Investigating the Effects of Various Crowd Characteristics on the Dynamic Properties of an Occupied Structure

One of the challenges for structural engineers during design is considering how the structure will respond to crowd-induced dynamic loading. It has been shown that human occupants of a structure do not simply add mass to the system when considering the overall dynamic response of the system, but interact with it and may induce changes of the dynamic properties from those of the empty structure. This study presents an investigation into the human-structure interaction based on several crowd characteristics and their effect on the dynamic properties of an empty structure. The dynamic properties including frequency, damping, and mode shapes were estimated for a single test structure by means of experimental modal analysis techniques. The same techniques were utilized to estimate the dynamic properties when the test structure was occupied by a crowd with different combinations of size, posture, and distribution. The goal of this study is to isolate the occupant characteristics in order to determine the significance of each to be considered when designing new structures to avoid crowd serviceability issues. The results are presented and summarized based on the level of influence of each characteristic. The posture that produces the most significant effects based on the scope of this research is standing with bent knees with a maximum decrease in frequency of the first mode of the empty structure by 32 percent atthe highest mass ratio. The associated damping also increased 36 times the damping of the empty structure. In addition to the analysis of the experimental data, finite element models and a two degree-of-freedom model were created. These models were used to gain an understanding of the test structure, model a crowd as an equivalent mass, and also to develop a single degree-of-freedom (SDOF) model to best represent a crowd of occupants based on the experimental results. The SDOF models created had an averagefrequency of 5.0 Hz, within the range presented in existing biomechanics research, and combined SDOF systems of the test structure and crowd were able to reproduce the frequency and damping ratios associated with experimental tests. Results of this study confirmed the existence of human-structure interaction andthe inability to simply model a crowd as only additional mass. The two degree-offreedom model determined was able to predict the change in natural frequency and damping ratio for a structure occupied by multiple group sizes in a single posture. These results and model are the preliminary steps in the development of an appropriate methodfor modeling a crowd in combination with a more complex FE model of the empty structure.

Fitting of Mixtures with Unspecified Number of Components Using Cross Validation Distance Estimate

Estimation of the number of mixture components (k) is an unsolved problem. Available methods for estimation of k include bootstrapping the likelihood ratio test statistics and optimizing a variety of validity functionals such as AIC, BIC/MDL, and ICOMP. We investigate the minimization of distance between fitted mixture model and the true density as a method for estimating k. The distances considered are Kullback-Leibler (KL) and “L sub 2”. We estimate these distances using cross validation. A reliable estimate of k is obtained by voting of B estimates of k corresponding to B cross validation estimates of distance. This estimation methods with KL distance is very similar to Monte Carlo cross validated likelihood methods discussed by Smyth (2000). With focus on univariate normal mixtures, we present simulation studies that compare the cross validated distance method with AIC, BIC/MDL, and ICOMP. We also apply the cross validation estimate of distance approach along with AIC, BIC/MDL and ICOMP approach, to data from an osteoporosis drug trial in order to find groups that differentially respond to treatment.

The Optimal Confidence Region for a Random Parameter

Under a two-level hierarchical model, suppose that the distribution of the random parameter is known or can be estimated well. Data are generated via a fixed, but unobservable realization of this parameter. In this paper, we derive the smallest confidence region of the random parameter under a joint Bayesian/frequentist paradigm. On average this optimal region can be much smaller than the corresponding Bayesian highest posterior density region. The new estimation procedure is appealing when one deals with data generated under a highly parallel structure, for example, data from a trial with a large number of clinical centers involved or genome-wide gene-expession data for estimating individual gene- or center-specific parameters simultaneously. The new proposal is illustrated with a typical microarray data set and its performance is examined via a small simulation study.

MODELING DIFFERENTIATED TREATMENT EFFECTS FOR MULTIPLE OUTCOMES DATA

Multiple outcomes data are commonly used to characterize treatment effects in medical research, for instance, multiple symptoms to characterize potential remission of a psychiatric disorder. Often either a global, i.e. symptom-invariant, treatment effect is evaluated. Such a treatment effect may over generalize the effect across the outcomes. On the other hand individual treatment effects, varying across all outcomes, are complicated to interpret, and their estimation may lose precision relative to a global summary. An effective compromise to summarize the treatment effect may be through patterns of the treatment effects, i.e. "differentiated effects." In this paper we propose a two-category model to differentiate treatment effects into two groups. A model fitting algorithm and simulation study are presented, and several methods are developed to analyze heterogeneity presenting in the treatment effects. The method is illustrated using an analysis of schizophrenia symptom data.

