Variability and uncertainty in empirical ground-motion prediction for probabilistic hazard and risk analyses

© The Author(s) 2015.The terms aleatory variability and epistemic uncertainty mean different things to people who routinely use them within the fields of seismic hazard and risk analysis. This state is not helped by the repetition of loosely framed generic definitions that actually inaccurate. The present paper takes a closer look at the components of total uncertainty that contribute to ground-motion modelling in hazard and risk applications. The sources and nature of uncertainty are discussed and it is shown that the common approach to deciding what should be included within hazard and risk integrals and what should be pushed into logic tree formulations warrants reconsideration. In addition, it is shown that current approaches to the generation of random fields of ground motions for spatial risk analyses are incorrect and a more appropriate framework is presented

Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting

For person re-identification, existing deep networks often focus on representation learning. However, without transfer learning, the learned model is fixed as is, which is not adaptable for handling various unseen scenarios. In this paper, beyond representation learning, we consider how to formulate person image matching directly in deep feature maps. We treat image matching as finding local correspondences in feature maps, and construct query-adaptive convolution kernels on the fly to achieve local matching. In this way, the matching process and results are interpretable, and this explicit matching is more generalizable than representation features to unseen scenarios, such as unknown misalignments, pose or viewpoint changes. To facilitate end-to-end training of this architecture, we further build a class memory module to cache feature maps of the most recent samples of each class, so as to compute image matching losses for metric learning. Through direct cross-dataset evaluation, the proposed Query-Adaptive Convolution (QAConv) method gains large improvements over popular learning methods (about 10%+ mAP), and achieves comparable results to many transfer learning methods. Besides, a model-free temporal cooccurrence based score weighting method called TLift is proposed, which improves the performance to a further extent, achieving state-of-the-art results in cross-dataset person re-identification. Code is available at https://github.com/ShengcaiLiao/QAConv.Comment: This is the ECCV 2020 version, including the appendi

A novel sliding mode controller for DC-DC boost converters under input/load variations

© 2015 IEEE. In this paper a simple sliding mode controller based on the averaging state space model is proposed for a DC-DC boost converter. It is demonstrated to be easily implemented and has time-variant sliding coefficients. The proposed controller can effectively regulate the output voltage by controlling the switch states (through the dynamic duty cycles) even when the input voltage, load or output command varies. Furthermore the controller is independent of the inductor current and the load, although the load value is needed when designing the sliding coefficients. The constant switching frequency is maintained thus simplifying the design procedure, enhancing the regulation properties and benefiting the filter design. The controller has good dynamic response, overshoot damping and robustness. Comparative simulations are carried in MATLAB/Simulink between the proposed approach and a widely used PID controller to verify the effectiveness and feasibility of the proposed method

An integrated native mass spectrometry and top-down proteomics method that connects sequence to structure and function of macromolecular complexes.

Mass spectrometry (MS) has become a crucial technique for the analysis of protein complexes. Native MS has traditionally examined protein subunit arrangements, while proteomics MS has focused on sequence identification. These two techniques are usually performed separately without taking advantage of the synergies between them. Here we describe the development of an integrated native MS and top-down proteomics method using Fourier-transform ion cyclotron resonance (FTICR) to analyse macromolecular protein complexes in a single experiment. We address previous concerns of employing FTICR MS to measure large macromolecular complexes by demonstrating the detection of complexes up to 1.8 MDa, and we demonstrate the efficacy of this technique for direct acquirement of sequence to higher-order structural information with several large complexes. We then summarize the unique functionalities of different activation/dissociation techniques. The platform expands the ability of MS to integrate proteomics and structural biology to provide insights into protein structure, function and regulation

Solid state NMR of salivary calculi: Proline-rich salivary proteins, citrate, polysaccharides, lipids, and organic–mineral interactions

