Fire responses and resistance of concrete-filled steel tubular frame structures

This paper presents the results of dynamic responses and fire resistance of concretefilled steel tubular (CFST) frame structures in fire conditions by using non-linear finite element method. Both strength and stability criteria are considered in the collapse analysis. The frame structures are constructed with circular CFST columns and steel beams of I-sections. In order to validate the finite element solutions, the numerical results are compared with those from a fire resistance test on CFST columns. The finite element model is then adopted to simulate the behaviour of frame structures in fire. The structural responses of the frames, including critical temperature and fire-resisting limit time, are obtained for the ISO-834 standard fire. Parametric studies are carried out to show their influence on the load capacity of the frame structures in fire. Suggestions and recommendations are presented for possible adoption in future construction and design of these structures

Zero Field precession and hysteretic threshold currents in spin torque oscillators with tilted polarizer

Using non-linear system theory and numerical simulations we map out the static and dynamic phase diagram in zero applied field of a spin torque oscillator with a tilted polarizer (TP-STO).We find that for sufficiently large currents, even very small tilt angles (beta>1 degree) will lead to steady free layer precession in zero field. Within a rather large range of tilt angles, 1 degree< beta <19 degree, we find coexisting static states and hysteretic switching between these using only current. In a more narrow window (1 degree<beta<5 degree) one of the static states turns into a limit cycle (precession). The coexistence of static and dynamic states in zero magnetic field is unique to the tilted polarizer and leads to large hysteresis in the upper and lower threshold currents for TP-STO operation.Comment: 5 pages, 4 figure

KDM2B/FBXL10 targets c-Fos for ubiquitylation and degradation in response to mitogenic stimulation.

KDM2B (also known as FBXL10) controls stem cell self-renewal, somatic cell reprogramming and senescence, and tumorigenesis. KDM2B contains multiple functional domains, including a JmjC domain that catalyzes H3K36 demethylation and a CxxC zinc-finger that recognizes CpG islands and recruits the polycomb repressive complex 1. Here, we report that KDM2B, via its F-box domain, functions as a subunit of the CUL1-RING ubiquitin ligase (CRL1/SCF(KDM2B)) complex. KDM2B targets c-Fos for polyubiquitylation and regulates c-Fos protein levels. Unlike the phosphorylation of other SCF (SKP1-CUL1-F-box)/CRL1 substrates that promotes substrates binding to F-box, epidermal growth factor (EGF)-induced c-Fos S374 phosphorylation dissociates c-Fos from KDM2B and stabilizes c-Fos protein. Non-phosphorylatable and phosphomimetic mutations at S374 result in c-Fos protein which cannot be induced by EGF or accumulates constitutively and lead to decreased or increased cell proliferation, respectively. Multiple tumor-derived KDM2B mutations impaired the function of KDM2B to target c-Fos degradation and to suppress cell proliferation. These results reveal a novel function of KDM2B in the negative regulation of cell proliferation by assembling an E3 ligase to targeting c-Fos protein degradation that is antagonized by mitogenic stimulations

Unraveling substrate dynamics and identifying inhibitors in hydrolysates of lignocellulosic biomass by exometabolomics

Lignocellulosic biomass is the 2nd generation feedstock for biofuel production through fermentation processes. The material has a rigid structure, which needs to be broken down by a pretreatment procedure to expose cellulose for hydrolysis. The hydrolysis products, so called biomass hydrolysates, contain next to the sugar monomers, toxic compounds released and formed during the pretreatment process. These compounds inhibit the growth of the fermenting host(s). To improve the fermentability of biomass hydrolysates, identification of these inhibitory compounds is of great importance. Chapter 1 of this thesis reviews the approaches and techniques that have been used to study the inhibitors in various biomass hydrolysates, and introduces a non-targeted methodology to systematically identify biomass hydrolysate inhibitors: the exometabolomics approach. To identify hydrolysate inhibitors through an exometabolomics approach, a wide range of biomass hydrolysates needs to be prepared. Chapter 2 describes the detailed procedures of four pretreatment methods and the overall fermentability of the generated hydrolysates. The hydrolysis efficiency of the carbohydrate polymers in pretreated biomass was analyzed by using high-performance anion-exchange chromatography coupled with mass spectrometry (HPAEC-MS), and the results of this analysis are presented in Chapter 3. The last three chapters of the thesis focus on identifying inhibitory compounds in lignocellulosic biomass hydrolysates and studying their effects on fermenting yeasts during fermentation processes. Chapter 4 examines the fermentability of a series of biomass hydrolysates, in relation to the presence and dynamics of a target group of inhibitors in these hydrolysates. Chapter 5 reports the detailed experimental procedure and results of the actual exometabolomics approach introduced in Chapter 1. The research question, identification of inhibitors in biomass hydrolysates, was answered by statistically correlating the fermentability of different biomass hydrolysates with their biochemical compositions. Finally, in search for potential ethanologenic host organisms resistant to biomass hydrolysate inhibitors, a Pichia anomala strain was isolated. In Chapter 6, the properties and fermentation performance of this strain in biomass hydrolysates were tested. Through further research and possibly genetic modifications, the strain has the potential to become a suitable yeast for fermenting lignocellulosic biomass hydrolysates.Netherlands Metabolomics Centre (NMC)UBL - phd migration 201

