Industrial ecology at factory level - A conceptual model

Growing environmental concerns caused by natural resource depletion and pollution need to be addressed. One approach to these problems is Sustainable Development, a key concept for our society to meet present as well as future needs worldwide. Manufacturing clearly has a major role to play in the move towards a more sustainable society. However it appears that basic principles of environmental sustainability are not systematically applied, with practice tending to focus on local improvements. The aim of the work presented in this paper is to adopt a more holistic view of the factory unit to enable opportunities for wider improvement. This research analyses environmental principles and industrial practice to develop a conceptual manufacturing ecosystem model as a foundation to improve environmental performance. The model developed focuses on material, energy and waste flows to better understand the interactions between manufacturing operations, supporting facilities and surrounding buildings. The research was conducted in three steps: (1) existing concepts and models for industrial sustainability were reviewed and environmental practices in manufacturing were collected and analysed; (2) gaps in knowledge and practice were identified; (3) the outcome is a manufacturing ecosystem model based on industrial ecology (IE). This conceptual model has novelty in detailing IE application at factory level and integrating all resource flows. The work is a base on which to build quantitative modelling tools to seek integrated solutions for lower resource input, higher resource productivity, fewer wastes and emissions, and lower operating cost within the boundary of a factory unit. © 2012 Elsevier Ltd. All rights reserved.

A global model for effective use and evaluation of e-learning in health.

Healthcare systems worldwide face a wide range of challenges, including demographic change, rising drug and medical technology costs, and persistent and widening health inequalities both within and between countries. Simultaneously, issues such as professional silos, static medical curricula, and perceptions of "information overload" have made it difficult for medical training and continued professional development (CPD) to adapt to the changing needs of healthcare professionals in increasingly patient-centered, collaborative, and/or remote delivery contexts. In response to these challenges, increasing numbers of medical education and CPD programs have adopted e-learning approaches, which have been shown to provide flexible, low-cost, user-centered, and easily updated learning. The effectiveness of e-learning varies from context to context, however, and has also been shown to make considerable demands on users' motivation and "digital literacy" and on providing institutions. Consequently, there is a need to evaluate the effectiveness of e-learning in healthcare as part of ongoing quality improvement efforts. This article outlines the key issues for developing successful models for analyzing e-health learning.

A single-Stream jet noise prediction model for a family of chevron nozzles

This study develops a single-stream jet noise prediction model for a family of chevron nozzles. An original equation is proposed for the fourth-order space-time cross-correlations. They are expressed in flow parameters such as streamwise circulation and turbulent kinetic energy. The cross-correlations based on a Reynolds Averaged Navier-Stokes (RANS) flowfield showed a good agreement with those based on a Large Eddy Simulation (LES) flowfield. This proves that the proposed equation describes the cross-correlations accurately. With this novel source description, there is an excellent agreement between our model's far-field noise predictions and measurements1 for a wide range of frequencies and radiation angles. Our model captures the spectral shape, amplitude and peak frequency very well. This establishes that our model holds good for a family of chevron nozzles. As our model provides quick and accurate predictions, a parametric study was performed to understand the effects of a chevron nozzle geometry on jet noise and thrust loss. Chevron penetration is the underpinning factor for jet noise reduction. The reduction of jet noise per unit thrust loss decreases linearly with chevron penetration. The number of chevrons also has a considerable effect on jet noise.

A global model for effective use and evaluation of e-learning in health.

Healthcare systems worldwide face a wide range of challenges, including demographic change, rising drug and medical technology costs, and persistent and widening health inequalities both within and between countries. Simultaneously, issues such as professional silos, static medical curricula, and perceptions of "information overload" have made it difficult for medical training and continued professional development (CPD) to adapt to the changing needs of healthcare professionals in increasingly patient-centered, collaborative, and/or remote delivery contexts. In response to these challenges, increasing numbers of medical education and CPD programs have adopted e-learning approaches, which have been shown to provide flexible, low-cost, user-centered, and easily updated learning. The effectiveness of e-learning varies from context to context, however, and has also been shown to make considerable demands on users' motivation and "digital literacy" and on providing institutions. Consequently, there is a need to evaluate the effectiveness of e-learning in healthcare as part of ongoing quality improvement efforts. This article outlines the key issues for developing successful models for analyzing e-health learning.

