Surface diffusion coefficients for room acoustics : free-field measures

A surface diffusion coefficient is needed in room acoustics to enable the quality of diffusing surfaces to be evaluated. It may also facilitate more accurate geometric room acoustic models. This paper concentrates on diffusion coefficients derived from free-field polar responses. An extensive set of two- and three-dimensional measurements and predictions was used to test the worth of different diffusion coefficient definitions. The merits and problems associated with these types of coefficients are discussed, and past parameters reviewed. Two new coefficients are described. The new measure based on the autocorrelation function is forwarded as the best free-field coefficient. The strengths and weaknesses of the coefficient are defined. © 2000 Acoustical Society of America

Ternary and quadriphase sequence diffusers

A room acoustic diffuser breaks up reflected wavefronts, and this can be achieved by presenting a spatially varying surface impedance. In hybrid surfaces, varying impedance is achieved by patches of absorption and reflection, giving reflection coefficients nominally of 0 and 1. These surfaces are hybrids, absorbing some of the incident sound while diffusing any reflected energy. A problem with planar hybrid surfaces is that specular energy is only removed by absorption. By exploiting interference, by reflecting waves out-of-phase with the specular energy, it is possible to diminish the specular energy further. This can be achieved by using a diffuser based on a ternary sequence that nominally has reflection coefficients of 0, -1, and +1. Ternary sequences are therefore a way of forming hybrid absorber-diffusers that achieve better scattering performance without additional absorption. This paper discusses methods for making ternary sequence diffusers, including giving sequence generation methods. It presents prediction results based on Fourier and boundary element method models to examine the performance. While ternary diffusers have better performance than unipolar binary diffusers at most frequencies, there are frequencies at which the performances are the same. This can be overcome by forming diffusers from four-level, quadriphase sequences

Correlational analysis between joint-level kinetics of countermovement jumps and weightlifting derivatives

The purpose of this study was to investigate the mechanical similarity between net joint moments (NJM) of the countermovement jump (CMJ) and the hang power clean (HPC) and jump shrug (JS). Twelve male Lacrosse players performed three maximal effort CMJs and three repetitions of the HPC and JS at 30%, 50%, and 70% of their HPC one repetition maximum (1-RM). Ground reaction forces and motion capture data were used to calculate the NJM of the hip, knee, and ankle joints during each exercise. Statistical comparison of the peak NJM indicated that NJM during the HPC and JS across all loads were equal to or greater than the NJM during the CMJ (all p < 0.025). In addition, correlation analyses indicated that CMJ hip NJM were associated (all p < 0.025) with HPC hip NJM at 30% and 70% (r = 0.611-0.822) and JS hip NJM at 50% and 70% (r = 0.674-0.739), whereas CMJ knee NJM were associated with HPC knee NJM at 70% (r = 0.638) and JS knee NJM at 50% and 70% (r = 0.664-0.732). Further, CMJ ankle NJM were associated with HPC ankle NJM at 30% and 50% (r = 0.615-0.697) and JS ankle NJM at 30%, 50%, and 70% (r = 0.735-0.824). Lastly, knee and ankle NJM during the JS were greater than during the HPC at 30% and 50% of 1-RM (all p < 0.017). The degree of mechanical similarity between the CMJ and the HPC and JS is dependent on the respective load and joint. [Abstract copyright: © Journal of Sports Science and Medicine.

The effect of training with weightlifting catching or pulling derivatives on squat jump and countermovement jump force–time adaptations

The purpose of this study was to examine the changes in squat jump (SJ) and countermovement jump (CMJ) force−time curve characteristics following 10 weeks of training with either load-matched weightlifting catching (CATCH) or pulling derivatives (PULL) or pulling derivatives that included force- and velocity-specific loading (OL). Twenty-five resistance-trained men were randomly assigned to the CATCH, PULL, or OL groups. Participants completed a 10 week, group-specific training program. SJ and CMJ height, propulsion mean force, and propulsion time were compared at baseline and after 3, 7, and 10 weeks. In addition, time-normalized SJ and CMJ force−time curves were compared between baseline and after 10 weeks. No between-group differences were present for any of the examined variables, and only trivial to small changes existed within each group. The greatest improvements in SJ and CMJ height were produced by the OL and PULL groups, respectively, while only trivial changes were present for the CATCH group. These changes were underpinned by greater propulsion forces and reduced propulsion times. The OL group displayed significantly greater relative force during the SJ and CMJ compared to the PULL and CATCH groups, respectively. Training with weightlifting pulling derivatives may produce greater vertical jump adaptations compared to training with catching derivatives

Molecular mechanism of MBX2319 inhibition of Escherichia coli AcrB multidrug efflux pump and comparison with other inhibitors

Efflux pumps of the resistance nodulation division (RND) superfamily, such as AcrB, make a major contribution to multidrug resistance in Gram-negative bacteria. The development of inhibitors of the RND pumps would improve the efficacy of current and next-generation antibiotics. To date, however, only one inhibitor has been cocrystallized with AcrB. Thus, in silico struc- ture-based analysis is essential for elucidating the interaction between other inhibitors and the efflux pumps. In this work, we used computer docking and molecular dynamics simulations to study the interaction between AcrB and the compound MBX2319, a novel pyranopyridine efflux pump inhibitor with potent activity against RND efflux pumps of Enterobacteriaceae species, as well as other known inhibitors (D13-9001, 1-[1-naphthylmethyl]-piperazine, and phenylalanylarginine-ß-naphthyl-amide) and the binding of doxorubicin to the efflux-defective F610A variant of AcrB. We also analyzed the binding of a sub- strate, minocycline, for comparison. Our results show that MBX2319 binds very tightly to the lower part of the distal pocket in the B protomer of AcrB, strongly interacting with the phenylalanines lining the hydrophobic trap, where the hydrophobic por- tion of D13-9001 was found to bind by X-ray crystallography. Additionally, MBX2319 binds to AcrB in a manner that is similar to the way in which doxorubicin binds to the F610A variant of AcrB. In contrast, 1-(1-naphthylmethyl)-piperazine and phenylalanylarginine-ß-naphthylamide appear to bind to somewhat different areas of the distal pocket in the B protomer of AcrB than does MBX2319. However, all inhibitors (except D13-9001) appear to distort the structure of the distal pocket, impairing the proper binding of substrates

