929 resultados para Solution of mathematical problems


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Potent anthelmintics were introduced into the Swiss market several decades ago. Despite this, gastrointestinal nematodes (GIN), lungworms and the large liver fluke (Fasciola hepatica) can successfully inhabit Swiss ruminant farms. This is mainly due to a high reproductive capacity as well as very efficient survival strategies. In addition some species readily develop anthelmintic resistance. GIN-infections in young cattle are under comparatively good control. However, prophylactic measures are compromised where adult stock is also affected due to incomplete development of immune protection. Under these circumstances control measures must include all age groups. This results in fewer helminths in refugia thus may accelerate the development of anthelmintic resistance. This review aims to present a synopsis of the significance of the major helminth infections obtained on pasture by large and small ruminants in Switzerland. Currently available strategies for strategic helminth control are summarized and an outlook is given on new developments which might expand the spectrum of control measures relevant for veterinary practice in the future.

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In this paper a superelement formulation for geometric nonlinear finite element analysis is proposed. The element formulation is based on matrices generated by the static condensation algorithm. After defining the element characteristics, a method for the calculation of the element forces in a large displacement and rotation analysis is developed. In order to use the element in the solution of stability problems, the formulation of the geometric stiffness matrix is derived. An example shows the benefits of the element for the calculation of lattice-boom cranes.

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Liver transplantation recipients, like other solid organ transplantation recipients, have an increased risk of dermatologic problems due to their long-term immunosuppression and benefit from pre-and post-transplantation screenings, and management by a dermatologist and dermatologic care should be integrated into the comprehensive, multidisciplinary care of liver transplantation recipients [1,2]. Cutaneous findings include aesthetic alterations, infections, precancerous lesions, and malignancies. The severity of skin alterations ranges from benign, unpleasant changes to life-threatening conditions [3-5]. In addition to skin cancer diagnosis and management, visits with a dermatologist serve to educate and improve the patient's sun-protection behavior. Among all solid organ transplantations, liver transplantation requires the least amount of immunosuppression, sometimes even permitting its complete cessation [6]. As a result, patients who have undergone liver transplantation tend to have fewer dermatologic complications compared with other solid organ transplantation recipients [7]. However, due to the large volume of the liver, patients undergoing liver transplantation receive more donor lymphocytes than kidney, heart, or lung transplantation recipients. Because of the immunosuppression, the transplanted lymphocytes proliferate and rarely trigger graft-versus-host-disease [8,9]. This topic will provide an overview of dermatologic disorders that may be seen following liver transplantation. A detailed discussion of skin cancer following solid organ transplantation and the general management of patients following liver transplantation are discussed separately. (See "Development of malignancy following solid organ transplantation" and "Management of skin cancer in solid organ transplant recipients" and "Long-term management of adult liver transplant recipients".)

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We study the relativistic version of the Schrödinger equation for a point particle in one dimension with the potential of the first derivative of the delta function. The momentum cutoff regularization is used to study the bound state and scattering states. The initial calculations show that the reciprocal of the bare coupling constant is ultraviolet divergent, and the resultant expression cannot be renormalized in the usual sense, where the divergent terms can just be omitted. Therefore, a general procedure has been developed to derive different physical properties of the system. The procedure is used first in the nonrelativistic case for the purpose of clarification and comparisons. For the relativistic case, the results show that this system behaves exactly like the delta function potential, which means that this system also shares features with quantum filed theories, like being asymptotically free. In addition, in the massless limit, it undergoes dimensional transmutation, and it possesses an infrared conformal fixed point. The comparison of the solution with the relativistic delta function potential solution shows evidence of universality.

