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Biological samples of lipids and metabolites degrade after extensive years in −80 °C storage. We aimed to determine if associated multivariate models are also impacted. Prior TOFI_Asia metabolomics studies from our laboratory established multivariate models of metabolic risks associated with ethnic diversity. Therefore, to compare multivariate modelling degradation after years of −80 °C storage, we selected a subset of aged (≥5-years) plasma samples from the TOFI_Asia study to re-analyze via untargeted LC-MS metabolomics. Samples from European Caucasian (n = 28) and Asian Chinese (n = 28) participants were evaluated for ethnic discrimination by partial least squares discriminative analysis (PLS–DA) of lipids and polar metabolites. Both showed a strong discernment between participants ethnicity by features, before (Initial) and after (Aged) 5-years of −80 °C storage. With receiver operator characteristic curves, sparse PLS–DA derived confusion matrix and prediction error rates, a considerable reduction in model integrity was apparent with the Aged polar metabolite model relative to Initial modelling. Ethnicity modelling with lipids maintained predictive integrity in Aged plasma samples, while equivalent polar metabolite models reduced in integrity. Our results indicate that researchers re-evaluating samples for multivariate modelling should consider time at −80 °C when producing predictive metrics from polar metabolites, more so than lipids. [ABSTRACT FROM AUTHOR]

Contaminated air is unhealthy for people to breathe and live in. To maintain the sustainability of clean air, air pollution must be analyzed and controlled, especially after unhealthy events. To do so, the characteristics of unhealthy events, namely intensity, duration, and severity are studied using multivariate modeling. In this study, the vine copula approach is selected to study the characteristics data. Vine copula is chosen here because it is more potent than the standard multivariate distributions, and multivariate copulas, especially in modeling the tails related to extreme events. Here, all nine different vine copulas are analyzed and compared based on model fitting and the comparison of models. In model fitting, the best model obtained is Rv123-Joint-MLE, a model with a root nodes sequence of 123, and optimized using the joint maximum likelihood. The components for the best model are the Tawn type 1 and Rotated Tawn type 1 180 degrees representing the pair copulas of (intensity, duration), and (intensity, severity), respectively, with the Survival Gumbel for the conditional pair copula of (duration, severity; intensity). Based on the best model, the tri-variate dependence structure of the intensity, duration, and severity relationship is positively correlated, skewed, and follows an asymmetric distribution. This indicates that the characteristic's, including intensity, duration, and severity, tend to increase together. Using comparison tests, the best model is significantly different from others, whereas only two models are quite similar. This shows that the best model is well-fitted, compared to most models. Overall, this paper highlights the capability of vine copula in modeling the asymmetric dependence structure of air pollution characteristics, where the obtained model has a better potential to become a tool to assess the risks of extreme events in future work. [ABSTRACT FROM AUTHOR]

Directional sensitivity, the more efficient response of cerebral autoregulation to increases, compared to decreases, in mean arterial pressure (MAP), has been demonstrated with repeated squat-stand maneuvers (SSM). In 43 healthy subjects (26 male, 23.1 ± 4.2 years old), five min. recordings of cerebral blood velocity (bilateral Doppler ultrasound), MAP (Finometer), end-tidal CO2 (capnograph), and heart rate (ECG) were obtained during sitting (SIT), standing (STA) and SSM. A new analytical procedure, based on autoregressive-moving average models, allowed distinct estimates of the autoregulation index (ARI) by separating the MAP signal into its positive (MAP+D) and negative (MAP−D) derivatives. ARI+D was higher than ARI−D (p < 0.0001), SIT: 5.61 ± 1.58 vs 4.31 ± 2.16; STA: 5.70 ± 1.24 vs 4.63 ± 1.92; SSM: 4.70 ± 1.11 vs 3.31 ± 1.53, but the difference ARI+D–ARI−D was not influenced by the condition. A bootstrap procedure determined the critical number of subjects needed to identify a significant difference between ARI+D and ARI−D, corresponding to 24, 37 and 38 subjects, respectively, for SSM, STA and SIT. Further investigations are needed on the influences of sex, aging and other phenotypical characteristics on the phenomenon of directional sensitivity of dynamic autoregulation. [ABSTRACT FROM AUTHOR]

