bluuebunny/crossref_metadata_2025_split huggingface dataset:
Postnatal expression of myostatin propeptide cDNA maintained high muscle growth and normal adipose tissue mass in transgenic mice fed a high‐fat diet
Authors: Yang Jinzeng , Zhao Baoping 
Published: January 2006

AbstractMyostatin plays a robust, negative role in controlling muscle mass. A disruption of myostatin function by transgenic expression of its propeptide (the 5′region, 866 nucleotides) results in significant muscle growth (Yang et al., 2001. Mol Rep Dev 60:351–361). Studies from myostatin and the propeptide transgene mRNA indicated that myostatin mRNA was detected at day 10.5 postcoitum in fetal mice. Its level remained low, but increased by 180% during the postnatal fast‐growth period (day 0–10). An early, high‐level postnatal expression of the transgene was identified as being responsible for a highly muscled phenotype. High‐fat diet induces adiposity in rodents. To study the effects of dietary fat on muscle growth and adipose tissue fat deposition in the transgenic mice, we challenged the mice with a high‐fat diet (45% kcal fat) for 21 weeks. Transgenic mice showed 24%–50% further enhancement of growth on the high‐fat diet compared to the normal‐fat diet (P = 0.004) from 17 to 25 weeks of age. The total mass of the main muscles of transgenic mice showed a 27% increase on the high‐fat diet compared to the normal‐fat diet (P = 0.004), while the white adipose tissue mass of the transgenic mice was not significantly different from that of wild‐type mice fed a normal‐fat diet (P = 0.434). The high‐fat diet induced wild‐type mice developed 190% greater mass of white adipose tissues compared to the normal‐fat diet (P = 0.008), which primarily resulted from enlarged adipocytes. These results demonstrate that disruption of myostatin function by its propeptide shifted dietary fat utilization toward muscle tissues with minimal effects on adiposity. These results suggest that enhancing muscle growth by myostatin propeptide or other means during the early developmental stage may serve as an effective means for obesity prevention. Mol. Reprod. Dev. © 2006 Wiley‐Liss, Inc.
Multiple mapping method: A novel approach to the sequence‐to‐structure alignment problem in comparative protein structure modeling
Authors: Rai Brajesh K. , Fiser András 
Published: January 2006

AbstractA major bottleneck in comparative protein structure modeling is the quality of input alignment between the target sequence and the template structure. A number of alignment methods are available, but none of these techniques produce consistently good solutions for all cases. Alignments produced by alternative methods may be superior in certain segments but inferior in others when compared to each other; therefore, an accurate solution often requires an optimal combination of them. To address this problem, we have developed a new approach, Multiple Mapping Method (MMM). The algorithm first identifies the alternatively aligned regions from a set of input alignments. These alternatively aligned segments are scored using a composite scoring function, which determines their fitness within the structural environment of the template. The best scoring regions from a set of alternative segments are combined with the core part of the alignments to produce the final MMM alignment. The algorithm was tested on a dataset of 1400 protein pairs using 11 combinations of two to four alignment methods. In all cases MMM showed statistically significant improvement by reducing alignment errors in the range of 3 to 17%. MMM also compared favorably over two alignment meta‐servers. The algorithm is computationally efficient; therefore, it is a suitable tool for genome scale modeling studies. Proteins 2006. © 2006 Wiley‐Liss, Inc.
Kernel Functions for Attributed Molecular Graphs – A New Similarity‐Based Approach to ADME Prediction in Classification and Regression
Authors: Fröhlich Holger , Wegner Jörg. K. , Sieker Florian , Zell Andreas 
Published: January 2006

