Application of mid-infrared spectroscopy to the prediction of maturity and sensory texture attributes of cheddar cheese

The objective of this study was to determine the potential of mid-infrared spectroscopy in conjunction with partial least squares (PLS) regression to predict various quality parameters in cheddar cheese. Cheddar cheeses (n = 24) were manufactured and stored at 8 degrees C for 12 mo. Mid-infrared spectra (640 to 4000/cm) were recorded after 4, 6, 9, and 12 mo storage. At 4, 6, and 9 mo, the water-soluble nitrogen (WSN) content of the samples was determined and the samples were also evaluated for 11 sensory texture attributes using descriptive sensory analysis. The mid-infrared spectra were subjected to a number of pretreatments, and predictive models were developed for all parameters. Age was predicted using scatter-corrected, 1st derivative spectra with a root mean square error of cross-validation (RMSECV) of 1 mo, while WSN was predicted using 1st derivative spectra (RMSECV = 2.6%). The sensory texture attributes most successfully predicted were rubbery, crumbly, chewy, and massforming. These attributes were modeled using 2nd derivative spectra and had, corresponding RMSECV values in the range of 2.5 to 4.2 on a scale of 0 to 100. It was concluded that mid-infrared spectroscopy has the potential to predict age, WSN, and several sensory texture attributes of cheddar cheese..

Conditioning of incremental variational data assimilation, with application to the Met Office system

Implementations of incremental variational data assimilation require the iterative minimization of a series of linear least-squares cost functions. The accuracy and speed with which these linear minimization problems can be solved is determined by the condition number of the Hessian of the problem. In this study, we examine how different components of the assimilation system influence this condition number. Theoretical bounds on the condition number for a single parameter system are presented and used to predict how the condition number is affected by the observation distribution and accuracy and by the specified lengthscales in the background error covariance matrix. The theoretical results are verified in the Met Office variational data assimilation system, using both pseudo-observations and real data.

State estimation using model order reduction for unstable systems

The problem of state estimation occurs in many applications of fluid flow. For example, to produce a reliable weather forecast it is essential to find the best possible estimate of the true state of the atmosphere. To find this best estimate a nonlinear least squares problem has to be solved subject to dynamical system constraints. Usually this is solved iteratively by an approximate Gauss–Newton method where the underlying discrete linear system is in general unstable. In this paper we propose a new method for deriving low order approximations to the problem based on a recently developed model reduction method for unstable systems. To illustrate the theoretical results, numerical experiments are performed using a two-dimensional Eady model – a simple model of baroclinic instability, which is the dominant mechanism for the growth of storms at mid-latitudes. It is a suitable test model to show the benefit that may be obtained by using model reduction techniques to approximate unstable systems within the state estimation problem.

Conditioning and preconditioning of the variational data assimilation problem

Numerical weather prediction (NWP) centres use numerical models of the atmospheric flow to forecast future weather states from an estimate of the current state. Variational data assimilation (VAR) is used commonly to determine an optimal state estimate that miminizes the errors between observations of the dynamical system and model predictions of the flow. The rate of convergence of the VAR scheme and the sensitivity of the solution to errors in the data are dependent on the condition number of the Hessian of the variational least-squares objective function. The traditional formulation of VAR is ill-conditioned and hence leads to slow convergence and an inaccurate solution. In practice, operational NWP centres precondition the system via a control variable transform to reduce the condition number of the Hessian. In this paper we investigate the conditioning of VAR for a single, periodic, spatially-distributed state variable. We present theoretical bounds on the condition number of the original and preconditioned Hessians and hence demonstrate the improvement produced by the preconditioning. We also investigate theoretically the effect of observation position and error variance on the preconditioned system and show that the problem becomes more ill-conditioned with increasingly dense and accurate observations. Finally, we confirm the theoretical results in an operational setting by giving experimental results from the Met Office variational system.

The gender gap in real estate sales: negotiation skill or agent selection?