Water transport in complex, non-wetting porous layers with applications to water management in low temperature fuel cells

An experimental setup was designed to visualize water percolation inside the porous transport layer, PTL, of proton exchange membrane, PEM, fuel cells and identify the relevant characterization parameters. In parallel with the observation of the water movement, the injection pressure (pressure required to transport water through the PTL) was measured. A new scaling for the drainage in porous media has been proposed based on the ratio between the input and the dissipated energies during percolation. A proportional dependency was obtained between the energy ratio and a non-dimensional time and this relationship is not dependent on the flow regime; stable displacement or capillary fingering. Experimental results show that for different PTL samples (from different manufacturers) the proportionality is different. The identification of this proportionality allows a unique characterization of PTLs with respect to water transport. This scaling has relevance in porous media flows ranging far beyond fuel cells. In parallel with the experimental analysis, a two-dimensional numerical model was developed in order to simulate the phenomena observed in the experiments. The stochastic nature of the pore size distribution, the role of the PTL wettability and morphology properties on the water transport were analyzed. The effect of a second porous layer placed between the porous transport layer and the catalyst layer called microporous layer, MPL, was also studied. It was found that the presence of the MPL significantly reduced the water content on the PTL by enhancing fingering formation. Moreover, the presence of small defects (cracks) within the MPL was shown to enhance water management. Finally, a corroboration of the numerical simulation was carried out. A threedimensional version of the network model was developed mimicking the experimental conditions. The morphology and wettability of the PTL are tuned to the experiment data by using the new energy scaling of drainage in porous media. Once the fit between numerical and experimental data is obtained, the computational PTL structure can be used in different types of simulations where the conditions are representative of the fuel cell operating conditions.

Gingival labial recessions in orthodontically treated and untreated individuals: a case - control study

OBJECTIVES To evaluate the long-term development of labial gingival recessions during orthodontic treatment and retention phase. MATERIAL AND METHODS In this retrospective case-control study, the presence of gingival recession was scored (Yes or No) on plaster models of 100 orthodontic patients (cases) and 120 controls at the age of 12 (T12 ), 15 (T15 ), 18 (T18 ), and 21 (T21 ) years. In the treated group, T12 reflected the start of orthodontic treatment and T15 - the end of active treatment and the start of retention phase with bonded retainers. Independent t-tests, Fisher's exact tests and a fitted two-part "hurdle" model were used to identify the effect of orthodontic treatment/retention on recessions. RESULTS The proportion of subjects with recessions was consistently higher in cases than controls. Overall, the odds ratio for orthodontic patients as compared with controls to have recessions is 4.48 (p < 0.001; 95% CI: 2.61-7.70). CONCLUSIONS Within the limits of the present research design, orthodontic treatment and/or the retention phase may be risk factors for the development of labial gingival recessions. In orthodontically treated subjects, mandibular incisors seem to be the most vulnerable to the development of gingival recessions.

Expectation Conditional Maximization-Based Deformable Shape Registration

This paper addresses the issue of matching statistical and non-rigid shapes, and introduces an Expectation Conditional Maximization-based deformable shape registration (ECM-DSR) algorithm. Similar to previous works, we cast the statistical and non-rigid shape registration problem into a missing data framework and handle the unknown correspondences with Gaussian Mixture Models (GMM). The registration problem is then solved by fitting the GMM centroids to the data. But unlike previous works where equal isotropic covariances are used, our new algorithm uses heteroscedastic covariances whose values are iteratively estimated from the data. A previously introduced virtual observation concept is adopted here to simplify the estimation of the registration parameters. Based on this concept, we derive closed-form solutions to estimate parameters for statistical or non-rigid shape registrations in each iteration. Our experiments conducted on synthesized and real data demonstrate that the ECM-DSR algorithm has various advantages over existing algorithms.