AbstractKernel methods, like the well‐known Support Vector Machine (SVM), have received growing attention in recent years for designing QSAR models that have a high predictive strength. One of the key concepts of SVMs is the usage of a so‐called kernel function, which can be thought of as a special similarity measure. In this paper we consider kernels for molecular structures, which are based on a graph representation of chemical compounds. The similarity score is calculated by computing an optimal assignment of the atoms from one molecule to those of another one, including information on specific chemical properties, membership to a substructure (e.g., aromatic ring, carbonyl group, etc.) and neighborhood for each atom. We show that by using this kernel we can achieve a generalization performance comparable to a classical model with a few descriptors, which are a‐priori known to be relevant for the problem, and significantly better results than with and without performing an automatic descriptor selection. For this purpose we investigate ADME classification and regression datasets for predicting bioavailability (Yoshida), Human Intestinal Absorption (HIA), Blood‐Brain‐Barrier (BBB) penetration and a dataset consisting of four different inhibitor classes (SOL). We further explore the effect of combining our kernel with a problem‐dependent descriptor set. We also demonstrate the usefulness of an extension of our method to a reduced graph representation of molecules, in which certain structural features, like, e.g., rings, donors or acceptors, are represented as a single node in the molecular graph.
A Factor Analysis of Certain Neurotic Symptoms
Authors: Mosier Charles I. 
Published: January 2006

In an attempt to investigate the concept of neurotic tendency thirty-nine of the forty-two most discriminative items in the Thurstone Neurotic Inventory were administered as a questionnaire to a group of five hundred male college students. An analysis of the table of intercorrelations by Thurstone's centroid method showed that eight factors were sufficient to account for the observed intercorrelations with negligible residuals. The eight centroid factors were then transformed into a simple structure. It is concluded that a single trait of neurotic tendency cannot be postulated and tentative hypotheses are formed as to the nature of the primary traits revealed by the analysis.Readministering the same test to the same students a week later showed a high consistency of response both on the test as a whole, and on the individual items.
The Approximation of One Matrix by Another of Lower Rank
Authors: Eckart Carl , Young Gale 
Published: January 2006

The mathematical problem of approximating one matrix by another of lower rank is closely related to the fundamental postulate of factor-theory. When formulated as a least-squares problem, the normal equations cannot be immediately written down, since the elements of the approximate matrix are not independent of one another. The solution of the problem is simplified by first expressing the matrices in a canonic form. It is found that the problem always has a solution which is usually unique. Several conclusions can be drawn from the form of this solution.A hypothetical interpretation of the canonic components of a score matrix is discussed.
Psychometric Theory: General and Specific
Authors: Tucker Ledyard R 
Published: January 2006

Fellow members of the Psychometric Society, and our colleagues, members of Division 5 of the American Psychological Association, I understand my mission tonight is to provide you with both humor and a mild message. Precedent has established an eminently high standard. Maybe I can explain the humbleness with which I approach this task by relating the account of an episode. This occurrence, like much illustrative data in Psychometrika, is fictitious, of course.During my trip from the splendorous East Coast to the beauteous West Coast, I took vacation time to tour part of the magnificent country in between, as many of you, undoubtedly, did also. 0he afternoon I came upon a small tent village in a fairly remote mountain section. Not that such camps were so uncommon as to be remarkable in themselves; something about this particular camp caught my eye. In the center of this camp was a rustic conference table flanked on one side by a large blackboard mounted on cedar posts.
Note on Miller's “Finite Markov Processes in Psychology”
Authors: Kao Richard C. W. 
Published: January 2006

In his article “Finite Markov Processes in Psychology,” G. A. Miller derived a least-squares “estimate” for a matrix of transitional probabilities. However, the mathematical proof is found to be invalid.On page 158, Miller defined by the equation = N + C,“where the elements of the matrix C are the corrections that must be added to the observed values in N to give the best estimate ”.
A Note on the Effects of Selection in Factor Analysis
Authors: Degan James W. 
Published: January 2006

