Multidimensional Signals and Analytic Flexibility: Estimating Degrees of Freedom in Human-Speech Analyses

Recent empirical studies have highlighted the large degree of analytic flexibility in data analysis that can lead to substantially different conclusions based on the same data set. Thus, researchers have expressed their concerns that these researcher degrees of freedom might facilitate bias and can lead to claims that do not stand the test of time. Even greater flexibility is to be expected in fields in which the primary data lend themselves to a variety of possible operationalizations. The multidimensional, temporally extended nature of speech constitutes an ideal testing ground for assessing the variability in analytic approaches, which derives not only from aspects of statistical modeling but also from decisions regarding the quantification of the measured behavior. In this study, we gave the same speech-production data set to 46 teams of researchers and asked them to answer the same research question, resulting in substantial variability in reported effect sizes and their interpretation. Using Bayesian meta-analytic tools, we further found little to no evidence that the observed variability can be explained by analysts’ prior beliefs, expertise, or the perceived quality of their analyses. In light of this idiosyncratic variability, we recommend that researchers more transparently share details of their analysis, strengthen the link between theoretical construct and quantitative system, and calibrate their (un)certainty in their conclusions

Frequency response calculations of a nonlinear structure a comparison of numerical methods

Mechanical systems having presence of nonlinearities are often represented by nonlinear ordinary differential equations. For most of such equations, exact analytic solutions are not found; thus numerical techniques have to be used. In many applications, among which model calibration can be one, steady-state frequency response functions are the desired quantities to calculate. The objective of this paper is to compare the performance of computations of nonlinear frequency response functions (FRFs) calculated directly within the frequency domain, using the Multi-Harmonic Balance method, with the time-domain methods Runge-Kutta, Newmark and Pseudo Force in State Space (PFSS). The PFSS method is a recently developed state-space based force feedback method. The accuracy and efficiency of the methods are studied and compared using a model of a cantilever beam connected to a non-linear spring at its free end

Structure of the 26S proteasome from Schizosaccharomyces pombe at subnanometer resolution

The structure of the 26S proteasome from Schizosaccharomyces pombe has been determined to a resolution of 9.1 Å by cryoelectron microscopy and single particle analysis. In addition, chemical cross-linking in conjunction with mass spectrometry has been used to identify numerous residue pairs in close proximity to each other, providing an array of spatial restraints. Taken together these data clarify the topology of the AAA-ATPase module in the 19S regulatory particle and its spatial relationship to the α-ring of the 20S core particle. Image classification and variance analysis reveal a belt of high “activity” surrounding the AAA-ATPase module which is tentatively assigned to the reversible association of proteasome interacting proteins and the conformational heterogeneity among the particles. An integrated model is presented which sheds light on the early steps of protein degradation by the 26S complex