In-situ diffusion of HTO, 22Na+, Cs+ and I- in Opalinus Clay at the Mont Terri underground rock laboratory

The diffusion properties of the Opalinus Clay were studied in the underground research laboratory at Mont Terri (Canton Jura, Switzerland) and the results were compared with diffusion data measured in the laboratory on small-scale samples. The diffusion of HTO, Na-22(+), Cs+ and I- were investigated for a period of 10 months. The diffusion equipment used in the field experiment was designed in such a way that a solution of tracers was circulated through a sintered metal screen placed at the end of a borehole drilled in the formation. The concentration decrease caused by the diffusion of tracers into the rock could be followed with time and allowed first estimations of the effective diffusion coefficient. After 10 months, the diffusion zone was over-cored and the tracer profiles measured. From these profiles, effective diffusion coefficients and rock capacity factors Could be extracted by applying a two-dimensional transport model including diffusion and sorption. The simulations were done with the reactive transport code CRUNCH. In addition, results obtained from through-diffusion experiments oil small-sized samples with HTO, Cl-36(-) and Na-22(+) are presented and compared with the in situ data. In all cases. excellent agreement between the two data sets exists. Results for Cs+ indicated five times higher diffusion rates relative to HTO. Corresponding laboratory diffusion measurements are still lacking. However. our Cs+ data are in qualitative agreement wish through-diffusion data for Callovo-Oxfordian argillite rock samples. which also indicate significantly higher effective diffusivities for Cs+ relative to HTO.

Effect of VEGF treatment on the blood-spinal cord barrier permeability in experimental spinal cord injury: dynamic contrast-enhanced magnetic resonance imaging.

Compromised blood-spinal cord barrier (BSCB) is a factor in the outcome following traumatic spinal cord injury (SCI). Vascular endothelial growth factor (VEGF) is a potent stimulator of angiogenesis and vascular permeability. The role of VEGF in SCI is controversial. Relatively little is known about the spatial and temporal changes in the BSCB permeability following administration of VEGF in experimental SCI. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) studies were performed to noninvasively follow spatial and temporal changes in the BSCB permeability following acute administration of VEGF in experimental SCI over a post-injury period of 56 days. The DCE-MRI data was analyzed using a two-compartment pharmacokinetic model. Animals were assessed for open field locomotion using the Basso-Beattie-Bresnahan score. These studies demonstrate that the BSCB permeability was greater at all time points in the VEGF-treated animals compared to saline controls, most significantly in the epicenter region of injury. Although a significant temporal reduction in the BSCB permeability was observed in the VEGF-treated animals, BSCB permeability remained elevated even during the chronic phase. VEGF treatment resulted in earlier improvement in locomotor ability during the chronic phase of SCI. This study suggests a beneficial role of acutely administered VEGF in hastening neurobehavioral recovery after SCI.

From Broadstone to Zackenberg

Ecological networks are typically complex constructions of species and their interactions. During the last decade, the study of networks has moved from static to dynamic analyses, and has attained a deeper insight into their internal structure, heterogeneity, and temporal and spatial resolution. Here, we review, discuss and suggest research lines in the study of the spatio-temporal heterogeneity of networks and their hierarchical nature. We use case study data from two well-characterized model systems (the food web in Broadstone Stream in England and the pollination network at Zackenberg in Greenland), which are complemented with additional information from other studies. We focus upon eight topics: temporal dynamic space-for-time substitutions linkage constraints habitat borders network modularity individual-based networks invasions of networks and super networks that integrate different network types. Few studies have explicitly examined temporal change in networks, and we present examples that span from daily to decadal change: a common pattern that we see is a stable core surrounded by a group of dynamic, peripheral species, which, in pollinator networks enter the web via preferential linkage to the most generalist species. To some extent, temporal and spatial scales are interchangeable (i.e. networks exhibit ‘ergodicity’) and we explore how space-for-time substitutions can be used in the study of networks. Network structure is commonly constrained by phenological uncoupling (a temporal phenomenon), abundance, body size and population structure. Some potential links are never observed, that is they are ‘forbidden’ (fully constrained) or ‘missing’ (a sampling effect), and their absence can be just as ecologically significant as their presence. Spatial habitat borders can add heterogeneity to network structure, but their importance has rarely been studied: we explore how habitat generalization can be related to other resource dimensions. Many networks are hierarchically structured, with modules forming the basic building blocks, which can result in self-similarity. Scaling down from networks of species reveals another, finer-grained level of individual-based organization, the ecological consequences of which have yet to be fully explored. The few studies of individual-based ecological networks that are available suggest the potential for large intraspecific variance and, in the case of food webs, strong size-structuring. However, such data are still scarce and more studies are required to link individual-level and species-level networks. Invasions by alien species can be tracked by following the topological ‘career’ of the invader as it establishes itself within a network, with potentially important implications for conservation biology. Finally, by scaling up to a higher level of organization, it is possible to combine different network types (e.g. food webs and mutualistic networks) to form super networks, and this new approach has yet to be integrated into mainstream ecological research. We conclude by listing a set of research topics that we see as emerging candidates for ecological network studies in the near future.

