Solar position diagram

Program SOLVEJ är ett användarvänligt program som visar solens vandring över himlavalvet vid upp till fem valfria datum och vid valfri ort. Programmet är utvecklat av två skäl. För det första, att demonstreras för en intresserad allmänhet som del av vandringsutställning om solenergi, vilken är initierad och utarbetad av SERC. För det andra, att användas av solenerglintressenter för att snabbt få en uppfattning om solinstrålningen på en ort vid olika tidpunkter på året.Indata till programmet ges från tangentbordet. Som svar på frågor skrivs för vilken ort diagrammet skall gälla, max fem datum, ortens latitud och longitud, som anges positiv i västlig riktning, samt tidszonen. Varje uppgift avslutas med tryck på tangenten ENTER. Programmet kommer nu att rita ett koordinatsystem på skärmen. Första axeln visar vädersträcken, norr, öster, söder, väster och norr, varje delstreck utgör 10 grader. För södra halvklotet byter norr och söder plats. Andra axeln visar höjden över horisonten i grader, 0 till 90 grader och 10 grader för varje delstreck. Efter några sekunder ritas diagrammet upp med solhöjden som funktion av väderstrecket och varje hel timme markerad. Se fig. 1-4. Slutligen frågas efter om diagrammet skall ritas ut på printer. SOLVEJ avbrytes med att trycka CTRL+BREAK.SOLVEJ är skrivet i Quick-BASIC (se App. 1) och leveras både som källkod och körklar version. Lämplig dator är IBM-kompatibel AT med EGA- eller VGA-skärmkort (ej Herkules Lämplig printer är IBM Proprinter eller liknande matrisskrivare, kopplad till LPT1 på kommunikationskortet.Till grund för beräkningarna har använts artikeln On Calculating the Position of the Sun, publicerad i nr. 1 1988 av The International Journal of Ambient Energy. Fem empiriska ekvationer beträffande beräkningar av solens position har studerats för att undersöka deras tillförlitlighet. Felaktigheter på fem grader eller mer kan uppträda om man använder sig av de enkla ekvationer som kan hittas solenergi-böcker och som inte kräver tillgång till dator. FORTRAN-rutinen SUNAE2 (se App. 2) beräknar solpositionen med noggrannast kända metod. Program SOLVEJ är en utveckling av SUNAE2.

Barnfri : en stigmatiserad position

Childfree: a stigmatized position International research has addressed the subject but in Sweden voluntary childlessness has until now been overlooked. This article draws on qualitative, semi-structured interviews with 21 Swedish childfree women. The interviews focused their decision not to have children and attitudes they faced due to their rejection of motherhood. They all had encountered pressure to conform to a pronatalistic norm, proclaiming parenthood to be self-evident in an adult normal life. The results highlight different strategies used by the women to avoid instigating the dislike of those around them. The article argues that understanding childfree as a stigmatized position helps providing new insights to what conditions the social relations between the childfree and ‘the normals’, i.e. persons who advocate having children. Further, viewing the childfree as a stigmatized group has theoretical implications that contribute to developing Goffman’s classical theory of social stigma.

After work : en longitudinell studie i arbetsmiljöns långsiktiga inverkan på sambandet mellan socioekonomisk position och äldres ohälsa

After Work. The long-term effects of work environment on the association between adult socioeconomic position and ill health among the elderly The aim of this study is to analyse the long-term effects of work environment on the association between adult socioeconomic position (SEP) and six ill health outcomes among the elderly. Data was drawn from the longitudinal Level of Living and the SWEOLD-surveys. The individuals are followed from 1968 to 1992 and from 1981 to 2002 and 2004, combining baseline information regarding SEP and work environment during the period of occupational activity with the ill health outcomes from the follow-up studies. Strongest effects where revealed when controlling for the physical work environment on the association between both measures of SEP and two of the ill health outcomes: musculoskeleta lpain and physical performance. The psychological work environment, however, explained very small parts of the associations. The results, even controlled for SEP, exposed strong direct relations between ill health and psychological work environment and rather strong relations to physical work environment. As socioeconomic position indicates a particular structural position within society it may determine the likelihood of health damaging exposures during the period of occupational activity. This study shows that the effect of work environment significantly affects ill health among the elderly. Hence, the results indicate the importance of taking measures in improving work environment during the labour-market participation period, especially since policy-makers attempt to convince workers to stay longer in the workforce.

