An Electroactive and Transparent Haptic Interface Utilizing Soft Elastomer Actuators with Silver Nanowire Electrodes

An electroactive and transparent haptic interface having a rectangular void pattern creates tunable surface textures by controlling the wavelength and amplitude of independent void‐lines. To make an active tactile surface, the transparent haptic interface employs a silver nanowire (AgNW) electrode to be compliant with the deformed elastomer surface. Here, the dielectric elastomer is newly blended with polydimethylsiloxane and Ecoflex prepolymer to simultaneously control the mechanical stiffness and transparency. The relative resistance of the AgNW electrode on a single void line is nearly unchanged under bending test, confirming the high stretchability and conductivity of the nanowire‐networked electrode. The optical transparencies are 92–85%, depending on the ratio of the Ecoflex solution. Transparency values decreas by 7 and 16% after coating with AgNWs at densities of 30 and 140 mg m^?2, respectively. Using EP31, the void line is deformed by 90 µm under a field intensity of 13.0 V µm^?1. The haptic surface is successfully controlled by applying voltage, which produces four different surface textures, from relatively smooth to rough feeling, depending on the distance between deformed void lines. This haptic interface can be applied to diverse display systems as an external add‐on screen and will help to realize programmable surface textures in the future.     

Microalgae-Based Biohybrid Microrobot for Accelerated Diabetic Wound Healing

A variety of wound healing platforms have been proposed to alleviate the hypoxic condition and/or to modulate the immune responses for the treatment of chronic wounds in diabetes. However, these platforms with the passive diffusion of therapeutic agents through the blood clot result in the relatively low delivery efficiency into the deep wound site. Here, a microalgae-based biohybrid microrobot for accelerated diabetic wound healing is developed. The biohybrid microrobot autonomously moves at velocity of 33.3 µm s⁻¹ and generates oxygen for the alleviation of hypoxic condition. In addition, the microrobot efficiently bound with inflammatory chemokines of interleukin-8 (IL-8) and monocyte chemoattractant protein-1 (MCP-1) for modulating the immune responses. The enhanced penetration of microrobot is corroborated by measuring fibrin clots in biomimetic wound using microfluidic devices and the enhanced retention of microrobot is confirmed in the real wounded mouse skin tissue. After deposition on the chronic wound in diabetic mice without wound dressing, the wounds treated with microrobots are completely healed after 9 days with the significant decrease of inflammatory cytokines below 31% of the control level and the upregulated angiogenesis above 20 times of CD31⁺ cells. These results confirm the feasibility of microrobots as a next-generation platform for diabetic wound healing.     

A Hemispherical Image Sensor Array Fabricated with Organic Photomemory Transistors

Hemispherical image sensors simplify lens designs, reduce optical aberrations, and improve image resolution for compact wide-field-of-view cameras. To achieve hemispherical image sensors, organic materials are promising candidates due to the following advantages: tunability of optoelectronic/spectral response and low-temperature low-cost processes. Here, a photolithographic process is developed to prepare a hemispherical image sensor array using organic thin film photomemory transistors with a density of 308 pixels per square centimeter. This design includes only one photomemory transistor as a single active pixel, in contrast to the conventional pixel architecture, consisting of select/readout/reset transistors and a photodiode. The organic photomemory transistor, comprising light-sensitive organic semiconductor and charge-trapping dielectric, is able to achieve a linear photoresponse (light intensity range, from 1 to 50 W m⁻²), along with a responsivity as high as 1.6 A W⁻¹ (wavelength = 465 nm) for a dark current of 0.24 A m⁻² (drain voltage = −1.5 V). These observed values represent the best responsivity for similar dark currents among all the reported hemispherical image sensor arrays to date. A transfer method was further developed that does not damage organic materials for hemispherical organic photomemory transistor arrays. These developed techniques are scalable and are amenable for other high-resolution 3D organic semiconductor devices.     

