Novel 3-dimensional sixfold interpenetrating diamondoid networks of copper(I) coordination polymers of polypyridyl ligands - Syntheses,characterization and crystal structures

Two new coordination polymers [Cu(L-1)(2)](n)(ClO4)(n)center dot 2nH(2)O (1), [Cu(L-2)(2)](n)(ClO4)(n)center dot 2nH(2)O (2) of polydentate imine/pyridyl ligands, L-1 and L-2 with Cu(I) ion have been synthesized and characterized by single crystal X-ray diffraction studies, elemental analyses, IR' UV-vis and NMR spectroscopy. They represent 3-dimensional, sixfold interpenetrating diamondoid network structures having large pores of dimension, 35 x 21 angstrom(2) in 1 and 38 x 19 angstrom(2) in 2, respectively.

Ultrasonic degradation of poly(methyl methacrylate-co-alkyl acrylate) copolymers

The copolymers, poly(methyl methacrylate-co-methyl acrylate) (PMMAMA), poly(methyl methacrylate-co-ethyl acrylate) (PMMAEA) and poly(methyl methacrylate-co-butyl acrylate) (PMMABA), of different compositions were synthesized and characterized. The effect of alkyl acrylate content, alkyl group substituents and solvents on the ultrasonic degradation of these copolymers was studied. A model based on continuous distribution kinetics was used to study the kinetics of degradation. The rate coefficients were obtained by fitting the experimental data with the model. The linear dependence of the rate coefficients on the logarithm of the vapor pressure of the solvent indicated that vapor pressure is the crucial parameter that controls the degradation process. The rate of degradation increases with an increase in the alkyl acrylate content. At any particular copolymer composition, the rate of degradation follows the order: PMMAMA > PMMAEA > PMMABA. It was observed that the degradation rate coefficient varies linearly with the mole percentage of the alkyl acrylate in the copolymer.

Predicting the temporal response of seagrass meadows to dredging using Dynamic Bayesian Networks

Predicting temporal responses of ecosystems to disturbances associated with industrial activities is critical for their management and conservation. However, prediction of ecosystem responses is challenging due to the complexity and potential non-linearities stemming from interactions between system components and multiple environmental drivers. Prediction is particularly difficult for marine ecosystems due to their often highly variable and complex natures and large uncertainties surrounding their dynamic responses. Consequently, current management of such systems often rely on expert judgement and/or complex quantitative models that consider only a subset of the relevant ecological processes. Hence there exists an urgent need for the development of whole-of-systems predictive models to support decision and policy makers in managing complex marine systems in the context of industry based disturbances. This paper presents Dynamic Bayesian Networks (DBNs) for predicting the temporal response of a marine ecosystem to anthropogenic disturbances. The DBN provides a visual representation of the problem domain in terms of factors (parts of the ecosystem) and their relationships. These relationships are quantified via Conditional Probability Tables (CPTs), which estimate the variability and uncertainty in the distribution of each factor. The combination of qualitative visual and quantitative elements in a DBN facilitates the integration of a wide array of data, published and expert knowledge and other models. Such multiple sources are often essential as one single source of information is rarely sufficient to cover the diverse range of factors relevant to a management task. Here, a DBN model is developed for tropical, annual Halophila and temperate, persistent Amphibolis seagrass meadows to inform dredging management and help meet environmental guidelines. Specifically, the impacts of capital (e.g. new port development) and maintenance (e.g. maintaining channel depths in established ports) dredging is evaluated with respect to the risk of permanent loss, defined as no recovery within 5 years (Environmental Protection Agency guidelines). The model is developed using expert knowledge, existing literature, statistical models of environmental light, and experimental data. The model is then demonstrated in a case study through the analysis of a variety of dredging, environmental and seagrass ecosystem recovery scenarios. In spatial zones significantly affected by dredging, such as the zone of moderate impact, shoot density has a very high probability of being driven to zero by capital dredging due to the duration of such dredging. Here, fast growing Halophila species can recover, however, the probability of recovery depends on the presence of seed banks. On the other hand, slow growing Amphibolis meadows have a high probability of suffering permanent loss. However, in the maintenance dredging scenario, due to the shorter duration of dredging, Amphibolis is better able to resist the impacts of dredging. For both types of seagrass meadows, the probability of loss was strongly dependent on the biological and ecological status of the meadow, as well as environmental conditions post-dredging. The ability to predict the ecosystem response under cumulative, non-linear interactions across a complex ecosystem highlights the utility of DBNs for decision support and environmental management.

