Dynamic rheological measurements on heat-induced myosin gels: An evaluation of the method's suitability for the filamentous gels

Formation of bovine myosin gels (10 mg ml^?1) by heat treatment at pH 6 and an ionic strength of 0.24 M has been monitored by using the Bohlin Rheometer System in the oscillatory mode. Rheological thermograms were determined with a general repeatability of about 2% for a given suspension. A pronounced maximum and an accompanying minimum in storage modulus (G′) were found at about 50 and 55°C, respectively. The thermograms for the loss modulus (G″) and the phase angle (δ) displayed complex behaviour as well, suggesting a multitransition process. Presumably, denaturational events in parts of the molecule are responsible for the complex rheology observed. This complexity is not related to trivial wall slippage as data obtained from cells with different gap sizes were highly reproducible and consistent with other measurements. A decrease in heating rate from 2.5 to 0.1°C min^?1 had a large effect on G′; it increased from 905 to 1600 N m^?2 for gels at 75°C. The phase angle was also affected by the heating rate, especially at about 55°C. The effect of increasing the strain from 0.003 to about 0.1 was significant in two temperature regions; G′ at temperatures higher than 65°C and δ at temperatures lower than 54°C increased with increasing strain.     

Understanding the scalability of Bayesian network inference using clique tree growth curves

One of the main approaches to performing computation in Bayesian networks (BNs) is clique tree clustering and propagation. The clique tree approach consists of propagation in a clique tree compiled from a BN, and while it was introduced in the 1980s, there is still a lack of understanding of how clique tree computation time depends on variations in BN size and structure. In this article, we improve this understanding by developing an approach to characterizing clique tree growth as a function of parameters that can be computed in polynomial time from BNs, specifically: (i) the ratio of the number of a BN's non-root nodes to the number of root nodes, and (ii) the expected number of moral edges in their moral graphs. Analytically, we partition the set of cliques in a clique tree into different sets, and introduce a growth curve for the total size of each set. For the special case of bipartite BNs, there are two sets and two growth curves, a mixed clique growth curve and a root clique growth curve. In experiments, where random bipartite BNs generated using the BPART algorithm are studied, we systematically increase the out-degree of the root nodes in bipartite Bayesian networks, by increasing the number of leaf nodes. Surprisingly, root clique growth is well-approximated by Gompertz growth curves, an S-shaped family of curves that has previously been used to describe growth processes in biology, medicine, and neuroscience. We believe that this research improves the understanding of the scaling behavior of clique tree clustering for a certain class of Bayesian networks; presents an aid for trade-off studies of clique tree clustering using growth curves; and ultimately provides a foundation for benchmarking and developing improved BN inference and machine learning algorithms.     

Dust and the Sick Building Syndrome

Background. In the Danish Town Hall Study" it has previously been shown that the sick building syndrome is a widespread phenomenon. This has given rise to speculations as to whether biologically active components in dust or whether absorbed organic gases and vapours in the indoor climate may be partly responsible for the sick building syndrome. Therefore, we wished to study whether qualitative conditions in dust, of a physical, chemical, and biological nature, are related to the prevalence of symptoms of the sick building syndrome. Material and methods. The study included 12 town halls in the Copenhagen area. A total of 870 persons participated, 584 women and 286 men. All the participants filled out a questionnaire regarding health and working conditions, and dust samples were collected with a special vacuum cleaner in the working environment of the participants, after which the contents of inorganic and organic particles as well as of human source fragments the (hair, nails, skin) and various fibres were determined. Results. There was a significant correlation (P<0.05) between the prevalence of gram-negative bacteria in the indoor climate dust, and general symptoms (fatigue, heavy-headedness, headache, dizziness, concentration problems) (corr.coeff.=0.73), as well as symptoms from the mucous membranes of the upper respiratory tract (corr.coeff.=0.76). Also, there was a significant relation between the prevalence of particles in the dust and the prevalence of symptoms from the mucous membranes (corr.coeff.=0.81). There was a strong and significant correlation between the total amount of volatile organic components (TVOC) and lack of concentration (corr.coeff. =0.85) and feeling heavy-headed (corr.coeff.=0.72). Macromolecular dust (potentially allergenetic material) was significantly correlated to the prevalence of headache and general malaise/dizziness (corr.coeff.=0.66), while the ability of the dust to liberate histamine was significantly related to the prevalence of general malaise, dizziness (corr.coeff.=0.65) and lack of concentration (corr.coeff. =0.58). Further analyses including a number of potential confounders did not change the results of the above analyses. Conclusion. The results of this study support the hypothesis that qualitative properties of dust are important to the sick building syndrome. The study was based on relatively few buildings, but nevertheless strong correlations were found. In perspective, epidemiological intervention studies should be carried out to investigate whether minimizing the amount of both dust and bacteria in the indoor climate affect the prevalence of sick building syndrome.     