Localization of atrial natriuretic peptide receptors in the rat tongue and hard palate

The effect of a naturally occurring plant phenolic constituent (the acylphloroglucinol derivative, jensenone, derived from Eucalyptus jensenii) on the food intake of two folivorous marsupials, the common ringtail (Pseudocheirus peregrinus) and the common brushtail possum (Trichosurus vulpecula) was studied. When fed diets containing varying concentrations of jensenone, both species regulated their intake of jensenone so as not to exceed a ceiling intake. This ceiling was about twice as high for common ringtails as for common brushtails from northern Australia. Southern populations of common ringtails showed greatly reduced capacities to tolerate jensenone. When common brushtails were injected (0.5 mg.kg-0.75 body mass) with ondansetron (a selective antagonist of serotonin 5HT3 receptors), they ate significantly more jensenone than animals injected with physiological saline. The same pattern was observed when common ringtails were fed diets containing both jensenone and ondansetron (0.0035 mg.g-1 wet mass of diet). Ondansetron injection had no effect on food intake when the food did not contain jensenone while the addition of higher doses of ondansetron to diets of common ringtails very slightly reduced food intakes of a non-jensenone diet. When common brushtails were given 50 mg of jensenone by gastric lavage, their average subsequent intake of dietary jensenone matched the difference between the daily threshold and the dose given, although the response of individuals was highly variable. Lavage with water alone had no effect on subsequent jensenone intake compared with the pre-dose period. We interpret these results as evidence that the antifeedant effects of jensenone and related compounds are partly mediated by serotonin action on 5HT3 receptors most likely via "nausea" to condition a food aversion.     

An algorithmic mitigation of large spurious interprocedural cycles in static analysis

We present a simple algorithmic extension of the approximate call‐strings approach to mitigate substantial performance degradation caused by spurious interprocedural cycles. Spurious interprocedural cycles are, in a realistic setting, the key reasons for why approximate call‐return semantics in both context‐sensitive and ‐insensitive static analysis can make the analysis much slower than expected. In the approximate call‐strings‐based context‐sensitive static analysis, because the number of distinguished contexts is finite, multiple call‐contexts are inevitably joined at the entry of a procedure and the output at the exit is propagated to multiple return‐sites. We found that these multiple returns frequently create a single large cycle (we call it ‘butterfly cycle’) covering almost all parts of the program and such a spurious cycle makes analyses very slow and inaccurate. Our simple algorithmic technique (within the fixpoint iteration algorithm) identifies and prunes these spurious interprocedural flows. The technique's effectiveness is proven by experiments with a realistic C analyzer to reduce the analysis time by 7–96%. As the technique is algorithmic, it can be easily applicable to existing analyses without changing the underlying abstract semantics, it is orthogonal to the underlying abstract semantics' context‐sensitivity, and its correctness is obvious. Copyright © 2010 John Wiley & Sons, Ltd.     

Spin-valve planar Hall sensor for single bead detection

The planar Hall effect (PHE) sensor with a junction size of 3 μm × 3 μm for a single micro-bead detection has been fabricated successfully using a typical spin-valve thin film Ta(5)/NiFe(16)/Cu(1.2)/NiFe(2)/IrMn(15)/Ta(5) nm. The PHE sensor exhibits a sensitivity of about 7.2 μV Oe^?1 in the magnetic field range of ±7 Oe approximately. We have performed an experiment to illustrated the possibility of single micro-bead detection by using a PHE sensor. A single micro-bead of 2.8 μm diameter size is secluded from 0.1% dilute solution of the Dynabeads^® M-280 dropped on the sensor surface and is located on the sensor junction by using a micro magnetic needle. The comparison of the PHE voltage profiles in the field range from 0 to 20 Oe in the absence and presence of a single micro-bead identifies a single Dynabeads^® M-280, the maximal signal change as large as ΔV ～ 1.1 μV can be obtained at the field ～6.6 Oe. The results are well described in terms of the reversal of a basic single domain structure.     

