601 research outputs found

    Clustering South African households based on their asset status using latent variable models

    Full text link
    The Agincourt Health and Demographic Surveillance System has since 2001 conducted a biannual household asset survey in order to quantify household socio-economic status (SES) in a rural population living in northeast South Africa. The survey contains binary, ordinal and nominal items. In the absence of income or expenditure data, the SES landscape in the study population is explored and described by clustering the households into homogeneous groups based on their asset status. A model-based approach to clustering the Agincourt households, based on latent variable models, is proposed. In the case of modeling binary or ordinal items, item response theory models are employed. For nominal survey items, a factor analysis model, similar in nature to a multinomial probit model, is used. Both model types have an underlying latent variable structure - this similarity is exploited and the models are combined to produce a hybrid model capable of handling mixed data types. Further, a mixture of the hybrid models is considered to provide clustering capabilities within the context of mixed binary, ordinal and nominal response data. The proposed model is termed a mixture of factor analyzers for mixed data (MFA-MD). The MFA-MD model is applied to the survey data to cluster the Agincourt households into homogeneous groups. The model is estimated within the Bayesian paradigm, using a Markov chain Monte Carlo algorithm. Intuitive groupings result, providing insight to the different socio-economic strata within the Agincourt region.Comment: Published in at http://dx.doi.org/10.1214/14-AOAS726 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

    Catastrophizing mediates the relationship between the personal belief in a just world and pain outcomes among chronic pain support group attendees

    Get PDF
    Health-related research suggests the belief in a just world can act as a personal resource that protects against the adverse effects of pain and illness. However, currently, little is known about how this belief, particularly in relation to one’s own life, might influence pain. Consistent with the suggestions of previous research, the present study undertook a secondary data analysis to investigate pain catastrophizing as a mediator of the relationship between the personal just world belief and chronic pain outcomes in a sample of chronic pain support group attendees. Partially supporting the hypotheses, catastrophizing was negatively correlated with the personal just world belief and mediated the relationship between this belief and pain and disability, but not distress. Suggestions for future research and intervention development are made

    An interpretative phenomenological analysis of the psychosexual identity development in adolescent and young adult survivors of testicular cancer

    Get PDF
    Background Qualitative research has explored how some testicular cancer survivors (TCS) experience the psychological impacts of diagnosis and treatment. More research into the impacts of testicular cancer (TC) on adolescent and young adults (AYA) is needed due to the critical period of identity development. The present study aimed to explore how AYA with TC appraise and make sense of their experience and to develop a greater understanding of psychosexual identity development in AYA TCS. Method Eight AYA TCS were interviewed. The results were analysed using Interpretative Phenomenological Analysis. The questions explored the experiences relating to diagnosis and treatment, how it affected their psychosexual identity development (e.g., sexual relationships and self-image) and the meanings attached to the experiences. Analysis Four Group Experiential Themes were developed from the data; ‘Dealing with the shock’, ‘Fear and weight of responsibility’, ‘those closest to me’ and ‘sense of change’. Discussion The AYA TCS experiences may result in adoption of traditional masculine traits (e.g., stoicism) or abandonment of traditionally masculine traits (E.g. violence and aggression). AYA TCS also described feelings of insecurity when compared to other men. Psychology input could help manage stoicism and feelings of inferiority when compared to men with two testicles

    Effect of using internal teat sealant with or without antibiotic therapy at dry-off on subsequent somatic cell count and milk production