This study examines differences in net selling price for residential real estate across male and female agents. A sample of 2,020 home sales transactions from Fulton County, Georgia are analyzed in a two-stage least squares, geospatial autoregressive corrected, semi-log hedonic model to test for gender and gender selection effects. Although agent gender seems to play a role in naïve models, its role becomes inconclusive as variables controlling for possible price and time on market expectations of the buyers and sellers are introduced to the models. Clear differences in real estate sales prices, time on market, and agent incomes across genders are unlikely due to differences in negotiation performance between genders or the mix of genders in a two-agent negotiation. The evidence suggests an interesting alternative to agent performance: that buyers and sellers with different reservation price and time on market expectations, such as those selling foreclosure homes, tend to select agents along gender lines.

Impact of serving method on the consumption of nutritional supplement drinks: randomised trial in older adults with cognitive impairment

Aim: To analyse the influence of serving method on compliance and consumption of nutritional supplement drinks in older adults with cognitive impairment. Background: Oral nutritional supplement drinks have positive benefits on increasing nutritional status within undernourished elderly people leading to weight gain. However, consumption of these drinks is low and therefore limits their effectiveness. Design: This study was a non blind randomised control trial where participants either consumed nutritional supplement drinks in a glass/beaker or consumed them through a straw inserted directly into the container. Method: Participants with longstanding cognitive impairment were recruited from nursing homes (n=31) and hospitals (n=14). Participants were randomised to serving method. Nursing and care staff were instructed to give the supplement drinks three times per day on alternate days over a week by the allocated serving method. The researcher weighed the amount of supplement drink remaining after consumption. Data were collected over 12 months in 2011-2012. Results: 45 people participated in this study mean age 86.7 (SD 7.5 ) years. After randomisation there was no significant difference between the baseline characteristics of the two groups. Participants randomised to consume nutritional drinks from a glass / beaker drank significantly more than those who consumed them via a straw inserted directly into the container. However, supplements allocated to be given in a glass/beaker were more frequently omitted. Conclusion: Nutritional supplement drinks should be given to people with dementia who are able to feed themselves in a glass or a beaker if staffing resources allow (NIHR CSP ref 31101).

Large-scale two-dimensional turbulence in the atmosphere

Global FGGE data are used to investigate several aspects of large-scale turbulence in the atmosphere. The approach follows that for two-dimensional, nondivergent turbulent flows which are homogeneous and isotropic on the sphere. Spectra of kinetic energy, enstrophy and available potential energy are obtained for both the stationary and transient parts of the flow. Nonlinear interaction terms and fluxes of energy and enstrophy through wavenumber space are calculated and compared with the theory. A possible method of parameterizing the interactions with unresolved scales is considered. Two rather different flow regimes are found in wavenumber space. The high-wavenumber regime is dominated by the transient components of the flow and exhibits, at least approximately, several of the conditions characterizing homogeneous and isotropic turbulence. This region of wavenumber space also displays some of the features of an enstrophy-cascading inertial subrange. The low-wavenumber region, on the other hand, is dominated by the stationary component of the flow, exhibits marked anisotropy and, in contrast to the high-wavenumber regime, displays a marked change between January and July.

Sparse model construction using coordinate descent optimization

We propose a new sparse model construction method aimed at maximizing a model’s generalisation capability for a large class of linear-in-the-parameters models. The coordinate descent optimization algorithm is employed with a modified l1- penalized least squares cost function in order to estimate a single parameter and its regularization parameter simultaneously based on the leave one out mean square error (LOOMSE). Our original contribution is to derive a closed form of optimal LOOMSE regularization parameter for a single term model, for which we show that the LOOMSE can be analytically computed without actually splitting the data set leading to a very simple parameter estimation method. We then integrate the new results within the coordinate descent optimization algorithm to update model parameters one at the time for linear-in-the-parameters models. Consequently a fully automated procedure is achieved without resort to any other validation data set for iterative model evaluation. Illustrative examples are included to demonstrate the effectiveness of the new approaches.