Vibration analysis, a vital tool in the scheduling of equipment for maintenance is used to assess the useful life of equipment for allocation of resources to mitigate downtime. Compared to previous approaches of univariate prediction, this study presents a more practical model by employing vibration analysis data as a multivariate problem in predicting the remaining useful life (RUL) of an equipment. Applying the model, Multiple Linear Regression (MLR) and Linear Programming (LP) were explored to determine the deterioration rate and the RUL of the equipment. The results showed that the MLR had a high predictive accuracy on the data sets. Furthermore, a p-value of 1.546e-06 and Multiple R-squared value of 0.8215 were obtained showing that the MLR appears to be a good prediction model. From the solution of the LP formulation, the RUL of the equipment was 181 days. These results closely matched the historical data of the equipment which implied this model could be used for planning of maintenance activity for this equipment and any similar equipment. [ABSTRACT FROM AUTHOR]

Road traffic casualties represent a hidden global epidemic, demanding evidence‐based interventions. This paper demonstrates a network lattice approach for identifying road segments of particular concern, based on a case study of a major city (Leeds, UK), in which 5862 crashes of different severities were recorded over an 8‐year period (2011–2018). We consider a family of Bayesian hierarchical models that include spatially structured and unstructured random effects to capture the dependencies between the severity levels. Results highlight roads that are more prone to collisions, relative to estimated traffic volumes, in the north‐west and south of city centre. We analyse the modifiable areal unit problem (MAUP), proposing a novel procedure to investigate the presence of MAUP on a network lattice. We conclude that our methods enable a reliable estimation of road safety levels to help identify 'hotspots' on the road network and to inform effective local interventions. [ABSTRACT FROM AUTHOR]

Aims and Objectives: This study aims to examine the association between person, environment, health and illness factors, pain care and the patient experience in the emergency department, guided by symptom management theory. Background: Current outcome measures of pain care in the emergency department focus on process measures such as the time taken to deliver analgesic medication. Patient‐reported outcomes of pain care are rare in emergency department literature and predominantly focus on patient satisfaction. Measuring overall patient experience is common, with extensive surveys undertaken in the United Kingdom, United States of America and Australia; however, these are not used as an outcome of pain care. Design: Prospective cohort study. Methods: One hundred and ninety patients arriving at a large, inner‐city adults‐only emergency department in moderate to severe pain were recruited to answer a modified version of the emergency department patient experience of care survey. Results: Fifteen factors were identified as influencing the patient experience of care when presenting in pain. These influences of patient experience included the emergency department environment, time to first analgesic medication and the provision of analgesic medication. Conclusions: In addition to pain care factors, there is a significant association between the emergency department environment—especially workload, throughput and patient placement—and the experience of patients who present in pain to the emergency department. Relevance to Clinical Practice: This study demonstrated an association between time to first analgesic medication and the patient experience of care. Providing timely care, including pain care, in emergency departments is difficult, but necessary to improve the patient experience of care. [ABSTRACT FROM AUTHOR]

Massive Open Online Courses, universally labelled as MOOCs, become more and more relevant in the era of digitalization of higher education. The availability of free education resources without access restrictions for a plenty of potential users has changed the learning market in a way unthinkable only few decades ago. This form of web-based education allows to track all the actions of the students, thus providing an information base to understand how students' behaviour can influence their performance. The paper proposes a structural equation model in the framework of the component-based approach to measure which are the main factors affecting students' performance (Partial Least Squares Path Modelling). The novelty of the approach is the simultaneous analysis of more than one factor that exerts an impact on the performance. The analysis is carried out on the log data of a course available on the edX MOOCs platform named FedericaX. [ABSTRACT FROM AUTHOR]

