The effect of prosody on conceptual combination

Research into people's comprehension of novel noun-noun phrases has long neglected the possible influences of prosody during meaning construction. At the same time, work in conceptual combination has disagreed about whether different classes of interpretation emerge from single or multiple processes; for example, whether people use distinct mechanisms when they interpret octopus apartment as property-based (e.g., an apartment with eight rooms) or relation-based (e.g., an apartment where an octopus lives). In two studies, we manipulate the prosodic emphasis patterns of novel noun-noun combinations (placing stress on the modifier noun, the head noun, or dual stress on both nouns) and ask participants to generate an interpretation for the novel phrase. Results show that people are faster to generate property-based interpretations when dual emphasis stresses both nouns equally, with prosody having little effect on the speed of relation-based interpretations. These findings highlight a role for prosody during meaning construction and underline important differences between relation- and property-based interpretations that are difficult to reconcile with unitary process views of conceptual combination.     

精诚合一:医学哲学事业的永恒主题

医学哲学事业的价值在于发现并弘扬医学的基本精神。“精诚合一”是医学亘古不变的基本精神。当代医学哲学研究的任务是揭示医学的“精诚合一”特征及其深刻内涵,注重“精”与“诚”的有机结合,批判现实医疗活动和理论研究在“精”、“诚”问题上的片面,弘扬医学的基本精神。     

On component analyses

Principal components analysis can be redefined in terms of the regression of observed variables upon component variables. Two criteria for the adequacy of a component representation in this context are developed and are shown to lead to different component solutions. Both criteria are generalized to allow weighting, the choice of weights determining the scale invariance properties of the resulting solution. A theorem is presented giving necessary and sufficient conditions for equivalent component solutions under different choices of weighting. Applications of the theorem are discussed that involve the components analysis of linearly derived variables and of external variables.Preparation of this article was supported in part by National Institute of Aging Grant NIA-AG03164-03 to William Meredith.     

Testing equality of correlated proportions with incomplete data on both responses

Two test statistics are proposed for testing the equality of two correlated proportions when some observations are missing on both responses. The performance of these tests in terms of size and power is compared with other tests by means of Monte Carlo simulations. The proposed tests are easily computed and compare favorably with other tests.     

Describing the elephant: Structure and function in multivariate data

There is a unity underlying the diversity of models for the analysis of multivariate data. Essentially, they constitute a family models, most generally nonlinear, for structural/functional relations between variables drawn from a behavior domain.     

Why Combine Logics?

Combining logics has become a rapidly expanding entreprise that is inspired mainly by concerns about modularity and the wish to join together tailor made logical tools into more powerful but still manageable ones. A natural question is whether it offers anything new over and above existing standard languages.By analysing a number of applications where combined logics arise, we argue that combined logics are a potentially valuable tool in applied logic, and that endorsements of standard languages often miss the point. Using the history of quantified modal logic as our main example, we also show that the use of combined structures and logics is a recurring theme in the analysis of existing logical systems.     

Uniqueness proof for a family of models sharing features of Tucker's three-mode factor analysis and PARAFAC/candecomp

Some existing three-way factor analysis and MDS models incorporate Cattell's “Principle of Parallel Proportional Profiles”. These models can—with appropriate data—empirically determine a unique best fitting axis orientation without the need for a separate factor rotation stage, but they have not been general enough to deal with what Tucker has called “interactions” among dimensions. This article presents a proof of unique axis orientation for a considerably more general parallel profiles model which incorporates interacting dimensions. The model, X_k=A^AD_k H^BD_k B', does not assume symmetry in the data or in the interactions among factors. A second proof is presented for the symmetrically weighted case (i.e., where^AD_k=^BD_k). The generality of these models allows one to impose successive restrictions to obtain several useful special cases, including PARAFAC2 and three-way DEDICOM. We want to express appreciation for the contributions of several colleagues: Jos M. F. ten Berge and Henk A. L. Kiers carefully went through more than one version of this article, found an important error, and contributed many improvements. J. Douglas Carroll and Shizuhiko Nishisato acted with unusual editorial preserverance and flexibility, thereby making possible the successful completion of a difficult assessment and revision process. Joseph B. Kruskal has long provided crucial mathematical insights and inspiration to those working in this area, but this is particularly true for us. His contributions to this specific article include early discussion of basic questions and careful examination of some earlier attempted proofs, finding them to be invalid. The anonymous reviewers also made useful suggestions. Some portions of this work were supported in part by a grant from the Natural Sciences and Engineering Research Council of Canada.     

The analysis of three-way contingency tables by three-mode association models

TheRC(M) association model (Goodman, 1979, 1985, 1986, 1991) is useful for analyzing the relationship between the variables of a 2-way cross-classification. The models presented here are generalizations of theRC(M) association model for 3-way tables. The family of models proposed here, 3-mode association models, use Tucker's 3-mode components model (Tucker, 1964, 1966; Kroonenberg, 1983) to represent either the three factor interaction or the combined effects of two and three factor interactions. An example from a study in developmental psychology (Kramer & Gottman, 1992) is provided to illustrate the usefulness of the proposed models.I thank Stanley Wasserman, Laurie Kramer, Ulf Böckenholt, Larwence Hubert, Jeffrey Tanaka, and five anonymous reviewers for valuable comments.     

Fixed versus variable sequences of food and stimulus presentation in second-order schedules

Three pigeons were exposed to a second-order schedule in which the behavior specified by a fixed-interval component schedule was reinforced according to a ratio overall schedule. The completion of components not followed by food was signalled by a brief stimulus never paired with food. Food and the stimulus occurred in a random sequence or in fixed alternation, but the overall schedules (variable ratio 2 or fixed ratio 2) ensured that an equal number of food and brief-stimulus presentations occurred in each session. The control exerted by the food and by the brief stimulus was measured by overall response rates, mean pauses, frequency distributions of pauses, and response patterning across components. In general, the stimulus controlled patterns of behavior more similar to those controlled by food when food and the stimulus occurred in a random sequence than when they occurred in fixed alternation.