A Competence-Based Post-Disaster Reconstruction Process: Findings from Sri Lanka

As natural disasters continue to escalate in frequency and magnitude, NGOs are faced with numerous barriers as they attempt to implement post-disaster reconstruction (PDR) projects. In many cases, a lack of competency in key areas leads to a reduction in overall project success. This paper utilizes the competency-based framework of von Meding et al. (2010) as the starting point of its inquiry. In this context, a leading NGO responsible for the implementation of reconstruction and rehabilitation in Sri Lanka following the Asian Tsunami has been investigated in depth using a causal mapping interview procedure with key project staff. The combined barriers within this organization’s PDR operations have been identified and measured and solutions articulated. The study found that within this organization key objectives were to achieve the ‘build back better’ mantra and to effectively plan interventions in advance. The primary barriers to successful reconstruction were identified as the high turnover rate of humanitarian staff and a poor level of communication and co-operation between agencies. An essential strategy employed to combat these barriers is the consideration of staff capabilities, which links us back to competence-based theory. The results are highly valuable in the context of an ongoing wider research study on competence within humanitarian organizations.

Rotational Molding Cycle Time Reduction Using a Combination of Physical Techniques

Rotational molding is a process used to manufacture hollow plastic products, and has been heralded as a molding method with great potential. Reduction of cycle times is an important issue for the rotational molding industry, addressing a significant disadvantage of the process. Previous attempts to reduce cycle times have addressed surface enhanced molds, internal pressure, internal cooling, water spray cooling, and higher oven air flow rates within the existing process. This article explores the potential benefits of these cycle time reduction techniques, and combinations of them. Recommendations on a best practice combination are made, based on experimental observations and resulting product quality. Applying the proposed molding conditions (i.e., a combination of surface-enhanced molds, higher oven flow rates, internal mold pressure, and water spray cooling), cycle time reductions of up to 70% were achieved. Such savings are very significant, inviting the rotomolding community to incorporate these techniques efficiently in an industrial setting. POLYM. ENG. SCI., 49:1846-1854, 2009. (C) 2009 Society of Plastics Engineers

Photochemical reduction of oxygen adsorbed to nanocrystalline TiO2 films: A transient absorption and oxygen scavenging study of different TiO2 preparations

Transient absorption spectroscopy (TAS) has been used to study the interfacial electron-transfer reaction between photogenerated electrons in nanocrystalline titanium dioxide (TiO2) films and molecular oxygen. TiO2 films from three different starting materials (TiO2 anatase colloidal paste and commercial anatase/rutile powders Degussa TiO2 P25 and VP TiO2 P90) have been investigated in the presence of ethanol as a hole scavenger. Separate investigations on the photocatalytic oxygen consumption by the films have also been performed with an oxygen membrane polarographic detector. Results show that a correlation exists between the electron dynamics of oxygen consumption observed by TAS and the rate of oxygen consumption through the photocatalytic process. The highest activity and the fastest oxygen reduction dynamics were observed with films fabricated from anatase TiO2 colloidal paste. The use of TAS as a tool for the prediction of the photocatalytic activities of the materials is discussed. TAS studies indicate that the rate of reduction of molecular oxygen is limited by interfacial electron-transfer kinetics rather than by the electron trapping/detrapping dynamics within the TiO2 particles.

Temporal extension of Laplacian Eigenmaps for unsupervised dimensionality reduction of time series

A novel non-linear dimensionality reduction method, called Temporal Laplacian Eigenmaps, is introduced to process efficiently time series data. In this embedded-based approach, temporal information is intrinsic to the objective function, which produces description of low dimensional spaces with time coherence between data points. Since the proposed scheme also includes bidirectional mapping between data and embedded spaces and automatic tuning of key parameters, it offers the same benefits as mapping-based approaches. Experiments on a couple of computer vision applications demonstrate the superiority of the new approach to other dimensionality reduction method in term of accuracy. Moreover, its lower computational cost and generalisation abilities suggest it is scalable to larger datasets. © 2010 IEEE.

