Recurrence with affine level mappings is P-time decidable for CLP(R)

In this paper we introduce a class of constraint logic programs such that their termination can be proved by using affine level mappings. We show that membership to this class is decidable in polynomial time.Comment: To appear in Theory and Practice of Logic Programming (TPLP

Long Chaotic Transients in Complex Networks

We show that long chaotic transients dominate the dynamics of randomly diluted networks of pulse-coupled oscillators. This contrasts with the rapid convergence towards limit cycle attractors found in networks of globally coupled units. The lengths of the transients strongly depend on the network connectivity and varies by several orders of magnitude, with maximum transient lengths at intermediate connectivities. The dynamics of the transient exhibits a novel form of robust synchronization. An approximation to the largest Lyapunov exponent characterizing the chaotic nature of the transient dynamics is calculated analytically.Comment: 4 pages; 5 figure

Cost minimizing plans for various types of farms in Northeast Missouri

This bulletin is a report on Department of Agricultural Economics research project 110 'Farm Enterprise'--P. [2].Includes bibliographical references

Differential Effects of Incentive Motivators on Work Performance

In this field experiment, we first compared the performance effects of money systematically administered through the organizational behavior modification (O.B. Mod.) model and routine pay for performance and then compared the effects of O.B. Mod.- administered money, social recognition, and performance feedback. The money intervention based on the O.B. Mod. outperformed routine pay for performance (performance increase = 37% vs. 11%) and also had stronger effects on performance than social recognition (24%) and performance feedback (20%)

The Traveling Salesman Problem Under Squared Euclidean Distances

Let $P$ be a set of points in $\mathbb{R}^d$, and let $\alpha \ge 1$ be a real number. We define the distance between two points $p,q\in P$ as $|pq|^{\alpha}$, where $|pq|$ denotes the standard Euclidean distance between $p$ and $q$. We denote the traveling salesman problem under this distance function by TSP($d,\alpha$). We design a 5-approximation algorithm for TSP(2,2) and generalize this result to obtain an approximation factor of $3^{\alpha-1}+\sqrt{6}^{\alpha}/3$ for $d=2$ and all $\alpha\ge2$. We also study the variant Rev-TSP of the problem where the traveling salesman is allowed to revisit points. We present a polynomial-time approximation scheme for Rev-TSP$(2,\alpha)$ with $\alpha\ge2$, and we show that Rev-TSP$(d, \alpha)$ is APX-hard if $d\ge3$ and $\alpha>1$. The APX-hardness proof carries over to TSP$(d, \alpha)$ for the same parameter ranges.Comment: 12 pages, 4 figures. (v2) Minor linguistic change

Behavioral Management and Task Performance in Organizations: Conceptual Background, Meta-Analysis, and Test of Alternative Models

In this study, we provide the conceptual background, meta-analyze available behavioral management studies (N = 72) in organizational settings, and examine whether combined reinforcement effects on task performance are additive (sum of individual effects), redundant (combined effects are less than the additive effects), or synergistic (combined effects are greater than the sum of the individual effects). We found a significant overall average effect size of (d.) = .47 (16% improvement in performance; 63% probability of success), and a significant within-group heterogeneity of effect sizes. To account for this variation, we conducted a theory-driven moderator analysis, which indicated that money, feedback, and social recognition each had a significant impact on task performance. However, when these 3 reinforcers were used in combination, they produced the strongest (synergistic) effect on task performance. Based on our findings, we offer directions for future research, and suggestions for effective application of behavioral management at work

Reinforce for performance: The need to go beyond pay and even rewards

Perhaps the most talked about, if not actually implemented. practical solution for making human resources more productive is pay for performance. Yet many researchers and practitioners doubt the true effectiveness of this approach. To help solve this controversy. we suggest drawing from reinforcement theory and behavioral management. This approach can be used to explain the simple statements: You get what you reinforce. but you do not necessarily get what you pay for. We first critically review the traditional pay for performance practices and address the question of whether rewards. not reinforcers. do more harm than good. Next, we discuss the theoretical foundation that you get what you reinforce. Finally. we outline the behavioral management steps of organizational behavior modification (O.B. Mod.). When O.B. Mod. has been systematically applied over the years using both monetary and nonmonetary reinforcers. our recent meta-analysis found that performance on average increased 17 percent. The contingencies and practical implications of this behavioral management approach that advocates reinforce for performance instead of payor even reward for performance are discussed