Functional copolymer of geraniol and acrylonitrile: Synthesis and characterization

The radical copolymerization of acyclic terpene namely geraniol [GER] with acrylonitrile [AN] in DMF at (70 ± 0.1)°C for 1 h, using benzoylperoxide (BPO) as an initiator has been carried out under inert atmosphere of nitrogen. The kinetic expression for reaction is R_p ∝ [BPO]^0.5 [AN]^1.0 [GER]^1.0. The IR spectrum of the copolymer shows bands at 3432 and at 2244 cm^?1 due to ? OH group of GER and ? CN group of AN, respectively. The ¹³C‐NMR spectrum shows peaks at 73–75 δ ppm and 116–120 δ ppm due to ? OH group of GER and ? CN group of AN, respectively. The thermogravimetric analysis and differential scanning calorimetry study shows that copolymer is thermally stable up to 407°C and has glass transition temperatures (T_g) 56°C. The reactivity ratios r₁ (AN) and r₂ (GER) have been calculated as 0.05 and 0.005, respectively. The Alfrey‐Price Q‐e parameter for GER has been calculated as 0.094 and ?2.0, respectively. The molecular weights of the copolymers have been evaluated by gel‐permeation chromatography. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Cervid Prion Protein Polymorphisms: Role in Chronic Wasting Disease Pathogenesis

Chronic wasting disease (CWD) is a prion disease found in both free-ranging and farmed cervids. Susceptibility of these animals to CWD is governed by various exogenous and endogenous factors. Past studies have demonstrated that polymorphisms within the prion protein (PrP) sequence itself affect an animal’s susceptibility to CWD. PrP polymorphisms can modulate CWD pathogenesis in two ways: the ability of the endogenous prion protein (PrP^C) to convert into infectious prions (PrP^Sc) or it can give rise to novel prion strains. In vivo studies in susceptible cervids, complemented by studies in transgenic mice expressing the corresponding cervid PrP sequence, show that each polymorphism has distinct effects on both PrP^C and PrP^Sc. It is not entirely clear how these polymorphisms are responsible for these effects, but in vitro studies suggest they play a role in modifying PrP epitopes crucial for PrP^C to PrP^Sc conversion and determining PrP^C stability. PrP polymorphisms are unique to one or two cervid species and most confer a certain degree of reduced susceptibility to CWD. However, to date, there are no reports of polymorphic cervid PrP alleles providing absolute resistance to CWD. Studies on polymorphisms have focused on those found in CWD-endemic areas, with the hope that understanding the role of an animal’s genetics in CWD can help to predict, contain, or prevent transmission of CWD.     

2,2′-oxo-1,1′-azobenzene: microbial transformation of rye (Secale cereale L.) allelochemical in field soils byAcinetobacter calcoaceticus: III

Acinetobacter calcoaceticus, a gram-negative bacterium isolated from field soil, was found to be responsible for the biotransformation of 2(3H)-benzoxazolinone (BOA) to 2,2-oxo-1,1-azobenzene (AZOB). Experiments were conducted to evaluate the transformation of BOA to AZOB by this microbe in sterile and nonsterile soil. Transformation studies with soils inoculated withA. calcoaceticus indicated that the production of AZOB increased linearly with the concentration of BOA in sterile soil and showed a quadratic trend in nonsterile soils. This also indicated that all soil types studied for the transformation experiments might containA. calcoaceticus capable of the conversion of benzoxazolinones.     

Fuzzy logic techniques for navigation of several mobile robots

In this paper, navigation techniques for several mobile robots as many as one thousand robots using fuzzy logic are investigated in a totally unknown environment. Fuzzy logic controllers (FLC) using different membership functions are developed and used to navigate mobile robots. First a fuzzy controller has been used with four types of input members, two types of output members and three parameters each. Next two types of fuzzy controllers have been developed having same input members and output members with five parameters each. Each robot has an array of ultrasonic sensors for measuring the distances of obstacles around it and an infrared sensor for detecting the bearing of the target. These techniques have been demonstrated in various exercises, which depicts that the robots are able to avoid obstacles as well as negotiate the dead ends and reach the targets efficiently. Amongst the techniques developed, FLC having Gaussian membership function is found to be most efficient for mobile robots navigation.     