Improved predictions for μ\to e conversion in nuclei and Higgs-induced lepton flavor violation

Compared to μ→eγ and μ→eee, the process μ→e conversion in nuclei receives enhanced contributions from Higgs-induced lepton flavor violation. Upcoming μ→e conversion experiments with drastically increased sensitivity will be able to put extremely stringent bounds on Higgs-mediated μ→e transitions. We point out that the theoretical uncertainties associated with these Higgs effects, encoded in the couplings of quark scalar operators to the nucleon, can be accurately assessed using our recently developed approach based on SU(2) chiral perturbation theory that cleanly separates two- and three-flavor observables. We emphasize that with input from lattice QCD for the coupling to strangeness fNs, hadronic uncertainties are appreciably reduced compared to the traditional approach where fNs is determined from the pion-nucleon σ term by means of an SU(3) relation. We illustrate this point by considering Higgs-mediated lepton flavor violation in the standard model supplemented with higher-dimensional operators, the two-Higgs-doublet model with generic Yukawa couplings, and the minimal supersymmetric standard model. Furthermore, we compare bounds from present and future μ→e conversion and μ→eγ experiments.

Real-time simulation of large open quantum spin systems driven by dissipation

We consider a large quantum system with spins 12 whose dynamics is driven entirely by measurements of the total spin of spin pairs. This gives rise to a dissipative coupling to the environment. When one averages over the measurement results, the corresponding real-time path integral does not suffer from a sign problem. Using an efficient cluster algorithm, we study the real-time evolution from an initial antiferromagnetic state of the two-dimensional Heisenberg model, which is driven to a disordered phase, not by a Hamiltonian, but by sporadic measurements or by continuous Lindblad evolution.

Updated Next-to-Next-to-Leading-Order QCD Predictions for the Weak Radiative B -Meson Decays

Weak radiative decays of the B mesons belong to the most important flavor changing processes that provide constraints on physics at the TeV scale. In the derivation of such constraints, accurate standard model predictions for the inclusive branching ratios play a crucial role. In the current Letter we present an update of these predictions, incorporating all our results for the O(α2s) and lower-order perturbative corrections that have been calculated after 2006. New estimates of nonperturbative effects are taken into account, too. For the CP- and isospin-averaged branching ratios, we find Bsγ=(3.36±0.23)×10−4 and Bdγ=(1.73+0.12−0.22)×10−5, for Eγ>1.6  GeV. Both results remain in agreement with the current experimental averages. Normalizing their sum to the inclusive semileptonic branching ratio, we obtain Rγ≡(Bsγ+Bdγ)/Bcℓν=(3.31±0.22)×10−3. A new bound from Bsγ on the charged Higgs boson mass in the two-Higgs-doublet-model II reads MH±>480  GeV at 95% C.L.

Reevaluation of the MASTER-2009 MLI and H-10 Debris Modeling

The current paper is an excerpt from the doctoral thesis ”Multi-Layer Insulation as Contribution to Orbital Debris”written at the Institute of Aerospace Systems of the Technische Universit ̈at of Braunschweig. The Multi-Layer In-sulation (MLI) population included in ESA’s MASTER-2009 (M eteoroid and Space-Debris Terrestrial Environment Reference) software is based on models for two mechanisms: One model simulates the release of MLI debris during fragmentation events while another estimates the continuo us release of larger MLI pieces due to aging related deterioration of the material. The aim of the thesis was to revise the MLI models from the base up followed by a re-validation of the simulated MLI debris population. The validation is based on comparison to measurement data of the GEO and GTO debris environment obtained by the Astronomical Institute of the University of Bern (AIUB) using ESA’s Space Debris Telescope (ESASDT), the 1-m Zeiss telescope located at the Optical Ground Station (OGS) at the Teide Observatory at Tenerife, Spain. The re-validation led to the conclusion that MLI may cover a much smaller portion of the observed objects than previously published. Further investigation of the resulting discrepancy revealed that the contribution of altogether nine known Ariane H-10 upper stage explosion events which occurred between 1984 and 2002 has very likely been underestimated in past simulations.