the most challenging optimization problems, namely, Lennard–Jones (LJ) problem is considered. LJ clusters containing atoms from three to ten have been taken into consideration, and results are presented. To the best of our knowledge, this is the first attempt to apply SMO and its proposed variant on a real‐life problem. The results demonstrate that incorporation of QA in SMO has positive effects on its performance in terms of reliability, efficiency, and accuracy.     

Development of extended zero-order release gliclazide tablets by central composite design

The purpose of this study was to develop an extended release tablet formulation containing gliclazide as a model drug by optimization technique. A central composite design was employed with pH-dependent matrix forming polymers like keltone-HVCR (X1) and eudragit-EPO (X2) as independent variables. Five dependent variables were considered: hardness, percent drug release after 1 hr, percent drug release after 6 hr, diffusion exponent and time required for 50% of drug release. Response surface methodology and multiple response optimization utilizing a quadratic polynomial equation were used to obtain an optimal formulation. The results indicate that Factor X1 along its interaction with Factor X2 was found to be significantly affecting the studied response variables. An optimized formulation, containing 8 mg of keltone-HVCR and 14.10mg of eudragit-EPO, provides a sufficient hardness (> 4.5 kg/cm2) and optimal release properties. The desirability function was used to optimize the response variables, each having a different target and the observed responses were highly agreed with experimental values. The release kinetics of gliclazide from optimized formulation followed zero-order release pattern. The dissolution profiles of optimized formulation before and after stability studies were evaluated by using similarity factor (f2) and were found to be similar. The results demonstrate the feasibility of the model in the development of extended release dosage form.