Professor Godfrey Thomson, in a communication to this laboratory, has drawn our attention to certain computational and editorial errors in a recent publication on the effects of selection in factor analysis. The purpose of this note is to rectify these errors. In so doing, we wish to express our gratitude to Professor Thomson for preventing their prepetuation.Since the particular tables under consideration appear also in Chapter XIX, “The Effects of Selection,” of and are identical with those of, the material presented in this note is equally applicable to both publications. These tables were numbered identically in both and may be referred to non-differentially. In order to facilitate the exposition in this note, the numbers assigned to each of the corrected tables and figure correspond to the analogous tables and figure of the original publications.
Matrix Representation of Models for the Analysis of Variance and Covariance
Authors: Rulon Phillip Justin 
Published: January 2006

Beginning students of analysis of variance frequently find that the explanations concerning numbers of degrees of freedom are rather more mystical than explanatory, and that the dependencies and independencies among parameters and linear restraints are not systematically covered or explicitly presented. It is the purpose of this paper to set forth the simple matrix representation of these models in a way which has been found useful for teaching purposes, and may be found of some value in the setting up of mathematical models for experimental designs calling for the analysis of variance or the analysis of covariance.The system I shall portray is a more or less natural outgrowth of suggestions made by Dr. R. C. Bose, with whom I have discussed some of the features very slightly. I am also indebted to Professor Frederick Mosteller for assistance with the mechanics of some of the models. Any deficiencies which the system may have are not to be laid to the doors of these gentlemen, however, as they have not had any opportunity to go over the material at any length.
Fechner: Inadvertent Founder of Psychophysics
Authors: Boring Edwin G. 
Published: January 2006

Certainly the most interesting tool that science employs in its perpetual pursuit of knowledge is the scientist, with his enthusiasms, egoisms, and prejudices, his inevitable unconscious attitudinal orientation in the consensus of contemporary opinion, which we call the Zeitgeist. One wonders what science would be like if automation could take over completely. Are there mechanical equivalents for jealousy and pride and pigheadedness and insight, and those other interacting personal forces that contribute to contemporary truth in the scientific field?Fechner never tried to found psychophysics or a new experimental psychology. He was, in his own estimation in those last forty-five years of his life, a philosopher, fighting what he regarded as the crass materialism of his day, the Nachtansicht or “night view,” as he called it, and promoting the faith that mind and soul are the ultimates of reality, the Tagesansicht or “day view.” This favoring of the clear philosophical vision in the day view as opposed to the materialistic darkness of the night view is Fechner’s panpsychism, a faith that seems mystical to most modern scientists, partly because the German word Seele does not distinguish between mind and soul, between that which compares the sensory intensities of two lifted weights and whatever it is that persists after the body’s death.
Alpha Factor Analysis
Authors: Kaiser Henry F. , Caffrey John 
Published: January 2006

A distinction is made between statistical inference and psychometric inference in factor analysis. After reviewing Rao's canonical factor analysis (CFA), a fundamental statistical method of factoring, a new method of factor analysis based upon the psychometric concept of generalizability is described. This new procedure (alpha factor analysis, AFA) determines factors which have maximum generalizability in the Kuder-Richardson, or alpha, sense. The two methods, CFA and AFA, each have the important property of giving the same factors regardless of the units of measurement of the observable variables. In determining factors, the principal distinction between the two methods is that CFA operates in the metric of the unique parts of the observable variables while AFA operates in the metric of the common (“communality”) parts.On the other hand, the two methods are substantially different as to how they establish the number of factors. CFA answers this crucial question with a statistical test of significance while AFA retains only those alpha factors with positive generalizability. This difference is discussed at some length. A brief outline of a computer program for AFA is described and an example of the application of AFA is given.
A Method for Studying Differences between Groups
Authors: Meredith William 
Published: January 2006