In the field of mineral resources extraction, one main challenge is to meet production targets in terms of geometallurgical properties. These properties influence the processing of the ore and are often represented in resource modeling by coregionalized variables with a complex relationship between them. Valuable data are available about geometalurgical properties and their interaction with the beneficiation process given sensor technologies during production monitoring. The aim of this research is to update resource models as new observations become available. A popular method for updating is the ensemble Kalman filter. This method relies on Gaussian assumptions and uses a set of realizations of the simulated models to derive sample covariances that can propagate the uncertainty between real observations and simulated ones. Hence, the relationship among variables has a compositional nature, such that updating these models while keeping the compositional constraints is a practical requirement in order to improve the accuracy of the updated models. This paper presents an updating framework for compositional data based on ensemble Kalman filter which allows us to work with compositions that are transformed into a multivariate Gaussian space by log-ratio transformation and flow anamorphosis. This flow anamorphosis, transforms the distribution of the variables to joint normality while reasonably keeping the dependencies between components. Furthermore, the positiveness of those variables, after updating the simulated models, is satisfied. The method is implemented in a bauxite deposit, demonstrating the performance of the proposed approach. [ABSTRACT FROM AUTHOR]

Aim and Objective: To examine the factors associated with time to first analgesic medication in the emergency department. Background: Pain is the most common symptom presenting to the emergency department, and the time taken to deliver analgesic medication is a common outcome measure. Factors associated with time to first analgesic medication are likely to be multifaceted, but currently poorly described. Design: Retrospective cohort study. Methods: Cox proportional hazards regression modelling was undertaken to evaluate the associations between person, environment, health and illness variables within Symptom Management Theory and time to first analgesic medication in a sample of adult patients presenting with moderate‐to‐severe pain to an emergency department over twelve months. This study was completed in line with the STROBE statement. Results: 383 patients were included in the study, 290 (75.92%) of these patients received an analgesic medication in a median time of 45 minutes (interquartile range, 70 minutes). A model containing nine explanatory variables associated with time to first analgesic medication was identified. These nine variables (employment status, discharge location, triage score, Charlson score, arrival pain score, socio‐economic status, first location, daily total treatment time and patient time to be seen) represent all of the domains of the Symptom Management Theory. Conclusions: Person, environment, health and illness factors are associated with the time taken to deliver analgesic medication to those in pain in the emergency department. This study demonstrates the complexity of factors associated with pain care and the applicability of Symptom Management Theory to pain care in the emergency department. Relevance to Clinical Practice: Identifying a model of factors that are associated with the time in which the most common symptom presenting to the emergency department is treated allows for targeted interventions to groups likely to receive poor care and a framework for its evaluation. [ABSTRACT FROM AUTHOR]

Life history strategies are fundamental to the ecology and evolution of organisms and are important for understanding extinction risk and responses to global change. Using global datasets and a multiple response modelling framework we show that trait‐climate interactions are associated with life history strategies for a diverse range of plant species at the global scale. Our modelling framework informs our understanding of trade‐offs and positive correlations between elements of life history after accounting for environmental context and evolutionary and trait‐based constraints. Interactions between plant traits and climatic context were needed to explain variation in age at maturity, distribution of mortality across the lifespan and generation times of species. Mean age at maturity and the distribution of mortality across plants' lifespan were under evolutionary constraints. These findings provide empirical support for the theoretical expectation that climatic context is key to understanding trait to life history relationships globally. [ABSTRACT FROM AUTHOR]

