A new blind-equalization algorithm for an FIR SIMO system driven by MPSK signal

We consider the problem of blind equalization of a finite impulse response and single-input multiple-output system driven by an M-ary phase-shift-keying signal. The existing single-mode algorithms for this problem include the constant modulus algorithm (CMA) and the multimodulus algorithm (MMA). It has been shown that the MMA outperforms the CMA when the input signal has no more than four constellation points, i.e., Mles4. In this brief, we present a new adaptive equalization algorithm that jointly exploits the amplitude and phase information of the input signal. Theoretical analysis shows that the proposed algorithm has less mean square error, i.e., better equalization performance, at steady state than the CMA regardless of the value of M. The superior performance of our algorithm to the CMA and the MMA is validated by simulation examples

Movement patterns for a critically endangered species, the Leatherback Turtle (Dermochelys coriacea), linked to foraging success and population status

Foraging success for pelagic vertebrates may be revealed by horizontal and vertical movement patterns. We show markedly different patterns for leatherback turtles in the North Atlantic versus Eastern Pacific, which feed on gelatinous zooplankton that are only occasionally found in high densities. In the Atlantic, travel speed was characterized by two modes, indicative of high foraging success at low speeds (<15 km d−1) and transit at high speeds (20–45 km d−1). Only a single mode was evident in the Pacific, which occurred at speeds of 21 km d−1 indicative of transit. The mean dive depth was more variable in relation to latitude but closer to the mean annual depth of the thermocline and nutricline for North Atlantic than Eastern Pacific turtles. The most parsimonious explanation for these findings is that Eastern Pacific turtles rarely achieve high foraging success. This is the first support for foraging behaviour differences between populations of this critically endangered species and suggests that longer periods searching for prey may be hindering population recovery in the Pacific while aiding population maintenance in the Atlantic.

Mixing vector construction for single channel semi-blind source separation using empirical mode decomposition

The Empirical Mode Decomposition (EMD) method is a commonly used method for solving the problem of single channel blind source separation (SCBSS) in signal processing. However, the mixing vector of SCBSS, which is the base of the EMD method, has not yet been effectively constructed. The mixing vector reflects the weights of original signal sources that form the single channel blind signal source. In this paper, we propose a novel method to construct a mixing vector for a single channel blind signal source to approximate the actual mixing vector in terms of keeping the same ratios between signal weights. The constructed mixing vector can be used to improve signal separations. Our method incorporates the adaptive filter, least square method, EMD method and signal source samples to construct the mixing vector. Experimental tests using audio signal evaluations were conducted and the results indicated that our method can improve the similar values of sources energy ratio from 0.2644 to 0.8366. This kind of recognition is very important in weak signal detection.

Dynamic output feedback control of single-link flexible manipulators

This paper presents an efficient technique to design dynamic feedback control scheme for single-link flexible manipulators.  A linear model can be derived for the robotic system using the assumed-mode method.  Conventional techniques such as pole-placement or LQR require physical measurements of all systme states,  posing a stringent requirement for its implementation.  To overcome this problem, a low-order state functional observer is proposed here for reconstruction of the state feedback control action.  The observer design involves solving an optimisation problem with the objective to generate a feedback gain that is as close as possible to that of the required feedback controller.  A condition for robust stability of the closed-loop system under the observer-based control scheme is given.  The attractive features of the propsed technique are the resulted functional state observer is of a very low order and it requires only sensor measurements of only the output- the tip position of the arm.

Retention mechanism divergence of a mixed mode stationary phase for high performance liquid chromatography

Mixed mode stationary phases utilize secondary retention mechanisms to add a dimensionality to the surface of high performance liquid chromatography (HPLC) adsorbents. This approach was used by several authors to improve the separation performance of single dimension separations. We explored the magnitude of these secondary interactions by performing an off-line two-dimensional (2D)-HPLC separation with a Scherzo SM-C18 column of a β-lactoglobulin tryptic digest with a mobile phase pH of 7 in the first dimension and 2 in the second. Mechanism divergence was determined using the peak capacity and a geometric approach to factor analysis, to measure the correlation. This separation was repeated with a C18 stationary phase as a control. It was found that the C18 column had a correlation coefficient of 0.784, smaller than the mixed mode column, 0.884. This indicated that the retention mechanisms of the C18 column were more divergent under these two pH environments than the mixed mode column. However, the SM-C18 still provided alternative selectivity of the peptides to that of the C18 and could be considered as a good alternative for further 2D-HPLC separations.

