On the stabilization of a cable with a tip mass

In this note, we consider a vertical cable which is pinched at the upper end. A mass is attached at the lower end where a control force is also applied. We show that this hybrid system is uniformly stabilized by choosing a suitable control law for the control force depending on the velocity and angular velocity at the free end. Moreover for specific values of the feedback coefficients, we obtain the rate of decay of the energy of the system     

Adapting selected nucleic acid ligands (aptamers) to biosensors

A flexible biosensor has been developed that utilizes immobilized nucleic acid aptamers to specifically detect free nonlabeled non-nucleic acid targets such as proteins. In a model system, an anti-thrombin DNA aptamer was fluorescently labeled and covalently attached to a glass support. Thrombin in solution was selectively detected by following changes in the evanescent-wave-induced fluorescence anisotropy of the immobilized aptamer. The new biosensor can detect as little as 0.7 amol of thrombin in a 140-pL interrogated volume, has a dynamic range of 3 orders of magnitude, has an inter-sensing-element measurement precision of better than 4% RSD over the range 0-200 nM, and requires less than 10 min for sample analysis. The aptamer-sensor format is generalizable and should allow sensitive, selective, and fast determination of a wide range of analytes.     

Neurotoxicity of CI-980, a novel mitotic inhibitor

PURPOSE: To compare the simulated keratometric results of the PAR CTS and the EyeSys corneal imaging systems with Javal keratometer readings in keratoconus eyes, in eyes after corneal grafting, and in healthy eyes. SETTING: Cornea Service, Wills Eye Hospital, Philadelphia, Pennsylvania, USA. METHODS: This prospective study evaluated 69 patients divided into three groups (keratoconus; 6 to 12 months postkeratoplasty; normal corneas) treated at the cornea service. The eyes were measured with each of the three instruments. Keratometry results and number of attempts needed to obtain the results were collected. RESULTS: Thirty keratoconus, 18 transplanted, and 21 normal corneas were examined. The PAR CTS Imaged all corneas and the EyeSys, 86% (P = .000627). The PAR CTS and Javal flat and steep K-readings in all three groups were the same. The EyeSys simulated keratometry results were lower than those of Javal keratometer in the flat K (P < .00001) and steep K (P < .00001) in the normal group and in the steep K in the transplanted cornea group (P = .00823). The EyeSys also measured less astigmatism than the Javal in the normal (P = .00124) and transplanted cornea groups (P = .00376). CONCLUSION: The PAR CTS was better able than the EyeSys to provide keratometric values that agreed with those obtained with the Javal keratometer.     

Effect of extraction methods and UHT treatment conditions on the level of isoflavones during soymilk manufacture

The objective of this study was to compare the effect of hot and cold grinding as well as the effect of direct and indirect ultra high temperature (UHT) treatment conditions on the level of isoflavones during the manufacture of soymilk. Soymilks were manufactured from dehulled soybeans by hot grinding or cold grinding processes. After inactivation of lipoxygenase at 85 °C, the resulting slurries were decanted and supernatants were held at 120 °C for 80 s to inactivate the trypsin inhibitor. The decanted soya bases were cooled and subjected to different temperature/time regimes by direct and indirect UHT treatments. Samples were drawn at different points in the processing operation and a reversed phase high performance liquid chromatography method was used to determine the concentration of isoflavones. Results showed that hot grinding caused a higher extraction of isoflavones into the soymilk than the cold-grinding process. However, direct or indirect heating in the UHT process did not significantly influence the concentration of isoflavones.     

Piecewise empirical model (PEM) of resistive memory for pulsed analog and neuromorphic applications

With the end of Dennard scaling and the ever-increasing need for more efficient, faster computation, resistive switching devices (ReRAM), often referred to as memristors, are a promising candidate for next generation computer hardware. These devices show particular promise for use in an analog neuromorphic computing accelerator as they can be tuned to multiple states and be updated like the weights in neuromorphic algorithms. Modeling a ReRAM-based neuromorphic computing accelerator requires a compact model capable of correctly simulating the small weight update behavior associated with neuromorphic training. These small updates have a nonlinear dependence on the initial state, which has a significant impact on neural network training. Consequently, we propose the piecewise empirical model (PEM), an empirically derived general purpose compact model that can accurately capture the nonlinearity of an arbitrary two-terminal device to match pulse measurements important for neuromorphic computing applications. By defining the state of the device to be proportional to its current, the model parameters can be extracted from a series of voltages pulses that mimic the behavior of a device in an analog neuromorphic computing accelerator. This allows for a general, accurate, and intuitive compact circuit model that is applicable to different resistance-switching device technologies. In this work, we explain the details of the model, implement the model in the circuit simulator Xyce, and give an example of its usage to model a specific \(\hbox {Ta}/\hbox {TaO}_{\mathrm{x}}\) device.     