Impact of geographical region on urinary metabolomic and plasma fatty acid profiles in subjects with the metabolic syndrome across Europe: the LIPGENE study

The application of metabolomics in multi-centre studies is increasing. The aim of the present study was to assess the effects of geographical location on the metabolic profiles of individuals with the metabolic syndrome. Blood and urine samples were collected from 219 adults from seven European centres participating in the LIPGENE project (Diet, genomics and the metabolic syndrome: an integrated nutrition, agro-food, social and economic analysis). Nutrient intakes, BMI, waist:hip ratio, blood pressure, and plasma glucose, insulin and blood lipid levels were assessed. Plasma fatty acid levels and urine were assessed using a metabolomic technique. The separation of three European geographical groups (NW, northwest; NE, northeast; SW, southwest) was identified using partial least-squares discriminant analysis models for urine (R 2 X: 0•33, Q 2: 0•39) and plasma fatty acid (R 2 X: 0•32, Q 2: 0•60) data. The NW group was characterised by higher levels of urinary hippurate and N-methylnicotinate. The NE group was characterised by higher levels of urinary creatine and citrate and plasma EPA (20 : 5 n-3). The SW group was characterised by higher levels of urinary trimethylamine oxide and lower levels of plasma EPA. The indicators of metabolic health appeared to be consistent across the groups. The SW group had higher intakes of total fat and MUFA compared with both the NW and NE groups (P≤ 0•001). The NE group had higher intakes of fibre and n-3 and n-6 fatty acids compared with both the NW and SW groups (all P< 0•001). It is likely that differences in dietary intakes contributed to the separation of the three groups. Evaluation of geographical factors including diet should be considered in the interpretation of metabolomic data from multi-centre studies.

Access and excess in The Texas Chain Saw Massacre

Much is made of the viscerally disturbing qualities embedded in The Texas Chain Saw Massacre - human bodies are traumatised, mutilated and distorted – and the way these are matched by close and often intense access to the performers involved. Graphic violence focused on the body specifically indicates the film as a key contemporary horror text. Yet, for all this closeness to the performers, it soon becomes clear in undertaking close-analysis of the film that access to them is equally characterised by extreme distance, both spatially and cognitively. The issue of distance is particularly striking, not least because of its ramifications on engagement, which throws up various aesthetic and methodological questions concerning performers’ expressive authenticity. This article considers the lack of access to performance in The Texas Chain Saw Massacre, paying particular attention to how this fits in with contemporaneous presentations of performance more generally, as seen in films such as Junior Bonner (Sam Peckinpah, 1972). As part of this investigation I consider the affect of such a severe disruption to access on engagement with, and discussion of, performance. At the heart of this investigation lie methodological considerations of the place of performance analysis in the post-studio period. How can we perceive anything of a character’s interior life, and therefore engage with performers who we fundamentally lack access to? Does such an apparently significant difference in the way performers and their embodiment is treated mean that they can even be thought of as delivering a performance?

Brief communication: a proposed method for the assessment of pubertal stage in human skeletal remains using cervical vertebrae maturation.

The assessment of age-at-death in non-adult skeletal remains is under constant review. However, in many past societies an individual's physical maturation may have been more important in social terms than their exact age, particularly during the period of adolescence. In a recent article (Shapland and Lewis: Am J Phys Anthropol 151 (2013) 302–310) highlighted a set of dental and skeletal indicators that may be useful in mapping the progress of the pubertal growth spurt. This article presents a further skeletal indicator of adolescent development commonly used by modern clinicians: cervical vertebrae maturation (CVM). This method is applied to a collection of 594 adolescents from the medieval cemetery of St. Mary Spital, London. Analysis reveals a potential delay in ages of attainment of the later CVM stages compared with modern adolescents, presumably reflecting negative environmental conditions for growth and development. The data gathered on CVM is compared to other skeletal indicators of pubertal maturity and long bone growth from this site to ascertain the usefulness of this method on archaeological collections.

The effect of phase-correlated returns and spatial smoothing on the accuracy of radar refractivity retrievals