Identification of metabolic bone disease in patients with endogenous hyperthyroidism: role of biological markers of bone turnover

Active hyperthyroidism is associated with reduced bone mass. Nevertheless, not all patients show the same risk for developing osteoporosis. Our aim was to analyze some clinical and biochemical potential predictors of low bone mass in hyperthyroid patients. We studied 127 consecutive hyperthyroid patients (110 females, 17 males; aged 42 +/- 16 years). Bone mineral density (BMD) was measured by dual X-ray absorptiometry (DXA) at lumbar spine (LS; L2-L4) and femoral neck (FN). Data were expressed as g/cm2 and T-score. Patients were placed into two groups based on recent WHO criteria: Group A, no osteoporosis (n = 98); and group B, lumbar or femoral osteoporosis (n = 29). Study protocol included evaluation of osteoporosis risk factors, anthropometrical variables, thyroid function, and bone turnover markers. Receiver-operating characteristic (ROC) plots for the precision of bone markers and multivariate analysis for the prediction of BMD and osteoporosis were performed. Group B showed greater age and proportion of menopausal females; lower weight, height, and calcium intake; longer duration of menopause; and greater levels of total and bone alkaline phosphatase and of urine hydroxyproline. No differences in thyroid function, osteocalcin, tartrate-resistant acid phosphatase, and type I collagen C-telopeptide (ICTP) were found. The best predictive model accounted for 46% and 62% of the variability of lumbar and femoral BMD respectively and correctly classified 89% of the osteoporotic hyperthyroid patients. No significant difference in ROC plots was observed. It is concluded that hyperthyroid patients with lumbar or femoral osteoporosis show a typical clinical and biochemical profile illustrating that the relationship between BMD and bone markers is better in high turnover states. Classical bone turnover markers show high performance in the evaluation of hyperthyroid bone disease.     

Synthesis and Measurement of the Thermoelectric Properties of Multiphase Composites: ZnSb Matrix with Zn4Sb3, Zn3P2, and Cu5Zn8

We synthesized a series of samples with composition around 52 at.% zinc (Zn), 44 at.% antimony (Sb), 4 at.% phosphorus (P), and up to 3 at.% copper (Cu) by melting the elements and subsequent annealing. This resulted in dense and almost crack-free samples. X-ray powder diffraction (XRD) and scanning electron microscopy (SEM) revealed composites with a majority phase of ZnSb containing varying amounts of Zn₃P₂ and Cu₅Zn₈, in addition to Zn₄Sb₃ in some of the samples. We measured the Seebeck coefficient, electrical conductivity, and thermal conductivity as a function of temperature. The thermoelectric performance tended to improve with increasing Cu content. At Cu content of 2 at.%, a reduced resistivity allows for the highest dimensionless figure of merit, with a maximum zT value of 0.18 at around 573 K.     

Sorption-controlled degradation kinetics of MCPA in soil

The relationship between sorption strength and degradation kinetics has been studied for the pesticide MCPA in a sandy top- and subsoil. After adding two types of sorbents (crushed peat and activated carbon) in various amounts to the sandy soils, sorption, desorption, and mineralization of 14C-MCPA were measured. The obtained Freundlich constants (KF) varied between 0.7 and 27.2 mg(1-nF) x L(nF)/kg, and the first-order mineralization rate constants varied between 0.001 and 0.128 d(-1). The results showed an inverse relationship between sorption strength and mineralization. A higher KF value corresponded to a smaller mineralization rate and less mineralization. A correlation coefficient of r2 = 0.934 between the log-transformed Freundlich desorption coefficient (K(F,des)) and the log-transformed mineralization rate constant (k) was obtained. After 7, 14, 22, and 35 days of incubation, soil samples were consecutively extracted by water, methanol, and 5 M NaOH to separate the remaining 14C into 3 different pools. The extractions showed that the mineralization only proceeded from the water extractable pool of MCPA. Thin-layer chromatography revealed a formation of small amounts of metabolites; <7% of initially added 14C was present as other compounds than 14C-MCPA in the water and methanol extractable pools. The study showed mineralization to be strongly correlated with sorption, represented by the desorption coefficient, and hence stresses the significance of bonding strength for estimating pesticide degradation in soil.     

Efficient use of iterative solvers in nested topology optimization

In the nested approach to structural optimization, most of the computational effort is invested in the solution of the analysis equations. In this study, it is suggested to reduce this computational cost by using an approximation to the solution of the analysis problem, generated by a Krylov subspace iterative solver. By choosing convergence criteria for the iterative solver that are strongly related to the optimization objective and to the design sensitivities, it is possible to terminate the iterative solution of the nested equations earlier compared to traditional convergence measures. The approximation is computationally shown to be sufficiently accurate for the purpose of optimization though the nested equation system is not necessarily solved accurately. The approach is tested on several large-scale topology optimization problems, including minimum compliance problems and compliant mechanism design problems. The optimized designs are practically identical while the time spent on the analysis is reduced significantly.     

Effects of road lighting: An analysis based on Dutch accident statistics 1987-2006

This study estimates the safety effect of road lighting on accidents in darkness on Dutch roads, using data from an interactive database containing 763,000 injury accidents and 3.3 million property damage accidents covering the period 1987-2006. Two estimators of effect are used, and the results are combined by applying techniques of meta-analysis. Injury accidents are reduced by 50%. This effect is larger than the effects found in most of the earlier studies. The effect on fatal accidents is slightly larger than the effect on injury accidents. The effect during twilight is about 2/3 of the effect in darkness. The effect of road lighting is significantly smaller during adverse weather and road surface conditions than during fine conditions. The effects on pedestrian, bicycle and moped accidents are significantly larger than the effects on automobile and motorcycle accidents. The risk of injury accidents was found to increase in darkness. The average increase in risk was estimated to 17% on lit rural roads and 145% on unlit rural roads. The average increase in risk during rainy conditions is about 50% on lit rural roads and about 190% on unlit rural roads. The average increase in risk with respect to pedestrian accidents is about 140% on lit rural roads and about 360% on unlit rural roads.