Seismic design of special moment‐resisting steel frame with prevention of soft‐storey mechanism failure

Most structures with masonry infills that are continuous along their height, which are interrupted in the lowest storey, are damaged by earthquakes. These structures are anticipated to collapse due to the undesirable soft‐storey mechanism formed by lateral stiffness of masonry infills in other storeys. The seismic design criteria of UBC97 code for special moment‐resisting steel frame (SMRSF) are reviewed. In this paper, a new criterion for seismic design of such structures is presented. The proposed criteria are used to design three SMRSFs: 5, 8 and 15 storeys. Nonlinear time‐history dynamic analyses are applied for the designed SMRSFs based on the proposed criteria. Displacements and storey drifts, which are obtained by the proposed method, are compared with nonlinear time‐history dynamic analysis results, finally. Copyright © 2011 John Wiley & Sons, Ltd.     

Effect of soft‐storey mechanism caused by infill elimination on displacement demand in nonlinear static procedure using coefficient method

In recent earthquakes, many buildings have been damaged due to the soft‐storey mechanism failure. The seismic design codes for buildings do not contain enough criteria to predict the real displacement of such buildings. This paper focuses on evaluating the nonlinear displacement of buildings that fail in soft‐storey mechanism form. Results show that the nonlinear static procedure with coefficient method, which is described in Chapter 3 of ASCE/SEI 41‐06, does not have sufficient accuracy for estimation of structure displacement demand in such buildings. In this paper, the coefficient methodology is used for evaluating the target displacement for 5‐storey, 8‐storey and 15‐storey special moment resisting steel frames. For this purpose, dynamic nonlinear time‐history analysis has been applied for the mentioned structures having a soft‐storey mechanism failure form. The numerical results of storey displacement and interstorey drift were compared with those values obtained from the coefficient method described in Chapter 3 of ASCE/SEI 41‐06. Copyright © 2012 John Wiley & Sons, Ltd.     

Hydrodynamics of pulsed spouted beds: Effects of pulsation waveform,amplitude, and frequency

The effect of flow pulsations is studied via a discrete element model on hydrodynamics of spouted bed, which is being used in many important industries like drying processes. Decreased horizontal air percolation and preserving upward momentum, increased particle circulation, increased particle traverse distance, and better homogeneity are resulted from flow pulsations in spouted beds. Among the waveforms studied, square and triangular waveforms differ most and least from steady spouting, respectively. The predictions indicate that the pulsed spouted bed has the potential to enhance both gas and particle motion, hence being useful in drying and other operations.     

Thermal conductivity of the ionic liquid [HMIm][Tf2N] with compressed carbon dioxide

The liquid thermal conductivity of the ionic liquid (IL), 1-hexyl-3-methyl-imidazolium bis(trifluoromethylsulfonyl)amide ([HMIm][Tf₂N]), saturated with compressed vapor and supercritical carbon dioxide was measured over three isotherms (298.15, 323.15, and 348.15 K) and pressures up to approximately 20 MPa using a transient hot-wire technique. Pure [HMIm][Tf₂N] thermal conductivity was also measured over a temperature range of 293.15–353.15 K at ambient pressure and with hydrostatic pressure to approximately 20 MPa. Literature vapor–liquid equilibrium data were used to predict the liquid CO₂ composition at the conditions investigated. Initially, the liquid thermal conductivity slightly decreased with pressure/composition of CO₂ followed by a gradual increase that is mainly attributed to hydrostatic pressure effects. Simple composition-based mixing rules for mixture properties are not qualitatively nor quantitatively accurate. These data could be used to engineer heat transfer equipment required for a variety of proposed IL applications in CO₂ capture, absorption refrigeration, biphasic CO₂/IL reaction platforms, etc.     