Simulated morphological landscape of polymer single crystals by phase-field model

The novel phase field model with the "polymer characteristic" was established based on a nonconserved spatiotemporal Ginzburg-Landau equation (TDGL model A). Especially, we relate the diffusion equation with the crystal growth faces of polymer single crystals. Namely, the diffusion equations are discretized according to the diffusion coefficient of every lattice site in various crystal growth faces and the shape of lattice is selected based on the real proportion of the unit cell dimensions.

Luminescence functionalization of mesoporous silica with different morphologies and applications as drug delivery systems

Ordered mesoporous silica (MCM-41) particles with different morphologies were synthesized through a simple hydrothermal process. Then these silica particles were functionalized with luminescent YVO4:EU3+ layers via the Pechini sol-gel process. The obtained YVO4:Eu3+ and MCM-41 composites, which maintained the mesoporous structure of MCM-41 and the red luminescence property of YVO4:Eu3+ were investigated as drug delivery systems using ibuprofen (IBU) as model drug. The physicochemical properties of the samples were characterized by X-ray diffraction (XRD), Fourier transform-infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), transmission electron microscopy (TEM), N-2 adsorption, and photoluminescence (PL) spectra, respectively.

Construction of hollow DNA/PLL microcapsule as a dual carrier for controlled delivery of DNA and drug

DNA/poly-L-lysine (PLL) capsules were constructed through a layer-by-layer (LbL) self-assembly of DNA and PLL on CaCO3 microparticles, and then used as dual carriers for DNA and drug after dissolution of carbonate cores. The permeability of DNA/PLL microcapsules was investigated with fluorescence probes with different molecular weights by confocal microscopy. The result revealed that the fluorescence probes were able to penetrate the capsule walls even its molecular weight up to 150 kDa. The resultant capsules were used to load drug model molecules-fluorescein isothiocyanate (FITC)-dextran (4 kDa) via spontaneous deposition mechanism.

Fabrication and characterization of microstructured and pH sensitive interpenetrating networks hydrogel films and application in drug delivery field

Novel microstructured and pH sensitive poly(acryliac acid-co-2-hydroxyethyl methacrylate)/poly(vinyl alcohol) (P(AA-co-HEMA)/PVA) interpenetrating network (IPN) hydrogel films were prepared by radical precipitation copolymerization and sequential IPN technology. The first P(AA-co-HEMA) network was synthesized in the present of IPN aqueous solution by radical initiating, then followed by condensation reaction (Glutaraldehyde as crosslinking agent) within the resultant latex, it formed multiple IPN microstructured hydrogel film. The film samples were characterized by IR, SEM and DSC. Swelling and deswelling behaviors and mechanical property showed the novel multiple IPN nanostuctured film had rapid response and good mechanical property. The IPN films were studied as controlled drug delivery material in different pH buffer solution using cationic compound, crystal violet as a model drug.

Glycyrrhetinic acid-modified nanoparticles for drug delivery: Preparation and characterization

In this work, glycyrrhetinic acid-modified chitosan (mGA-suc-CTS) used as liver targeted carrier for drug delivery, was prepared via hemisuccinate as a bridged group. The structure of the product was confirmed by IR and NMR methods and the degree of substitution (DS) of glycyrrhetinic acid groups was estimated via elemental analysis. Nanoparticles were formed by ionic gelation methold. The drug-loading and release behavior of the nanoparticles were investigated using BSA as the model drug. The results indicated that the carrier with a highest DS of 5.19% could be got and the DS was controlled by changing reaction temperature or feed ratio. BSA could be entrapped into the nanoparticles with the drug-loading ratio of 26.3% and the encapsulation efficiency of 81.5%. A sustained release over an 11-day period was observed in pH 7.4 in vitro.

Crosslinking of polyimides via spirodilactone unit in polymer backbone

A new approach for the crosslinking of polyimides via the lactamization of spirodilactone unit in polyimide backbone was studied by two means: model reaction and the comparison of the properties of the polyimide precursors to those of the crosslinking polymers. Polyimides 4 and 5 were soluble in N,N'dimethylacetamide (DMAc), dimethylformamide (DMF), dimethylsulfoxide (DMSO), N'-methylpyrrolidone (NMP), and other common organic solvents, whereas their corresponding crosslinking polymers were insoluble in these solvents. The glass transition temperatures for polyimide 5 and its crosslinking polymer were 262 degrees C and 291 degrees C, whereas those for polyimide 4 and its crosslinking polymer were 265 degrees C and 360 degrees C. The weight-loss rate of the crosslinling polymers was apparently slower than that of the precursors when the temperature was >400 degrees C. The 10% weight-loss temperature for the polyimides 4 and 5 was <500 degrees C, whereas that for the crosslinking polymers was close to or above 600 degrees C. The results indicate that this type of crosslinking polymer has good thermal properties. The temperature for the formation of lactam was above 180 degrees C. (C) 1999 John Wiley & Sons, Inc.