The researcher in behavioral or biological science has available a large arsenal of methods for studying the nature and statistical significance of differences between various groups of individuals. He may use any of a wide variety of univariate methods to test hypotheses about differences in location, in dispersion, in correlation between pairs of attributes, etc. In a multivariate situation methods are available to test hypotheses about mean vectors, variance-covariance matrices, correlation matrices, factor structures, etc.There are two points of view involved in studying the nature of differences between groups. One point of view is descriptive, and has traditionally been treated under the topic of estimation in statistics. The other usually involves a question as to whether it is reasonable to assume that some hypothesized model about the nature of differences between populations is in fact true, and has usually been treated under the ~pic of tests of hypotheses. The descriptive and inferential points of view must of necessity often overlap.
A Goodness of Fit Test for the Rasch Model
Authors: Andersen Erling B. 
Published: January 2006

The Rasch model is an item analysis model with logistic item characteristic curves of equal slope, i.e. with constant item discriminating powers. The proposed goodness of fit test is based on a comparison between difficulties estimated from different scoregroups and over-all estimates.Based on the within scoregroup estimates and the over-all estimates of item difficulties a conditional likelihood ratio is formed. It is shown that—2 times the logarithm of this ratio is x2-distributed when the Rasch model is true.The power of the proposed goodness of fit test is discussed for alternative models with logistic item characteristic curves, but unequal discriminating items from a scholastic aptitude test.
Measurement as Structural Theory
Authors: Guttman Louis 
Published: January 2006

Definitions are of course arbitrary. Following Lewis Carroll, one can make words mean what one wishes [cf. Gardner, 1960]. Basically, all that is formally required of a definition is that it be clear: that it enable reliable use of the concept concerned. A more informal, heuristic, desideratum is that it actually influence theorists and researchers to progress in their work.A strategy for attaining reliability is to make a list of related concepts which might be confused with the one intended, and then to define all the concepts simultaneously in one facet framework. Such a mapping helps to make explicit what the target concept has in common with the others, and how it differs from them. This facet strategy has proved to be useful for distinguishing, for example, among varieties of intelligence [Guttman, 1965; Schlesinger and Guttman, 1969], among varieties of attitude [Guttman, 1959; Elizur, 1970; Jordan, 1971], and even between intelligence and attitude [Guttman, in press]. Evidence is accumulating as to the stimulating effect of the approach for the development of new insights and for the discovery of new forms of lawfulness in data.
Bias and Runs in Dice Throwing and Recording: A Few Million Throws
Authors: Iversen Gudmund R. , Longcor Willard H. , Mosteller Frederick , Gilbert John P. , Youtz Cleo 
Published: January 2006

An experimenter threw individually 219 different dice of four different brands and recorded even and odd outcomes for one block of 20,000 trials for each die—4,380,000 throws in all. The resulting data on runs offer a basis for comparing the observed properties of such a physical randomizing process with theory and with simulations based on pseudo-random numbers and RAND Corporation random numbers. Although generally the results are close to those forecast by theory, some notable exceptions raise questions about the surprise value that should be associated with occurrences two standard deviations from the mean. These data suggest that the usual significance level may well actually be running from 7 to 15 percent instead of the theoretical 5 percent.The data base is the largest of its kind. A set generated by one brand of dice contains 2,000,000 bits and is the first handmade empirical data of such size to fail to show a significant departure from ideal theory in either location or scale.
On Browne's Solution for Oblique Procrustes Rotation
Authors: Cramer Elliot M. 
Published: January 2006

Browne [1967] has given a method of solving the problem (originally stated by Mosier, [1939]) of finding a least squares fit to a specified factor structure. The problem is one of minimizing the sum of squared residuals of Φ — FT with Diag (T'T)= I. Browne's solution involves the eigenvectors and values of F'F and leads to an iterative solution.This paper gives a form of the solution which does not involve solution of an eigenvalue problem but does require an iteration similar to Browne's. It suggests the possible existence of a singularity, and a simple modification of Browne's computational procedure is proposed which deals with this case. A better starting value for the iteration is also proposed for which convergence is guaranteed using the ordinary Newton iteration.
Testing Pattern Hypotheses for Covariance Matrices
Authors: McDonald R. P. 
Published: January 2006

