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The VDR BsmI polymorphism may have a protective role against the development of osteoporosis.

Using the forced-oscillation method, we measure the dispersion of Young's modulus, extensional attenuation, and Poisson's ratio of tight sandstone and carbonate samples at seismic frequencies (1-1000 Hz) under a constant confining pressure of 20 MPa and for a water saturation varying between 0% and 100%. The experimental data suggest that the dispersion of Young's modulus and attenuation of tight rocks is significant in a broad frequency band spanning over 1-1000 Hz. A comparison with the high-porosity and high-permeability sample data shows a contrasting dispersion and attenuation characteristics. For the tight sandstone, Young's modulus reaches a maximum dispersion of 16% at 60% water saturation and a 13% dispersion at 100% saturation. Attenuation is insignificant in dry condition and for water saturation ≤30%. In contrast with the peak attenuation occurring at very high water saturation (e.g., 80-100%) in partially saturated high-porosity rocks, peak attenuation of tight sandstone takes place at a water saturation of 60%. For the tight carbonate, the magnitude of dispersion (~3%) and attenuation are markedly lower for all saturation levels. In the explored frequency range (1-1000 Hz), Young's modulus increases monotonously, and no obvious attenuation peak is observed when saturation levels are greater than 10%. Using well-established theoretical models based on physical properties and microstructure of the tested rocks, we suggest that the observed attenuation characteristics are possibly attributed to the combined physical mechanism of microscopic (squirt) flow, mesoscopic flow in partially saturated rock, and shear dispersion due to viscous flow in grain contacts. Key Points:• Dispersion and attenuation of both tight sandstone and carbonate are distributed across frequency range of 1-1000 Hz • Extensional attenuation in tight sandstone is saturation dependent with a maximum at 60% saturation, which contrasts with that of porous sandstones • The coupled pore fabric and fluid distribution heterogeneity in tight rocks might cause complex dispersion and attenuation characteristics

This work aimed to compare the stress distribution and mechanical properties of our bridge combined fixation system and commonly used metal locking plate screw system by finite element analysis and by using the Zwick/Z100 testing machine. In addition, we also investigated the clinical outcome of our bridge combined fixation system for femoral fractures in 59 patients from June 2005 to January 2013. As a result, the stress distribution in the bone plate and screws of metal locking plate screw system during walking and climbing stairs was significantly lower than that of metal locking plate screw system. No significant difference in the displacement was observed between two systems. The equivalent bending stiffness of bridge combined fixation system was significantly lower than that of metal locking plate screw system. There were no significant differences in the bending strength, yield load, and maximum force between two systems. All the cases were followed up for 12-24 months (average 18 months). The X-ray showed bone callus was formed in most patients after 3 months, and the fracture line was faint and disappeared at 6-9 months postoperatively. No serious complications, such as implant breakage and wound infection, occurred postoperatively. According to self-developed standard for bone healing, clinical outcomes were rated as excellent or good in 55 out of 59 patients (success rate: 93.2%). Therefore, our findings suggest that our bridge combined fixation system may be a promising approach for treatment of long-bone fractures.

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Traditional ensemble learning approaches explore the feature space and the sample space, respectively, which will prevent them to construct more powerful learning models for noisy real-world dataset classification. The random subspace method only search for the selection of features. Meanwhile, the bagging approach only search for the selection of samples. To overcome these limitations, we propose the hybrid incremental ensemble learning (HIEL) approach which takes into consideration the feature space and the sample space simultaneously to handle noisy dataset. Specifically, HIEL first adopts the bagging technique and linear discriminant analysis to remove noisy attributes, and generates a set of bootstraps and the corresponding ensemble members in the subspaces. Then, the classifiers are selected incrementally based on a classifier-specific criterion function and an ensemble criterion function. The corresponding weights for the classifiers are assigned during the same process. Finally, the final label is summarized by a weighted voting scheme, which serves as the final result of the classification. We also explore various classifier-specific criterion functions based on different newly proposed similarity measures, which will alleviate the effect of noisy samples on the distance functions. In addition, the computational cost of HIEL is analyzed theoretically. A set of nonparametric tests are adopted to compare HIEL and other algorithms over several datasets. The experiment results show that HIEL performs well on the noisy datasets. HIEL outperforms most of the compared classifier ensemble methods on 14 out of 24 noisy real-world UCI and KEEL datasets.

Pore structure determines the ability of fluid storage and migration in rocks, expressed as porosity and permeability in the macroscopic aspects, and the pore throat radius in the microcosmic aspects. However, complex pore structure and strong heterogeneity make the accurate description of the tight sandstone reservoir of the Triassic Yanchang Formation, Ordos Basin, China still a problem. In this paper, mercury injection capillary pressure (MICP) parameters were applied to characterize the heterogeneity of pore structure, and three types of pore structure were divided, from high to low quality and defined as Type I, Type II and Type III, separately. Then, the multifractal analysis based on the MICP data was conducted to investigate the heterogeneity of the tight sandstone reservoir. The relationships among physical properties, MICP parameters and a series of multifractal parameters have been detailed analyzed. The results showed that four multifractal parameters, singularity exponent parameter (αmin), generalized dimension parameter (Dmax), information dimension (D1), and correlation dimension (D2) were in good correlations with the porosity and permeability, which can well characterize the pore structure and reservoir heterogeneity of the study area, while the others didn’t respond well. Meanwhile, there also were good relationships between these multifractal and MICP parameters.

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