Using Bayesian networks to model surveillance in complex plant and animal health systems

In this chapter we consider biosecurity surveillance as part of a complex system comprising many different biological, environmental and human factors and their interactions. Modelling and analysis of surveillance strategies should take into account these complexities, and also facilitate the use and integration of the many types of different information that can provide insight into the system as a whole. After a brief discussion of a range of options, we focus on Bayesian networks for representing such complex systems. We summarize the features of Bayesian networks and describe these in the context of surveillance.

A flexible tool for integrated planning of active distribution networks

This paper presents a flexible and integrated planning tool for active distribution network to maximise the benefits of having high level s of renewables, customer engagement, and new technology implementations. The tool has two main processing parts: “optimisation” and “forecast”. The “optimization” part is an automated and integrated planning framework to optimize the net present value (NPV) of investment strategy for electric distribution network augmentation over large areas and long planning horizons (e.g. 5 to 20 years) based on a modified particle swarm optimization (MPSO). The “forecast” is a flexible agent-based framework to produce load duration curves (LDCs) of load forecasts for different levels of customer engagement, energy storage controls, and electric vehicles (EVs). In addition, “forecast” connects the existing databases of utility to the proposed tool as well as outputs the load profiles and network plan in Google Earth. This integrated tool enables different divisions within a utility to analyze their programs and options in a single platform using comprehensive information.

Allostery and conformational free energy changes in human tryptophanyl-tRNA synthetase from essential dynamics and structure networks

The interdependence of the concept of allostery and enzymatic catalysis, and they being guided by conformational mobility is gaining increased prominence. However, to gain a molecular level understanding of llostery and hence of enzymatic catalysis, it is of utter importance that the networks of amino acids participating in allostery be deciphered. Our lab has been exploring the methods of network analysis combined with molecular dynamics simulations to understand allostery at molecular level. Earlier we had outlined methods to obtain communication paths and then to map the rigid/flexible regions of proteins through network parameters like the shortest correlated paths, cliques, and communities. In this article, we advance the methodology to estimate the conformational populations in terms of cliques/communities formed by interactions including the side-chains and then to compute the ligand-induced population shift. Finally, we obtain the free-energy landscape of the protein in equilibrium, characterizing the free-energy minima accessed by the protein complexes. We have chosen human tryptophanyl-tRNA synthetase (hTrpRS), a protein esponsible for charging tryptophan to its cognate tRNA during protein biosynthesis for this investigation. This is a multidomain protein exhibiting excellent allosteric communication. Our approach has provided valuable structural as well as functional insights into the protein. The methodology adopted here is highly generalized to illuminate the linkage between protein structure networks and conformational mobility involved in the allosteric mechanism in any protein with known structure.

The effects of low-intensity ultrasound in bioabsorbable self-reinforced poly-L-lactide -fixed cancellous bone fracture

The purpose of the present study was to investigate the effects of low-intensity ultrasound on bioabsorbable self-reinforced poly-L-lactide (SR-PLLA) screws and on fracture healing after SR-PLLA device fixation in experimental and clinical cancellous bone fracture. In the first experimental study, the assessment of the mechanical strengths of the SR-PLLA screws was performed after 12 weeks of daily 20-minute ultrasound exposure in vitro. In the second experimental study, 32 male Wistar rats with an experimental distal femur osteotomy fixed with an SR-PLLA rod were exposed for daily low-intensity ultrasound treatment for 21 days. The effects on the healing bone were assessed. The clinical studies consist of three prospective, randomized, and placebo-controlled series of dislocated lateral malleolar fractures fixed with one SR-PLLA screw. The total number of the patients in these series was 52. Half of the patients were provided randomly with a sham ultrasound device. The patients underwent ultrasound therapy 20 minutes daily for six weeks. Radiological bone healing was assessed both by radiographs at two, six, nine, and 12 weeks and by multidetector computed tomography (MDCT) scans at two weeks, nine weeks, and 18 months. Bone mineral density was assessed by dual-energy X-ray absorptiometry (DXA). The clinical outcome was assessed by both Olerud-Molander scoring and clinical examination of the ankle. Low-intensity ultrasound had no effects on the mechanical properties and degradation behaviour of the SR-PLLA screws in vitro. There were no obvious signs of low-intensity ultrasound-induced enhancement in the bone healing in SR-PLLA-rod-fixed metaphyseal distal femur osteotomy in rats. The biocompatibility of low-intensity ultrasound treatment and SR-PLLA was found to be good. In the clinical series low-intensity ultrasound was observed to have no obvious effects on the bone mineral density of the fractured lateral malleolus. There were no obvious differences in the radiological bone healing times of the SR-PLLA-screw-fixed lateral malleolar fractures after low-intensity ultrasound treatment. Low-intensity ultrasound did not have any effects on radiological bone morphology, bone mineral density or clinical outcome 18 months after the injury. There were no obvious findings in the present study to support the hypothesis that low-intensity pulsed ultrasound enhances bone healing in SR-PLLA-rod-fixed experimental metaphyseal distal femur osteotomy in rats or in clinical SR-PLLA-screw-fixed lateral malleolar fractures. It is important to limit the conclusions of the present set of studies only to lateral malleolar fractures fixed with an SR-PLLA screw.