Synthesis and dissolution behavior of nanosized silicon and magnesium co-doped fluorapatite obtained by high energy ball milling

Nanosized hydroxyapatite (HA) powders exhibit a greater surface area than coarser crystals and are expected to show an improved bioactivity. In addition, properties of HA can be tailored over a wide range by incorporating different ions into HA lattice. The aim of this study was to prepare and characterize silicon and magnesium co-doped fluorapatite (Si–Mg–FA) with a chemical composition of Ca_9.5Mg_0.5 (PO₄)_5.5(SiO₄)_0.5F₂ by the high-energy ball milling method. Characterization techniques such as X-ray diffraction analysis (XRD), Fourier transformed infrared spectroscopy (FTIR), energy dispersive X-ray spectroscopy (EDX) and transmission electron microscopy (TEM) were utilized to investigate the structural properties of the obtained powders. Dissolution behavior was evaluated in simulated body fluid (SBF) and physiological normal saline solution at 37 °C for up to 28 days. The results of XRD and FTIR showed that nanocrystalline single-phase Si–Mg–FA powders were synthesized after 12 h of milling. In addition, incorporation of magnesium and silicon into fluorapatite lattice decreased the crystallite size from 53 nm to 40 nm and increased the lattice strain from 0.220% to 0.296%. Dissolution studies revealed that Si–Mg–FA in comparison to fluorapatite (FA), releases more Ca, P and Mg ions into SBF during immersion. 175 ppm Ca, 33.5 ppm P and 48 ppm Mg were detected in the SBF containing Si–Mg–FA after 7days of immersion, while for FA, it was 75 ppm Ca, 21.5 ppm P and 29 ppm Mg. Release of these ions could improve the bioactivity of the obtained nanopowder. It could be concluded that the prepared nanopowders have structural properties such as crystallite size (~40 nm), crystallinity degree (~40%) and chemical composition similar to biological apatite. Therefore, prepared Si–Mg–FA nanopowders are expected to be appropriate candidates for bone substitution materials and also as a phase in polymer or ceramic-based composites for bone regeneration in tissue engineering applications.     

Polyunsaturated Fatty Acid-Enriched Lipid Fingerprint of Glioblastoma Proliferative Regions Is Differentially Regulated According to Glioblastoma Molecular Subtype

Glioblastoma (GBM) represents one of the deadliest tumors owing to a lack of effective treatments. The adverse outcomes are worsened by high rates of treatment discontinuation, caused by the severe side effects of temozolomide (TMZ), the reference treatment. Therefore, understanding TMZ’s effects on GBM and healthy brain tissue could reveal new approaches to address chemotherapy side effects. In this context, we have previously demonstrated the membrane lipidome is highly cell type-specific and very sensitive to pathophysiological states. However, little remains known as to how membrane lipids participate in GBM onset and progression. Hence, we employed an ex vivo model to assess the impact of TMZ treatment on healthy and GBM lipidome, which was established through imaging mass spectrometry techniques. This approach revealed that bioactive lipid metabolic hubs (phosphatidylinositol and phosphatidylethanolamine plasmalogen species) were altered in healthy brain tissue treated with TMZ. To better understand these changes, we interrogated RNA expression and DNA methylation datasets of the Cancer Genome Atlas database. The results enabled GBM subtypes and patient survival to be linked with the expression of enzymes accounting for the observed lipidome, thus proving that exploring the lipid changes could reveal promising therapeutic approaches for GBM, and ways to ameliorate TMZ side effects.     

网格环境下大批量作业提交管理系统

设计并实现了一个网格环境下满足大批量作业提交管理需要的图形系统,可以很好地克服命令行方式的困难,实现大批量作业的提交、管理和监控,该系统可以很好地应用于本地机群之上,并且易于扩展并应用到其他网格应用领域.     

Recent Developments in Predicting Impact and Shock Sensitivities of Energetic Materials （英）

Empirical, quantum mechanical and artificial neural network methods are three usual methods in recent years that were used to predict sensitivity of different classes of high explosives. Some recent developments in predicting sensitivity by various methods are reviewed and discussed for various classes of energetic materials.