Solid state NMR (ssNMR) can characterize mineral (31P) and organic (13C) components of human salivary stones (n = 8). All show apatitic 31P spectra. 13C ssNMR indicates more protein, of more consistent composition, than apatitic uroliths, with signals from Tyr, Phe and His prominent. Citrate and lipid, identified by dipolar dephasing (DD), and polysaccharides are also observable in varying amounts. 13C{31P} rotational echo double resonance (13C{31P} REDOR) identifies carbon atoms in close (< ca. 0.5 nm) proximity to phosphorus and therefore probably binding with mineral. Citrate, sugar and carboxylate signals undergo strong 13C{31P} REDOR, also seen to signals between 50 and 60 ppm, from protein α- carbons and, possibly, phosphoserines and phospholipids, and sometimes to a 35 – 40 ppm envelope containing Asp-Cβ and Glu-Cγ signals. Amino acid analysis indicates high proline and aromatic content. 13C ssNMR and amino acid composition is consistent with preponderance of proline-rich salivary proteins such as statherin.The U.K. EPSRC (Y. L.) and MRC (D. G. R.) for fundingThis is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.crci.2015.07.00

Relationships of trace gases and aerosols and the emission characteristics at Lin'an, a rural site in eastern China, during spring 2001

We present measurements of trace gases and fine aerosols obtained from a rural site in eastern China during 18 February to 30 April 2001. The field program aimed to characterize the variations in aerosol and gaseous pollutant concentrations and the emission signatures from the inland region of eastern China in the spring season. The data included O3, CO, NO, NOy*, SO2, methane, C2-C8 nonmethane hydrocarbons (NMHCs), C 1-C2 halocarbons, and the chemical composition of PM2.5. The average hourly mixing ratios (±standard deviation) of CO, SO2, and NOy* were 677 (±315) ppbv, 15.9 (±14.6) ppbv, and 13.8 (±7.2) ppbv, respectively. The mean daytime ozone mixing ratio was 41 (± 19) ppbv. The most abundant NMHC was ethane (3189 ± 717 pptv), followed by ethyne (2475 ± 1395 pptv), ethene (1679 ± 1455 pptv), and toluene (1529 ± 1608 pptv). Methyl chloride was the most abundant halocarbon (1108 ± 653 pptv). The average concentrations of particulate organic matter (POM, as organic carbon, OC, times 1.4) and elemental carbon (EC) in PM2.5 were 21.5 (±7) μg/m3 and 2.5 (±0.7) μg/m3, respectively, and sulfate and nitrate levels were 17.3 (±6.6) and 6.5 (±4) μg/m3, respectively. CO showed moderate to good correlation with NOy* (r2 = 0.59), OC (r2 = 0.65), CH3Cl (r2 = 0.59), soluble potassium (r2 = 0.53), and many NMHCs, indicating contributions from the burning of biofuel/biomass. CO also correlated with an industrial tracer, C2Cl4, indicative of some influence from industrial sources. SO2, on the other hand, correlated well with EC (r2 = 0.56), reflecting the contribution from the burning of coal. Ammonium was sufficiently abundant to fully neutralize sulfate and nitrate, indicating that there were strong emissions of ammonia from agricultural activities. Silicon and calcium had poor correlations with iron and aluminum, revealing the presence of source(s) for Si and Ca other than from soil. Examination of C2H2/CO, C3H8/C 2H6, nitrate/(nitrate + NOy* , and sulfate/(SO2 + sulfate) suggested that relatively fresh air masses had been sampled at the study site in the spring season. Comparison of the observed ratios/slopes with those derived from emission inventories showed that while the observed SO2/NO y* ratio (1.29 ppbv/ppbv) in March was comparable (within 20%) to the inventory-derived ratio for the study region, the measured CO/NOy* slope (37 ppbv/ppbv) was about 200% larger. The observed slope of CO relative to NMHC (including ethane, propane, butanes, ethene, and ethyne) also indicated the presence of excess CO, compared to the ratios from the inventories. These results strongly suggest that emissions of CO in eastern China have been underrepresented. The findings of this study highlight the importance of characterizing trace gases and aerosols within source regions of the Asian continent. The springtime results were also compared with data previously collected at the site in 1999-2000 and with those obtained on the Transport and Chemical Evolution over the Pacific (TRACE-P) aircraft and from a coastal site in South China for the same study period. Copyright 2004 by the American Geophysical Union

Eyelid and Sternum Fibroblasts Differ in Their Contraction Potential and Responses to Inflammatory Cytokines

