A comparative study of U.S. and Iraqi students

This study uses a sample comprised of U.S. students and Iraqi students to determine if differences occur over ethical perceptions based on cultural/demographic issues. Irrespective of demographics, the results of this study indicate significant cultural differences between Iraqi students and American students with regard to selected ethical issues concerning graduate education. Specifically the differences occurred in the students' perceptions of winning is everything, selling one's soul, logic before emotion, and pander to professors. Iraqi students consistently viewed these beliefs as more necessary for success in their graduate education than did their American counterparts.     

Ethical Futures and Public-Private Partnerships: Peering Far Down the Track

This article employs an institutional perspective in formulating predictions about the ethical futures of privatization partnerships. Although this paper focuses on ethical concerns in the U.S. public sector, it incorporates a multinational dimension in (a) comparing the meaning of privatization among societies and (b) probing privatization financing in the global economy. Five assumptions that flow from institutional reasoning are made explicit as supports for subsequent predictions. The institutional logic shifts privatization conversation away from conventional debate about competition and efficiency toward centralizing forces in both sectors in response to globalization. In that regard, this study identifies the systemic erosion of (local) community integrity as the key privatization problem of the future.     

Examining the link between social responsibility and decision styles

The paper examines the factors that influence socially responsible decision making by individuals. The study found four social responsibility styles: Playing it Safe, Weather The Storm, Problem to Solve, and Hope it Goes Away. These styles describe individuals on the basis of decision style, propensity for risk, and coping style. The styles explain why people with different values might come to the same decision in the same circumstances.     

Approximation Algorithms for Quadratic Programming

We consider the problem of approximating the global minimum of a general quadratic program (QP) with n variables subject to m ellipsoidal constraints. For m=1, we rigorously show that an -minimizer, where error (0, 1), can be obtained in polynomial time, meaning that the number of arithmetic operations is a polynomial in n, m, and log(1/). For m 2, we present a polynomial-time (1- )-approximation algorithm as well as a semidefinite programming relaxation for this problem. In addition, we present approximation algorithms for solving QP under the box constraints and the assignment polytope constraints.     

Fundamentals of Health Risk Assessment. Use,Derivation, Validity and Limitations of Safety Indices

We investigated the way results of human health risk assessments are used, and the theory used to describe those methods, sometimes called the NAS paradigm. Contrary to a key tenet of that theory, current methods have strictly limited utility. The characterizations now considered standard, Safety Indices such as Acceptable Daily Intake, Reference Dose, and so on, usefully inform only decisions that require a choice between two policy alternatives (e.g., approve a food additive or not), decided solely on the basis of a finding of safety. Risk is characterized as the quotient of one of these Safety Indices divided by an estimate of exposure: a quotient greater than one implies that the situation may be considered safe. Such decisions are very widespread, both in the U. S. federal government and elsewhere. No current method is universal; different policies lead to different practices, for example, in California's Proposition 65, where statutory provisions specify some practices. Further, an important kind of human health risk assessment is not recognized by this theory: this kind characterizes risk as likelihood of harm, given estimates of exposure consequent to various decision choices. Likelihood estimates are necessary whenever decision makers have many possible decision choices and must weigh more than two societal values, such as in EPA's implementation of conventional air pollutants. These estimates can not be derived using current methods; different methods are needed. Our analysis suggests changes needed in both the theory and practice of human health risk assessment, and how what is done is depicted.     

Human Interindividual Variability in Parameters Related to Health Risks

This paper reviews existing data on the variability in parameters relevant for health risk analyses. We cover both exposure-related parameters and parameters related to individual susceptibility to toxicity. The toxicity/susceptibility data base under construction is part of a longer term research effort to lay the groundwork for quantitative distributional analyses of non-cancer toxic risks. These data are broken down into a variety of parameter types that encompass different portions of the pathway from external exposure to the production of biological responses. The discrete steps in this pathway, as we now conceive them, are:Contact Rate (Breathing rates per body weight; fish consumption per body weight)Uptake or Absorption as a Fraction of Intake or Contact RateGeneral Systemic Availability Net of First Pass Elimination and Dilution via Distribution Volume (e.g., initial blood concentration per mg/kg of uptake)Systemic Elimination (half life or clearance)Active Site Concentration per Systemic Blood or Plasma ConcentrationPhysiological Parameter Change per Active Site Concentration (expressed as the dose required to make a given percentage change in different people, or the dose required to achieve some proportion of an individual's maximum response to the drug or toxicant)Functional Reserve Capacity–Change in Baseline Physiological Parameter Needed to Produce a Biological Response or Pass a Criterion of Abnormal FunctionComparison of the amounts of variability observed for the different parameter types suggests that appreciable variability is associated with the final step in the process–differences among people in functional reserve capacity. This has the implication that relevant information for estimating effective toxic susceptibility distributions may be gleaned by direct studies of the population distributions of key physiological parameters in people that are not exposed to the environmental and occupational toxicants that are thought to perturb those parameters. This is illustrated with some recent observations of the population distributions of Low Density Lipoprotein Cholesterol from the second and third National Health and Nutrition Examination Surveys.     

