Nanosized polymetallic resorcinarene-based host assemblies that strongly bind fullerenes

Polymetallic nanodimensional assemblies have been prepared via metal directed assembly of dithiocarbamate functionalized cavitand structural frameworks with late transition metals (Ni, Pd, Cu, Au, Zn, and Cd). The coordination geometry about the metal centers is shown to dictate the architecture adopted. X-ray crystallographic studies confirm that square planar coordination geometries result in "cagelike" octanuclear complexes, whereas square-based pyramidal metal geometries favor hexanuclear "molecular loop" structures. Both classes of complex are sterically and electronically complementary to the fullerenes (C-60 and C-70). The strong binding of these guests occurred via favorable interactions with the sulfur atoms of multiple dithiocarbamate moieties of the hosts. In the case of the tetrameric copper(II) complexes, the lability of the copper(II)-dithiocarbamate bond enabled the fullerene guests to be encapsulated in the electron-rich cavity of the host, over time. The examination of the binding of fullerenes has been undertaken using spectroscopic and electrochemical methods, electrospray mass spectrometry, and molecular modeling.

Modeling the structure of amorphous MoS3: a neutron diffraction and reverse Monte Carlo study

A model for the structure of amorphous molybdenum trisulfide, a-MoS3, has been created using reverse Monte Carlo methods. This model, which consists of chains Of MoS6 units sharing three sulfurs with each of its two neighbors and forming alternate long, nonbonded, and short, bonded, Mo-Mo separations, is a good fit to the neutron diffraction data and is chemically and physically realistic. The paper identifies the limitations of previous models based on Mo-3 triangular clusters in accounting for the available experimental data.

MULTIMODE quantum calculations of intramolecular vibrational energies of the water dimer and trimer using ab initio-based potential energy surfaces

We report vibrational configuration interaction calculations of the monomer fundamentals of (H2O)(2), (D2O)(2), (H2O)(3), and (D2O)(3) using the code MULTIMODE and full dimensional ab initio-based global potential energies surfaces (PESs). For the dimer the HBB PES [Huang , J. Chem. Phys 128, 034312 (2008)] is used and for the trimer a new PES, reported here, is used. The salient properties of the new trimer PES are presented and compared to previous single-point calculations and the vibrational energies are compared with experiments. (C) 2008 American Institute of Physics.

Modeling the variability of single-cell lag times for Listeria innocua populations after sublethal and lethal heat treatments

Optical density measurements were used to estimate the effect of heat treatments on the single-cell lag times of Listeria innocua fitted to a shifted gamma distribution. The single-cell lag time was subdivided into repair time ( the shift of the distribution assumed to be uniform for all cells) and adjustment time (varying randomly from cell to cell). After heat treatments in which all of the cells recovered (sublethal), the repair time and the mean and the variance of the single-cell adjustment time increased with the severity of the treatment. When the heat treatments resulted in a loss of viability (lethal), the repair time of the survivors increased with the decimal reduction of the cell numbers independently of the temperature, while the mean and variance of the single-cell adjustment times remained the same irrespective of the heat treatment. Based on these observations and modeling of the effect of time and temperature of the heat treatment, we propose that the severity of a heat treatment can be characterized by the repair time of the cells whether the heat treatment is lethal or not, an extension of the F value concept for sublethal heat treatments. In addition, the repair time could be interpreted as the extent or degree of injury with a multiple-hit lethality model. Another implication of these results is that the distribution of the time for cells to reach unacceptable numbers in food is not affected by the time-temperature combination resulting in a given decimal reduction.

New mathematical modeling approach for predicting microbial inactivation by high hydrostatic pressure

A new primary model based on a thermodynamically consistent first-order kinetic approach was constructed to describe non-log-linear inactivation kinetics of pressure-treated bacteria. The model assumes a first-order process in which the specific inactivation rate changes inversely with the square root of time. The model gave reasonable fits to experimental data over six to seven orders of magnitude. It was also tested on 138 published data sets and provided good fits in about 70% of cases in which the shape of the curve followed the typical convex upward form. In the remainder of published examples, curves contained additional shoulder regions or extended tail regions. Curves with shoulders could be accommodated by including an additional time delay parameter and curves with tails shoulders could be accommodated by omitting points in the tail beyond the point at which survival levels remained more or less constant. The model parameters varied regularly with pressure, which may reflect a genuine mechanistic basis for the model. This property also allowed the calculation of (a) parameters analogous to the decimal reduction time D and z, the temperature increase needed to change the D value by a factor of 10, in thermal processing, and hence the processing conditions needed to attain a desired level of inactivation; and (b) the apparent thermodynamic volumes of activation associated with the lethal events. The hypothesis that inactivation rates changed as a function of the square root of time would be consistent with a diffusion-limited process.

