A backbone-reversed all-{beta} polypeptide (retro-CspA) folds and assembles into amyloid nanofibres

The backbone-reversed or ‘retro’, form of a modelall-ß-sheet protein, Escherichia coli CspA, was producedfrom a synthetic gene in E.coli in fusion with an N-terminalaffinity tag. Following purification under denaturing conditionsand dialysis-based removal of urea, the protein was found tofold into a soluble, poorly structured multimer. Upon concentration,this state readily transformed into amyloid nanofibres. CongoRed-binding amorphous forms were also observed. Since a ß-sheet-formingsequence is expected to retain high ß-sheet-formingpropensity even after backbone reversal and given the fact thatfolding of retro-CspA occurs only to a poorly structured form,we conclude that the increase effected in protein concentrationmay be responsible for the formation of intermolecular ß-sheets,facilitating the bleeding away of the protein’s conformationalequilibrium into aggregates that generate well-formed fibres.Since every molecule in these fibres contains a peptide tagfor binding Ni²⁺, the fibres may provide a template for depositionof nickel to generate novel materials. Received April 1, 2003; revised October 27, 2003; accepted October 30, 2003     

VILO: a rapid learning nearest-neighbor classifier for malware triage

VILO is a lazy learner system designed for malware classification and triage. It implements a nearest neighbor (NN) algorithm with similarities computed over Term Frequency $\times $ Inverse Document Frequency (TFIDF) weighted opcode mnemonic permutation features (N-perms). Being an NN-classifier, VILO makes minimal structural assumptions about class boundaries, and thus is well suited for the constantly changing malware population. This paper presents an extensive study of application of VILO in malware analysis. Our experiments demonstrate that (a) VILO is a rapid learner of malware families, i.e., VILO’s learning curve stabilizes at high accuracies quickly (training on less than 20 variants per family is sufficient); (b) similarity scores derived from TDIDF weighted features should primarily be treated as ordinal measurements; and (c) VILO with N-perm feature vectors outperforms traditional N-gram feature vectors when used to classify real-world malware into their respective families.     

Least eccentric ellipses for geometric Hermite interpolation

We present a rational Bézier solution to the geometric Hermite interpolation problem. Given two points and respective unit tangent vectors, we provide an interpolant that can reproduce a circle if possible. When the tangents permit an ellipse, we produce one that deviates least from a circle. We cast the problem as a theorem and provide its proof, and a method for determining the weights of the control points of a rational curve. Our approach targets ellipses, but we also present a cubic interpolant that can find curves with inflection points and space curves when an ellipse cannot satisfy the tangent constraints.     

Performance analysis of tool electrode prepared through laser sintering process during electrical discharge machining of titanium

The International Journal of Advanced Manufacturing Technology - It is of great significance for intelligent manufacturing to study condition monitoring and diagnosis methods to realize early...     

Ab initio and thermodynamic modelling of alloying effects on activity of sacrificial aluminium anodes

This work summarizes the experimental literature to date on Al-alloy sacrificial anodes and shows that the presence of Sn as an alloying element in solid solution form consistently debases the alloy corrosion potential. This study then assesses the lattice expander theory, which states that lattice-expanding dopants can be used to increase Sn solubility in Al and thereby reduce passivation. The thermodynamic effects on Sn solubility of lattice expanders (Ga, Mg, Zr, In and Bi) are predicted with ab-initio methods. Our results support lattice expander theory although we demonstrate that Sn solubility can decrease by alloying with even large dopants if they form compounds with Sn.     

Active wafer shape modulation using a multi-actuator chucking system

Jet and Flash Imprint Lithography has proven to be a viable alternative to optical lithography for fabrication of sub 30 nm nanostructures for large volume semiconductor manufacturing. Machine throughput, overlay and process defectivity that meet and exceed the International Technology Roadmap for Semiconductors (ITRS) are essential for commercial viability of any new lithography technology. Jet and Flash Imprint Lithography uses an inkjet head to dispense a grid of liquid drops on the wafer surface to match the volume requirements of the pattern being imprinted. Wafer shape modulation has been shown to increase imprinting speed significantly by reducing air bubble trapping in the drop interstitial sites. A wafer shape modulation chuck that can address arbitrary field locations and sizes on a wafer with a novel actuation scheme that minimizes the number of actuators while increasing imprinting speed and reducing process defects significantly is presented.     

Analysis of Test Application Time for Test Data Compression Methods Based on Compression Codes

We present an analysis of test application time for test data compression techniques that are used for reducing test data volume and testing time in system-on-a-chip (SOC) designs. These techniques are based on data compression codes and on-chip decompression. The compression/decompression scheme decreases test data volume and the amount of data that has to be transported from the tester to the SOC. We show via analysis as well as through experiments that the proposed scheme reduces testing time and allows the use of a slower tester. Results on test application time for the ISCAS'89 circuits are obtained using an ATE testbench developed in VHDL to emulate ATE functionality.     

Detection of tuberculosis using MEMS

Microsystem Technologies - Tuberculosis is a contagious disease caused by the bacteria, Mycobacterium Tuberculosis. Early detection of TB is vital to increase the chances of cure. In this paper, a...     

Fault detection during process transitions: a model-based approach

Startup, shutdown and other transitions are integral to batch and continuous process operations. Operators usually execute transitions in manual mode. Processes are therefore prone to operator errors in addition to process faults during transitions. If undetected, such abnormalities can lead to process downtime and in the worst case, accidents. Although essential, fault detection during transitions has received little attention in literature. This paper presents a novel multiple filters and observers based fault detection scheme using (i) a nonlinear process model, and (ii) knowledge of the standard operating procedure for executing the transition. Extended Kalman filters, Kalman filters, and open-loop observers are used to estimate process states during the transition and generate residuals. These residuals indicate deviations from normal operation due to process faults and operator errors. The model-based scheme has been implemented in Matlab/Simulink and found to successfully detect faults during the startup of an experimental pH neutralization CSTR.