Beyond performance: Feature awareness in personalized interfaces

Personalized graphical user interfaces have the potential to reduce visual complexity and improve interaction efficiency by tailoring elements such as menus and toolbars to better suit an individual user's needs. When an interface is personalized to make useful features more accessible for a user's current task, however, there may be a negative impact on the user's awareness of the full set of available features, making future tasks more difficult. To assess this tradeoff we introduce awareness as an evaluation metric to be used in conjunction with performance. We then discuss three studies we have conducted, which show that personalized interfaces tradeoff awareness of unused features for performance gains on core tasks. The first two studies, previously published and presented only in summary, demonstrate this tradeoff by measuring awareness using a recognition test of unused features in the interface. The studies also evaluated two different types of personalized interfaces: a layered interfaces approach and an adaptive split menu approach. The third study, presented in full, focuses on adaptive split menus and extends results from the first two studies to show that different levels of awareness also correspond to an impact on performance when users are asked to complete new tasks. Based on all three studies and a survey of related work, we outline a design space of personalized interfaces and present several factors that could affect the tradeoff between core task performance and awareness. Finally, we provide a set of design implications that should be considered for personalized interfaces.     

Hybrid phenol biosensor based on modified phenoloxidase electrode

Electrolytic deposition has been widely used to immobilize biomacromolecules, and it is always the most important factor to preserve or even increase an activity of the immobilized protein. We report here simple and rather universal method for the highly efficient immobilization of laccase for amperometric biosensing. Laccase from Cerrena unicolor has been successfully immobilized (electrolytic deposition) on the surface of thin, ordered polythiophene films (3-methylthiophene/3-thiopheneacetic acid/N-heptyl-3,6-bis(2-thiophene)carbazole). Two different compounds capable of mediating laccase-catalyzed reactions have been tested by cyclic voltammetry. They exhibited quasi-reversible electrodic behaviour with formal redox potentials ranging from 68 and 918 mV (E⁰vs. SCE). The immersion of the laccase-coated electrode in solution with substrate generated large catalytic currents easily recorded by cyclic voltammetry at low potential scan rates. Considering the fact, that immobilization strategy showed high efficiency, obtained results suggest that method for phenoloxidase immobilization has a great potential of enabling high throughput fabrication of bioelectronics’ devices.     

A survey and taxonomy on energy efficient resource allocation techniques for cloud computing systems

In a cloud computing paradigm, energy efficient allocation of different virtualized ICT resources (servers, storage disks, and networks, and the like) is a complex problem due to the presence of heterogeneous application (e.g., content delivery networks, MapReduce, web applications, and the like) workloads having contentious allocation requirements in terms of ICT resource capacities (e.g., network bandwidth, processing speed, response time, etc.). Several recent papers have tried to address the issue of improving energy efficiency in allocating cloud resources to applications with varying degree of success. However, to the best of our knowledge there is no published literature on this subject that clearly articulates the research problem and provides research taxonomy for succinct classification of existing techniques. Hence, the main aim of this paper is to identify open challenges associated with energy efficient resource allocation. In this regard, the study, first, outlines the problem and existing hardware and software-based techniques available for this purpose. Furthermore, available techniques already presented in the literature are summarized based on the energy-efficient research dimension taxonomy. The advantages and disadvantages of the existing techniques are comprehensively analyzed against the proposed research dimension taxonomy namely: resource adaption policy, objective function, allocation method, allocation operation, and interoperability.     

A modular approach to learning manipulation strategies from human demonstration

Object manipulation is a challenging task for robotics, as the physics involved in object interaction is complex and hard to express analytically. Here we introduce a modular approach for learning a manipulation strategy from human demonstration. Firstly we record a human performing a task that requires an adaptive control strategy in different conditions, i.e. different task contexts. We then perform modular decomposition of the control strategy, using phases of the recorded actions to guide segmentation. Each module represents a part of the strategy, encoded as a pair of forward and inverse models. All modules contribute to the final control policy; their recommendations are integrated via a system of weighting based on their own estimated error in the current task context. We validate our approach by demonstrating it, both in a simulation for clarity, and on a real robot platform to demonstrate robustness and capacity to generalise. The robot task is opening bottle caps. We show that our approach can modularize an adaptive control strategy and generate appropriate motor commands for the robot to accomplish the complete task, even for novel bottles.     