    Get PDF
    peer-reviewedThe objective of this study was to assess the effect of treating cows with teat sealant only compared with antibiotic plus teat sealant at drying off on weekly somatic cell count, potential intramammary infection, and milk production across the entire subsequent lactation. In 3 research herds in the south of Ireland, cows with SCC that did not exceed 200,000 cells/mL in the previous lactation (LowSCC) were randomly assigned to 1 of 2 treatments at drying off: internal teat sealant alone (ITS) or antibiotic plus teat sealant (AB+ITS). Cows with SCC that exceeded 200,000 cells/mL in the previous lactation were treated with AB+ITS and included in the analyses as a separate group (HighSCC). Weekly individual animal composite SCC records were available for 654 cow lactations and were transformed to somatic cell scores (SCS) for the purpose of analysis. Data were divided into 3 data sets to represent records obtained (1) up to 35 DIM, (2) up to 120 DIM, and (3) across the lactation. Foremilk secretions were taken from all quarters at drying off, at calving, 2 wk after calving, and in mid-lactation and were cultured to detect the presence of bacteria. The LowSCC cows treated with ITS alone had higher daily milk yield (0.67 kg/d) across lactation compared with LowSCC cows treated with AB+ITS. The LowSCC cows treated with ITS alone had higher SCS in early, up to mid, and across lactation compared with LowSCC cows treated with AB+ITS. We detected no difference in weekly SCS of LowSCC cows treated with ITS alone and SCS of HighSCC cows. The least squares means back-transformed SCC across lactation of the LowSCC cows treated with ITS alone, LowSCC cows treated with AB+ITS, and HighSCC cows were 41,523, 34,001, and 38,939 cells/mL respectively. The odds of LowSCC cows treated with ITS alone having bacteria present in their foremilk across lactation was 2.7 (95% confidence interval: 1.91 to 3.85) and 1.6 (1.22 to 2.03) times the odds of LowSCC cows treated with AB+ITS and of HighSCC cows treated with AB+ITS, respectively. In this study, Staphylococcus aureus was the most prevalent pathogen isolated from the population. Recategorizing the threshold for LowSCC cows as ≤150,000 cells/mL or ≤100,000 cells/mL in the previous lactation had no effect on the results. The results indicate that herds with good mastitis control programs may use ITS alone at dry-off in cows with SCC <200,000 cells/mL across lactation with only a small effect on herd SCC

    Analysis of cybersecurity threats in Industry 4.0: the case of intrusion detection

    Get PDF
    Nowadays, industrial control systems are experiencing a new revolution with the interconnection of the operational equipment with the Internet, and the introduction of cutting-edge technologies such as Cloud Computing or Big data within the organization. These and other technologies are paving the way to the Industry 4.0. However, the advent of these technologies, and the innovative services that are enabled by them, will also bring novel threats whose impact needs to be understood. As a result, this paper provides an analysis of the evolution of these cyber-security issues and the requirements that must be satis ed by intrusion detection defense mechanisms in this context.Springer ; Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

    Genetic and nongenetic factors associated with milk color in dairy cows

    Get PDF
    peer-reviewedMilk color is one of the sensory properties that can influence consumer choice of one product over another and it influences the quality of processed dairy products. This study aims to quantify the cow-level genetic and nongenetic factors associated with bovine milk color traits. A total of 136,807 spectra from Irish commercial and research herds (with multiple breeds and crosses) were used. Milk lightness (Lˆ*) , red-green index (aˆ*) and yellow-blue index (bˆ*) were predicted for individual milk samples using only the mid-infrared spectrum of the milk sample. Factors associated with milk color were breed, stage of lactation, parity, milking-time, udder health status, pasture grazing, and seasonal calving. (Co)variance components for Lˆ*,aˆ* , and bˆ* were estimated using random regressions on the additive genetic and within-lactation permanent environmental effects. Greater bˆ* value (i.e., more yellow color) was evident in milk from Jersey cows. Milk Lˆ* increased consistently with stage of lactation, whereas aˆ* increased until mid lactation to subsequently plateau. Milk bˆ* deteriorated until 31 to 60 DIM, but then improved thereafter until the end of lactation. Relative to multiparous cows, milk yielded by primiparae was, on average, lighter (i.e., greater Lˆ* ), more red (i.e., greater aˆ* ), and less yellow (i.e., lower bˆ* ). Milk from the morning milk session had lower Lˆ*,aˆ*, and bˆ* Heritability estimates (±SE) for milk color varied between 0.15 ± 0.02 (30 DIM) and 0.46 ± 0.02 (210 DIM) for Lˆ* , between 0.09 ± 0.01 (30 DIM) and 0.15 ± 0.02 (305 DIM) for aˆ* , and between 0.18 ± 0.02 (21 DIM) and 0.56 ± 0.03 (305 DIM) for bˆ* For all the 3 milk color features, the within-trait genetic correlations approached unity as the time intervals compared shortened and were generally <0.40 between the peripheries of the lactation. Strong positive genetic correlations existed between bˆ* value and milk fat concentration, ranging from 0.82 ± 0.19 at 5 DIM to 0.96 ± 0.01 at 305 DIM and confirming the observed phenotypic correlation (0.64, SE = 0.01). Results of the present study suggest that breeding strategies for the enhancement of milk color traits could be implemented for dairy cattle populations. Such strategies, coupled with the knowledge of milk color traits variation due to nongenetic factors, may represent a tool for the dairy processors to reduce, if not eliminate, the use of artificial pigments during milk manufacturing

