Development of an ethanol model using social insects: II. Effect of Antabuse on consumatory responses and learned behavior of the honey bee (Apis mellifera L.)

The ability of Antabuse (disulfiram) to influence ethanol consumption and learning in harnessed honey bees was investigated. In the first series of experiments a factorial design was used with 5 levels of ethanol concentration (0%, 1%, 5%, 10%, 20%), 4 doses of Antabuse (0, 37 microg/g, 3.7 microg/g, .37 microg/g), and 2 testing intervals (1 min., 10 min.). Animals were fed a single 1 microl dose of Antabuse and contact time with an ethanol solution measured. A second series of experiments investigated the influence of Antabuse on the formation of Pavlovian conditioning of the proboscis extension reflex. A factorial design was used with two levels of training (paired, unpaired), three levels of ethanol (0%, 1%, 5%), and 2 levels of pretreatment (distilled water, 3.7 microg/g). Analysis of the consumption experiments indicate that pretreatment with Antabuse reduces ethanol intake, although there was substantial variability. The findings of the Pavlovian experiments suggest that pretreatment with Antabuse significantly reduced responding to a CS signaling the availability of ethanol.     

An efficient alternating least-squares algorithm to perform multidimensional unfolding

We consider the problem of least-squares fitting of squared distances in unfolding. An alternating procedure is proposed which fixes the row or column configuration in turn and finds the global optimum of the objective criterion with respect to the free parameters, iterating in this fashion until convergence is reached. A considerable simplification in the algorithm results, namely that this conditional global optimum is identified by performing a single unidimensional search for each point, irrespective of the dimensionality of the unfolding solution.This work originally formed part of a doctoral thesis (Greenacre, 1978) presented at the University of Paris VI. The authors acknowledge the helpful comments of John Gower during the first author's sabbatical at Rothamsted Experimental Station. The authors are also indebted to Alexander Shapiro, who came up with the proof of the key result which the authors had long suspected, but had not proved, namely that the smallest root of function (13) provides the global minimum of function (7). The constructive comments of the referees of this paper are acknowledged with thanks. This research was supported in part by the South African Council for Scientific and Industrial Research.     

Properties of the maximum likelihood solution in factor analysis regression

Algebraic properties of the normal theory maximum likelihood solution in factor analysis regression are investigated. Two commonly employed measures of the within sample predictive accuracy of the factor analysis regression function are considered: the variance of the regression residuals and the squared correlation coefficient between the criterion variable and the regression function. It is shown that this within sample residual variance and within sample squared correlation may be obtained directly from the factor loading and unique variance estimates, without use of the original observations or the sample covariance matrix.     

Defining death

ABSTRACT Modern technology has made it uncertain as to when exactly death occurs, and this has put us in a quandary over when we can initiate behaviour traditionally deemed apt if and only if a patient is dead. In the light of this, there is general agreement that death should be redefined, but wide disagreement remains about how. I argue, against this, that it is a mistake to redefine death in any way: (1) redefining death will not help to settle the question of when traditional death-behaviour becomes appropriate, (2) any attempt to redefine death is attended with significant disutilities and no compensating utilities, and (3) the practical problems generated by the indeterminacy can be better handled in other ways.     

USE OF NEGATIVE REINFORCEMENT IN THE TREATMENT OF SELF-INJURIOUS BEHAVIOR

Behavioral assessment procedures were used to determine the maintaining conditions of self-injury exhibited by 2 children with severe multiple handicaps. For both children, negative reinforcement (escape from grooming activities) was determined to be the maintaining reinforcer for self-injury (hand/arm biting) within an alternating treatments design. The treatment packages involved the use of negative reinforcement (brief escape from grooming activities) contingent upon a behavior that was incompatible with self-injury (reaching and pressing a microswitch that activated a prerecorded message of “stop”). Treatment was evaluated with a reversal design for 1 child and with a multiple baseline across grooming activities for the 2nd child. The treatment led to a marked decrease in self-injury for both children. At follow-up, high rates of self-injury were reported for the 1st child, but low rates of self-injury and an increase in task-related appropriate behavior were observed for the 2nd child.     

THE TREATMENT OF SEVERE BEHAVIOR PROBLEMS IN SCHOOL SETTINGS USING A TECHNICAL ASSISTANCE MODEL

We evaluated the feasibility of local school personnel conducting functional analysis and reinforcement-based treatment procedures within actual classroom settings. Following an initial in-service workshop on functional assessment and differential reinforcement procedures, on-site technical assistance was provided two to four times per month to local school personnel working in transdisciplinary teams. Overall results suggest that local school personnel were able to implement all procedures adequately with periodic technical assistance. In addition, functional analysis was effective in identifying individual maintaining contingencies, the derived treatments were effective, and the results were maintained throughout the approximate 18 months of this investigation.     

The bits and bytes of computer/internet addiction: A factor analytic approach

A factor analytic approach was used to explore possible constructs underlying so-called computer/Internet addiction. A 94-item survey was developed, from which two major and two minor factors were derived. Factor 1 focused on problematic computer-related behaviors in heavy users of the Internet, whereas Factor 2 focused on the usefulness and general purpose nature of computers and the Internet. Factor 3 isolated a combination of use of the Internet for sexual gratification and shyness/introversion, and Factor 4 focused on an absence of problems related to Internet use that were coupled with a mild aversion or a disinterest in this technology. These data support the notion that some individuals have a mixture of obsessive-like characteristics related specifically to their computer/Internet use but that, not surprisingly, they also exhibit a preference for on-line, rather than in-person, interactions.     

Circumplex models for correlation matrices

Structural models that yield circumplex inequality patterns for the elements of correlation matrices are reviewed. Particular attention is given to a stochastic process defined on the circle proposed by T. W. Anderson. It is shown that the Anderson circumplex contains the Markov Process model for a simplex as a limiting case when a parameter tends to infinity.Anderson's model is intended for correlation matrices with positive elements. A replacement for Anderson's correlation function that permits negative correlations is suggested. It is shown that the resulting model may be reparametrzed as a factor analysis model with nonlinear constraints on the factor loadings. An unrestricted factor analysis, followed by an appropriate rotation, is employed to obtain parameter estimates. These estimates may be used as initial approximations in an iterative procedure to obtain minimum discrepancy estimates.Practical applications are reported.Presented as the 1992 Psychometric Society Presidential Address. I am greatly indebted to Stephen Du Toit for help in the development of the computer program employed here. Part of this research was carried out at the University of South Africa and at the Institute for Statistical Research of the South African Human Sciences Research Council.     

The comparison of interdependent correlations between optimal linear composites

A general procedure is provided for comparing correlation coefficients between optimal linear composites. The procedure allows computationally efficient significance tests on independent or dependent multiple correlations, partial correlations, and canonical correlations, with or without the assumption of multivariate normality. Evidence from some Monte Carlo studies on the effectiveness of the methods is also provided.This research was supported in part by an operating grant (#67-4640) to the first author from the National Sciences and Engineering Research Council of Canada. The authors would also like to acknowledge the helpful comments and encouragement of Alexander Shapiro, Stanley Nash, and Ingram Olkin.