Scalability of Multicast Delivery for Non-sequential Streaming Access

To serve asynchronous requests using multicast, two categories of techniques, stream merging and periodic broadcasting have been proposed. For sequential streaming access where requests are uninterrupted from the beginning to the end of an object, these techniques are highly scalable: the required server bandwidth for stream merging grows logarithmically as request arrival rate, and the required server bandwidth for periodic broadcasting varies logarithmically as the inverse of start-up delay. However, sequential access is inappropriate to model partial requests and client interactivity observed in various streaming access workloads. This paper analytically and experimentally studies the scalability of multicast delivery under a non-sequential access model where requests start at random points in the object. We show that the required server bandwidth for any protocols providing immediate service grows at least as the square root of request arrival rate, and the required server bandwidth for any protocols providing delayed service grows linearly with the inverse of start-up delay. We also investigate the impact of limited client receiving bandwidth on scalability. We optimize practical protocols which provide immediate service to non-sequential requests. The protocols utilize limited client receiving bandwidth, and they are near-optimal in that the required server bandwidth is very close to its lower bound.

CONFIGR: A Vision-Based Model for Long-Range Figure Completion

CONFIGR (CONtour FIgure GRound) is a computational model based on principles of biological vision that completes sparse and noisy image figures. Within an integrated vision/recognition system, CONFIGR posits an initial recognition stage which identifies figure pixels from spatially local input information. The resulting, and typically incomplete, figure is fed back to the “early vision” stage for long-range completion via filling-in. The reconstructed image is then re-presented to the recognition system for global functions such as object recognition. In the CONFIGR algorithm, the smallest independent image unit is the visible pixel, whose size defines a computational spatial scale. Once pixel size is fixed, the entire algorithm is fully determined, with no additional parameter choices. Multi-scale simulations illustrate the vision/recognition system. Open-source CONFIGR code is available online, but all examples can be derived analytically, and the design principles applied at each step are transparent. The model balances filling-in as figure against complementary filling-in as ground, which blocks spurious figure completions. Lobe computations occur on a subpixel spatial scale. Originally designed to fill-in missing contours in an incomplete image such as a dashed line, the same CONFIGR system connects and segments sparse dots, and unifies occluded objects from pieces locally identified as figure in the initial recognition stage. The model self-scales its completion distances, filling-in across gaps of any length, where unimpeded, while limiting connections among dense image-figure pixel groups that already have intrinsic form. Long-range image completion promises to play an important role in adaptive processors that reconstruct images from highly compressed video and still camera images.

P-glycoprotein inhibition as a strategy to increase drug delivery across the blood-brain barrier: focus on antidepressants

Depression is among the leading causes of disability worldwide. Currently available antidepressant drugs have unsatisfactory efficacy, with up to 60% of depressed patients failing to respond adequately to treatment. Emerging evidence has highlighted a potential role for the efflux transporter P-glycoprotein (P-gp), expressed at the blood-brain barrier (BBB), in the aetiology of treatment-resistant depression. In this thesis, the potential of P-gp inhibition as a strategy to enhance the brain distribution and pharmacodynamic effects of antidepressant drugs was investigated. Pharmacokinetic studies demonstrated that administration of the P-gp inhibitors verapamil or cyclosporin A (CsA) enhanced the BBB transport of the antidepressants imipramine and escitalopram in vivo. Furthermore, both imipramine and escitalopram were identified as transported substrates of human P-gp in vitro. Contrastingly, human P-gp exerted no effect on the transport of four other antidepressants (amitriptyline, duloxetine, fluoxetine and mirtazapine) in vitro. Pharmacodynamic studies revealed that pre-treatment with verapamil augmented the behavioural effects of escitalopram in the tail suspension test (TST) of antidepressant-like activity in mice. Moreover, pre-treatment with CsA exacerbated the behavioural manifestation of an escitalopram-induced mouse model of serotonin syndrome, a serious adverse reaction associated with serotonergic drugs. This finding highlights the potential for unwanted side-effects which may occur due to increasing brain levels of antidepressants by P-gp inhibition, although further studies are needed to fully elucidate the mechanism(s) at play. Taken together, the research outlined in this thesis indicates that P-gp may restrict brain concentrations of escitalopram and imipramine in patients. Moreover, we show that increasing the brain distribution of an antidepressant by P-gp inhibition can result in an augmentation of antidepressant-like activity in vivo. These findings raise the possibility that P-gp inhibition may represent a potentially beneficial strategy to augment antidepressant treatment in clinical practice. Further studies are now warranted to evaluate the safety and efficacy of this approach.