The strategic value of IT insourcing: An IT-enabled business process perspective

Although research on the business impact of IT outsourcing abounds, little is known about the relative strategic value of IT outsourcing and IT insourcing. Drawing upon the knowledge-based view of the firm, this study postulates that, compared with IT outsourcing, IT insourcing is more effective for developing IT-enabled business processes (IEBP), which subsequently lead to superior firm performance. Our analysis of the data from InformationWeek and Compustat shows that IT insourcing is positively associated with IEBP, while the relationship between IT outsourcing and IEBP is not statistically significant. We also find that IEBP have a significant influence on firm performance. Finally, the effect of IT sourcing mechanisms on IEBP and the effect of IEBP on firm performance are both moderated by the type of innovation related to IEBP. The results suggest that in order to improve their performance firms should consider IT an integral part of their strategic core and should be proactively involved in the internal development of IT resources. We conclude with managerial implications and directions for future research.     

A fuzzy ensemble of parallel polynomial neural networks with information granules formed by fuzzy clustering

In this paper, we introduce a new category of fuzzy models called a fuzzy ensemble of parallel polynomial neural network (FEP²N²), which consist of a series of polynomial neural networks weighted by activation levels of information granules formed with the use of fuzzy clustering. The two underlying design mechanisms of the proposed networks rely on information granules resulting from the use of fuzzy C-means clustering (FCM) and take advantage of polynomial neural networks (PNNs).The resulting model comes in the form of parallel polynomial neural networks. In the design procedure, in order to estimate the optimal values of the coefficients of polynomial neural networks we use a weighted least square estimation algorithm. We incorporate various types of structures as the consequent part of the fuzzy model when using the learning algorithm. Among the diverse structures being available, we consider polynomial neural networks, which exhibit highly nonlinear characteristics when being viewed as local learning models.We use FCM to form information granules and to overcome the high dimensionality problem. We adopt PNNs to find the optimal local models, which can describe the relationship between the input variables and output variable within some local region of the input space.We show that the generalization capabilities as well as the approximation abilities of the proposed model are improved as a result of using polynomial neural networks. The performance of the network is quantified through experimentation in which we use a number of benchmarks already exploited within the realm of fuzzy or neurofuzzy modeling.     

A hybrid observer for characterization and compensation of periodic disturbances

Usage of frequency based error correction methods for repetitive disturbances becomes popular in data storage devices that use a rotating mechanical power plant. Two distinct disturbance cancellation methods, disturbance observer (DOB) and adaptive feed forward control (AFC) are the most popular approaches used for current drive servo integration. DOB reduces error using a predetermined function that is calculated thorough a complicated process. Generally the response to disturbance and initiation of control action of DOB is relatively fast even if the amount of error reduction is limited. Meanwhile the error elimination capability of AFC for the repetitive disturbance is normally better than DOB as it utilizes a Fourier coefficients updating feature that supports an enhanced fine adaptation of a certain frequency disturbance. Of course, AFC suffers for disturbances that have neighboring close frequencies due to the inherent fundamental frequency dependencies of AFC formulation. In the present work, an attempt for combining benefits of AFC and DOB is made. This might enables control action not only to generate fast response to disturbance but also perform an accurate error rejection. This feature also provides to the closed loop system a frequency selection for enabling a strategic selective error rejection. The proposed method named Hybrid Disturbance Observer (HDOB) is compared to the traditional AFC and DOB.     

Calibrating parametric exponential Lévy models to option market data by incorporating statistical moments priors

We investigate a parametric method for calibrating European option pricing using the state-of-art exponential Lévy models. We propose a derivative-free calibration method constrained by four observable statistical moments (mean, variance, skewness and kurtosis) from underlying time series to conquer the ill-posed inverse problem and to incorporate priors on observable statistical moments. We present a numerical implementation scheme for calibrating the exponential Lévy models and show that it can resolve the instability of the inverse problems empirically and can produce good calibration results. In particular, we apply our approach to real market data sets of S&P 500 call options with significantly better performance.