Structural basis of biological nitrogen fixation

Biological nitrogen fixation is mediated by the nitrogenase enzyme system that catalyses the ATP dependent reduction of atmospheric dinitrogen to ammonia. Nitrogenase consists of two component metalloproteins, the MoFe-protein with the FeMo-cofactor that provides the active site for substrate reduction, and the Fe-protein that couples ATP hydrolysis to electron transfer. An overview of the nitrogenase system is presented that emphasizes the structural organization of the proteins and associated metalloclusters that have the remarkable ability to catalyse nitrogen fixation under ambient conditions. Although the mechanism of ammonia formation by nitrogenase remains enigmatic, mechanistic inferences motivated by recent developments in the areas of nitrogenase biochemistry, spectroscopy, model chemistry and computational studies are discussed within this structural framework.     

Vertical distribution of sediment enzyme activities involved in the cycling of carbon, nitrogen, phosphorus and sulphur in three boreal rural lakes

Vertical distribution of eleven hydrolytic enzyme activities were investigated with fluorogenic model substrates in boreal rural lake sediments, Lake Uurainen (13 km(2)), Lake J?mij?rvi (9 km(2)) and Lake Pyylampi (0.068 km(2)), in Finland. The eleven hydrolytic enzyme activities were high into deep sediment layers indicating potential for turnover of organic matter in the permanently anoxic zones. The activities of beta-glucosidase, sulphatase and N-acetyl-glucosaminidase were similar in the three lakes independent on the ecological status of the lake. Acetate- and butyrate-esterase were more active than the other enzymes in the three lakes. These unspecific esterases had sediment activities in forest Lake Pyylampi close to those reported for boreal coniferous forest soils in Finland. Similar beta-cellobiosidase activities throughout the sediment depths indicated constant depolymerisation potential for cellulose.     

Mathematical foundations of the quasistatic approximation in reactor physics

The quasistatic method used in reactor-physics calculations is applied to a model integro-differential equation in a Banach space. The resulting quasistatic equations are shown to be locally consistent with the original initial-value problem. An iterative scheme to solve these equations is presented and shown to be convergent.     

Diagnosing diabetic nephropathy by 1H NMR metabonomics of serum

Object: The most severe complication of type 1 diabetes (T1DM) is diabetic nephropathy. It is associated with a high risk of cardiovascular complications and premature death and requires early detection to be efficiently treated. The clinical practice to diagnose diabetic nephropathy is also a non-optimal and tedious set up based on albumin excretion rate in multiple overnight or 24h urine samples. Conversely, in this study, these independent diagnostic data are used to provide a realistic testing case for applying ¹H NMR metabonomics of serum in a diagnostic fashion. Materials and Methods: 182 T1DM and 21 non-diabetic (non-T1DM) individuals were studied. The ¹H NMR of serum at 500 MHz was targeted at two molecular windows: lipoprotein lipids and low-molecular-weight metabolites. Results: T1DM and non-T1DM individuals were exclusively separated by ¹H NMR. For diabetic nephropathy diagnosis in the T1DM patients, ¹H NMR data (and clinical biochemistry data) gave a sensitivity of 87.1% (83.9%) and a specificity of 87.7% (95.9%). The predictive values of positive and negative tests were 89.0% (95.5%) and 83.6% (79.2%), respectively. Conclusions: ¹H NMR metabonomics clearly distinguishes metabolic characteristics of T1DM and appears approximately as good a means to diagnose diabetic nephropathy from serum as an advanced set of biochemical variables.     

The use of an impure inorganic precursor for the synthesis of highly siliceous mesoporous materials under acidic conditions

Highly ordered mesoporous silica materials have been synthesized under acidic conditions using an industrial waste-product containing only 42 wt% silica as the precursor, using formic acid as pH-regulator. Non-ionic tri-block-co-polymers of the ABA type were used as the structure-directing agents, and high-quality SBA-15 and KIT-5 materials were obtained. The materials were characterized by small-angle X-ray diffraction, nitrogen physisorption, transmission electron microscopy, and elemental analysis. The methodology presented here is suggested to be widely applicable for the synthesis of siliceous materials using other impure inorganic silica precursors with different purity, as long as the precursors are soluble under acidic conditions.     