Stochastic volatility models with leverage and heavy-tailed distributions: A Bayesian approach using scale mixtures

This paper studies a heavy-tailed stochastic volatility (SV) model with leverage effect, where a bivariate Student-t distribution is used to model the error innovations of the return and volatility equations. Choy et al. (2008) studied this model by expressing the bivariate Student-t distribution as a scale mixture of bivariate normal distributions. We propose an alternative formulation by first deriving a conditional Student-t distribution for the return and a marginal Student-t distribution for the log-volatility and then express these two Student-t distributions as a scale mixture of normal (SMN) distributions. Our approach separates the sources of outliers and allows for distinguishing between outliers generated by the return process or by the volatility process, and hence is an improvement over the approach of Choy et al. (2008). In addition, it allows an efficient model implementation using the WinBUGS software. A simulation study is conducted to assess the performance of the proposed approach and its comparison with the approach by Choy et al. (2008). In the empirical study, daily exchange rate returns of the Australian dollar to various currencies and daily stock market index returns of various international stock markets are analysed. Model comparison relies on the Deviance Information Criterion and convergence diagnostic is monitored by Geweke’s convergence test.     

Sterol and steryl ester regulation of phospholipase A2 from the mosquito parasiteLagenidium giganteum

Lagenidium giganteum, a facultative parasite of mosquito larvae, cannot synthesize sterols, and requires an exogenous source of these lipids in order to enter its reproductive cycle. This parasite grows vegetatively in the absence of sterols, but requires cholesterol or structurally related compounds to produce motile zoospores, which are the only stage capable of infecting mosquitoes. Sterols structurally related to cholesterol and some steryl esters inhibited the activity ofL. giganteum phospholipase A₂ (PLA₂), an enzyme that hydrolyzes fatty acids from thesn-2 position of glycerophospholipids. Sterols that induce reproduction inhibitedL. giganteum PLA₂ activity, while sterols and steroids that do not support sporulation had minimal effect. Most steryl esters had no effect on enzyme activity, but cholesteryl arachidonate (CA) was a potent inhibitor of parasite PLA₂. Not all enzymes partly purified using a DEAE-Sephacel column were affected by these lipids, demonstrating selective inhibition of specific enzymes. Potency was enhanced by up to several orders of magnitude if epoxy fatty acids were esterified to the cholesterol nucleus. The steryl ester pool was dynamic during morphogenesis, and the fatty acid composition of the steryl esters did not mimic total cell or membrane (glycerophospholipid) fatty acid composition asL. giganteum proceeded through its growth cycle. Synthesis of CA and monoepoxy CA by the parasite was confirmed using electrospray mass spectrometry and collision-induced dissociation. Steryl derivatives selectively inhibited PLA₂ enzymes from bovine pancreas, snake venom, and human cytoplasmic 85-kDa PLA₂.     

Static and Dynamic Slider Air-Bearing Behavior in Heat-Assisted Magnetic Recording Under Thermal Flying Height Control and Laser System-Induced Protrusion

The air bearing’s response to regions of elevated temperature on its bounding surfaces (the slider and disk) may be an important consideration in the head–disk interface design of heat-assisted magnetic recording (HAMR) systems. We implement the general non-isothermal molecular gas lubrication equation into an iterative static solver and dynamic air-bearing solver to evaluate the effect of localized heating of the air-bearing surface (ABS) due to the near-field transducer (NFT). The heat-dissipating components in our simplified HAMR design are the NFT, laser diode, and thermal flying height control (TFC) heater. We investigate the effect of each HAMR slider component on ABS temperature and thermal deformation and the slider’s flying height. The NFT induces a localized thermal spot and protrusion on the larger TFC bulge, and it is the location of maximum temperature. This ABS temperature profile alters the air-bearing pressure distribution, increasing the pressure at the hot NFT location compared with predictions of an isothermal air-bearing solver, so that the center of the pressure acting on the ABS is slightly closer to the trailing edge, thereby decreasing the pitch angle and increasing the minimum flying height. Other researchers have shown that the NFT’s thermal response time may be much faster than its protrusion response time (Xu et al. in IEEE Trans Magn 48:3280–3283, 2012). The slider’s dynamic response to a time-varying NFT thermal spot on the ABS while the combined TFC and NFT induced thermal protrusion remains constant is investigated with our dynamic air-bearing solver. We simulate the slider’s step response to a suddenly applied ABS temperature profile and a pulsed temperature profile that represents laser-on over data zones and laser-off over servo zones. The sudden (step) or rapid (pulse) increase in ABS temperature induces a sudden or rapid increase in pressure at the NFT location, thereby exciting the air bearing’s first pitch mode. For the slider design and simulation conditions used here, the result of the pitch mode excitation is to alter the position of the center of pressure in the slider’s length direction, thereby changing the pitch moment. In response, the pitch angle and minimum flying height change. The step response decays after approximately 0.15 ms. Because the laser duty cycle is much shorter than this response time, a periodic disturbance is predicted for the center of pressure coordinate, pitch angle, and minimum flying height. The peak-to-peak minimum flying height modulations are relatively small (only up to 0.126 nm); more significantly, the time-averaged minimum flying height increases 0.5 nm for the NFT that reached 208 °C compared to simulations of the isothermal ABS at ambient temperature.