Kinetic modeling of the generation of 2-and 3-methylbutanal in a heated extract of beef liver

Quantitative control of aroma generation during the Maillard reaction presents great scientific and industrial interest. Although there have been many studies conducted in simplified model systems, the results are difficult to apply to complex food systems, where the presence of other components can have a significant impact. In this work, an aqueous extract of defatted beef liver was chosen as a simplified food matrix for studying the kinetics of the Mallard reaction. Aliquots of the extract were heated under different time and temperature conditions and analyzed for sugars, amino acids, and methylbutanals, which are important Maillard-derived aroma compounds formed in cooked meat. Multiresponse kinetic modeling, based on a simplified mechanistic pathway, gave a good fit with the experimental data, but only when additional steps were introduced to take into account the interactions of glucose and glucose-derived intermediates with protein and other amino compounds. This emphasizes the significant role of the food matrix in controlling the Maillard reaction.

Synthesis of cationic water-soluble copolymers and hydrogels based on [2-(methacryloyloxy)ethyl]trimethylammonium cloride and 2-hydroxyethylacrylate and their complex formation with poly(acrylic acid)

Water-soluble cationic copolymers and hydrogels were synthesized by radical copolymerization of [2-(methacryloyloxy)ethyl]trimetilylammonium chloride (MADQUAT) and 2-hydroxyethylacrylate (HEA). The kinetics of copolymerization has been studied and the reactivity ratios were determined. It was found that MADQUAT exhibits higher reactivity in copolymerization. The complexation between linear MADQUAT-HEA and linear poly(acrylic acid) (PAA) has been studied in aqueous solutions at different pH. It results in the formation of insoluble polyelectrolyte complexes, whose composition and stability to aggregate depends on MADQUAT content in copolymers and pH. The hydrogels were synthesized by three-dimensional radical copolymerization of MADQUAT and HEA in the presence of a crosslinker. The effects of the feed mixture composition on yield and swelling properties of the hydrogels were studied. The interactions of these hydrogels with linear PAA result in formation of gel-polyelectrolyte complexes and contraction of the samples. It was found that the contraction depends on copolymer composition, PAA molecular weight, and solution pH. (c) 2006 Wiley Periodicals, Inc.

Temperature-responsive water-soluble copolymers based on 2-hydroxyethyl acrylate and butyl acrylate

Amphiphilic copolymers have been synthesised by free radical copolymerisation of 2-hydroxyethyl acrylate with butyl acrylate, the reactivity ratios of which indicate practically equal reactivity. The copolymers containing less than 30 mol-% of BA were soluble in water and exhibited a LCST in aqueous solutions. It was found that the interaction between these copolymers and poly(acrylic acid) in aqueous solutions resulted in the formation of interpolymer complexes stabilised by hydrogen bonds and hydrophobic interactions. This interaction was significantly affected by solution I pH and led to modification of the temperature-responsive behaviour of the copolymers.

Novel temperature-responsive water-soluble copolymers based on 2-hydroxyethylacrylate and vinyl butyl ether and their interactions with poly(carboxylic acids)

Novel water-soluble amphiphilic copolymers have been synthesized by free radical copolymerization of 2-hydroxyethylacrylate with vinyl butyl ether. In water these copolymers exhibit lower critical solution temperature, which depends on the content of hydrophobic vinyl butyl ether units. The interaction between these copolymers and poly(acrylic acid) or poly(methacrylic acid) in aqueous solutions results in formation of interpolymer complexes stabilized by hydrogen bonds and hydrophobic interactions. An increase in hydrophobicity of the copolymers leads to the enhancement of their complex formation ability with respect to poly(acrylic acid) and poly(methacrylic acid). Poly(methacrylic acid) forms stronger complexes with the copolymers when compared with poly(acrylic acid). The complexes exhibit dual sensitivity to pH- and temperature and this property may be easily adjusted regulating the strength of interaction. (c) 2005 Wiley Periodicals, Inc.

