Solid acid (superacid) catalyzed regioselective adamantylation of substituted benzenes

Adamantylation of substituted benzenes with 1-bromo-adamantane was catalyzed by solid acids including acidic ion exchange and ionomer resins, HY zeolite, sulfated zirconia and supported superacids on HY zeolite and SiO₂. Adamantylation generally takes place in excellent yield giving predominantly para products without formation of byproducts. The reactions did not require the usual workup of Friedel-Crafts reactions as catalysts were simply filtered of. Cross-linked polystyrene resin sulfonic acid (Amberlyst) was found particularly suitable as besides its high catalytic activity, high regioselectivity was observed with almost exclusive formation ofp-adamantylated benzenes. AMI, PM3 and MNDO semiempirical calculations of heats of formation showed that of all regioisomers, the para isomer is the most stable. The temperature dependence of adamantylation was also investigated allowing the optimization ofp-substituted product in high yield and excellent selectivity. Lack of isomerization of 1-p-tolyla-damantane using solid (Amberlyst, Nafion-H) and liquid acids (neat and modified trifluoromethanesulfonic acid) indicates absence of product isomerization, while the intramolecular rearrangement of the intermediate arenium complex is still possible.Catalysis by solid superacids, Part 30. For part 29, see ref.[1A].     

Facile development,characterization, and optimization of new metformin-loaded nanocarrier system for efficient colon cancer adjunct therapy

Purpose: Metformin hydrochloride (MF) repurposing as adjuvant anticancer therapy for colorectal cancer (CRC) proved effective. Several studies attempted to develop MF-loaded nanoparticles (NPs), however the entrapment efficiency (EE%) was poor. Thus, the present study aimed at the facile development of a new series of chitosan (CS)-based semi-interpenetrating network (semi-IPN) NPs incorporating Pluronic^® nanomicelles as nanocarriers for enhanced entrapment and sustained release of MF for efficient treatment of CRC.

Methods: The NPs were prepared by ionic gelation and subsequently characterized using FTIR, DSC, TEM, and DLS. A full factorial design was also adopted to study the effect of various formulation variables on EE%, particle size, and zeta-potential of NPs.

Results: NPs had a spherical shape and a mean particle size ranging between 135 and 220?nm. FTIR and DSC studies results were indicative of successful ionic gelation with the drug being dispersed in its amorphous form within CS-Pluronic^® matrix. Maximum EE% reaching 57.00?±?12.90% was achieved using Pluronic^®-123 based NPs. NPs exhibited a sustained release profile over 48?h. The MF-loaded NPs sensitized RKO CRC cells relative to drug alone.

Conclusion: The reported results highlighted the novel utility of the developed NPs in the arena of colon cancer treatment.     

Switching Supervisory Control Using Calibrated Forecasts

In this paper, we approach supervisory control as an online decision problem. In particular, we introduce ldquocalibrated forecastsrdquo as a mechanism for controller selection in supervisory control. The forecasted quantity is a candidate controller's performance level, or reward, over finite implementation horizon. Controller selection is based on using the controller with the maximum calibrated forecast of the reward. The proposed supervisor does not perform a pre-routed search of candidate controllers and does not require the presence of exogenous inputs for excitation or identification. Assuming the existence of a stabilizing controller within the set of candidate controllers, we show that under the proposed supervisory controller, the output of the system remains bounded for any bounded disturbance, even if the disturbance is chosen in an adversarial manner. The use of calibrated forecasts enables one to establish overall performance guarantees for the supervisory scheme even though non-stabilizing controllers may be persistently selected by the supervisor because of the effects of initial conditions, exogenous disturbances, or random selection. The main results are obtained for a general class of system dynamics and specialized to linear systems.     

Discrimination of speech from nonspeech based on multiscale spectro-temporal Modulations

We describe a content-based audio classification algorithm based on novel multiscale spectro-temporal modulation features inspired by a model of auditory cortical processing. The task explored is to discriminate speech from nonspeech consisting of animal vocalizations, music, and environmental sounds. Although this is a relatively easy task for humans, it is still difficult to automate well, especially in noisy and reverberant environments. The auditory model captures basic processes occurring from the early cochlear stages to the central cortical areas. The model generates a multidimensional spectro-temporal representation of the sound, which is then analyzed by a multilinear dimensionality reduction technique and classified by a support vector machine (SVM). Generalization of the system to signals in high level of additive noise and reverberation is evaluated and compared to two existing approaches (Scheirer and Slaney, 2002 and Kingsbury et al., 2002). The results demonstrate the advantages of the auditory model over the other two systems, especially at low signal-to-noise ratios (SNRs) and high reverberation.     

Analysis of gain scheduled control for nonlinear plants

Gain scheduling has proven to be a successful design methodology in many engineering applications. In the absence of a sound theoretical analysis, these designs come with no guarantees of the robustness, performance, or even nominal stability of the overall gain-scheduled design. An analysis is presented for two types of nonlinear gain-scheduled control systems: (1) scheduling on a reference trajectory, and (2) scheduling on the plant output. Conditions which guarantee stability, robustness, and performance properties of the global gain schedule designs are given. These conditions confirm and formalize popular notions regarding gain scheduled designs, such as that the scheduling variable should vary slowly, and capture the plant's nonlinearities     

Visualizing live text streams using motion and temporal pooling

The informational context in which we live and work is becoming increasingly complex and rich, with information much more plentiful and accessible than ever before. Our informational context is also faster paced, with news and developments spreading across media and the Internet at an often astounding rate. In today's competitive world, the first response to a trend is usually the most effective. Thus far, the technology responsible for this information complexity offers little to help us quickly understand and act upon it. Although visualization is useful, its techniques are typically too slow or simply not designed to help users understand highly time-sensitive and dynamic information streams. To address this, we developed TextPool, a system that uses temporal pooling to visualize live text streams such as newswires and system telemetry. In temporal pooling, systems gather recent stream content into a buffer (pool) to use for visualization. Because the stream continues to flow through the pool in real time, the visualization must be dynamic, using motion to respond to the pool's changing content. The TextPool system processes live text streams in real time using information retrieval techniques, extracts the most frequently occurring salient terms from the buffered streams, and displays related terms next to one another in a dynamic text collage.     

The necessity of the small-gain theorem for time-varying andnonlinear systems

It is shown that an appropriately modified version of the small-gain theorem which uses the `asymptotic gain' of a fading-memory system leads to a necessary and sufficient condition for the stable invertibility of certain feedback operators. This modified small-gain theorem is then used to obtain conditions for robust finite-energy input-output stability of: (1) nonlinear plants subject to nonlinear time-varying perturbations; and (2) linear time-varying plants subject to linear time-varying perturbations. These conditions are shown to be necessary as well as sufficient     

Approximate set-valued observers for nonlinear systems

A set-valued observer (SVO) produces a set of possible states based on output measurements and a priori models of exogenous disturbances and noises. Previous work considered linear time-varying systems and unknown-but-bounded exogenous signals. In this case, the sets of possible state vectors take the form of polytopes whose centers are optimal state estimates. These polytopic sets can be computed by solving several small linear programs. An SVO can be constructed conceptually for nonlinear systems; however, the set of possible state vectors no longer takes the form of polytopes, which in turn inhibits their explicit computation. This paper considers an “extended SVO”. As in the extended Kalman filter, the state equations are linearized about the state estimate, and a linear SVO is designed along the linearization trajectory. Under appropriate observability assumptions, it is shown that the extended SVO provides an exponentially convergent state estimate in the case of sufficiently small initial condition uncertainty and provides a nondivergent state estimate in the case of sufficiently small exogenous signals