    Effectiveness of mid-infrared spectroscopy to predict the color of bovine milk and the relationship between milk color and traditional milk quality traits

    Get PDF
    The color of milk affects the subsequent color features of the resulting dairy products; milk color is also related to milk fat concentration. The objective of the present study was to quantify the ability of mid-infrared spectroscopy (MIRS) to predict color-related traits in milk samples and to estimate the correlations between these color-related characteristics and traditional milk quality traits. Mid-infrared spectral data were available on 601 milk samples from 529 cows, all of which had corresponding gold standard milk color measures determined using a Chroma Meter (Konica Minolta Sensing Europe, Nieuwegein, the Netherlands); milk color was expressed using the CIELAB uniform color space. Separate prediction equations were developed for each of the 3 color parameters (L* = lightness, a* = greenness, b* = yellowness) using partial least squares regression. Accuracy of prediction was determined using both cross validation on a calibration data set (n = 422 to 457 samples) and external validation on a data set of 144 to 152 samples. Moderate accuracy of prediction was achieved for the b* index (coefficient of correlation for external validation = 0.72), although poor predictive ability was obtained for both a* and L* indices (coefficient of correlation for external validation of 0.30 and 0.55, respectively). The linear regression coefficient of the gold standard values on the respective MIRS-predicted values of a*, L*, and b* was 0.81, 0.88, and 0.96, respectively; only the regression coefficient on L* was different from 1. The mean bias of prediction (i.e., the average difference between the MIRS-predicted values and gold standard values in external validation) was not different from zero for any of 3 parameters evaluated. A moderate correlation (0.56) existed between the MIRS-predicted L* and b* indices, both of which were weakly correlated with the a* index. Milk fat, protein, and casein were moderately correlated with both the gold standard and MIRS-predicted values for b*. Results from the present study indicate that MIRS data provides an efficient, low-cost screening method to determine the b* color of milk at a population level

    Factors associated with milk processing characteristics predicted by mid-infrared spectroscopy in a large database of dairy cows

    Get PDF
    Despite milk processing characteristics being important quality traits, little is known about the factors underlying their variability, due primarily to the resources required to measure these characteristics in a sufficiently large population. Cow milk coagulation properties (rennet coagulation time, curd-firming time, curd firmness 30 and 60 min after rennet addition), heat coagulation time, casein micelle size, and pH were generated from available mid-infrared spectroscopy prediction models. The prediction models were applied to 136,807 spectra collected from 9,824 Irish dairy cows from research and commercial herds. Sources of variation were investigated using linear mixed models that included the fixed effects of calendar month of test; milking time in the day; linear regressions on the proportion of Friesian, Jersey, Montb\ue9liarde, Norwegian Red, and \u201cother\u201d breeds in the cow; coefficients of heterosis and of recombination loss; parity; stage of lactation; and the 2-way interaction parity 7 stage of lactation. Withinand across-parity cow effects, contemporary group, and a residual term were also included as random effects in the model. Supplementary analyses considered the inclusion of either test-day milk yield or milk protein concentration as fixed-effects covariates in the multiple regression models. Milk coagulation properties were most favorable (i.e., short rennet coagulation time and strong curd firmness) for cheese manufacturing in early lactation, concurrent with the lowest values of both pH and casein micelle size. Milk coagulation properties and pH deteriorated in mid lactation but improved toward the end of lactation. In direct contrast, heat coagulation time was more favorable in mid lactation and less suitable (i.e., shorter) for high temperature treatments in both early and late lactation. Relative to multiparous cows, primiparous cows, on average, yielded milk with shorter rennet coagulation time and longer heat coagulation time. Milk from the evening milking session had shorter rennet coagulation time and greater curd firmness, as well as lower heat coagulation time and lower pH compared with milk from the morning session. Jersey cows, on average, yielded milk more suitable for cheese production rather than for milk powder production. When protein concentration was included in the model, the improvement of milk coagulation properties toward the end of lactation was no longer apparent. Results from the present study may aid in decisionmaking for milk manufacturing, especially in countries characterized by a seasonal supply of fresh milk

    Prediction of bovine milk technological traits from mid-infrared spectroscopy analysis in dairy cows