Local adaptation features critically in shaping species responses to changing environments, complicating efforts to revegetate degraded areas. Rapid climate change poses an additional challenge that could reduce fitness of even locally sourced seeds in restoration. Predictive restoration strategies that apply seeds with favourable adaptations to future climate may promote long‐term resilience. Landscape genomics is increasingly used to assess spatial patterns in local adaption and may represent a cost‐efficient approach for identifying future‐adapted genotypes. To demonstrate such an approach, we genotyped 760 plants from 64 Mojave Desert populations of the desert annual Plantago ovata. Genome scans on 5,960 SNPs identified 184 potentially adaptive loci related to climate and satellite vegetation metrics. Causal modelling indicated that variation in potentially adaptive loci was not confounded by isolation by distance or isolation by habitat resistance. A generalized dissimilarity model (GDM) attributed spatial turnover in potentially adaptive loci to temperature, precipitation and NDVI amplitude, a measure of vegetation green‐up potential. By integrating a species distribution model (SDM), we find evidence that summer maximum temperature may both constrain the range of P. ovata and drive adaptive divergence in populations exposed to higher temperatures. Within the species' current range, warm‐adapted genotypes are predicted to experience a fivefold expansion in climate niche by midcentury and could harbour key adaptations to cope with future climate. We recommend eight seed transfer zones and project each zone into its relative position in future climate. Prioritizing seed collection efforts on genotypes with expanding future habitat represents a promising strategy for restoration practitioners to address rapidly changing climates. [ABSTRACT FROM AUTHOR]

Loanword use has dominated the literature on language contact and its salient nature continues to draw interest from linguists and non-linguists. Traditionally, loanwords were investigated by means of raw frequencies, which are at best uninformative and at worst misleading. Following a new wave of studies which look at loans from a quantitatively more informed standpoint, modelling "success" by taking into account frequency of the counterparts available in the language adopting the loanwords, we propose a similar model of loan-use and demonstrate its benefits in a case study of loanwords from Māori into (New Zealand) English. Our model contributes to previous work in this area by combining both the success measure mentioned above with a rich range of linguistic characteristics of the loanwords (such as loan length and word class), as well as a similarly detailed group of sociolinguistic characteristics of the speakers using them (gender, age and ethnicity of both, speakers and addresses). Our model is unique in bringing together of all these factors at the same time. The findings presented here illustrate the benefit of a quantitatively balanced approach to modelling loanword use. Furthermore, they illustrate the complex interaction between linguistic and sociolinguistic factors in such language contact scenarios. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Advanced Nursing (John Wiley & Sons, Inc.) is the property of John Wiley & Sons, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Documenta Praehistorica is the property of Documenta Praehistorica and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

New Findings: What is the central question of this study?Does oestrous cycle synchronization influence myoelectrical activity of porcine myometrium?What is the main finding and its importance?Exogenous hormones used to synchronize oestrus in pigs altered myoelectrical activity, which was effectively modelled. Higher‐order multivariate statistic modelling provided evidence of similar activity in both types of oestrus, but a larger order of EMG signals during induced oestrus. Higher‐order statistical analysis of the probabilistic model suggests the beginning of the early follicular phase and the mid‐luteal phase to be most important in evaluation of the natural patterns of myoelectrical activity. Higher‐order multivariate cumulants are more informative than classical statistics in characterization of myoelectrical activity changes in porcine myometrium. In pig production units, control of the oestrous cycle and synchronization of ovulation have become routine herd management procedures. During the oestrous cycle, in both induced and spontaneous conditions, the ovaries and the uterus undergo hormone‐dominated physiological changes, which are consistent with the hypothesis that there is a functional role of uterine contractions in promoting fertilization. We have used electromyography to determine whether the use of exogenous hormones, such as equine chorionic gonadotrophin and human chorionic gonadotrophin, which have the potential to control the timing of ovulation in female pigs, changes the multivariate relationships between parameters of electrical bursts and modulates the patterns of myoelectrical activity. We used the mathematical approach of higher‐order multivariate cumulants in complex modelling of the myometrial electrical activity. The experiment was conducted on 12 mature Polish Landrace sows, and uterine activity was recorded during both spontaneous and induced oestrous cycles. The burst parameters were determined using six features in the time domain and, after Fast Fourier transformation, in the frequency domain. Evaluation of myoelectrical activity patterns was conducted based on classical univariate statistical methods and multivariate probabilistic modelling. The classical statistical approach indicated weaker myoelectrical activity after hormonal stimulation, whereas the higher‐order multivariate statistical model showed evidence of similar status of activity and a larger order of signals during induced oestrus. Routine oestrous cycle synchronization affects the multivariate probabilistic model of myometrial electrical activity. [ABSTRACT FROM AUTHOR]