Auto-generation of IEC standard PLC code using t-MPSG

The objective of this paper is to reduce the development time of a PLC (Programmable Logic Controller) by automating the task of code generation. For this purpose, we applied t-MPSG (Timed-Message Based Part State Graph). The t-MPSG is an extended finite state automata used to model and generate an execution module for a real-time shop floor controller system. In our proposed method, t-MPSG is used to model the formal specification of the controller system that can be translated into textual structure. After the verification of the t-MPSG model, it can be used as an input to the plc-builder tool. The plc-builder tool is an extended version of a conventional MPSG simulator. It can be used to translate the textual structure of the t-MPSG into an IEC standard PLC code. Finally, the generated code can be downloaded to a PLC emulator or a PLC device for the purpose of simulation and execution. The similarity in the hierarchical structure of the t-MPSG and the IEC standard PLC program has made it convenient to transform from one form to another. Furthermore, an illustration of the methodology to auto-generate IEC standard PLC code using t-MPSG is explained with a suitable example. Recommended by Editorial Board member Young Soo Suh under the direction of Editor Jae Weon Choi. This work was partially supported by Defense Acquisition Program Administration and Agency for Defense Development under the contract (UD080042AD). Devinder Thapa is a Postdoc Research Fellow in the Department of Industrial & information systems at Ajou University, Korea. He completed his Ph.D. from Ajou University in Industrial and Information Systems Engineering. His area of research is related to manufacturing automation and intelligent decision support systems. Chang Mok Park is a Professor in the Department of Technology & Systems Management at Induk Institute of Technology. He completed his Ph.D. in 2002 from Ajou University in Industrial Engineering. His research interest is related to manufacturing optimization, discrete event system simulation and signal analysis. Sang C. Park is an Associate Professor in the Department of Industrial & Information Systems Engineering at Ajou University. He received his B.S., M.S., and Ph.D. degrees from KAIST in 1994, 1996, and 2000, respectively, all in Industrial Engineering. His research interests include geometric algorithms in CAD/CAM, process planning, engineering knowledge management, and discrete event system simulation. Gi-Nam Wang is the Head and a Professor in the Department of Industrial & Information Systems Engineering at Ajou University, Korea. He completed his Ph.D. in 1992 from Texas A&M University, in Industrial Engineering. He has worked as Visiting Professor at University of Texas at Austin during 2000–2001. His area of research is related to Intelligent Information & manufacturing systems, system integration & automation, e-Business solutions and image processing.     

Extreme learning machine and bayesian optimization-driven intelligent framework for IoMT cyber-attack detection

The Journal of Supercomputing - The Internet of Medical Things (IoMT) is a bionetwork of allied medical devices, sensors, wearable biosensor devices, etc. It is gradually reforming the healthcare...     

Urban growth modeling of Kathmandu metropolitan region, Nepal

The complexity of urban system requires integrated tools and techniques to understand the spatial process of urban development and project the future scenarios. This research aims to simulate urban growth patterns in Kathmandu metropolitan region in Nepal. The region, surrounded by complex mountainous terrain, has very limited land resources for new developments. As similar to many cities of the developing world, it has been facing rapid population growth and daunting environmental problems. Three time series land use maps in a fine-scale (30 m resolution), derived from satellite remote sensing, for the last three decades of the 20th century were used to clarify the spatial process of urbanization. Based on the historical experiences of the land use transitions, we adopted weight of evidence method integrated in cellular automata framework for predicting the future spatial patterns of urban growth. We extrapolated urban development patterns to 2010 and 2020 under the current scenario across the metropolitan region. Depending on local characteristics and land cover transition rates, this model produced noticeable spatial pattern of changes in the region. Based on the extrapolated spatial patterns, the urban development in the Kathmandu valley will continue through both in-filling in existing urban areas and outward rapid expansion toward the east and south directions. Overall development will be greatly affected by the existing urban space, transportation network, and topographic complexity.     

A review of particle swarm optimization and its applications in Solar Photovoltaic system

Particle swarm optimization is a stochastic optimization, evolutionary and simulating algorithm derived from human behaviour and animal behaviour as well. Special property of particle swarm optimization is that it can be operated in continuous real number space directly, does not use gradient of an objective function similar to other algorithms. Particle swarm optimization has few parameters to adjust, is easy to implement and has special characteristic of memory. Paper presents extensive review of literature available on concept, development and modification of Particle swarm optimization. This paper is structured as first concept and development of PSO is discussed then modification with inertia weight and constriction factor is discussed. Issues related to parameter tuning, dynamic environments, stagnation, and hybridization are also discussed, including a brief review of selected works on particle swarm optimization, followed by application of PSO in Solar Photovoltaics.     

Autonomous bioremediation of a microbial protein (bioremediase) in Pozzolana cementitious composite

The self-bioremediation in cementitious composite material is one of the most interesting avenues relating to damage management and self-life of constructions, which needs to be cogitated. The self-bioremediation of a microbial protein-impregnated cementitious material has been explored in this work. The bioremediase protein was isolated from a hot spring bacterium (BKH1) and incorporated at three different concentrations into commercial Pozzolana cements that are widely used for mortar sample preparation. Artificial cracks were generated within the mortar samples by applying partial breaking load (50 %) and the samples were cured under water for different days. Image analysis by Crackscope and microstructure analysis by field emission scanning electron microscope ascertained the formation of irregular crystalline healing material within the cracks of the test samples. X-ray diffractometer and energy dispersive spectra analyses confirmed that the irregular crystalline structures were due to the deposition of new silicate phase (Gehlenite) within the cracks. Increase of ultrasonic pulse velocity and compressive strength, augmentation of sulphate resistance, decrease of chloride permeability and water absorption capacity revealed that there were overall improvement of mechanical properties and durability of the protein-incorporated mortar samples compared to the control (without protein incorporation) mortar samples. This cost effective and eco-friendly self-bioremediation phenomenon observed in mortar is evolved due to the biosilicification activity of bioremediase protein when amended in mortar samples. The exceptional potential of the microbial bioremediase protein for self-bioremediation attribute may add a new dimension in self-healing construction technology in near future.