Estimation of genetic variance for macro- and micro-environmental sensitivity using double hierarchical generalized linear models

Background: Genetic variation for environmental sensitivity indicates that animals are genetically different in their response to environmental factors. Environmental factors are either identifiable (e.g. temperature) and called macro-environmental or unknown and called micro-environmental. The objectives of this study were to develop a statistical method to estimate genetic parameters for macro- and micro-environmental sensitivities simultaneously, to investigate bias and precision of resulting estimates of genetic parameters and to develop and evaluate use of Akaike’s information criterion using h-likelihood to select the best fitting model. Methods: We assumed that genetic variation in macro- and micro-environmental sensitivities is expressed as genetic variance in the slope of a linear reaction norm and environmental variance, respectively. A reaction norm model to estimate genetic variance for macro-environmental sensitivity was combined with a structural model for residual variance to estimate genetic variance for micro-environmental sensitivity using a double hierarchical generalized linear model in ASReml. Akaike’s information criterion was constructed as model selection criterion using approximated h-likelihood. Populations of sires with large half-sib offspring groups were simulated to investigate bias and precision of estimated genetic parameters. Results: Designs with 100 sires, each with at least 100 offspring, are required to have standard deviations of estimated variances lower than 50% of the true value. When the number of offspring increased, standard deviations of estimates across replicates decreased substantially, especially for genetic variances of macro- and micro-environmental sensitivities. Standard deviations of estimated genetic correlations across replicates were quite large (between 0.1 and 0.4), especially when sires had few offspring. Practically, no bias was observed for estimates of any of the parameters. Using Akaike’s information criterion the true genetic model was selected as the best statistical model in at least 90% of 100 replicates when the number of offspring per sire was 100. Application of the model to lactation milk yield in dairy cattle showed that genetic variance for micro- and macro-environmental sensitivities existed. Conclusion: The algorithm and model selection criterion presented here can contribute to better understand genetic control of macro- and micro-environmental sensitivities. Designs or datasets should have at least 100 sires each with 100 offspring.

Hglm: A package for fitting hierarchical generalized linear models

We present the hglm package for fitting hierarchical generalized linear models. It can be used for linear mixed models and generalized linear mixed models with random effects for a variety of links and a variety of distributions for both the outcomes and the random effects. Fixed effects can also be fitted in the dispersion part of the model.

Genetic heterogeneity of residual variance : estimation of variance components using double hierarchical generalized linear models

Background: The sensitivity to microenvironmental changes varies among animals and may be under genetic control. It is essential to take this element into account when aiming at breeding robust farm animals. Here, linear mixed models with genetic effects in the residual variance part of the model can be used. Such models have previously been fitted using EM and MCMC algorithms. Results: We propose the use of double hierarchical generalized linear models (DHGLM), where the squared residuals are assumed to be gamma distributed and the residual variance is fitted using a generalized linear model. The algorithm iterates between two sets of mixed model equations, one on the level of observations and one on the level of variances. The method was validated using simulations and also by re-analyzing a data set on pig litter size that was previously analyzed using a Bayesian approach. The pig litter size data contained 10,060 records from 4,149 sows. The DHGLM was implemented using the ASReml software and the algorithm converged within three minutes on a Linux server. The estimates were similar to those previously obtained using Bayesian methodology, especially the variance components in the residual variance part of the model. Conclusions: We have shown that variance components in the residual variance part of a linear mixed model can be estimated using a DHGLM approach. The method enables analyses of animal models with large numbers of observations. An important future development of the DHGLM methodology is to include the genetic correlation between the random effects in the mean and residual variance parts of the model as a parameter of the DHGLM.