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Objectives. This paper seeks to assess the effect on statistical power of regression model misspecification in a variety of situations. ^ Methods and results. The effect of misspecification in regression can be approximated by evaluating the correlation between the correct specification and the misspecification of the outcome variable (Harris 2010).In this paper, three misspecified models (linear, categorical and fractional polynomial) were considered. In the first section, the mathematical method of calculating the correlation between correct and misspecified models with simple mathematical forms was derived and demonstrated. In the second section, data from the National Health and Nutrition Examination Survey (NHANES 2007-2008) were used to examine such correlations. Our study shows that comparing to linear or categorical models, the fractional polynomial models, with the higher correlations, provided a better approximation of the true relationship, which was illustrated by LOESS regression. In the third section, we present the results of simulation studies that demonstrate overall misspecification in regression can produce marked decreases in power with small sample sizes. However, the categorical model had greatest power, ranging from 0.877 to 0.936 depending on sample size and outcome variable used. The power of fractional polynomial model was close to that of linear model, which ranged from 0.69 to 0.83, and appeared to be affected by the increased degrees of freedom of this model.^ Conclusion. Correlations between alternative model specifications can be used to provide a good approximation of the effect on statistical power of misspecification when the sample size is large. When model specifications have known simple mathematical forms, such correlations can be calculated mathematically. Actual public health data from NHANES 2007-2008 were used as examples to demonstrate the situations with unknown or complex correct model specification. Simulation of power for misspecified models confirmed the results based on correlation methods but also illustrated the effect of model degrees of freedom on power.^

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This data set contains measurements of dissolved organic carbon in samples of soil water collected from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In April 2002 glass suction plates with a diameter of 12 cm, 1 cm thickness and a pore size of 1-1.6 mm (UMS GmbH, Munich, Germany) were installed in depths of 10, 20, 30 and 60 cm to collect soil solution. The sampling bottles were continuously evacuated to a negative pressure between 50 and 350 mbar, such that the suction pressure was about 50 mbar above the actual soil water tension. Thus, only the soil leachate was collected. Cumulative soil solution was sampled biweekly and analyzed for dissolved organic carbon concentration by a high TOC elemental analyzer (Elementar Analysensysteme GmbH, Hanau, Germany). Samples were analyzed as soon as possible and stored at 4°C if necessary. Often in summer, no free soil solution was available for collection, especially in the upper soil layers. Annual mean values of measured biweekly concentrations of dissolved organic carbon are provided.

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This data set contains measurements of dissolved organic carbon in samples of soil water collected from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In April 2002 glass suction plates with a diameter of 12 cm, 1 cm thickness and a pore size of 1-1.6 mm (UMS GmbH, Munich, Germany) were installed in depths of 10, 20, 30 and 60 cm to collect soil solution. The sampling bottles were continuously evacuated to a negative pressure between 50 and 350 mbar, such that the suction pressure was about 50 mbar above the actual soil water tension. Thus, only the soil leachate was collected. Cumulative soil solution was sampled biweekly and analyzed for dissolved organic carbon concentration by a high TOC elemental analyzer (Elementar Analysensysteme GmbH, Hanau, Germany). Samples were analyzed as soon as possible and stored at 4°C if necessary. Often in summer, no free soil solution was available for collection, especially in the upper soil layers. Annual mean values of measured biweekly concentrations of dissolved organic carbon are provided.

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This data set contains measurements of dissolved organic carbon in samples of soil water collected from the main experiment plots of a large grassland biodiversity experiment (the Jena Experiment; see further details below). In the main experiment, 82 grassland plots of 20 x 20 m were established from a pool of 60 species belonging to four functional groups (grasses, legumes, tall and small herbs). In May 2002, varying numbers of plant species from this species pool were sown into the plots to create a gradient of plant species richness (1, 2, 4, 8, 16 and 60 species) and functional richness (1, 2, 3, 4 functional groups). Plots were maintained by bi-annual weeding and mowing. In April 2002 glass suction plates with a diameter of 12 cm, 1 cm thickness and a pore size of 1-1.6 mm (UMS GmbH, Munich, Germany) were installed in depths of 10, 20, 30 and 60 cm to collect soil solution. The sampling bottles were continuously evacuated to a negative pressure between 50 and 350 mbar, such that the suction pressure was about 50 mbar above the actual soil water tension. Thus, only the soil leachate was collected. Cumulative soil solution was sampled biweekly and analyzed for dissolved organic carbon concentration by a high TOC elemental analyzer (Elementar Analysensysteme GmbH, Hanau, Germany). Samples were analyzed as soon as possible and stored at 4°C if necessary. Often in summer, no free soil solution was available for collection, especially in the upper soil layers. Annual mean values of measured biweekly concentrations of dissolved organic carbon are provided.