Contribution of the space charge to the grain boundary energy in yttria-stabilized zirconia

A model based on the effect of a modest applied dc electric field on grain growth is proposed for the contribution of the space charge to the grain boundary (GB) energy in 3 mol % yttria-stabilized zirconia (3 YSZ). The model considers that the total GB energy \( \gamma_{\text{b}}^0 \) (the capillary driving force for grain growth) consists of three major components: (a) \( \gamma_{\text{b}}^\varSigma \) due to the misorientation between neighboring grains, (b) \( \gamma_{\text{b}}^{\text{s}} \) due to the size misfit between the segregated solute and the solvent cations, and (c) \( \gamma_{\text{b}}^{\text{e}} \) the electrostatic (space charge) component, which results from the segregation of the aliovalent yttrium ions to the grain boundaries. The former two components combined comprise 40 % of the total GB energy in 3 YSZ and the electrostatic component 60 %. Based on the model, the calculated magnitudes of the three components were in qualitative accord with theoretical considerations and with values reported in the literature. A reduction in \( \gamma_{\text{b}}^{\text{e}} , \) and in turn in \( \gamma_{\text{b}}^0 , \) results from the bias exerted by the applied field on the space charge potential that occurs with the segregation of the yttrium ions to the grain boundaries. The observed reduction of grain growth in 3 YSZ by an applied electric field is attributed mainly to the reduction in \( \gamma_{\text{b}}^{\text{e}} \) by the field.     

A situated approach to the acquisition of shared SA in team contexts

Theories of team situation awareness (SA) differ in the information they require operators to have for effective coordination. Endsley stresses shared SA, whereas distributed SA argues that coordination involves transactive and compatible SA. We distinguish between weak and strong shared SA, and argue the latter enhances communication and increases team cohesion. Although we agree with Endsley on the importance of shared SA, we argue her account of how it is acquired exceeds the working memory capacity of individual team members. We offer an account consistent with our situated SA perspective that claims individuals off-load information to their environment whenever possible to minimise effortful internal processing. We argue that our approach, in conjunction with Pickering and Garrod's (2004, Towards a mechanistic psychology of dialogue. Behavioral and Brain Sciences, 27, pp. 169–226) interactive-alignment model, can explain how shared SA is acquired, relying on automatic processes enacted when individuals interact in conversations. This approach can be used to study team SA in many complex and distributed systems.     

Enhanced sintering rate and finer grain size in yttria-stablized zirconia (3Y-TZP) with combined DC electric field and increased heating rate

The influence of heating rate dT/dt = 2-25 °C/min on sintering of yttria-stabilized ZrO₂ (3Y-TZP) powder without and with a small initial DC electric field (E₀ = 13.9 V/cm) was determined. An increase in dT/dt and the application of electric field reduced both the sintering time and the grain size at a given density. Employing the master sintering curve approach it was determined that the apparent activation energy Q for sintering was 500 ± 5 kJ/mole, essentially independent of dT/dt and E. A major factor in the effects of dT/dt and E on the sintering rate is their reduction of the grain size. It is proposed that retardation of grain growth by the field results from the interaction of the field with the space charge at the grain boundaries.     

A comparison of artificial neural networks and partial least squares modelling for the rapid detection of the microbial spoilage of beef fillets based on Fourier transform infrared spectral fingerprints

A series of partial least squares (PLS) models were employed to correlate spectral data from FTIR analysis with beef fillet spoilage during aerobic storage at different temperatures (0, 5, 10, 15, and 20 °C) using the dataset presented by Argyri et al. (2010). The performance of the PLS models was compared with a three-layer feed-forward artificial neural network (ANN) developed using the same dataset. FTIR spectra were collected from the surface of meat samples in parallel with microbiological analyses to enumerate total viable counts. Sensory evaluation was based on a three-point hedonic scale classifying meat samples as fresh, semi-fresh, and spoiled. The purpose of the modelling approach employed in this work was to classify beef samples in the respective quality class as well as to predict their total viable counts directly from FTIR spectra. The results obtained demonstrated that both approaches showed good performance in discriminating meat samples in one of the three predefined sensory classes. The PLS classification models showed performances ranging from 72.0 to 98.2% using the training dataset, and from 63.1 to 94.7% using independent testing dataset. The ANN classification model performed equally well in discriminating meat samples, with correct classification rates from 98.2 to 100% and 63.1 to 73.7% in the train and test sessions, respectively. PLS and ANN approaches were also applied to create models for the prediction of microbial counts. The performance of these was based on graphical plots and statistical indices (bias factor, accuracy factor, root mean square error). Furthermore, results demonstrated reasonably good correlation of total viable counts on meat surface with FTIR spectral data with PLS models presenting better performance indices compared to ANN.