The quality requirements of wood biofuels are regulated by a series of harmonized international standards. These standards define the technical parameter limits that influence the quality of solid biomass as a fuel. In 2014 the European reference standard for solid biofuel was replaced by the International ISO standard. In the case of wood chips, the main difference between the European and International standards is the definition of particle size distribution classes. In this context, this study analyses the quality of wood chips and its variation over the years according to the "former" (EN 14691-4) and "in force" (ISO 17225-4) standards. A Soft Independent Modelling of Class Analogy (SIMCA) model was built to predict the best quality of wood chips and to clarify the relationship between quality and standard parameters, time and changes in the standard regulations. The results show that, compared to the EN standards, classification with the ISO standards increases the samples belonging to the best quality classes and decreases the not classified samples. Furthermore, all the SIMCA models have a high sensitivity (>90%), reflect the differences introduced to the quality standards and are therefore suitable for monitoring the quality of wood chips and their changes. [ABSTRACT FROM AUTHOR]

The paper investigates the dependences between levels of severity of road traffic accidents, accounting at the same time for spatial and temporal correlations. The study analyses road traffic accidents data at ward level in England over the period 2005-2013. We include in our model multivariate spatially structured and unstructured effects to capture the dependences between severities, within a Bayesian hierarchical formulation. We also include a temporal component to capture the time effects and we carry out an extensive model comparison. The results show important associations in both spatially structured and unstructured effects between severities, and a downward temporal trend is observed for low and high levels of severity. Maps of posterior accident rates indicate elevated risk within big cities for accidents of low severity and in suburban areas in the north and on the southern coast of England for accidents of high severity. The posterior probability of extreme rates is used to suggest the presence of hot spots in a public health perspective. [ABSTRACT FROM AUTHOR]

Antarctica is the world's largest fresh-water reservoir, with the potential to raise sea levels by about 60 m. An ice sheet contributes to sea-level rise (SLR) when its rate of ice discharge and/or surface melting exceeds accumulation through snowfall. Constraining the contribution of the ice sheets to present-day SLR is vital both for coastal development and planning, and climate projections. Information on various ice sheet processes is available from several remote sensing data sets, as well as in situ data such as global positioning system data. These data have differing coverage, spatial support, temporal sampling and sensing characteristics, and thus, it is advantageous to combine them all in a single framework for estimation of the SLR contribution and the assessment of processes controlling mass exchange with the ocean. In this paper, we predict the rate of height change due to salient geophysical processes in Antarctica and use these to provide estimates of SLR contribution with associated uncertainties. We employ a multivariate spatio-temporal model, approximated as a Gaussian Markov random field, to take advantage of differing spatio-temporal properties of the processes to separate the causes of the observed change. The process parameters are estimated from geophysical models, while the remaining parameters are estimated using a Markov chain Monte Carlo scheme, designed to operate in a high-performance computing environment across multiple nodes. We validate our methods against a separate data set and compare the results to those from studies that invariably employ numerical model outputs directly. We conclude that it is possible, and insightful, to assess Antarctica's contribution without explicit use of numerical models. Further, the results obtained here can be used to test the geophysical numerical models for which in situ data are hard to obtain. © 2015 The Authors. Environmetrics published by John Wiley & Sons Ltd. [ABSTRACT FROM AUTHOR]