Radar refractivity retrievals have the potential to accurately capture near-surface humidity fields from the phase change of ground clutter returns. In practice, phase changes are very noisy and the required smoothing will diminish large radial phase change gradients, leading to severe underestimates of large refractivity changes (ΔN). To mitigate this, the mean refractivity change over the field (ΔNfield) must be subtracted prior to smoothing. However, both observations and simulations indicate that highly correlated returns (e.g., when single targets straddle neighboring gates) result in underestimates of ΔNfield when pulse-pair processing is used. This may contribute to reported differences of up to 30 N units between surface observations and retrievals. This effect can be avoided if ΔNfield is estimated using a linear least squares fit to azimuthally averaged phase changes. Nevertheless, subsequent smoothing of the phase changes will still tend to diminish the all-important spatial perturbations in retrieved refractivity relative to ΔNfield; an iterative estimation approach may be required. The uncertainty in the target location within the range gate leads to additional phase noise proportional to ΔN, pulse length, and radar frequency. The use of short pulse lengths is recommended, not only to reduce this noise but to increase both the maximum detectable refractivity change and the number of suitable targets. Retrievals of refractivity fields must allow for large ΔN relative to an earlier reference field. This should be achievable for short pulses at S band, but phase noise due to target motion may prevent this at C band, while at X band even the retrieval of ΔN over shorter periods may at times be impossible.

An investigation into the impact of using various techniques to estimate Arctic surface air temperature anomalies

Time series of global and regional mean Surface Air Temperature (SAT) anomalies are a common metric used to estimate recent climate change. Various techniques can be used to create these time series from meteorological station data. The degree of difference arising from using five different techniques, based on existing temperature anomaly dataset techniques, to estimate Arctic SAT anomalies over land and sea ice were investigated using reanalysis data as a testbed. Techniques which interpolated anomalies were found to result in smaller errors than non-interpolating techniques relative to the reanalysis reference. Kriging techniques provided the smallest errors in estimates of Arctic anomalies and Simple Kriging was often the best kriging method in this study, especially over sea ice. A linear interpolation technique had, on average, Root Mean Square Errors (RMSEs) up to 0.55 K larger than the two kriging techniques tested. Non-interpolating techniques provided the least representative anomaly estimates. Nonetheless, they serve as useful checks for confirming whether estimates from interpolating techniques are reasonable. The interaction of meteorological station coverage with estimation techniques between 1850 and 2011 was simulated using an ensemble dataset comprising repeated individual years (1979-2011). All techniques were found to have larger RMSEs for earlier station coverages. This supports calls for increased data sharing and data rescue, especially in sparsely observed regions such as the Arctic.

The impact of social and relational contexts on innovation transfer in foreign subsidiaries

It is widely acknowledged that innovation is one of the pillars of multinational enterprises (MNEs) and that technological knowledge from different host locations is a key factor to the MNEs’ competitive advantages development. Concerning these assumptions, in this paper we aim to understand how the social and the relational contexts affect the conventional and reverse transfer of innovation from MNEs’ subsidiaries hosted in emerging markets. We analyzed the social context through the institutional profile (CIP) level and the relational context through trust and integration levels utilizing a survey sent to 172 foreign subsidiaries located in Brazil, as well as secondary data. Through an ordinary least squares regression (OLS) analysis we found that the relational context affects the conventional and reverse innovation transfer in subsidiaries hosted in emerging markets. We however did not find support for the social context effect.

The CURE scale: a multidimensional measure of service recovery strategy

Purpose – This paper aims to address the gaps in service recovery strategy assessment. An effective service recovery strategy that prevents customer defection after a service failure is a powerful managerial instrument. The literature to date does not present a comprehensive assessment of service recovery strategy. It also lacks a clear picture of the service recovery actions at managers’ disposal in case of failure and the effectiveness of individual strategies on customer outcomes. Design/methodology/approach – Based on service recovery theory, this paper proposes a formative index of service recovery strategy and empirically validates this measure using partial least-squares path modelling with survey data from 437 complainants in the telecommunications industry in Egypt. Findings – The CURE scale (CUstomer REcovery scale) presents evidence of reliability as well as convergent, discriminant and nomological validity. Findings also reveal that problem-solving, speed of response, effort, facilitation and apology are the actions that have an impact on the customer’s satisfaction with service recovery. Practical implications – This new formative index is of potential value in investigating links between strategy and customer evaluations of service by helping managers identify which actions contribute most to changes in the overall service recovery strategy as well as satisfaction with service recovery. Ultimately, the CURE scale facilitates the long-term planning of effective complaint management. Originality/value – This is the first study in the service marketing literature to propose a comprehensive assessment of service recovery strategy and clearly identify the service recovery actions that contribute most to changes in the overall service recovery strategy.