    Get PDF
    peer-reviewedRapid, cost-effective monitoring of milk technological traits is a significant challenge for dairy industries specialized in cheese manufacturing. The objective of the present study was to investigate the ability of mid-infrared spectroscopy to predict rennet coagulation time, curd-firming time, curd firmness at 30 and 60 min after rennet addition, heat coagulation time, casein micelle size, and pH in cow milk samples, and to quantify associations between these milk technological traits and conventional milk quality traits. Samples (n = 713) were collected from 605 cows from multiple herds; the samples represented multiple breeds, stages of lactation, parities, and milking times. Reference analyses were undertaken in accordance with standardized methods, and mid-infrared spectra in the range of 900 to 5,000 cm−1 were available for all samples. Prediction models were developed using partial least squares regression, and prediction accuracy was based on both cross and external validation. The proportion of variance explained by the prediction models in external validation was greatest for pH (71%), followed by rennet coagulation time (55%) and milk heat coagulation time (46%). Models to predict curd firmness 60 min from rennet addition and casein micelle size, however, were poor, explaining only 25 and 13%, respectively, of the total variance in each trait within external validation. On average, all prediction models tended to be unbiased. The linear regression coefficient of the reference value on the predicted value varied from 0.17 (casein micelle size regression model) to 0.83 (pH regression model) but all differed from 1. The ratio performance deviation of 1.07 (casein micelle size prediction model) to 1.79 (pH prediction model) for all prediction models in the external validation was <2, suggesting that none of the prediction models could be used for analytical purposes. With the exception of casein micelle size and curd firmness at 60 min after rennet addition, the developed prediction models may be useful as a screening method, because the concordance correlation coefficient ranged from 0.63 (heat coagulation time prediction model) to 0.84 (pH prediction model) in the external validation

    Processing characteristics of dairy cow milk are moderately heritable.

    Get PDF
    Milk processing attributes represent a group of milk quality traits that are important to the dairy industry to inform product portfolio. However, because of the resources required to routinely measure such quality traits, precise genetic parameter estimates from a large population of animals are lacking for these traits. Milk processing characteristics considered in the present study—rennet coagulation time, curd-firming time, curd firmness at 30 and 60 min after rennet addition, heat coagulation time, casein micelle size, and milk pH—were all estimated using mid-infrared spectroscopy prediction equations. Variance components for these traits were estimated using 136,807 test-day records from 5 to 305 d in milk (DIM) from 9,824 cows using random regressions to model the additive genetic and within-lactation permanent environmental variances. Heritability estimates ranged from 0.18 ± 0.01 (26 DIM) to 0.38 ± 0.02 (180 DIM) for rennet coagulation time; from 0.26 ± 0.02 (5 DIM) to 0.57 ± 0.02 (174 DIM) for curd-firming time; from 0.16 ± 0.01 (30 DIM) to 0.56 ± 0.02 (271 DIM) for curd firmness at 30 min; from 0.13 ± 0.01 (30 DIM) to 0.48 ± 0.02 (271 DIM) for curd firmness at 60 min; from 0.08 ± 0.01 (17 DIM) to 0.24 ± 0.01 (180 DIM) for heat coagulation time; from 0.23 ± 0.02 (30 DIM) to 0.43 ± 0.02 (261 DIM) for casein micelle size; and from 0.20 ± 0.01 (30 DIM) to 0.36 ± 0.02 (151 DIM) for milk pH. Within-trait genetic correlations across DIM weakened as the number of days between compared intervals increased but were mostly >0.4 except between the peripheries of the lactation. Eigenvalues and associated eigenfunctions of the additive genetic covariance matrix for all traits revealed that at least the 80% of the genetic variation among animals in lactation profiles was associated with the height of the lactation profile. Curd-firming time and curd firmness at 30 min were weakly to moderately genetically correlated with milk yield (from 0.33 ± 0.05 to 0.59 ± 0.05 for curd-firming time, and from −0.62 ± 0.03 to −0.21 ± 0.06 for curd firmness at 30 min). Milk protein concentration was strongly genetically correlated with curd firmness at 30 min (0.84 ± 0.02 to 0.94 ± 0.01) but only weakly genetically correlated with milk heat coagulation time (−0.27 ± 0.07 to 0.19 ± 0.06). Results from the present study indicate the existence of exploitable genetic variation for milk processing characteristics. Because of possible indirect deterioration in milk processing characteristics due to selection for greater milk yield, emphasis on milk processing characteristics is advised
    • …
    corecore