Experimental trends of NO in circulating fluidized bed combustion

Experimental trends for the dependence of CO, NO and N₂O emissions on bed temperature and oxygen concentration in circulating fluidized bed combustion (CFB) are presented. The main focus is on the nitrogen emission formation in the lower furnace area. A test campaign including seven tests with a laboratory scale CFB test rig were carried out to produce appropriate data of the phenomena. These experiments show that NO emissions above the dense bed decrease with decreasing temperature or oxygen concentration. Instead, N₂O emissions increase when the bed temperature is decreased and decrease when the oxygen concentration is decreased. These trends can partly be explained by heterogeneous reactions between NO and char, since decrease in temperature or oxygen concentration increases the bed char inventory. However, oxygen and temperature also affect directly on NO emissions. Correlations for the CO, NO, N₂O, NH₃ and HCN concentrations at the exit of dense bed were developed. This type of correlations can, among other things, be applied as boundary conditions to the more sophisticated CFD models that are usually applied to modelling of diluted part of the furnace. CFD modelling of the dense bed area is complicated and accuracy is not sufficient, thus simplified experimental correlations can aid in the development of furnace design towards better emission performance.     

DTI segmentation by statistical surface evolution

We address the problem of the segmentation of cerebral white matter structures from diffusion tensor images (DTI). A DTI produces, from a set of diffusion-weighted MR images, tensor-valued images where each voxel is assigned with a 3 x 3 symmetric, positive-definite matrix. This second order tensor is simply the covariance matrix of a local Gaussian process, with zero-mean, modeling the average motion of water molecules. As we will show in this paper, the definition of a dissimilarity measure and statistics between such quantities is a nontrivial task which must be tackled carefully. We claim and demonstrate that, by using the theoretically well-founded differential geometrical properties of the manifold of multivariate normal distributions, it is possible to improve the quality of the segmentation results obtained with other dissimilarity measures such as the Euclidean distance or the Kullback-Leibler divergence. The main goal of this paper is to prove that the choice of the probability metric, i.e., the dissimilarity measure, has a deep impact on the tensor statistics and, hence, on the achieved results. We introduce a variational formulation, in the level-set framework, to estimate the optimal segmentation of a DTI according to the following hypothesis: Diffusion tensors exhibit a Gaussian distribution in the different partitions. We must also respect the geometric constraints imposed by the interfaces existing among the cerebral structures and detected by the gradient of the DTI. We show how to express all the statistical quantities for the different probability metrics. We validate and compare the results obtained on various synthetic data-sets, a biological rat spinal cord phantom and human brain DTIs.     

Generation of urban road dust from anti-skid and asphalt concrete aggregates

Road dust forms an important component of airborne particulate matter in urban areas. In many winter cities the use of anti-skid aggregates and studded tires enhance the generation of mineral particles. The abrasion particles dominate the PM10 during springtime when the material deposited in snow is resuspended. This paper summarizes the results from three test series performed in a test facility to assess the factors that affect the generation of abrasion components of road dust. Concentrations, mass size distribution and composition of the particles were studied. Over 90% of the particles were aluminosilicates from either anti-skid or asphalt concrete aggregates. Mineral particles were observed mainly in the PM10 fraction, the fine fraction being 12% and submicron size being 6% of PM10 mass. The PM10 concentrations increased as a function of the amount of anti-skid aggregate dispersed. The use of anti-skid aggregate increased substantially the amount of PM10 originated from the asphalt concrete. It was concluded that anti-skid aggregate grains contribute to pavement wear. The particle size distribution of the anti-skid aggregates had great impact on PM10 emissions which were additionally enhanced by studded tires, modal composition, and texture of anti-skid aggregates. The results emphasize the interaction of tires, anti-skid aggregate, and asphalt concrete pavement in the production of dust emissions. They all must be taken into account when measures to reduce road dust are considered. The winter maintenance and springtime cleaning must be performed properly with methods which are efficient in reducing PM10 dust.     

运转平稳行星减速器的模块系统

 在2004年汉诺威博览会上,时代(Zeitlauf)公司首次展出了具有实际意义的行星减速器结构系列“Performax”。该系列由于高运转平稳性、高功率密度和高寿命,在市场上脱颖而出。结构系列一直是按照模块系统建造的,从而明显地减少了必需的组件数和加工步骤。     

多层帘式涂布和一种新型压光技术

帘式涂布是一种低冲击预计量涂布方式,可用于纸和纸板的涂布、帘式涂布技术所产生的涂层为仿形涂层,因而能提供良好的纤维覆盖。在多层帘式涂布中,可以同时进行多层涂布。与单层帘式涂布相比,多层帘式涂布具有许多优点：投资成本更低、设计不同涂层性质更具灵活性、具有更大的涂布操作空间及涂层更薄等,