In this paper, a multilayer artificial neural network is used to model simultaneously the effect of solute structure and eluent concentration profile on the retention of s-triazines in reversed-phase high-performance liquid chromatography under linear gradient elution. The retention data of 24 triazines, including common herbicides and their metabolites, are collected under 13 different elution modes, covering the following experimental domain: starting acetonitrile volume fraction ranging between 40 and 60% and gradient slope ranging between 0 and 1% acetonitrile/min. The gradient parameters together with five selected molecular descriptors, identified by quantitative structure-retention relationship modelling applied to individual separation conditions, are the network inputs. Predictive performance of this model is evaluated on six external triazines and four unseen separation conditions. For comparison, retention of triazines is modelled by both quantitative structure-retention relationships and response surface methodology, which describe separately the effect of molecular structure and gradient parameters on the retention. Although applied to a wider variable domain, the network provides a performance comparable to that of the above 'local' models and retention times of triazines are modelled with accuracy generally better than 7%. [ABSTRACT FROM AUTHOR]

The paper extends existing models for multilevel multivariate data with mixed response types to handle quite general types and patterns of missing data values in a wide range of multilevel generalized linear models. It proposes an efficient Bayesian modelling approach that allows missing values in covariates, including models where there are interactions or other functions of covariates such as polynomials. The procedure can also be used to produce multiply imputed complete data sets. A simulation study is presented as well as the analysis of a longitudinal data set. The paper also shows how existing multiprocess models for handling endogeneity can be extended by the framework proposed. [ABSTRACT FROM AUTHOR]

This paper deals with multivariate disease mapping. We propose a novel framework that encompasses most of the models already proposed. Our framework starts with a simple identity, reformulating Kronecker products of covariance matrices as simple matrix products. This formula is computationally convenient, and its generalizations reproduce most of the proposals in the disease mapping literature. Use of the identity leads to a flexible, general and computationally convenient modelling framework, making it possible to combine spatial dependence structures and different relationships between diseases with limited effort. Moreover, as the proposed modelling framework covers most of the Gaussian Markov random field-based multivariate disease mapping models in the literature, it allows comparison of all these models in a common context, thus helping us to understand them better. [ABSTRACT FROM AUTHOR]

This study was the first consumer study done in Japan, which investigated consumer preferences of raw Norwegian rainbow trout with the use of an experimental design. A full factorial design with three variables (body part, body weight and freshness) was applied at two levels. The results showed that the variation in body part had the greatest effect on the expected and experienced eating quality of raw rainbow trout among seventy-five young adult consumers. The effect was negative and it is possible that the high fat level observed in the belly region does not always lead to better overall likings. The high fat content could also result in the intense fishy odour distinctive to raw salmonidae at consumption and influence the perception of other quality attributes. The present study provides a new way of offering more practical and applicable suggestions to the fish farming industry. [ABSTRACT FROM AUTHOR]

Projection to Latent Structures (PLS) regression, a generalization of multiple linear regression, is used to model two datasets (40 observed data points each) of adsorption removal of three pharmaceutical compounds (PhCs), of different therapeutic classes and physical–chemical properties (carbamazepine, diclofenac, and sulfamethoxazole), from six real secondary effluents collected from wastewater treatment plants onto different powdered activated carbons (PACs). For the PLS regression, 25 descriptors were considered: 7 descriptors related to the PhCs properties, 10 descriptors related to the wastewaters properties (8 related to the organic matrix and 2 to the inorganic matrix), and 8 descriptors related to the PACs properties. This modelling approach showed good descriptive capability, showing that hydrophobic PhC-PAC interactions play the major role in the adsorption process, with the solvation energy and log Kow being the most suitable descriptors. The results also stress the importance of the competition effects of water dissolved organic matter (DOM), namely of its slightly hydrophobic compounds impacting the adsorption capacity or its charged hydrophilic compounds impacting the short-term adsorption, while the water inorganic matrix only appears to impact PAC adsorption capacity and not the short-term adsorption. For the pool of PACs tested, the results point to the BET area as a good descriptor of the PAC capacity, while the short-term adsorption kinetics appears to be better related to its supermicropore volume and density. The improvement in these PAC properties should be regarded as a way of refining their performance. The correlations obtained, involving the impact of water, PhC and PAC-related descriptors, show the existence of complex interactions that a univariate analysis is not sufficient to describe. [ABSTRACT FROM AUTHOR]