Modified cyclodextrins as novel non-viral vectors for neuronal siRNA delivery: focus on Huntington’s disease

Huntington’s Disease (HD) is a rare autosomal dominant neurodegenerative disease caused by the expression of a mutant Huntingtin (muHTT) protein. Therefore, preventing the expression of muHTT by harnessing the specificity of the RNA interference (RNAi) pathway is a key research avenue for developing novel therapies for HD. However, the biggest caveat in the RNAi approach is the delivery of short interfering RNA (siRNAs) to neurons, which are notoriously difficult to transfect. Indeed, despite the great advances in the field of nanotechnology, there remains a great need to develop more effective and less toxic carriers for siRNA delivery to the Central Nervous System (CNS). Thus, the aim of this thesis was to investigate the utility of modified amphiphilic β-cyclodextrins (CDs), oligosaccharide-based molecules, as non-viral vectors for siRNA delivery for HD. Modified CDs were able to bind and complex siRNAs forming nanoparticles capable of delivering siRNAs to ST14A-HTT120Q cells and to human HD fibroblasts, and reducing the expression of the HTT gene in these in vitro models of HD. Moreover, direct administration of CD.siRNA nanoparticles into the R6/2 mouse brain resulted in significant HTT gene expression knockdown and selective alleviation of rotarod motor deficits in this mouse model of HD. In contrast to widely used transfection reagents, CD.siRNA nanoparticles only induced limited cytotoxic and neuroinflammatory responses in multiple brain-derived cell-lines, and also in vivo after single direct injections into the mouse brain. Alternatively, we have also described a PEGylation-based formulation approach to further stabilise CD.siRNA nanoparticles and progress towards a systemic delivery nanosystem. Resulting PEGylated CD.siRNA nanoparticles showed increased stability in physiological saltconditions and, to some extent, reduced protein-induced aggregation. Taken together, the work outlined in this thesis identifies modified CDs as effective, safe and versatile siRNA delivery systems that hold great potential for the treatment of CNS disorders, such as HD.

At what price? A cost-effectiveness analysis comparing trial of labour after previous caesarean versus elective repeat caesarean delivery

Background: Elective repeat caesarean delivery (ERCD) rates have been increasing worldwide, thus prompting obstetric discourse on the risks and benefits for the mother and infant. Yet, these increasing rates also have major economic implications for the health care system. Given the dearth of information on the cost-effectiveness related to mode of delivery, the aim of this paper was to perform an economic evaluation on the costs and short-term maternal health consequences associated with a trial of labour after one previous caesarean delivery compared with ERCD for low risk women in Ireland.Methods: Using a decision analytic model, a cost-effectiveness analysis (CEA) was performed where the measure of health gain was quality-adjusted life years (QALYs) over a six-week time horizon. A review of international literature was conducted to derive representative estimates of adverse maternal health outcomes following a trial of labour after caesarean (TOLAC) and ERCD. Delivery/procedure costs derived from primary data collection and combined both "bottom-up" and "top-down" costing estimations.Results: Maternal morbidities emerged in twice as many cases in the TOLAC group than the ERCD group. However, a TOLAC was found to be the most-effective method of delivery because it was substantially less expensive than ERCD ((sic)1,835.06 versus (sic)4,039.87 per women, respectively), and QALYs were modestly higher (0.84 versus 0.70). Our findings were supported by probabilistic sensitivity analysis.Conclusions: Clinicians need to be well informed of the benefits and risks of TOLAC among low risk women. Ideally, clinician-patient discourse would address differences in length of hospital stay and postpartum recovery time. While it is premature advocate a policy of TOLAC across maternity units, the results of the study prompt further analysis and repeat iterations, encouraging future studies to synthesis previous research and new and relevant evidence under a single comprehensive decision model.