Evaluation of improvement of physical and mechanical properties of bamboo fibers due to alkali treatment

Bamboo strips treated with caustic solutions of different concentrations, e.g., 5%, 10%, 15%, 20%, 25%, and 50%, were subjected to mechanical testing giving stresses on tensile strength, percent elongation at break, flexural strength, flexural modulus, and toughness. The change in average density was ?15%, and the weight loss value shows a maximum of 21.94% at 50% alkali treatment. The mechanical properties of bamboo strips increase steadily with increasing concentration of caustic soda, showing a comparable increased value at 15 and 20%, and then exhibiting a gradual fall. The percent elongation at break corroborates these observations showing a continuous decreasing trend. The properties under investigation exhibit a clear transition in between 15 and 20% alkali concentration. The morphology of strips was studied by scanning electron microscope and polarizing light microscope. The crystal structure of both untreated and treated strips was compared by XRD analysis. In both cases, the breakdown of the crystal structures of the cellulose fibers and the recrystallization or reorientation of the degraded chains that are devoid of hemicellulose are quite apparent. However, at a very high concentration (to the extent of 25%) the breakdown of structure predominates much more over the reorientation or recrystallization. © 2007 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Microarchitectures for Managing Chip Revenues under Process Variations

As transistor feature sizes continue to shrink intothe sub-90nm range and beyond, the effects of process variationson critical path delay and chip yields have amplified. A commonconcept to remedy the effects of variation is speed-binning, bywhich chips from a single batch are rated by a discrete range offrequencies and sold at different prices. In this paper, we discussstrategies to modify the number of chips in different bins andhence enhance the profits obtained from them. Particularly, wepropose a scheme that introduces a small Substitute Cacheassociated with each cache way to replicate the data elementsthat will be stored in the high latency lines. Assuming a fixedpricing model, this method increases the revenue by as much as13.8% without any impact on the performance of the chips.     

The effect of random vaccine response on the vaccination coverage required to prevent epidemics

The response people have to vaccination varies because their immune systems differ and vaccine failures occur. Here we consider the effect that a random response, independent for each vaccinee, has on the vaccination coverage required to prevent epidemics in a large community. For a community of uniformly mixing individuals an explicit expression is found for the critical vaccination coverage (CVC) and the effect of the vaccine response is determined entirely by the mean E(AB), where A and B, respectively, reflect the infectivity and susceptibility of a vaccinated individual. This result shows that the usual concept of vaccine efficacy, which focuses on the amount of protection the vaccine provides the vaccinee against infection, is not adequate to describe the requirements for preventing epidemics when vaccination affect infectivity. The estimation of E(AB) poses a problem because A and B refer to the vaccine response of the same individual. Similar results are found when there are different types of individual, but now the mean E(AB) may differ between types. However, for a community made up of households it is shown that the CVC also depends on other characteristics of the vaccine response distribution. In practice this means that estimating a single measure of vaccine effectiveness is generally not enough to determine the CVC. For a specific community of households it is found that the vaccination coverage required to prevent epidemics decreases as the variation in the vaccine response increases.     

Evaluation of wear of turning carbide inserts using neural networks

Recent trends, being towards mostly unmanned automated machining systems and consistent system operations, need reliable on-line monitoring processes. A proper on-line cutting tool condition monitoring system is essential for deciding when to change the tool. Many methods have been attempted in this connection.Recently, artificial neural networks have been tried for this purpose because of its inherent simplicity and reasonably quick data-processing capability. The present work uses the back propagation algorithm for training the neural network of 5-3-1 structure. The technique shows close matching of estimation of average flank wear and directly measured wear value. Thus the system developed demonstrates the possibility of successful tool wear monitoring on-line.     

The differential effect of polymyxin B1 on guinea pig lung mitochondrial and microsomal glycerophosphate acyltransferase

The activities of guinea pig lung mitochondrial and microsomal glycerophosphate acyltransferase differed in sensitivity to polymyxin B₁. At an antibiotic concentration of 1 mg/ml, the mitochondrial enzyme activity was stimulated twofold, but the microsomal enzyme activity was completely inhibited. Furthermore, the mitochondrial enzyme activity was stimulated by polymyxin B₁ without the addition of exogenous acyl-CoA. Additional experiments ruled out the possibility of polymyxin B₁ acting as a substrate for the mitochondrial acyltransferase. These results suggest either that the polymyxin B₁ sensitivity of mitochondrial and microsomal glycerophosphate acyltransferase is different or that their accessibility to substrates is different because the two isoenzymes are located differently in the different phospholipid microenvironment of the membranes.     