Vocal rate as an assessment process during fallow deer contests

Two types of model propose that strategic decisions during contests are determined either by (i) a mutual-assessment process or (ii) a self-assessment process. Vocal signals are thought to convey information about the competitive abilities of individuals, the ultimate function of which is a reduction in costs associated with fighting consistent with the principle of mutual assessment. Nevertheless, the limited evidence that male ungulates engage in mutual assessment of vocal rates during dyadic contests has been questioned. Therefore, we examined the vocal rates of winners and losers during escalated dyadic contests between male fallow deer in order to further inform on this issue. Our results showed that winners and losers did not differ in vocal rate. The best model fit that accounted for individual vocal rates included a preponderance of factors related to the opponent indicating that contestants were attending to their opponent during fights. Vocal rate was, therefore, dependent on estimates of opponent quality without reference to self, supporting an 'opponent-only' rather than a mutual assessment process. © 2012 Elsevier B.V.

Automatic dimensional reduction and meshing of stiffened thin-wall structures

The creation of idealised, dimensionally reduced meshes for preliminary design and optimisation remains a time-consuming, manual task. A dimensionally reduced model is ideal for assessing design changes through modification of element properties without the need to create a new geometry or mesh. In this paper, a novel approach for automating the creation of mixed dimensional meshes is presented. The input to the process is a solid model which has been decomposed into a non-manifold assembly of smaller volumes with different meshing significance. Associativity between the original solid model and the dimensionally reduced equivalent is maintained. The approach is validated by means of a free-free modal analysis on an output mesh of a gas turbine engine component of industrial complexity. Extensions and enhancements to this work are also discussed.

Measuring oxygen reduction/evolution reactions on the nanoscale

The efficiency of fuel cells and metal-air batteries is significantly limited by the activation of oxygen reduction and evolution reactions. Despite the well-recognized role of oxygen reaction kinetics on the viability of energy technologies, the governing mechanisms remain elusive and until now have been addressable only by macroscopic studies. This lack of nanoscale understanding precludes optimization of material architecture. Here, we report direct measurements of oxygen reduction/evolution reactions and oxygen vacancy diffusion on oxygen-ion conductive solid surfaces with sub-10 nm resolution. In electrochemical strain microscopy, the biased scanning probe microscopy tip acts as a moving, electrocatalytically active probe exploring local electrochemical activity. The probe concentrates an electric field in a nanometre-scale volume of material, and bias-induced, picometre-level surface displacements provide information on local electrochemical processes. Systematic mapping of oxygen activity on bare and platinum-functionalized yttria-stabilized zirconia surfaces is demonstrated. This approach allows direct visualization of the oxygen reduction/evolution reaction activation process at the triple-phase boundary, and can be extended to a broad spectrum of oxygen-conductive and electrocatalytic materials.

One-Pot, High-Yield Synthesis of Convex Au Octahedra by H2O2 - Mediated Process In Solution Phase

A simple, non-seeding and high-yield synthesis of convex gold octahedra with size of ca. 50 nm in aqueous solution is described. The octahedral nanoparticles were systematically prepared by reduction of HAuCl4 using ascorbic acid (AA) in the presence of cetyltrimethylammonium bromide (CTAB) as the stabilizing surfactant while concentrations of Au3+ were fixed. The synthesizing process is especially different to other wet synthesis of metallic nanoparticles because it is mediated by H2O2. Mechanism of the H2O2 – mediated process will be described in details. The gold octahedra were shown to be single crystals with all 8 faces belonging to {111} family. Moreover, the single crystalline particles also showed attractive optical properties towards LSPR that should find uses as labels for microscopic imaging, materials for colorimetric biosensings, or nanosensor developments.

