Hybrid biomedical intelligent systems

"Copyright © 2012 Maysam Abbod et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited."The purpose of this special issue is to promote research and developments of the best work in the field of hybrid intelligent systems for biomedical applications

Large strain actuation in barium titanate single crystals under stress and electric field

Large strain actuation in barium titanate (BaTiO3) single crystals subjected to combined uniaxial stress and electric field is examined. A maximum strain of about 0.45% is measured under a combined loading of 2.7 MPa compressive stress and ±1.25 MVm-1 cyclic electric field. Above 2.7 MPa, the crystal does not cycle fully between the in-plane and out-of-plane polarized states due to large compressive stress, and consequently, a considerable reduction in actuation strain is apparent. The hysteresis evolution of the crystal under combined electromechanical loading reveals incomplete switching characteristics and a considerable disproportion of slope gradients at zero electric field for the measured polarization and strain hysteresis curves. A likely cause for the disproportion of slope gradients is the cooperative operation of multiple 90° switching systems by which “polarization-free” strain changes are induced

Generic Subsequence Matching Framework: Modularity, Flexibility, Efficiency

Subsequence matching has appeared to be an ideal approach for solving many problems related to the fields of data mining and similarity retrieval. It has been shown that almost any data class (audio, image, biometrics, signals) is or can be represented by some kind of time series or string of symbols, which can be seen as an input for various subsequence matching approaches. The variety of data types, specific tasks and their partial or full solutions is so wide that the choice, implementation and parametrization of a suitable solution for a given task might be complicated and time-consuming; a possibly fruitful combination of fragments from different research areas may not be obvious nor easy to realize. The leading authors of this field also mention the implementation bias that makes difficult a proper comparison of competing approaches. Therefore we present a new generic Subsequence Matching Framework (SMF) that tries to overcome the aforementioned problems by a uniform frame that simplifies and speeds up the design, development and evaluation of subsequence matching related systems. We identify several relatively separate subtasks solved differently over the literature and SMF enables to combine them in straightforward manner achieving new quality and efficiency. This framework can be used in many application domains and its components can be reused effectively. Its strictly modular architecture and openness enables also involvement of efficient solutions from different fields, for instance efficient metric-based indexes. This is an extended version of a paper published on DEXA 2012.Comment: This is an extended version of a paper published on DEXA 201

Transcriptome-Wide Profiling of Acute Stress Induced Changes in Ribosome Occupancy Level Using External Standards

Acute cellular stress is known to induce a global reduction in mRNA translation through suppression of cap dependent translation. Selective translation in response to acute stress has been shown to play important roles in regulating the stress response. However, accurately profiling translational changes transcriptome-wide in response to acute cellular stress has been challenging. Commonly used data normalization methods operate on the assumption that any systematic shifts are experimental artifacts. Consequently, if applied to profiling acute cellular stress-induced mRNA translation changes, these methods are expected to produce biased estimates. To address this issue, we designed, produced, and evaluated a panel of 16 oligomers to serve as external standards for ribosome profiling studies. Using Sodium Arsenite treatment-induced oxidative stress in lymphoblastoid cell lines as a model system, we applied spike-in oligomers as external standards. We found our spike-in oligomers to display a strong linear correlation between the observed and the expected quantification, with small ratio compression at the lower concentration range. Using the expected fold changes constructed from spike-in controls, we found in our dataset that TMM normalization, a popular global scaling normalization approach, produced 87.5% false positives at a significant cutoff that is expected to produce only 10% false positive discoveries. In addition, TMM normalization produced a systematic shift of fold change by 3.25 fold. These results highlight the consequences of applying global scaling approaches to conditions that clearly violate their key assumptions. In contrast, we found RUVg normalization using spike-in oligomers as control genes recapitulated the expected stress induced global reduction of translation and resulted in little, if any, systematic shifts in the expected fold change. Our results clearly demonstrated the utility of our spike-in oligomers, both for constructing expected results as controls and for data normalization

Quantum geometry and gravitational entropy

Most quantum states have wavefunctions that are widely spread over the accessible Hilbert space and hence do not have a good description in terms of a single classical geometry. In order to understand when geometric descriptions are possible, we exploit the AdS/CFT correspondence in the half-BPS sector of asymptotically AdS_5 x S^5 universes. In this sector we devise a "coarse-grained metric operator" whose eigenstates are well described by a single spacetime topology and geometry. We show that such half-BPS universes have a non-vanishing entropy if and only if the metric is singular, and that the entropy arises from coarse-graining the geometry. Finally, we use our entropy formula to find the most entropic spacetimes with fixed asymptotic moments beyond the global charges.Comment: 29 pages, 2 figures; references adde

Type-2 fuzzy sets applied to multivariable self-organizing fuzzy logic controllers for regulating anesthesia

In this paper, novel interval and general type-2 self-organizing fuzzy logic controllers (SOFLCs) are proposed for the automatic control of anesthesia during surgical procedures. The type-2 SOFLC is a hierarchical adaptive fuzzy controller able to generate and modify its rule-base in response to the controller's performance. The type-2 SOFLC uses type-2 fuzzy sets derived from real surgical data capturing patient variability in monitored physiological parameters during anesthetic sedation, which are used to define the footprint of uncertainty (FOU) of the type-2 fuzzy sets. Experimental simulations were carried out to evaluate the performance of the type-2 SOFLCs in their ability to control anesthetic delivery rates for maintaining desired physiological set points for anesthesia (muscle relaxation and blood pressure) under signal and patient noise. Results show that the type-2 SOFLCs can perform well and outperform previous type-1 SOFLC and comparative approaches for anesthesia control producing lower performance errors while using better defined rules in regulating anesthesia set points while handling the control uncertainties. The results are further supported by statistical analysis which also show that zSlices general type-2 SOFLCs are able to outperform interval type-2 SOFLC in terms of their steady state performance