Ion-solvent interaction from viscosity and apparent molar volume of bromates,iodates and sulphates of potassium and sodium in dioxane-water mixtures at different temperatures

The viscosity and apparent molar volume of solutions of KBrO₃, NaBrO₃ KIO₃, NaIO₃, K₂SO₄ and Na₂SO₄ in dioxane (mass fraction: 10, 20 and 30%)-water mixtures at 30, 35, 40 and 45°C have been measured. The ions appear to interact appreciably and the ion-solvent interaction is of the order BrO^?₃ > IO^?₃ > SO^2?₄ and K⁺ > Na⁺.     

Critical Density for Coverage and Connectivity in Three-Dimensional Wireless Sensor Networks Using Continuum Percolation

Although most of the studies on coverage and connectivity in wireless sensor networks (WSNs) considered two-dimensional (2D) settings, such networks can in reality be accurately modeled in a three-dimensional (3D) space. The concepts of continuum percolation theory best fit the problem of connectivity in WSNs to find out whether the network provides long-distance multihop communication. In this paper, we focus on percolation in coverage and connectivity in 3D WSNs. We say that the network exhibits a coverage percolation (respectively, connectivity percolation) when a giant covered region (respectively, giant connected component) almost surely spans the entire network for the first time. Because of the dependency between coverage and connectivity, the problem is not only a continuum percolation problem but also an integrated continuum percolation problem. Thus, we propose an integrated-concentric-sphere model to address coverage and connectivity in 3D WSNs in an integrated way. First, we compute the critical density lambda_C ^con above which coverage percolation in 3D WSNs will almost surely occur. Second, we compute the critical density lambda_c ^con above which connectivity percolation in 3D WSNs will almost surely occur. Third, we compute the critical density lambda_c ^cov-con above which both coverage and connectivity percolation in 3D WSNs will almost surely occur. For each of these three problems, we also compute their corresponding critical network degree. Our results can be helpful in the design of energy-efficient topology control protocols for 3D WSNs in terms of coverage and connectivity.     

An electromyographic investigation of asymmetric lifting and moving of a load: III. Models for determining muscle activity based on anthropometric characteristics

Regression models for six muscles, the left and right iliocostalis, the left and right erector spinae, and the left and right external oblique, were developed for asymmetry and height effects for floor and knuckle lifts. The models were based on participant anthropometric and other measures. Stepwise regression was performed for developing the prediction models. The models developed were discrete in terms of specific height and asymmetry. © 2009 Wiley Periodicals, Inc.     

Challenges in Liquid‐Phase Exfoliation,Processing, and Assembly of Pristine Graphene

Recent developments in the exfoliation, dispersion, and processing of pristine graphene (i.e., non‐oxidized graphene) are described. General metrics are outlined that can be used to assess the quality and processability of various “graphene” products, as well as metrics that determine the potential for industrial scale‐up. The pristine graphene production process is categorized from a chemical engineering point of view with three key steps: i) pretreatment, ii) exfoliation, and iii) separation. How pristine graphene colloidal stability is distinct from the exfoliation step and is dependent upon graphene interactions with solvents and dispersants are extensively reviewed. Finally, the challenges and opportunities of using pristine graphene as nanofillers in polymer composites, as well as as building blocks for macrostructure assemblies are summarized in the context of large‐scale production.     

A synopsis on node compromise detection in wireless sensor networks using sequential analysis (Invited Review Article)

By exploiting the unattended nature of the wireless sensor networks, an attacker can physically capture and compromise sensor nodes and then launch a variety of attacks. He can additionally create many replicas of a few compromised nodes and spread these replicas over the network, thus launching further attacks with their help. In order to minimize the damage incurred by compromised and replicated nodes, it is very important to detect such malicious nodes as quickly as possible. In this review article, we synthesize our previous works on node compromise detection in sensor networks while providing the extended analysis in terms of performance comparison to the related work. More specifically, we use the methodology of the sequential analysis to detect static and mobile compromised nodes, as well as mobile replicated nodes in sensor networks. With the help of analytical and simulation results, we also demonstrate that our schemes provide robust and efficient node compromise detection capability.