BACKGROUND: Adverse skin scarring varies by anatomical site with, for example, presternal skin showing a greater hypertrophic response when compared with eyelid; such differences have traditionally been attributed to regional variations in skin tension, thickness, and Langer's lines. Fibroblasts are the main cell implicated in fibrosis, and they too are known to show anatomical variation in their expression, differentiation, and intercellular interactions. We, therefore, investigated whether intrinsic differences in skin fibroblasts derived from separate locations might contribute to the observed discrepancies in clinical scarring. METHODS: Primary in vitro cultures were established using matched eyelid and presternal skin from 3 healthy donors undergoing blepharoplasty surgery. We used an in vitro collagen gel model of fibroblast-mediated tissue contraction to compare the properties of the dermal fibroblasts from each site. Cell contractile force and matrix stiffness were assessed in 3-dimensional tissue constructs using an automated high-throughput device. RESULTS: Dermal fibroblasts isolated from eyelid and sternum differ both in their ability to contract a gel matrix and in their response to cytokine stimulation; despite having lower intrinsic contractile force (P < 0.01) and resting stiffness (P < 0.02), the presternal cells were more contractile (P < 0.001) following stimulation with serum, or inflammatory cytokines transforming growth factor-β (P < 0.01) and interleukin-1β (P < 0.05). CONCLUSIONS: The propensity to cutaneous scarring may, at least in part, result from intrinsic differences in the local fibroblasts' ability to contract and their sensitivity to inflammatory cytokines. Improved understanding of the underlying molecular pathways should prove useful in identifying new therapeutic targets for altering surgical and other scarring

Nanofibers Fabricated Using Triaxial Electrospinning as Zero Order Drug Delivery Systems

A new strategy for creating functional trilayer nanofibers through triaxial electrospinning is demonstrated. Ethyl cellulose (EC) was used as the filament-forming matrix in the outer, middle, and inner working solutions and was combined with varied contents of the model active ingredient ketoprofen (KET) in the three fluids. Triaxial electrospinning was successfully carried out to generate medicated nanofibers. The resultant nanofibers had diameters of 0.74 ± 0.06 μm, linear morphologies, smooth surfaces, and clear trilayer nanostructures. The KET concentration in each layer gradually increased from the outer to the inner layer. In vitro dissolution tests demonstrated that the nanofibers could provide linear release of KET over 20 h. The protocol reported in this study thus provides a facile approach to creating functional nanofibers with sophisticated structural features

TIFA, an inflammatory signaling adaptor, is tumor suppressive for liver cancer.

TIFA (TNF receptor associated factor (TRAF)-interacting protein with a Forkhead-associated (FHA) domain), also called T2BP, was first identified using a yeast two-hybrid screening. TIFA contains a FHA domain, which directly binds phosphothreonine and phosphoserine, and a consensus TRAF6-binding motif. TIFA-mediated oligomerization and poly-ubiquitinylation of TRAF6 mediates signaling downstream of the Tumor necrosis factor alpha receptor 1 (TNFaR-I) and interleukin-1/Toll-like receptor 4 (TLR4) pathways. Examining TIFA expression in hepatocellular carcinoma (HCC) tissues microarrays, we noted marked decreases TIFA reactivity in tumor versus control samples. In agreement, we found that HCC cell lines show reduced TIFA expression levels versus normal liver controls. Reconstituting TIFA expression in HCC cell lines promoted two independent apoptosis signaling pathways: the induction of p53 and cell cycle arrest, and the activation of caspase-8 and caspase-3. In contrast, the expression of a non-oligomerizing mutant of TIFA impacted cells minimally, and suppression of TIFA expression protected cells from apoptosis. Mice bearing TIFA overexpression hepatocellular xenografts develop smaller tumors versus TIFA mutant tumors; terminal deoxynucleotidyl transferase dUTP nick end labeling staining demonstrates increased cell apoptosis, and decreased proliferation, reflecting cell cycle arrest. Interestingly, p53 has a greater role in decreased proliferation than cell death, as it appeared dispensable for TIFA-induced cell killing. The findings demonstrate a novel suppressive role of TIFA in HCC progression via promotion of cell death independent of p53