A multi-organisational approach for disaster preparedness and response:the use of optimisation and GIS for facility location, stock pre-positioning, resource allocation and relief distribution

From 1992 to 2012 4.4 billion people were affected by disasters with almost 2 trillion USD in damages and 1.3 million people killed worldwide. The increasing threat of disasters stresses the need to provide solutions for the challenges faced by disaster managers, such as the logistical deployment of resources required to provide relief to victims. The location of emergency facilities, stock prepositioning, evacuation, inventory management, resource allocation, and relief distribution have been identified to directly impact the relief provided to victims during the disaster. Managing appropriately these factors is critical to reduce suffering. Disaster management commonly attracts several organisations working alongside each other and sharing resources to cope with the emergency. Coordinating these agencies is a complex task but there is little research considering multiple organisations, and none actually optimising the number of actors required to avoid shortages and convergence. The aim of the this research is to develop a system for disaster management based on a combination of optimisation techniques and geographical information systems (GIS) to aid multi-organisational decision-making. An integrated decision system was created comprising a cartographic model implemented in GIS to discard floodable facilities, combined with two models focused on optimising the decisions regarding location of emergency facilities, stock prepositioning, the allocation of resources and relief distribution, along with the number of actors required to perform these activities. Three in-depth case studies in Mexico were studied gathering information from different organisations. The cartographic model proved to reduce the risk to select unsuitable facilities. The preparedness and response models showed the capacity to optimise the decisions and the number of organisations required for logistical activities, pointing towards an excess of actors involved in all cases. The system as a whole demonstrated its capacity to provide integrated support for disaster preparedness and response, along with the existence of room for improvement for Mexican organisations in flood management.

Estimating the SCAN*PRO model of store sales: HB, FM or just OLS?

In this paper we investigate whether consideration of store-level heterogeneity in marketing mix effects improves the accuracy of the marketing mix elasticities, fit, and forecasting accuracy of the widely-applied SCAN*PRO model of store sales. Models with continuous and discrete representations of heterogeneity, estimated using hierarchical Bayes (HB) and finite mixture (FM) techniques, respectively, are empirically compared to the original model, which does not account for store-level heterogeneity in marketing mix effects, and is estimated using ordinary least squares (OLS). The empirical comparisons are conducted in two contexts: Dutch store-level scanner data for the shampoo product category, and an extensive simulation experiment. The simulation investigates how between- and within-segment variance in marketing mix effects, error variance, the number of weeks of data, and the number of stores impact the accuracy of marketing mix elasticities, model fit, and forecasting accuracy. Contrary to expectations, accommodating store-level heterogeneity does not improve the accuracy of marketing mix elasticities relative to the homogeneous SCAN*PRO model, suggesting that little may be lost by employing the original homogeneous SCAN*PRO model estimated using ordinary least squares. Improvements in fit and forecasting accuracy are also fairly modest. We pursue an explanation for this result since research in other contexts has shown clear advantages from assuming some type of heterogeneity in market response models. In an Afterthought section, we comment on the controversial nature of our result, distinguishing factors inherent to household-level data and associated models vs. general store-level data and associated models vs. the unique SCAN*PRO model specification.

Optimal design for correlated processes with input-dependent noise

Optimal design for parameter estimation in Gaussian process regression models with input-dependent noise is examined. The motivation stems from the area of computer experiments, where computationally demanding simulators are approximated using Gaussian process emulators to act as statistical surrogates. In the case of stochastic simulators, which produce a random output for a given set of model inputs, repeated evaluations are useful, supporting the use of replicate observations in the experimental design. The findings are also applicable to the wider context of experimental design for Gaussian process regression and kriging. Designs are proposed with the aim of minimising the variance of the Gaussian process parameter estimates. A heteroscedastic Gaussian process model is presented which allows for an experimental design technique based on an extension of Fisher information to heteroscedastic models. It is empirically shown that the error of the approximation of the parameter variance by the inverse of the Fisher information is reduced as the number of replicated points is increased. Through a series of simulation experiments on both synthetic data and a systems biology stochastic simulator, optimal designs with replicate observations are shown to outperform space-filling designs both with and without replicate observations. Guidance is provided on best practice for optimal experimental design for stochastic response models. © 2013 Elsevier Inc. All rights reserved.

