Pervaporation separation of pentane-alcohol mixtures through ionically crosslinked blended membranes. I. Thermal measurements,electron microscopy and tensile studies

Ionically crosslinked blended membranes were prepared from blends of nylon 6 and poly(acrylic acid) (PAA) with the proportion of PAA ranging from 25 to 45 wt.-%. The technique consists of casting a film of the blend, followed by drying and immersion in an aluminum salt crosslinking solution for a predetermined time. The glass transition temperature (T_g) of the membranes was determined by differential scanning calorimetry (DSC). All the samples exhibited a single T_g, which is higher than that of either polymer. There is also a shift in the T_g with increasing scanning time. This phenomenon is attributed to the elimination of water molecules and the formation of anhydrides in the non-crosslinked PAA portion of the membrane. The membrane morphology was studied using scanning electron microscopy (SEM) and shows a dense structure without any pores. No phase separation is observed by scanning cross-sections of the samples, indicating that nylon 6 and PAA are completely miscible in the ranges studied. The membrane material strength lies in the range of 5 to 26 MPa and varies with the amount of PAA in the membrane. Samples with higher PAA content show lower tensile strength in spite of increased crosslinking density. This is due to the inherent low strength of PAA, coupled with increasing swelling of the membrane with increasing PAA content. The latter is confirmed by the measurement of water uptake into a dry membrane which increases from 23.6% to 76.3% with the membrane PAA content increasing from 25 to 45 wt.%.     

Comparison of a sports-hydration drink containing high amylose starch with usual hydration practice in Australian rules footballers during intense summer training

Background

Fluid deficits exceeding 1.6% can lead to physical and cognitive impairment in athletes. Sport drinks used by athletes are often hyper-osmolar but this is known to be suboptimal for rehydration in medical settings and does not utilize colonic absorptive capacity. Colonic absorption can be enhanced by fermentative production of short chain fatty acids (SCFA) from substrates such as high amylose maize starch (HAMS). This study therefore compared, in elite Australian Football League (AFL) players at the height of outdoor summer training, a novel dual-action sports oral rehydration strategy that contained HAMS as well as glucose, to their usual rehydration practices (Control). The primary outcome markers of hydration were hematocrit and body weight.

Methods

A randomized single-blind crossover study was undertaken in thirty-one AFL players; twenty-seven completed the study which was conducted on four days (two days in the Intervention arm and two in Control arm). The Intervention arm was comprised a 50-100 g evening preload of an acetylated HAMS (Ingredion Pty Ltd) followed by consumption of a specially formulated sports oral rehydration solution (SpORS) drink during intense training and recovery. Players followed their usual hydration routine in the Control arm. Quantitative assessments of body weight, hematocrit and urine specific gravity were made at three time-points on each day of training: pre-training, post-training (90 min), and at end of recovery (30–60 min later). GPS tracking monitored player exertion.

Results

Across the three time-points, hematocrit was significantly lower and body weight significantly higher in Intervention compared to Control arms (p <?0.02 and p =?0.001 respectively, mixed effects model). Weights were significantly heavier at all three assessment points for Intervention compared to Control arms (Δ =?0.30?±?0.13, p =?0.02 pre-training; Δ =?0.43?±?0.14, p =?0.002 post training; and Δ =?0.68?±?0.14, p <?0.001 for recovery). Between the pre-training and end-of-recovery assessments, the Control arm lost 0.80 kg overall compared with 0.12 kg in the Intervention arm, an 85% lower reduction of bodyweight across the assessment period.

Conclusion

The combination of the significantly lower hematocrit and increased body weight in the Intervention arm represents better hydration not only at the end of training as well as following a recovery period but also at its commencement. The magnitude of the benefit seems sufficient to have an impact on performance and further studies to test this possibility are now indicated.

Trial registration

Trial is listed on the Australian New Zealand Clinical Trials Registry (ACTRN 12613001373763). 

     

Lyapunov functionals in complex /spl mu/ analysis

Conditions for robust stability of linear time-invariant systems subject to structured linear time-invariant uncertainties can be derived in the complex /spl mu/ framework, or, equivalently, in the framework of integral quadratic constraints. These conditions can be checked numerically with linear matrix inequality (LMI)-based convex optimization using the Kalman-Yakubovich-Popov lemma. We show how LMI tests also yield a convex parametrization of (a subset of) Lyapunov functionals that prove robust stability of such uncertain systems. We show that for uncertainties that are pure delays, the Lyapunov functionals reduce to the standard Lyapunov-Krasovksii functionals that are encountered in the stability analysis of delay systems. We demonstrate the practical utility of the Lyapunov functional parametrization by deriving bounds for a number of measures of robust performance (beyond the usual H/sub /spl infin// performance); these bounds can be efficiently computed using convex optimization over linear matrix inequalities.     

