Impressive Gelation in Organic Solvents by Synthetic, Low Molecular Mass, Self-Organizing Urethane Amides of L-Phenylalanine

Synthetic routes leading to 12 L-phenylalanine based mono- and bipolar derivatives (1-12) and an in-depth study of their structure-property relationship with respect to gelation have been presented. These include monopolar systems such as N-[(benzyloxy)carbonyl]-L-phenylalanine-N-alkylamides and the corresponding bipolar derivatives with flexible and rigid spacers such as with 1,12-diaminododecane and 4,4'-diaminodiphenylmethane, respectively. The two ends of the latter have been functionalized with N-[(benzyloxy)carbonyl]-L-phenylalanine units via amide connection. Another bipolar molecule was synthesized in which the middle portion of the hydrocarbon segment contained polymerizable diacetylene unit. To ascertain the role of the presence of urethane linkages in the gelator molecule protected L-phenylalanine derivatives were also synthesized in which the (benzyloxy)carbonyl group has been replaced with (tert-butyloxy)carbonyl, acetyl, and benzoyl groups, respectively. Upon completion of the synthesis and adequate characterization of the newly described molecules, we examined the aggregation and gelation properties of each of them in a number of solvents and their mixtures. Optical microscopy and electron microscopy further characterized the systems that formed gels. Few representative systems, which showed excellent gelation behavior was, further examined by FT-IR, calorimetric, and powder X-ray diffraction studies. To explain the possible reasons for gelation, the results of molecular modeling and energy-minimization studies were also included. Taken together these results demonstrate the importance of the presence of (benzyloxy)carbonyl unit, urethane and secondary amide linkages, chiral purities of the headgroup and the length of the alkyl chain of the hydrophobic segment as critical determinants toward effective gelation.

Stochastic optimization for adaptive labor staffing in service systems

Service systems are labor intensive. Further, the workload tends to vary greatly with time. Adapting the staffing levels to the workloads in such systems is nontrivial due to a large number of parameters and operational variations, but crucial for business objectives such as minimal labor inventory. One of the central challenges is to optimize the staffing while maintaining system steady-state and compliance to aggregate SLA constraints. We formulate this problem as a parametrized constrained Markov process and propose a novel stochastic optimization algorithm for solving it. Our algorithm is a multi-timescale stochastic approximation scheme that incorporates a SPSA based algorithm for ‘primal descent' and couples it with a ‘dual ascent' scheme for the Lagrange multipliers. We validate this optimization scheme on five real-life service systems and compare it with a state-of-the-art optimization tool-kit OptQuest. Being two orders of magnitude faster than OptQuest, our scheme is particularly suitable for adaptive labor staffing. Also, we observe that it guarantees convergence and finds better solutions than OptQuest in many cases.

Division of Labor in Hand Usage in Free- Ranging Bonnet Macaques, Macaca radiata

Primates exhibit laterality in hand usage either in terms of (a) hand with which an individual solves a task or while solving a task that requires both hands, executes the most complex action, that is, hand preference, or (b) hand with which an individual executes actions most efficiently, that is, hand performance. Observations from previous studies indicate that laterality in hand usage might reflect specialization of the two hands for accomplishing tasks that require maneuvering dexterity or physical strength. However, no existing study has investigated handedness with regard to this possibility. In this study, we examined laterality in hand usage in urban free-ranging bonnet macaques, Macaca radiata with regard to the above possibility. While solving four distinct food extraction tasks which varied in the number of steps involved in the food extraction process and the dexterity required in executing the individual steps, the macaques consistently used one hand for extracting food (i.e., task requiring maneuvering dexterity)the maneuvering hand, and the other hand for supporting the body (i.e., task requiring physical strength)the supporting hand. Analogously, the macaques used the maneuvering hand for the spontaneous routine activities that involved maneuvering in three-dimensional space, such as grooming, and hitting an opponent during an agonistic interaction, and the supporting hand for those that required physical strength, such as pulling the body up while climbing. Moreover, while solving a task that ergonomically forced the usage of a particular hand, the macaques extracted food faster with the maneuvering hand as compared to the supporting hand, demonstrating the higher maneuvering dexterity of the maneuvering hand. As opposed to the conventional ideas of handedness in non-human primates, these observations demonstrate division of labor between the two hands marked by their consistent usage across spontaneous and experimental tasks requiring maneuvering in three-dimensional space or those requiring physical strength. Am. J. Primatol. 76:576-585, 2014. (c) 2013 Wiley Periodicals, Inc.

Simultaneous perturbation methods for adaptive labor staffing in service systems

We consider the problem of optimizing the workforce of a service system. Adapting the staffing levels in such systems is non-trivial due to large variations in workload and the large number of system parameters do not allow for a brute force search. Further, because these parameters change on a weekly basis, the optimization should not take longer than a few hours. Our aim is to find the optimum staffing levels from a discrete high-dimensional parameter set, that minimizes the long run average of the single-stage cost function, while adhering to the constraints relating to queue stability and service-level agreement (SLA) compliance. The single-stage cost function balances the conflicting objectives of utilizing workers better and attaining the target SLAs. We formulate this problem as a constrained parameterized Markov cost process parameterized by the (discrete) staffing levels. We propose novel simultaneous perturbation stochastic approximation (SPSA)-based algorithms for solving the above problem. The algorithms include both first-order as well as second-order methods and incorporate SPSA-based gradient/Hessian estimates for primal descent, while performing dual ascent for the Lagrange multipliers. Both algorithms are online and update the staffing levels in an incremental fashion. Further, they involve a certain generalized smooth projection operator, which is essential to project the continuous-valued worker parameter tuned by our algorithms onto the discrete set. The smoothness is necessary to ensure that the underlying transition dynamics of the constrained Markov cost process is itself smooth (as a function of the continuous-valued parameter): a critical requirement to prove the convergence of both algorithms. We validate our algorithms via performance simulations based on data from five real-life service systems. For the sake of comparison, we also implement a scatter search based algorithm using state-of-the-art optimization tool-kit OptQuest. From the experiments, we observe that both our algorithms converge empirically and consistently outperform OptQuest in most of the settings considered. This finding coupled with the computational advantage of our algorithms make them amenable for adaptive labor staffing in real-life service systems.