Semantic Wide and Deep Learning for Detecting Crisis-Information Categories on Social Media

When crises hit, many flog to social media to share or consume information related to the event. Social media posts during crises tend to provide valuable reports on affected people, donation offers, help requests, advice provision, etc. Automatically identifying the category of information (e.g., reports on affected individuals, donations and volunteers) contained in these posts is vital for their efficient handling and consumption by effected communities and concerned organisations. In this paper, we introduce Sem-CNN; a wide and deep Convolutional Neural Network (CNN) model designed for identifying the category of information contained in crisis-related social media content. Unlike previous models, which mainly rely on the lexical representations of words in the text, the proposed model integrates an additional layer of semantics that represents the named entities in the text, into a wide and deep CNN network. Results show that the Sem-CNN model consistently outperforms the baselines which consist of statistical and non-semantic deep learning models

Blind estimation of reverberation time in classrooms and hospital wards

This paper investigates blind Reverberation Time (RT) estimation in occupied classrooms and hospital wards. Measurements are usually made while these spaces are unoccupied for logistical reasons. However, occupancy can have a significant impact on the rate of reverberant decay. Recent work has developed a Maximum Likelihood Estimation (MLE) method which utilises only passively recorded speech and music signals, this enables measurements to be made while the room is in use. In this paper the MLE method is applied to recordings made in classrooms during lessons. Classroom occupancy levels differ for each lesson, therefore a model is developed using blind estimates to predict the RT for any occupancy level to within ±0.07s for the mid-frequency octave bands. The model is also able to predict the effective room and per person absorption area. Ambient sound recordings were also carried out in a number of rooms in two hospitals for a week. Hospital measurements are more challenging as the occurrence of free reverberant decay is rarer than in schools and the acoustic conditions may be non-stationary. However, by gaining recordings over a period of a week, estimates can be gained within ±0.07 s. These estimates are representative of the times when the room contains the highest acoustic absorption. In other words when curtains are drawn, there are many visitors or perhaps a window may be open

An experimental and computational analysis of buoyancy driven flows by laser sheet tomography, particle image velocimetry and computational fluid dynamics

This paper contains details of a three pronged investigation into the development of a buoyant jet impinging on a wall in a closed vessel. The development of the flow was measured experimentally by particle image velocimetry (PIV) and laser sheet tomography. The experimental results are compared with a computational model of the flow calculated by the computational fluid dynamics (CFD) package PHOENICS

Integrated multiple mediation analysis: A robustness–specificity trade-off in causal structure

Recent methodological developments in causal mediation analysis have addressed several issues regarding multiple mediators. However, these developed methods differ in their definitions of causal parameters, assumptions for identification, and interpretations of causal effects, making it unclear which method ought to be selected when investigating a given causal effect. Thus, in this study, we construct an integrated framework, which unifies all existing methodologies, as a standard for mediation analysis with multiple mediators. To clarify the relationship between existing methods, we propose four strategies for effect decomposition: two-way, partially forward, partially backward, and complete decompositions. This study reveals how the direct and indirect effects of each strategy are explicitly and correctly interpreted as path-specific effects under different causal mediation structures. In the integrated framework, we further verify the utility of the interventional analogues of direct and indirect effects, especially when natural direct and indirect effects cannot be identified or when cross-world exchangeability is invalid. Consequently, this study yields a robustness–specificity trade-off in the choice of strategies. Inverse probability weighting is considered for estimation. The four strategies are further applied to a simulation study for performance evaluation and for analyzing the Risk Evaluation of Viral Load Elevation and Associated Liver Disease/Cancer data set from Taiwan to investigate the causal effect of hepatitis C virus infection on mortality

Bayesian astrostatistics: a backward look to the future

This perspective chapter briefly surveys: (1) past growth in the use of Bayesian methods in astrophysics; (2) current misconceptions about both frequentist and Bayesian statistical inference that hinder wider adoption of Bayesian methods by astronomers; and (3) multilevel (hierarchical) Bayesian modeling as a major future direction for research in Bayesian astrostatistics, exemplified in part by presentations at the first ISI invited session on astrostatistics, commemorated in this volume. It closes with an intentionally provocative recommendation for astronomical survey data reporting, motivated by the multilevel Bayesian perspective on modeling cosmic populations: that astronomers cease producing catalogs of estimated fluxes and other source properties from surveys. Instead, summaries of likelihood functions (or marginal likelihood functions) for source properties should be reported (not posterior probability density functions), including nontrivial summaries (not simply upper limits) for candidate objects that do not pass traditional detection thresholds.Comment: 27 pp, 4 figures. A lightly revised version of a chapter in "Astrostatistical Challenges for the New Astronomy" (Joseph M. Hilbe, ed., Springer, New York, forthcoming in 2012), the inaugural volume for the Springer Series in Astrostatistics. Version 2 has minor clarifications and an additional referenc