Improved stability analysis and gain-scheduled controller synthesisfor parameter-dependent systems

We present new algorithms for robust stability analysis and gain-scheduled controller synthesis for linear systems affected by time-varying parametric uncertainties. These new techniques can also be applied to parameter-dependent nonlinear systems with real-rational nonlinearities. Sufficient conditions for robust stability, as well as conditions for the existence of a robustly stabilizing gain-scheduled controller, are given in terms of a finite number of linear matrix inequalities (LMIs); explicit formulas for constructing robustly stabilizing gain-scheduled controllers are given in terms of the feasible set of these LMIs. The improvement offered by our approach over existing methods for stability analysis and gain-scheduled controller synthesis for parameter-dependent linear systems are analyzed in theory. Numerical examples demonstrate that our approach can offer significant improvement in practice     

Form and objective of the decision rule in absolute identification

In several conditions of a line length identification experiment, the subjects' decision making strategies were systematically biased against the responses on the edges of the stimulus range. When the range and number of the stimuli were small, the bias caused the percentage of correct responses to be highest in the center and lowest on the extremes of the range. Two general classes of decision rules that would explain these results are considered. The first class assumes that subjects intend to adopt an optimal decision rule, but systematically misrepresent one or more parameters of the decision making context. The second class assumes that subjects use a different measure of performance than the one assumed by the experimenter: instead of maximizing the chances of a correct response, the subject attempts to minimize the expected size of the response error (a "fidelity criterion"). In a second experiment, extended experience and feedback did not diminish the bias effect, but explicitly penalizing all response errors equally, regardless of their size, did reduce or eliminate it in some subjects. Both results favor the fidelity criterion over the optimal rule.     

Error Probability and Throughput Analysis of IRS-Assisted Wireless System Over Generalized $$\kappa$$ κ – $$\mu$$ μ Fading Channels

Wireless Personal Communications - Intelligent reflecting surfaces (IRS)-assisted wireless transmission has recently emerged as a potential candidate to enable a smart and reconfigurable radio...     

An automatic non-English sentiment lexicon builder using unannotated corpus

The Journal of Supercomputing - Sentiment lexicons in the English language are widely accessible while in many other languages, these resources are extremely deficient. Current techniques and...     

Mobile Technology in the Classroom: What Drives Student-Lecturer Interactions?

Online learning when combined with mobile technology transforms the traditional classrooms from teacher-centered to student-centered classrooms. Despite the widespread use of mobile technology among students and educators today, limited researches have been conducted to study the effects of using mobile technology to enhance student–lecturer interactions. In addition, existing theories of technology acceptances, chiefly Information System Success Model (ISSM), Motivational Model (MM), Social Cognitive Theory (SCT), Technology Acceptance Model (TAM), and Cultural Dimension Theory (CDT) are widely recognized for their predictive power in determining adoption intentions. In this study, determinants from all five theories were unified and examined, namely system quality and information quality from ISSM, enjoyment from MM, perceived usefulness and perceived ease of use from TAM, self-efficacy from SCT, and uncertainty avoidance from CDT as predictors of adoption intention in the context of predicting student–lecturer interactions. This empirical study was conducted using an online survey. Data collected from the samples (n = 328) were analyzed using PLS-SEM. Results obtained exhibited adequate explanatory power, where information quality, system quality, enjoyment, and uncertainty avoidance significantly predict adoption intention, while perceived usefulness, perceived ease of use, and self-efficacy were insignificant. Secondly, each theory was independently analyzed, and the predictive power and relevance of ISSM, MM, TAM, and UDT confirmed the importance and relevance of these theories. Results obtained provided a comprehensive understanding of the factors that significantly affect students’ intentions to use mobile technology to interact with their lecturers on academic matters. The discussions and implications of this study are crucial for researchers and practitioners of educational technologies in higher education.     

Analysing stable feature selection through an augmented marine predator algorithm based on opposition-based learning

Retrieving the relevant information from the high-dimensional dataset enhances the classification accuracy of a predictive model. This research critique has devised an improved marine predator algorithm based on opposition learning for stable feature selection to overcome the problem of high-dimensionality. Marine predator algorithm is a population-based meta-heuristics optimization algorithm that works on the ‘survival-of-the-fittest’ theory. Classical marine predator algorithm explores the search space merely in one direction, affecting its converging capacity while being responsible for stagnation at local minima. The proposed opposition-based learning nuances enhance the exploration capacity of marine predator algorithm and productively converges the model to global optima. The proposed OBL-based marine predator algorithm selects stable, substantial elements from six different high-dimensional microarray datasets. The performance of the proposed method is investigated using five predominantly used classifiers. From the result, it is understood that the proposed approach outperforms other conventional feature selection techniques in terms of converging capability, classification accuracy, and stable feature selection.     

Closed‐form solution to finite‐horizon suboptimal control of nonlinear systems

Finite‐horizon optimal control of input‐affine nonlinear systems with fixed final time is considered in this study. It is first shown that the associated Hamilton–Jacobi–Bellman partial differential equation to the problem is reducible to a state‐dependent differential Riccati equation after some approximations. With a truncation in the control equation, a near optimal solution to the problem is obtained, and the global onvergence properties of the closed‐loop system are analyzed. Afterwards, an approximate method, called Finite‐horizon State‐Dependent Riccati Equation (Finite‐SDRE), is suggested for solving the differential Riccati equation, which renders the origin a locally exponentially stable point. The proposed method provides online feedback solution for controlling different initial conditions. Finally, through some examples, the performance of the resulting controller in finite‐horizon control is analyzed. Copyright © 2014 John Wiley & Sons, Ltd.