A comparison of sales response predictions from demand models applied to store-level versus panel data

In order to generate sales promotion response predictions, marketing analysts estimate demand models using either disaggregated (consumer-level) or aggregated (store-level) scanner data. Comparison of predictions from these demand models is complicated by the fact that models may accommodate different forms of consumer heterogeneity depending on the level of data aggregation. This study shows via simulation that demand models with various heterogeneity specifications do not produce more accurate sales response predictions than a homogeneous demand model applied to store-level data, with one major exception: a random coefficients model designed to capture within-store heterogeneity using store-level data produced significantly more accurate sales response predictions (as well as better fit) compared to other model specifications. An empirical application to the paper towel product category adds additional insights. This article has supplementary material online.

HRM in context:applicability of HRM models in India

Using the core aspects of five main models of human resource management (HRM), this article investigates the dominant HRM practices in the Indian manufacturing sector. The evaluation is conducted in the context of the recently liberalized economic environment. In response to ever-increasing levels of globalization of business, the article initially highlights the need for more cross-national comparative HRM research. Then it briefly analyzes the five models of HRM (namely, the `Matching model'; the `Harvard model'; the `Contextual model'; the `5-P model'; and the `European model') and identifies the main research questions emerging from these that could be used to reveal and highlight the HRM practices in different national/regional settings. The findings of the research are based on a questionnaire survey of 137 large Indian firms and 24 in-depth interviews in as many firms. The examination not only helped to present the scenario of HRM practices in the Indian context but also the logic dictating the presence of such practices. The article contributes to the fields of cross-national HRM and industrial relations research. It also has key messages for policy makers and opens avenues for further research.

Updating finite element models using measured vibration data

The modelling of mechanical structures using finite element analysis has become an indispensable stage in the design of new components and products. Once the theoretical design has been optimised a prototype may be constructed and tested. What can the engineer do if the measured and theoretically predicted vibration characteristics of the structure are significantly different? This thesis considers the problems of changing the parameters of the finite element model to improve the correlation between a physical structure and its mathematical model. Two new methods are introduced to perform the systematic parameter updating. The first uses the measured modal model to derive the parameter values with the minimum variance. The user must provide estimates for the variance of the theoretical parameter values and the measured data. Previous authors using similar methods have assumed that the estimated parameters and measured modal properties are statistically independent. This will generally be the case during the first iteration but will not be the case subsequently. The second method updates the parameters directly from the frequency response functions. The order of the finite element model of the structure is reduced as a function of the unknown parameters. A method related to a weighted equation error algorithm is used to update the parameters. After each iteration the weighting changes so that on convergence the output error is minimised. The suggested methods are extensively tested using simulated data. An H frame is then used to demonstrate the algorithms on a physical structure.

Neuronal convergence in early contrast vision: binocular summation is followed by response nonlinearity and area summation

We assessed summation of contrast across eyes and area at detection threshold ( C t). Stimuli were sine-wave gratings (2.5 c/deg) spatially modulated by cosine- and anticosine-phase raised plaids (0.5 c/deg components oriented at ±45°). When presented dichoptically the signal regions were interdigitated across eyes but produced a smooth continuous grating following their linear binocular sum. The average summation ratio ( C t1/([ C t1+2]) for this stimulus pair was 1.64 (4.3 dB). This was only slightly less than the binocular summation found for the same patch type presented to both eyes, and the area summation found for the two different patch types presented to the same eye. We considered 192 model architectures containing each of the following four elements in all possible orders: (i) linear summation or a MAX operator across eyes, (ii) linear summation or a MAX operator across area, (iii) linear or accelerating contrast transduction, and (iv) additive Gaussian, stochastic noise. Formal equivalences reduced this to 62 different models. The most successful four-element model was: linear summation across eyes followed by nonlinear contrast transduction, linear summation across area, and late noise. Model performance was enhanced when additional nonlinearities were placed before binocular summation and after area summation. The implications for models of probability summation and uncertainty are discussed.

Visual evoked electrical and magnetic response to half-field stimulation using pattern reversal stimulation

The visual evoked magnetic response to half-field stimulation using pattern reversal was studied using a d.c. SQUID coupled to a second order gradiometer. The main component of the magnetic response consisted of a positive wave at around 100 ms (P100M). At the time this component was present the response to half-field stimulation consisted of an outgoing magnetic field contralateral and extending to the midline. When the left half field was stimulated the outgoing field was over the posterior right visual cortex and when the right half field was stimulated it was over the left anterior visual cortex. These findings would correctly identify a source located in the contralateral visual cortex. The orientation of the dipoles was not that previously assumed to explain the paradoxical lateralization of the visual evoked potential. The results are discussed in terms of both electrical and magnetic models of the calcarine fissure. © 1992.

