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The aim of this study is to model the test day milk yields via time series methodology and to determine the number of test days which provide the most accurate forecasts. For this purpose, 10700 test day records belonging to 1070 dairy cattle were used. Data were divided into two groups of 5350 records in each. One set of observations was used to model parameters, while the remaining was used for evaluating the forecast power of the model and for determining the number of test day records which provide the most accurate forecasts. ARIMA(2,0,0)(1,1,1) 10model was determined to be suitable and it was used to obtain the. forecast values. The expression of the model using estimated parameter values is (1-B10)1yt, = [(1-0.99129B10)/(1-0.36889B-0.06934B)(1-0.08352B,0)]at. Statistically significant and high correlations were determined between the actual and forecast values. The results indicated that the time series approach can be useful for prediction of milk yields. [ABSTRACT FROM AUTHOR]

The purpose of this study was to test the reliability and validity of the Turkish version of the CQOLC in Turkey. The 35-item English version of the CQOLC was translated into Turkish following the standard translation methodology. The questionnaire was administered to 237 caregivers of patients with cancer. Confirmatory and exploratory factor analyses (CFA and EFA) were carried out using principal component analysis with varimax rotation and Kaiser Normalization to test its construct validity. We used Cronbach’s alpha to examine the CQOLC’s reliability (internal consistency). The CFA did not confirm the original factor model. The EFA yielded a 25-item measure with a four-factor solution with different labels for three of the four original scales (shown in parentheses): Psychological Distress (Burden), Disruption in Daily Life (Disruptiveness), Caregiving Responsibility (Positive Adaptation), and Financial Concerns (Financial Concerns). Cronbach’s alpha for the total scale was 0.88 and subscale alpha coefficients ranged from 0.73 to 0.83. The results indicate some differences in the factor structures of the CQOLC scale between Turkish and American samples but provided preliminary support for the Turkish version of the CQOLC as a reliable and valid measure of the quality of life of Turkish cancer caregivers. [ABSTRACT FROM AUTHOR]

This study aims at characterizing the asymptotic behavior of genomic prediction R2 as the size of the reference population increases for common or rare QTL alleles through simulations. Haplotypes derived from whole-genome sequence of 85 Caucasian individuals from the 1,000 Genomes Project were used to simulate random mating in a population of 10,000 individuals for at least 100 generations to create the LD structure in humans for a large number of individuals. To reduce computational demands, only SNPs within a 0.1M region of each of the first 5 chromosomes were used in simulations, and therefore, the total genome length simulated was 0.5M. When the genome length is 30M, to get the same genomic prediction R2 as with a 0.5M genome would require a reference population 60 fold larger. Three scenarios were considered varying in minor allele frequency distributions of markers and QTL, for h2 = 0.8 resembling height in humans. Total number of markers was 4,200 and QTL were 70 for each scenario. In this study, we considered the prediction accuracy in terms of an estimability problem, and thereby provided an upper bound for reliability of prediction, and thus, for prediction R2. Genomic prediction methods GBLUP, BayesB and BayesC were compared. Our results imply that for human height variable selection methods BayesB and BayesC applied to a 30M genome have no advantage over GBLUP when the size of reference population was small (<6,000 individuals), but are superior as more individuals are included in the reference population. All methods become asymptotically equivalent in terms of prediction R2, which approaches genomic heritability when the size of the reference population reaches 480,000 individuals. [ABSTRACT FROM AUTHOR]

It is believed that there is an association between the weather and rheumatic symptoms. We aimed to investigate what kind of association is present and what are the factors which determine the nature of this association. Fifty-six subjects with rheumatic disease (31 RA, 15 SpA, 10 OA) who live in Antalya were followed between December 2005 and July 2006. Patients were asked to fill diaries which contain questions regarding the symptoms of their rheumatic diseases everyday. In every monthly visit, disease activity measurement, laboratory assessment and Beck depression inventory assessment were recorded. The symptomatic and psychological measurements were matched with the meteorological data of Antalya Regional Directorate of Meteorological Service of Turkish State. Correlation of symptoms with weather variables was investigated. Contributory effect of weather and of psychologic factors on symptom scores were evaluated by stepwise multiple regression analysis. Eighty-four percent of subjects belive in an association between weather and rheumatism, while 57% claimed to have ability to forecast weather. The maximum correlation coefficient between weather and arthritis symptoms was −0.451 and the maximum contribution of weather on symptoms was 17.1%. Arthritis symptoms were significantly contributed by Beck depression score. The belief about presence of weather-arthritis association was found to be stronger than its statistical power. Our results did not prove or rule out the presence of weather-rheumatism association. As long as the scientific attempts result in failure, the intuitive support in favour of the presence of weather-arthritis association will go on forever. [ABSTRACT FROM AUTHOR]