Effects of process parameters upon the shape memory and pseudo-elastic behaviors of laser-welded NiTi thin foil

This article discusses the effects of laser welding parameters such as power, welding speed, and focus position on the weld bead profile, microstructure, pseudo-elasticity (PE), and shape memory effect (SME) of NiTi foil with thickness of 250 um using 100W CW fiber laser. The parameter settings to produce the NiTi welds for analysis in this article were chosen from a fractional factorial design to ensure the welds produced were free of any apparent defect. The welds obtained were mainly of cellular dendrites with grain sizes ranging from 2.5 to 4.8 um at the weld centerline. A small amount of Ni3Ti was found in the welds. The onset of transformation temperatures (As and Ms) of the NiTi welds shifted to the negative side as compared to the as-received NiTi alloy. Ultimate tensile stress of the NiTi welds was comparable to the as received NiTi alloy, but a little reduction in the pseudo-elastic property was noted. Full penetration welds with desirable weld bead profiles and mechanical properties were successfully obtained in this study.

Fault Location on a Distribution Network Using a Decentralised Analysis Process

A reduction in the time required to locate and restore faults on a utility's distribution network improves the customer minutes lost (CML) measurement and hence brings direct cost savings to the operating company. The traditional approach to fault location involves fault impedance determination from high volume waveform files dispatched across a communications channel to a central location for processing and analysis. This paper examines an alternative scheme where data processing is undertaken locally within a recording instrument thus reducing the volume of data to be transmitted. Processed event fault reports may be emailed to relevant operational staff for the timely repair and restoration of the line.

Morphology and compression behaviour of biodegradable scaffolds produced by the sintering process

Porous poly(L-lactic acid) (PLA) scaffolds of 85 per cent and 90 per cent porosity are prepared using polymer sintering and porogen leaching method. Different weight fractions of 10 per cent, 30 per cent, and 50 per cent of hydroxyapatite (HA) are added to the PLA to control the acidity and degradation rate. The three-dimensional (3D) morphology and surface porosity are tested using micro-computer tomography (micro-CT), optical microscopy, and scanning electron microscopy (SEM). Results indicate that the surface porosity does not change on the addition of HA. The micro-CT examinations show a slight decrease in the pore size and increase in the wall thickness accompanied by reduced anisotropy for the scaffolds containing HA. Scanning electron micrographs show detectable interconnected pores for the scaffold with pure PLA. Addition of the HA results in agglomeration of the HA particles and reduced leaching of the porogen. Compression tests of the scaffold identify three stages in the stress-strain curve. The addition of HA results in a reduction in the modulus of the scaffold at the first stage of elastic bending of the wall, but this is reversed for the second and third stages of collapse of the wall and densification in the compression tests. In the scaffolds with 85 per cent porosity, the addition of a high percentage of HA could result in 70 per cent decrease in stiffness in the first stage, 200 per cent increase in stiffness in the second stage, and 20 per cent increase in stiffness in the third stage. The results of these tests are compared with the Gibson cellular material model that is proposed for prediction of the behaviour of cellular material under compression. The pH and molecular weight changes are tracked for the scaffolds within a period of 35 days. The addition of HA keeps the pH in the alkaline region, which results in higher rate of degradation at an early period of observation, followed by a reduced rate of degradation later in the process. The final molecular weight is higher for the scaffolds with HA than for scaffolds of pure PLA. The manufactured scaffolds offer acceptable properties in terms of the pore size range and interconnectivity of the pores and porosity for non-load-bearing bone graft substitute; however, improvement to the mixing of the phases of PLA and HA is required to achieve better integrity of the composite scaffolds. © 2008 IMechE.