Visual evoked electrical and magnetic response to half-field stimulation using pattern reversal stimulation

The visual evoked magnetic response to half-field stimulation using pattern reversal was studied using a dc-SQUID coupled to a second-order gradiometer. The main component of the magnetic response consisted of a positive wave at around 100ms (P100M). At the same time this component was present the reponse to half-field stimulation consisted of an outgoing field contralateral and extending to the midline. When the left half-field was stimulates the outgoing field was over the posterior right visual cortex and when the right half field was stimulated it was over the left anterior visual cortex. These findings would correltly identify a source located in the contralateral visual cortex. The orientation of the dipoles was not that previously assumed to explain the paradoxical lateralization of the visual evoked potential. The results are discussed in terms of both electrical and magnetic models of the calcarine fissure.

Models of gas-liquid solubilities

A recent method for phase equilibria, the AGAPE method, has been used to predict activity coefficients and excess Gibbs energy for binary mixtures with good accuracy. The theory, based on a generalised London potential (GLP), accounts for intermolecular attractive forces. Unlike existing prediction methods, for example UNIFAC, the AGAPE method uses only information derived from accessible experimental data and molecular information for pure components. Presently, the AGAPE method has some limitations, namely that the mixtures must consist of small, non-polar compounds with no hydrogen bonding, at low moderate pressures and at conditions below the critical conditions of the components. Distinction between vapour-liquid equilibria and gas-liquid solubility is rather arbitrary and it seems reasonable to extend these ideas to solubility. The AGAPE model uses a molecular lattice-based mixing rule. By judicious use of computer programs a methodology was created to examine a body of experimental gas-liquid solubility data for gases such as carbon dioxide, propane, n-butane or sulphur hexafluoride which all have critical temperatures a little above 298 K dissolved in benzene, cyclo-hexane and methanol. Within this methodology the value of the GLP as an ab initio combining rule for such solutes in very dilute solutions in a variety of liquids has been tested. Using the GLP as a mixing rule involves the computation of rotationally averaged interactions between the constituent atoms, and new calculations have had to be made to discover the magnitude of the unlike pair interactions. These numbers have been seen as significant in their own right in the context of the behaviour of infinitely-dilute solutions. A method for extending this treatment to "permanent" gases has also been developed. The findings from the GLP method and from the more general AGAPE approach have been examined in the context of other models for gas-liquid solubility, both "classical" and contemporary, in particular those derived from equations-of-state methods and from reference solvent methods.

Have the GIPSI settled down? Breaks and multivariate stochastic volatility models for, and not against, the European financial integration

We investigate the integration of the European peripheral financial markets with Germany, France, and the UK using a combination of tests for structural breaks and return correlations derived from several multivariate stochastic volatility models. Our findings suggest that financial integration intensified in anticipation of the Euro, further strengthened by the EMU inception, and amplified in response to the 2007/2008 financial crisis. Hence, no evidence is found of decoupling of the equity markets in more troubled European countries from the core. Interestingly, the UK, despite staying outside the EMU, is not worse integrated with the GIPSI than Germany or France. © 2013 Elsevier B.V.

Effects of oxidative stress and neuroprotection in apoptosis in neuronal cell models

The PC12 and SH-SY5Y cell models have been proposed as potentially realistic models to investigate neuronal cell toxicity. The effects of oxidative stress (OS) caused by both H2O2 and Aβ on both cell models were assessed by several methods. Cell toxicity was quantitated by measuring cell viability using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium (MTT) viability assay, an indicator of the integrity of the electron transfer chain (ETC), and cell morphology by fluorescence and video microscopy, both of which showed OS to cause decreased viability and changes in morphology. Levels of intracellular peroxide production, and changes in glutathione and carbonyl levels were also assessed, which showed OS to cause increases in intracellular peroxide production, glutathione and carbonyl levels. Differentiated SH-SY5y cells were also employed and observed to exhibit the greatest sensitivity to toxicity. The neurotrophic factor, nerve growth factor (NGF) was shown to cause protection against OS. Cells pre-treated with NGF showed higher viability after OS, generally less apoptotic morphology, recorded less apoptotic nucleiods, generally lower levels of intracellular peroxides and changes in gene expression. The neutrophic factor, brain derived growth factor (BDNF) and ascorbic acid (AA) were also investigated. BDNF showed no specific neuroprotection, however the preliminary data does warrant further investigation. AA showed a 'janus face' showing either anti-oxidant action and neuroprotection or pro-oxidant action depending on the situation. Results showed that the toxic effects of compounds such as Aβ and H2O2 are cell type dependent, and that OS alters glutathione metabolism in neuronal cells. Following toxic insult, glutathione levels are depleted to low levels. It is herein suggested that this lowering triggers an adaptive response causing alterations in glutathione metabolism as assessed by evaluation of glutathione mRNA biosynthetic enzyme expression and the subsequent increase in glutathione peroxidase (GPX) levels.

