Engineering a lever into the kinesin neck

To probe for a lever arm action in the kinesin stepping mechanism, we engineered a rodlike extension piece into the tail of rat kinesin at various points close to the head-tail junction and measured its effects on the temperature dependence of velocity in microtubule gliding assays. The insert comprised two contiguous alpha-actinin triple-coil repeats and was predicted to fold into a stiff rodlike module about 11 nm long. The effects of this module were greater the closer it was placed to the head-tail junction. When inserted distal to the head-tail junction, at Asn401 in the dimeric K partial differential401GST, the insert had no effect. When inserted closer to the heads at Val376 into K partial differential376GST, the insert slowed progress below 22 degreesC but accelerated progress to approximately 125% of wild type above 22 degreesC. The most dramatic effect of the synthetic lever occurred when it was inserted very close to the head-neck junction, at Glu340 into the single-headed construct K partial differential340GST. This construct was immotile without the insert, but motile with it, at about 30% of the velocity of the dimeric control. The alpha-actinin module thus confers some gain-of-function when inserted close to the head-neck junction but not when placed distal to it. The data exclude the presence of a lever arm C-terminal to Val376 in the kinesin tail but suggest that a short-throw lever arm may be present, N-terminal to Val376 and contiguous with the head-neck junction at Ala339.     

Abrasion Resistance of Field-Assisted Ion-Exchanged Glass

The fracture strength of HF-etched samples was measured as a function of field-assisted K-Na ion exchange depth, as well as the severity of abrasion. As expected, the more severe the abrasion, the greater the depth required to make the strength insensitive to abrasion. An abrasion-independent weakening mechanism that increased with exchange depth was also found to be operative.     

Efficient mining of discriminative co-clusters from gene expression data

Discriminative models are used to analyze the differences between two classes and to identify class-specific patterns. Most of the existing discriminative models depend on using the entire feature space to compute the discriminative patterns for each class. Co-clustering has been proposed to capture the patterns that are correlated in a subset of features, but it cannot handle discriminative patterns in labeled datasets. In certain biological applications such as gene expression analysis, it is critical to consider the discriminative patterns that are correlated only in a subset of the feature space. The objective of this paper is twofold: first, it presents an algorithm to efficiently find arbitrarily positioned co-clusters from complex data. Second, it extends this co-clustering algorithm to discover discriminative co-clusters by incorporating the class information into the co-cluster search process. In addition, we also characterize the discriminative co-clusters and propose three novel measures that can be used to evaluate the performance of any discriminative subspace pattern-mining algorithm. We evaluated the proposed algorithms on several synthetic and real gene expression datasets, and our experimental results showed that the proposed algorithms outperformed several existing algorithms available in the literature.     

Mechanical and dynamic mechanical properties of jute fibers–Novolac–epoxy composite laminates

A study was done of jute composite using a polymer matrix of epoxidized Novolac resin (ENR), diglycidyl ether of bisphenol A (DGEBA)–based epoxy, and their blends with different weight percentages of the resins. It was found that on blending ENR with DGEBA, the storage modulii at room temperature are enhanced by about 100% or more in the case of 30 and 40% ENR‐containing matrices, whereas the enhancement in the case of 20 and 12% ENR‐containing matrices is only 50% that of the pure matrix. It was also observed that the tan δ peak heights of the composites containing 30 and 40% ENR are closer to that of 20% ENR‐containing composite. The probable explanation drawn on the basis of experimental findings of DMA and mechanical analysis is that by blending ENR with DGEBA epoxy it is possible to manufacture jute composites with increased stiffness without sacrificing their ductility. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 85: 2800–2807, 2002     

Elevated temperature instrumented Charpy impact of a sintered silicon carbide

A commercially available, densely sintered alpha silicon carbide was tested in air from room temperature to 1700°C using a modified instrumented pendulum unit and standard Charpy size test specimens. The resistance heated silicon carbide specimens exhibited only elastic behavior, even at 1700°C. A compliance analysis of the test revealed a linear elastic decrease of the absorbed impact energy and also a decrease of the fracture stress of the silicon carbide with increasing temperature.     

A Formal Methodology for Detecting Managerial Vulnerabilities and Threats in an Enterprise Information System

From information security point of view, an enterprise is considered as a collection of assets and their interrelationships. These interrelationships may be built into the enterprise information infrastructure, as in the case of connection of hardware elements in network architecture, or in the installation of software or in the information assets. As a result, access to one element may enable access to another if they are connected. An enterprise may specify conditions on the access of certain assets in certain mode (read, write etc.) as policies. The interconnection of assets, along with specified policies, may lead to managerial vulnerabilities in the enterprise information system. These vulnerabilities, if exploited by threats, may cause disruption to the normal functioning of information systems. This paper presents a formal methodology for detection of managerial vulnerabilities of, and threats to, enterprise information systems in linear time.     

A dynamic model for short-term prediction of stream attributes

Multiple data streams coming out of a complex system form the observable state of the system. The streams may correspond to various sensors attached with the system or outcome of internal processes. Such stream data may consist of multiple attributes and may differ in terms of their frequency of generation and observation. The streams may have dependency among themselves. One will have to rely on such data streams for monitoring the health of the system or to take any corrective measure. Predicting the value of certain stream data is an important task that can help one to take decision and act accordingly. In this work, a simple but generic visualization of a complex system is presented and thereafter a linear regression-based dynamic model for short-term prediction is proposed. The model is based on the past history of the attributes of multiple streams as suggested by the domain experts. But, it automatically determines the meaningful attributes and reformulates the model. The model is also re-computed if the prediction error exceeds the allowable tolerance. All these make the model dynamic. Experiment is carried out with stock market data streams to predict the close value well in advance. It is observed that in terms of quality of prediction and performance metric, the proposed model is quite effective.     

Some spectral response characteristics of ZnTe thin films

Zinc telluride thin films have been grown at room temperature and higher temperature substrates by thermal evaporation technique in a vacuum of 10^-6 torr. A main peak in the photocurrent is observed at 781 nm (1.58 eV) with two lower amplitude peaks on the lower wavelength side and one on higher wavelength side. The evaluated thermal activation energy is found to correspond well with the main spectral peak. From these studies it can be inferred that temperatures up to 453 K is still in the extrinsic conductivity region of the studied ZnTe thin films. The paper was presented at the 6th Asian Thermophysical Properties Conference (6th ATPC), held at Gauhati University, during 8–11 October 2001.     

e-Commerce security — A life cycle approach

The rapid evolution of computing and communication technologies and their standardizations have made the boom in e-commerce possible. Lowering of the cost of operation, increase in the speed of transactions, and easy global reach to customers and vendors have been the reasons for the overwhelming popularity of this new way of commerce. This article examines the issues related to the security of the assets and transactions in the e-commerce components and activities. Since large public money is involved in the transactions, the role of information security and privacy is not exaggerated in this kind of business. After examining the technologies used in e-commerce, the article goes on to identify the security requirement of e-commerce systems from perceived threats and vulnerabilities. Then e-commerce security is viewed as an engineering management problem and a life cycle approach is put forward. How the e-commerce systems can be made secure using the life cycle approach is outlined. The relevant standards and laws are also discussed in the perspective of e-commerce. The article closes with some future research directions and conclusions.