Maximum likelihood estimates of the free parameters, and an asymptotic likelihood-ratio test, are given for the hypothesis that one or more elements of a covariance matrix are zero, and/or that two or more of its elements are equal. The theory applies immediately to a transformation of the covariance matrix by a known nonsingular matrix. Estimation is by Newton's method, starting conveniently from a closed-form least-squares solution.Numerical illustrations include a test for equality of diagonal blocks of a covariance matrix, and estimation of quasi-simplex structures.
A Proposal for Handling Missing Data
Authors: Gleason Terry C. , Staelin Richard 
Published: January 2006

A method for dealing with the problem of missing observations in multivariate data is developed and evaluated. The method uses a transformation of the principal components of the data to estimate missing entries. The properties of this method and four alternative methods are investigated by means of a Monte Carlo study of 42 computer-generated data matrices. The methods are compared with respect to their ability to predict correlation matrices as well as missing entries.The results indicate that whenever there exists modest intercorrelations among the variables (i.e., average off diagonal correlation above .2) the proposed method is at least as good as the best alternative (a regression method) while being considerably faster and simpler computationally. Models for determining the best alternative based upon easily calculated characteristics of the matrix are given. The generality of these models is demonstrated using the previously published results of Timm.
Representation of Structure in Similarity Data: Problems and Prospects
Authors: Shepard Roger N. 
Published: January 2006

ConclusionAfter struggling with the problem of representing structure in similarity data for over 20 years, I find that a number of challenging problems still remain to be overcome—even in the simplest case of the analysis of a single symmetric matrix of similarity estimates. At the same time, I am more optimistic than ever that efforts directed toward surmounting the remaining difficulties will reap both methodological and substantive benefits. The methodological benefits that I forsee include both an improved efficiency and a deeper understanding of “discovery” methods of data analysis. And the substantive benefits should follow, through the greater leverage that such methods will provide for the study of complex empirical phenomena—perhaps particularly those characteristic of the human mind.
The Additive Difference Model and a Metric and an Ordering on Sets
Authors: Becker Johannes , Pipahl Werner 
Published: January 2006

On the basis of the idea of common elements to account for similarity, Restle [1959] developed a set-theoretical model on the generation of similarity judgments. Restle differentiates between his “more qualitative discussion” (p. 207), regarding stimuli as sets of elements and using no geometric concepts or assumptions, and metric quantitative developments of similarity, regarding stimuli as points in a geometric space. To the latter we can count the additive difference model of Beals, Krantz, & Tversky [1968] and Tversky & Krantz [1970].Despite these differences the two models lead to the same conclusions on the characteristics of similarity judgments.
An Alternative Method of Fitting a Model of Individual Differences in Multidimensional Scaling
Authors: Bloxom Bruce 
Published: January 2006

In articles by Homn [1969] and Carroll and Chang [1970] and in a memorandum by Bloxom [1968], a model was proposed for individual differences in multidimensional scaling. The distance in a p-dimensional space between stimuli j and k for person i is assumed to be given byfor N persons and for all pairs of n stimuli, where wim, is the “weight” given to axis m by person i and ajm, is the projection of stimulus j on that axis.
Sufficient Statistics and Latent Trait Models
Authors: Andersen Erling B. 
Published: January 2006

For questionnaires with two answer categories, it has been proven in complete generality that if a minimal sufficient statistic exists for the individual parameter and if it is the same statistic for all values of the item parameters, then the raw score (or the number of correct answers) is the minimal sufficient statistic. It follows that the model must by of the Rasch type with logistic item characteristic curves and equal item-discriminating powers.This paper extends these results to multiple choice questionnaires. It is shown that the minimal sufficient statistic for the individual parameter is a function of the so-called score vector. It is also shown that the so-called equidistant scoring is the only scoring of a questionnaire that allows for a real valued sufficient statistic that is independent of the item parameters, if a certain ordering property for the sufficient statistic holds.