Drug action on anxiety models with special reference to serotonergic mechanisms

A study has been made of drugs acting at 5-HT receptors on animal models of anxiety. An elevated X-maze was used as a model of anxiety for rats and the actions of various ligands for the 5-HT receptor, and its subtypes, were examined in this model. 5-HT agonists, with varying affinities for the 5-HT receptor subtypes, were demonstrated to have anxiogenic-like activity. The 5-HT2 receptor antagonists ritanserin and ketanserin exhibited an anxiolytic-like profile. The new putatuve anxiolytics ipsapirone and buspirone, which are believed to be selective for 5-HT1 receptors, were also examined. The former had an anxiolytic profile whilst the latter was without effect. Antagonism studies showed the anxiogenic response to 8-hydroxy-2-(Di-n-propylamino)tetralin (8-OH-DPAT) to be antagonised by ipsapirone, pindolol, alprenolol and para-chlorophenylalanine, but not by diazepam, ritanserin, metoprolol, ICI118,551 or buspirone. To confirm some of the results obtained in the elevated X-maze the Social Interaction Test of anxiety was used. Results in this test mirrored the effects seen with the 5-HT agonists, ipsapirone and pindolol, whilst the 5-HT2 receptor antagonists were without effect. Studies using operant conflict models of anxiety produced marginal and varying results which appear to be in agreement with recent criticisms of such models. Finally, lesions of the dorsal raphe nucleus (DRN) were performed in order to investigate the mechanisms involved in the production of the anxiogenic response to 8-OH-DPAT. Overall the results lend support to the involvement of 5-HT, and more precisely 5-HT1, receptors in the manifestation of anxiety in such animal models.

The chromatic visual evoked response as an indication of visual development

In an endeavour to provide further insight into the maturation of the cortical visual system in human infants, chromatic transient pattern reversal visual evoked potentials to red/green stimuli, were studied in a group of normal full term infants between the ages of 1 and 14 weeks post term in both cross sectional and longitudinal studies. In order to produce stimuli in which luminance cues had been eliminated with an aim to eliciting a chromatic response, preliminary studies of isoluminance determination in adults and infants were undertaken using behavioural and electrophysiological techniques. The results showed close similarity between the isoluminant ratio for adults and infants and all values were close to photometric isoluminance. Pattern reversal VEPs were recorded to stimuli of a range of red/green luminance ratios and an achromatic checkerboard. No transient VEP could be elicited with an isoluminant chromatic pattern reversal stimulus from any infant less than 7 weeks post term and similarly, all infants more than 7 weeks post term showed clear chromatic VEPs. The chromatic response first appeared at that age as a major positive component (P1) of long latency. This was delayed and reduced in comparison to the achromatic response. As the infant grew older, the latency of the P1 component decreased with the appearance of N1 and N by the 10th week post term. This finding was consistent throughout all infants assessed. In a behavioural study, no infant less than 7 weeks post term demonstrated clear discrimination of the chromatic stimulus, while those infants older than 7 weeks could do so. These findings are reviewed with respect to current neural models of visual development.

Hypoxia-inducible factor (HIF) network:insights from mathematical models

Oxygen is a crucial molecule for cellular function. When oxygen demand exceeds supply, the oxygen sensing pathway centred on the hypoxia inducible factor (HIF) is switched on and promotes adaptation to hypoxia by up-regulating genes involved in angiogenesis, erythropoiesis and glycolysis. The regulation of HIF is tightly modulated through intricate regulatory mechanisms. Notably, its protein stability is controlled by the oxygen sensing prolyl hydroxylase domain (PHD) enzymes and its transcriptional activity is controlled by the asparaginyl hydroxylase FIH (factor inhibiting HIF-1).To probe the complexity of hypoxia-induced HIF signalling, efforts in mathematical modelling of the pathway have been underway for around a decade. In this paper, we review the existing mathematical models developed to describe and explain specific behaviours of the HIF pathway and how they have contributed new insights into our understanding of the network. Topics for modelling included the switch-like response to decreased oxygen gradient, the role of micro environmental factors, the regulation by FIH and the temporal dynamics of the HIF response. We will also discuss the technical aspects, extent and limitations of these models. Recently, HIF pathway has been implicated in other disease contexts such as hypoxic inflammation and cancer through crosstalking with pathways like NF?B and mTOR. We will examine how future mathematical modelling and simulation of interlinked networks can aid in understanding HIF behaviour in complex pathophysiological situations. Ultimately this would allow the identification of new pharmacological targets in different disease settings.