This study analyzes the relationship between Corporate Real Estate (CRE) strategy and the financial performance of major companies in the UK for two time periods, 1998 and 2003. The identification of specific CRE strategies is based on the seminal work of Nourse and Roulac (1993). The results indicate that more than 75% of the companies examined had a CRE strategy that could be mapped to the Nourse and Roulac framework and that certain CRE strategies made a contribution in enhancing the financial performance of companies. The relationship was stronger for companies in 2003 than for 1998. This was tested for both share price and profit margin as the dependent variable. This study concludes that CRE strategy can make a limited contribution to company financial performance. [ABSTRACT FROM AUTHOR]

Traffic safety in the UK is one of the increasing number of areas where central government sets targets based on ‘outcome-focused’ performance indicators (PIs). Judgments about such PIs are often based solely on rankings of raw indicators and simple league tables dominate centrally published analyses. There is a considerable statistical literature examining health and education issues which has tended to use the generalized linear mixed model (GLMM) to address variability in the data when drawing inferences about relative performance from headline PIs. This methodology could obviously be applied in contexts such as traffic safety. However, when such models are applied to the fairly crude data sets that are currently available, the interval estimates generated, e.g. in respect of rankings, are often too broad to allow much real differentiation between the traffic safety performance of the units that are being considered. Such results sit uncomfortably with the ethos of ‘performance management’ and raise the question of whether the inference from such data sets about relative performance can be improved in some way. Motivated by consideration of a set of nine road safety performance indicators measured on English local authorities in the year 2000, the paper considers methods to strengthen the weak inference that is obtained from GLMMs of individual indicators by simultaneous, multivariate modelling of a range of related indicators. The correlation structure between indicators is used to reduce the uncertainty that is associated with rankings of any one of the individual indicators. The results demonstrate that credible intervals can be substantially narrowed by the use of the multivariate GLMM approach and that multivariate modelling of multiple PIs may therefore have considerable potential for introducing more robust and realistic assessments of differential performance in some contexts. [ABSTRACT FROM AUTHOR]

Quantifying the organic carbon content of soil over large areas is essential for characterising the soil and the effects of its management. However, analytical methods can be laborious and costly. Reflectance spectroscopy is a well-established and widespread method for estimating the chemical-element content of soils. The aim of this study was to estimate the soil organic carbon (SOC) content using hyperspectral remote sensing. The data were from soils from two localities in the semi-arid region of Brazil. The spectral reflectance factors of the collected soil samples were recorded at wavelengths ranging from 350–2500 nm. Pre-processing techniques were employed, including normalisation, Savitzky–Golay smoothing and first-order derivative analysis. The data (n = 65) were examined both jointly and by soil class, and subdivided into calibration and validation to independently assess the performance of the linear methods. Two multivariate models were calibrated using the SOC content estimated in the laboratory by principal component regression (PCR) and partial least squares regression (PLSR). The study showed significant success in predicting the SOC with transformed and untransformed data, yielding acceptable-to-excellent predictions (with the performance-to-deviation ratio ranging from 1.40–3.38). In general, the spectral reflectance factors of the soils decreased with the increasing levels of SOC. PLSR was considered more robust than PCR, whose wavelengths from 354 to 380 nm, 1685, 1718, 1757, 1840, 1876, 1880, 2018, 2037, 2042, and 2057 nm showed outstanding absorption characteristics between the predicted models. The results found here are of significant practical value for estimating SOC in Neosols and Cambisols in the semi-arid region of Brazil using VIS-NIR-SWIR spectroscopy. [ABSTRACT FROM AUTHOR]

We present models based on the multivariate normal distribution to represent the process of dilution and adulteration of citrius juice. The models specify a common dilution parameter for those components of the juice which are affected by dilution but not adulteration. Statistical testing of the hypothesis of no dilution or adulteration presents theoretical difficulties. These difficulties are resolved by model comparisons based on averaged, rather than maximized, likelihoods. [ABSTRACT FROM AUTHOR]