Characterisation of blends based on hydroxyethylcellulose and maleic acid-alt-methyl vinyl ether

Hydrophilic polymeric films based on blends of hydroxyethylcellulose and maleic acid-co-methyl vinyl ether were produced by casting from aqueous solutions. The physicochemical properties of the blends have been assessed using Fourier transform infrared spectroscopy, thermal gravimetric analysis, differential scanning calorimetry, dielectric spectroscopy, etc. The pristine films exhibit complete miscibility due to the formation of intermacromolecular hydrogen bonding. The thermal treatment of the blend films leads to cross-linking via intermacromolecular esterification and anhydride formation. The cross-linked materials are able to swell in water and their swelling degree can be easily controlled by temperature and thermal treatment time. The formation of the crosslinks is apparent in the dynamic properties of the blends as observed through the mechanical relaxation and dielectric relaxation spectra. The dielectric characteristics of the material are influenced by the effects of change in the local structure of the blend on the ionic conduction processes and the rate of dipolar relaxation. Separation of these processes is attempted using the dielectric modulus method. Significant deviations from a simple additive rule of mixing on the activation energy are observed consistent with hydrogen bonding and crosslinking of the matrix. This paper indicates a method for the creation of films with good mechanical and physical characteristics by exposing the blends to a relatively mild thermal treatment.

Inverse problems in dynamic cognitive modeling

Inverse problems for dynamical system models of cognitive processes comprise the determination of synaptic weight matrices or kernel functions for neural networks or neural/dynamic field models, respectively. We introduce dynamic cognitive modeling as a three tier top-down approach where cognitive processes are first described as algorithms that operate on complex symbolic data structures. Second, symbolic expressions and operations are represented by states and transformations in abstract vector spaces. Third, prescribed trajectories through representation space are implemented in neurodynamical systems. We discuss the Amari equation for a neural/dynamic field theory as a special case and show that the kernel construction problem is particularly ill-posed. We suggest a Tikhonov-Hebbian learning method as regularization technique and demonstrate its validity and robustness for basic examples of cognitive computations.

Modeling the effects of node heterogeneity on the performance of a real grid application

The performance benefit when using Grid systems comes from different strategies, among which partitioning the applications into parallel tasks is the most important. However, in most cases the enhancement coming from partitioning is smoothed by the effect of the synchronization overhead, mainly due to the high variability of completion times of the different tasks, which, in turn, is due to the large heterogeneity of Grid nodes. For this reason, it is important to have models which capture the performance of such systems. In this paper we describe a queueing-network-based performance model able to accurately analyze Grid architectures, and we use the model to study a real parallel application executed in a Grid. The proposed model improves the classical modelling techniques and highlights the impact of resource heterogeneity and network latency on the application performance.

Applying semiotic analysis to the design and modeling of distributed multimedia systems

Semiotics is the study of signs. Application of semiotics in information systems design is based on the notion that information systems are organizations within which agents deploy signs in the form of actions according to a set of norms. An analysis of the relationships among the agents, their actions and the norms would give a better specification of the system. Distributed multimedia systems (DMMS) could be viewed as a system consisted of many dynamic, self-controlled normative agents engaging in complex interaction and processing of multimedia information. This paper reports the work of applying the semiotic approach to the design and modeling of DMMS, with emphasis on using semantic analysis under the semiotic framework. A semantic model of DMMS describing various components and their ontological dependencies is presented, which then serves as a design model and implemented in a semantic database. Benefits of using the semantic database are discussed with reference to various design scenarios.

Sparse modeling using orthogonal forward regression with PRESS statistic and regularization

The paper introduces an efficient construction algorithm for obtaining sparse linear-in-the-weights regression models based on an approach of directly optimizing model generalization capability. This is achieved by utilizing the delete-1 cross validation concept and the associated leave-one-out test error also known as the predicted residual sums of squares (PRESS) statistic, without resorting to any other validation data set for model evaluation in the model construction process. Computational efficiency is ensured using an orthogonal forward regression, but the algorithm incrementally minimizes the PRESS statistic instead of the usual sum of the squared training errors. A local regularization method can naturally be incorporated into the model selection procedure to further enforce model sparsity. The proposed algorithm is fully automatic, and the user is not required to specify any criterion to terminate the model construction procedure. Comparisons with some of the existing state-of-art modeling methods are given, and several examples are included to demonstrate the ability of the proposed algorithm to effectively construct sparse models that generalize well.

Modeling the effects of node heterogeneity on the performance of grid applications

The performance benefit when using grid systems comes from different strategies, among which partitioning the applications into parallel tasks is the most important. However, in most cases the enhancement coming from partitioning is smoothed by the effects of synchronization overheads, mainly due to the high variability in the execution times of the different tasks, which, in turn, is accentuated by the large heterogeneity of grid nodes. In this paper we design hierarchical, queuing network performance models able to accurately analyze grid architectures and applications. Thanks to the model results, we introduce a new allocation policy based on a combination between task partitioning and task replication. The models are used to study two real applications and to evaluate the performance benefits obtained with allocation policies based on task replication.