Sliding mode-like learning control for SISO complex systems with T-S fuzzy models

In this paper, a sliding mode-like learning control scheme is developed for a class of single input single output (SISO) complex systems. First, the Takagi-Sugeno (T-S) fuzzy modelling technique is employed to model the uncertain complex dynamical systems. Second, a sliding mode-like learning control is designed to drive the sliding variable to converge to the sliding surface, and the system states can then asymptotically converge to zero on the sliding surface. The advantages of this scheme are that: 1) the information about the uncertain system dynamics and the system model structure is not required for the design of the learning controller; 2) the closed-loop system behaves with a strong robustness with respect to uncertainties; 3) the control input is chattering-free. The sufficient conditions for the sliding mode-like learning control to stabilise the global fuzzy model are discussed in detail. A simulation example for the control of an inverted pendulum cart is presented to demonstrate the effectiveness of the proposed control scheme.

Investigating retention characteristics of a mixed-mode stationary phase and the enhancement of monolith selectivity for high-performance liquid chromatography

The synthesis and chromatographic behavior of an analytical size mixed-mode bonded silica monolith was investigated. The monolith was functionalized by an in situ modification process of a bare silica rod with chloro(3-cyanopropyl)dimethyl silane and chlorodimethyl propyl phenyl silane solutions. These ligands were selected in order to combine both resonance and nonresonance π-type bonding within a single separation environment. Selectivity studies were undertaken using n-alkyl benzenes and polycyclic aromatic hydrocarbons in aqueous methanol and acetonitrile mobile phases to assess the methylene and aromatic selectivities of the column. The results fit with the linear solvent strength theory suggesting excellent selectivity of the column was achieved. Comparison studies were performed on monolithic columns that were functionalized separately with cyano and phenyl ligands, suggesting highly conjugated molecules were able to successfully exploit both of the π-type selectivities afforded by the two different ligands on the mixed-mode column.

Effect of resistance exercise contraction mode and protein supplementation on members of the STARS signalling pathway

The striated muscle activator of Rho signalling (STARS) pathway is suggested to provide a link between external stress responses and transcriptional regulation in muscle. However, the sensitivity of STARS signalling to different mechanical stresses has not been investigated. In a comparative study, we examined the regulation of the STARS signalling pathway in response to unilateral resistance exercise performed as either eccentric (ECC) or concentric (CONC) contractions as well as prolonged training; with and without whey protein supplementation. Skeletal muscle STARS, myocardian-related transcription factor-A (MRTF-A) and serum response factor (SRF) mRNA and protein, as well as muscle cross-sectional area and maximal voluntary contraction, were measured. A single-bout of exercise produced increases in STARS and SRF mRNA and decreases in MRTF-A mRNA with both ECC and CONC exercise, but with an enhanced response occurring following ECC exercise. A 31% increase in STARS protein was observed exclusively after CONC exercise (P < 0.001), while pSRF protein levels increased similarly by 48% with both CONC and ECC exercise (P < 0.001). Prolonged ECC and CONC training equally stimulated muscle hypertrophy and produced increases in MRTF-A protein of 125% and 99%, respectively (P < 0.001). No changes occurred for total SRF protein. There was no effect of whey protein supplementation. These results show that resistance exercise provides an acute stimulation of the STARS pathway that is contraction mode dependent. The responses to acute exercise were more pronounced than responses to accumulated training, suggesting that STARS signalling is primarily involved in the initial phase of exercise-induced muscle adaptations.