Multivariate autoregressive modelling provides a method to analyse the dynamic interactions between heart rate (HR), blood pressure (BP) and respiration (RESP) by means of noise source contributions (NSCs). The conventional approach presumes the modelled noise sources are mutually independent. This presumption is, in general, not satisfied and causes an error in the results. In the present study, the effect of this error is analysed. A method is presented to remove the error by making the noise sources independent. The method is based on the inclusion of immediate transfer paths in the model. To quantify the strength of the interactions, a measure called NSC ratio (NSCR); is calculated; this states the amount of variability of the signal arising from other signals. The method is demonstrated by studying the inter-relationships between HR, BP and RESP in a healthy male subject in supine and standing positions. It is found that the error is marked and that the presented method provides corrected estimates for spectral decomposition and NSC analysis. The results show it is necessary to include the immediate transfer mechanisms in the model, while analysing the cardiopulmonary dynamics by means of HR and BP variability. [ABSTRACT FROM AUTHOR]

The aim of this study is to evaluate the effect of farmers' socioeconomic characteristics on sustainable forage crop production after forage crop subsidies. One of the innovative aspects of the study is the simultaneous modeling of alfalfa, silage corn and vetch production efficiency. For this, the multivariate linear regression model was used. In this way, the effect of socioeconomic characteristics on production is more clearly demonstrated by taking into account the dependency structure between forage crop production. For the study, 487 farmers in the Aegean region, where fodder crops can be produced throughout the year, were interviewed face-to-face and data were collected through a questionnaire. According to the results obtained, it was determined that the width of the land had a positive effect on the increase in alfalfa, silage corn, and vetch production. The number of animals was found to have a positive effect on alfalfa and silage maize production growth. The production of alfalfa was higher in rural farmers, and vetch production was higher in urban farmers. Farmers who do not have non-agricultural income focused on vetch production, and farmers with non-agricultural income focused on alfalfa production. It was seen that the majority of the farmers participating in the study were primary school graduates and lived in rural areas. In general, a significant increase was observed in the production of silage corn, vetch, and alfalfa, respectively. After the subsidies, it was concluded that this increase in the production of silage corn, vetch, and alfalfa was not at a level to meet the amount of forage crops needed by animal husbandry. [ABSTRACT FROM AUTHOR]

Background: Nocturia is common and associated with multiple disease states. Many potential mechanisms have been proposed for nocturia, which also remains challenging to manage. Purpose: To use multivariate analysis to determine which combinations of factors can accurately discriminate clinically significant nocturia in patients to facilitate clinical management and treatment decisions. Patients and methods: Data analysis was based on frequency volume charts from three randomized controlled trials. There were 1479 patients included, of which 215 patients had no/mild nocturia and 1264 had clinically significant nocturia with at least two voids per night. Factors studied that may influence nocturia were demographics, sleep duration, functional bladder capacity, 24 h urine volume and literature-suggested definitions of nocturnal polyuria. We used univariate analysis and cross-validated multivariate modelling to assess association between factors and nocturia status, redundancy between factors and whether the combined use of factors could explain patients′ nocturia status. Results: The multivariate analyses showed that the most useful definitions of nocturia are 'Nocturia Index' (NI) and 'Nocturnal Urine Production per hour' (NUPh) in combination with functional bladder capacity and sleep duration. Published definitions providing binary nocturnal polyuria outcomes had lower performance than continuous indices. These analyses also showed that NI was not specific to nocturnal polyuria as it also captured nocturia due to low functional bladder capacity. By contrast, NUPh was demonstrated to be specific to nocturnal polyuria. Conclusion: NUPh has previously been shown among elderly males to be essential in nocturia and a very valid measure of nocturnal polyuria. However, the current, large and independent dataset now confirms that it can be applied in an adult population with a complaint of nocturia covering both males and females. [ABSTRACT FROM AUTHOR]