The NMR of High Temperature Superconductors without Anti-Ferromagnetic Spin Fluctuations

A microscopic theory for the NMR anomalies of the planar Cu and O sites in superconducting La_1.85Sr_0.15CuO_4 is presented that quantitatively explains the observations without the need to invoke anit-ferromagnetic spin fluctuations on the planar Cu sites and its significant discrepancy with the observed incommensurate neutron spin fluctuations. The theory is derived from the recently published ab-initio band structure calculations that correct LDA computations tendency to overestimate the self-coulomb repulsion for the half-filled Cu d_x2-y2 orbital for these ionic systems. The new band structure leads to two bands at the Fermi level with holes in the Cu d_z2 and apical O p_z orbitals in addition to the standard Cu d_x2-y2 and planar O p_sigma orbitals. This band structure is part of a new theory for the cuprates that explains a broad range of experiments and is based upon the formation of Cooper pairs comprised of a k up spin electron from one band and a -k down spin electron from another band (Interband Pairing Model).Comment: In Press, Journal of Physical Chemistry. See also http://www.firstprinciples.com. Minor changes to references and figure readabilit

Superconducting Order Parameter in Bi-Layer Cuprates: Occurrence of π\pi Phase Shifts in Corner Junctions

We study the order parameter symmetry in bi-layer cuprates such as YBaCuO, where interesting $\pi$ phase shifts have been observed in Josephson junctions. Taking models which represent the measured spin fluctuation spectra of this cuprate, as well as more general models of Coulomb correlation effects, we classify the allowed symmetries and determine their associated physical properties. $\pi$ phase shifts are shown to be a general consequence of repulsive interactions, independent of whether a magnetic mechanism is operative. While it is known to occur in d-states, this behavior can also be associated with (orthorhombic) s-symmetry when the two sub-band gaps have opposite phase. Implications for the magnitude of $T_c$ are discussed.Comment: 5 pages, RevTeX 3.0, 9 figures (available upon request

Scalable Influence Maximization for Multiple Products in Continuous-Time Diffusion Networks

A typical viral marketing model identifies influential users in a social network to maximize a single product adoption assuming unlimited user attention, campaign budgets, and time. In reality, multiple products need campaigns, users have limited attention, convincing users incurs costs, and advertisers have limited budgets and expect the adoptions to be maximized soon. Facing these user, monetary, and timing constraints, we formulate the problem as a submodular maximization task in a continuous-time diffusion model under the intersection of a matroid and multiple knapsack constraints. We propose a randomized algorithm estimating the user influence in a network ($|\mathcal{V}|$ nodes, $|\mathcal{E}|$ edges) to an accuracy of $\epsilon$ with $n=\mathcal{O}(1/\epsilon^2)$ randomizations and $\tilde{\mathcal{O}}(n|\mathcal{E}|+n|\mathcal{V}|)$ computations. By exploiting the influence estimation algorithm as a subroutine, we develop an adaptive threshold greedy algorithm achieving an approximation factor $k_a/(2+2 k)$ of the optimal when $k_a$ out of the $k$ knapsack constraints are active. Extensive experiments on networks of millions of nodes demonstrate that the proposed algorithms achieve the state-of-the-art in terms of effectiveness and scalability