Evaluation of the Biocompatibility of Poly (ortho ester), Copolymer of ε-caprolactone/D,L-lactide and the Composite of Copolymer of ε-caprolactone/D,L-lactide and Tricalciumphosphate as Bone Filling Material

The purpose of this series of studies was to evaluate the biocompatibility of poly (ortho) ester (POE), copolymer of ε-caprolactone and D,L-lactide [P (ε-CL/DL-LA)] and the composite of P(ε-CL/DL-LA) and tricalciumphosphate (TCP) as bone filling material in bone defects. Tissue reactions and resorption times of two solid POE-implants (POE 140 and POE 46) with different methods of sterilization (gamma- and ethylene oxide sterilization), P(ε-CL/DL-LA)(40/60 w/w) in paste form and 50/50 w/w composite of 40/60 w/w P(ε-CL/DL-LA) and TCP and 27/73 w/w composite of 60/40 w/w P(ε-CL/DL-LA) and TCP were examined in experimental animals. The follow-up times were from one week to 52 weeks. The bone samples were evaluated histologically and the soft tissue samples histologically, immunohistochemically and electronmicroscopically. The results showed that the resorption time of gamma sterilized POE 140 was eight weeks and ethylene oxide sterilized POE 140 13 weeks in bone. The resorption time of POE 46 was more than 24 weeks. The gamma sterilized rods started to erode from the surface faster than ethylene oxide sterilized rods for both POEs. Inflammation in bone was from slight to moderate with POE 140 and moderate with POE 46. No highly fluorescent layer of tenascin or fibronectin was found in the soft tissue. Bone healing at the sites of implantation was slower than at control sites with the copolymer in small bone defects. The resorption time for the copolymer was over one year. Inflammation in bone was mostly moderate. Bone healing at the sites of implantation was also slower than at the control sites with the composite in small and large mandibular bone defects. Bone formation had ceased at both sites by the end of follow-up in large mandibular bone defects. The ultrastructure of the connective tissue was normal during the period of observation. It can be concluded that the method of sterilization influenced the resorption time of both POEs. Gamma sterilized POE 140 could have been suitable material for filling small bone defects, whereas the degradation times of solid EO-sterilized POE 140 and POE 46 were too slow to be considered as bone filling material. Solid material is difficult to contour, which can be considered as a disadvantage. The composites were excellent to handle, but the degradation time of the polymer and the composites were too slow. Therefore, the copolymer and the composite can not be recommended as bone filling material.

An adaptive drug delivery design using neural networks for effective treatment of infectious diseases: A simulation study

An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.

Analyzing information flow in brain networks with nonparametric Granger causality

Multielectrode neurophysiological recording and high-resolution neuroimaging generate multivariate data that are the basis for understanding the patterns of neural interactions. How to extract directions of information flow in brain networks from these data remains a key challenge. Research over the last few years has identified Granger causality as a statistically principled technique to furnish this capability. The estimation of Granger causality currently requires autoregressive modeling of neural data. Here, we propose a nonparametric approach based on widely used Fourier and wavelet transforms to estimate both pairwise and conditional measures of Granger causality, eliminating the need of explicit autoregressive data modeling. We demonstrate the effectiveness of this approach by applying it to synthetic data generated by network models with known connectivity and to local field potentials recorded from monkeys performing a sensorimotor task.

Comparison of performance parameters of poly(3,4 ethylenedioxythiophene) (PEDOT) based electrochromic device on glass with and without counter electrode

Conjugated polymers are promising materials for electrochromic device technology. Aqueous dispersions of poly(3,4-ethylenedioxythiophene)-(PEDOT) were spin coated onto transparent conducting oxide (TCO) coated glass substrates. A seven-layer electrochromic device was fabricated with the following configuration: glass/transparent conducting oxide (TCO)/PEDOT (main electrochromic layer)/gel electrolyte/prussian blue (counter electrode)/TCO/glass. The device fabricated with counter electrode (Prussian blue) showed a contrast of 18% and without counter electrode showed visible contrast of 5% at 632 nm at a voltage of 1.9 V. The comparison of the device is done in terms of the colouration efficiency of the devices with and without counter electrode.