Optimized process for the inclusion of carbon nanotubes in elastomers with improved thermal and mechanical properties

The effects of addition of reinforcing carbon nanotubes (CNTs) into hydrogenated nitrile-butadiene rubber (HNBR) matrix on the mechanical, dynamic viscoelastic, and permeability properties were studied in this investigation. Different techniques of incorporating nanotubes in HNBR were investigated in this research. The techniques considered were more suitable for industrial preparation of rubber composites. The nanotubes were modified with different surfactants and dispersion agents to improve the compatibility and adhesion of nanotubes on the HNBR matrix. The effects of the surface modification of the nanotubes on various properties were examined in detail. The amount of CNTs was varied from 2.5 to 10 phr in different formulations prepared to identify the optimum CNT levels. A detailed analysis was made to investigate the morphological structure and mechanical behavior at room temperature. The viscoelastic behavior of the nanotube filler elastomer was studied by dynamic mechanical thermal analysis (DMTA). Morphological analysis indicated a very good dispersion of the CNTs for a low nanotube loading of 3.5 phr. A significant improvement in the mechanical properties was observed with the addition of nanotubes. DMTA studies revealed an increase in the storage modulus and a reduction in the glass-transition temperature after the incorporation of the nanotubes. Further, the HNBR/CNT nanocomposites were subjected to permeability studies. The studies showed a significant reduction in the permeability of nitrogen gas. Copyright © 2011 Wiley Periodicals, Inc.

Novel comparison of kinetic models for the adsorption-coupled reduction of Cr(VI) using untreated date pit biomaterial

Biosorption of Cr(VI) onto date pit biomass has been investigated via kinetic studies as functions of initial Cr(VI) concentration, solution temperature and date pit particle size. Kinetic experiments indicated that chromate ions accumulate onto the date pits and then reduce to less toxic Cr(III) compounds. The López-García, Escudero and Park Cr(VI) biosorption kinetic models, which take into consideration the direct reduction, the passivation process and the follow-on decrease of the active surface area of reaction, were applied to the kinetic data. The models represented the experimental data accurately at low Cr(VI) concentration (0.480 mM) and small particle size (0.11–0.22 mm) at which the Cr(VI) was completely removed from the aqueous solution and completely reduced to Cr(III) after 420 min. Date pit biomass thus offers a green chemical process for the remediation of chromium from wastewater. This investigation will help researchers employ the adsorption-coupled reduction of Cr(VI) models and simplify their application to kinetic experimental data.

The development of internal water cooling techniques for the rotational moulding process

This paper reports the findings from internal mould cooling trials using a water spray configuration applied at various internal mould air temperatures from 120°C to 180°C for an aluminium mould. To achieve maximum benefit in terms of cycle time reduction, internal mould water cooling was used in conjunction with a combination of external forced air and water cooling. Savings in cooling times of up to 30% were achieved compared to conventional external only forced air cooling.

Efficient Marginal Likelihood Computation for Gaussian Process Regression

In a Bayesian learning setting, the posterior distribution of a predictive model arises from a trade-off between its prior distribution and the conditional likelihood of observed data. Such distribution functions usually rely on additional hyperparameters which need to be tuned in order to achieve optimum predictive performance; this operation can be efficiently performed in an Empirical Bayes fashion by maximizing the posterior marginal likelihood of the observed data. Since the score function of this optimization problem is in general characterized by the presence of local optima, it is necessary to resort to global optimization strategies, which require a large number of function evaluations. Given that the evaluation is usually computationally intensive and badly scaled with respect to the dataset size, the maximum number of observations that can be treated simultaneously is quite limited. In this paper, we consider the case of hyperparameter tuning in Gaussian process regression. A straightforward implementation of the posterior log-likelihood for this model requires O(N^3) operations for every iteration of the optimization procedure, where N is the number of examples in the input dataset. We derive a novel set of identities that allow, after an initial overhead of O(N^3), the evaluation of the score function, as well as the Jacobian and Hessian matrices, in O(N) operations. We prove how the proposed identities, that follow from the eigendecomposition of the kernel matrix, yield a reduction of several orders of magnitude in the computation time for the hyperparameter optimization problem. Notably, the proposed solution provides computational advantages even with respect to state of the art approximations that rely on sparse kernel matrices.