Context in the Risk Assessment of Digital Systems

As the use of digital computers for instrumentation and control of safety-critical systems has increased, there has been a growing debate over the issue of whether probabilistic risk assessment techniques can be applied to these systems. This debate has centered on the issue of whether software failures can be modeled probabilistically. This paper describes a context-based approach to software risk assessment that explicitly recognizes the fact that the behavior of software is not probabilistic. The source of the perceived uncertainty in its behavior results from both the input to the software as well as the application and environment in which the software is operating. Failures occur as the result of encountering some context for which the software was not properly designed, as opposed to the software simply failing randomly. The paper elaborates on the concept of error-forcing context as it applies to software. It also illustrates a methodology which utilizes event trees, fault trees, and the Dynamic Flowgraph Methodology (DFM) to identify error-forcing contexts for software in the form of fault tree prime implicants.     

On Shortest k-Edge-Connected Steiner Networks in Metric Spaces

Given a set of points P in a metric space, let l(P) denote the ratio of lengths between the shortest k-edge-connected Steiner network and the shortest k-edge-connected spanning network on P, and let r = inf l(P) P for k 1. In this paper, we show that in any metric space, r 3/4 for k 2, and there exists a polynomial-time -approximation for the shortest k-edge-connected Steiner network, where = 2 for even k and = 2 + 4/(3k) for odd k. In the Euclidean plane, and .     

Combining Probability Distributions From Experts in Risk Analysis

This paper concerns the combination of experts' probability distributions in risk analysis, discussing a variety of combination methods and attempting to highlight the important conceptual and practical issues to be considered in designing a combination process in practice. The role of experts is important because their judgments can provide valuable information, particularly in view of the limited availability of hard data regarding many important uncertainties in risk analysis. Because uncertainties are represented in terms of probability distributions in probabilistic risk analysis (PRA), we consider expert information in terms of probability distributions. The motivation for the use of multiple experts is simply the desire to obtain as much information as possible. Combining experts' probability distributions summarizes the accumulated information for risk analysts and decision-makers. Procedures for combining probability distributions are often compartmentalized as mathematical aggregation methods or behavioral approaches, and we discuss both categories. However, an overall aggregation process could involve both mathematical and behavioral aspects, and no single process is best in all circumstances. An understanding of the pros and cons of different methods and the key issues to consider is valuable in the design of a combination process for a specific PRA. The output, a combined probability distribution, can ideally be viewed as representing a summary of the current state of expert opinion regarding the uncertainty of interest.     

On Approximability of Boolean Formula Minimization

For a Boolean function given by a Boolean formula (or a binary circuit) S we discuss the problem of building a Boolean formula (binary circuit) of minimal size, which computes the function g equivalent to , or -equivalent to , i.e., . In this paper we prove that if P NP then this problem can not be approximated with a good approximation ratio by a polynomial time algorithm.     

Leadership styles,Machiavellianism, and needs of Saudi Arabian managers

The findings indicated that the economic environment and the cultural and religious orientations of managers in Saudi Arabia significantly influenced their scores on Machiavellianism and the relationships between their needs and leadership styles. In comparison to the U.S. norms the Saudi Arabian managers were found to be lower on Machiavellianism. Need for achievement was found to be positively related to need for power and structure dimension of leadership. The findings also showed Machiavellianism to be positively related to need for power and negatively related to consideration dimension of leadership. The findings are discussed in the context of a fast-growing economy and a highly religious and a traditional society.     

Comments on the Paper: Attacking the Market Split Problem with Lattice Point Enumeration

We present a few comments on the paper Attacking the market split problem with lattice point enumeration by A. Wasserman, published in Journal of Combinatorial Optimization, vol. 6, pp. 5–16, 2002.     

Managerial prerogatives,employee expectations,and property rights in job security: Institutionalizing the “new equity”

Changes in the structure and provisions of the employment relationship create substantial challenges for the management community. The employer-manager's traditional prerogatives to terminate at will are being eroded in response to changing socioeconomic values that recognize the emergence of an employee's reasonable expectations of job security. The United States lags far behind the international community in protecting these expectations. The authors survey the erosion of the employment-at-will doctrine, and review the concepts of corporate due process and property rights relating to employment. To ensure the institutionalization of this new equity, the authors call on the management community to take the initiative in crafting progressive legislation that strikes a sensible balance between managerial prerogatives and employee expectations of job security.     

Counseling models and their impact on how therapists handle values issues

Counseling is not a value free enterprise. Therapeutic models are value laden. Counselors and clients are both emotionally invested in right living issues. Since no therapy is value free, clients face the dilemma of finding a therapist with values similar to their own or having their values challenged. Therapists face the ethical issue of clarifying their own values and determining how to make them known.     

A Further Improved Approximation Algorithm for Breakpoint Graph Decomposition

Breakpoint graph decomposition is a crucial step in all recent approximation algorithms for SORTING BY REVERSALS, which is one of the best-known algorithmic problems in computational molecular biology. Caprara and Rizzi recently improved the approximation ratio for breakpoint graph decomposition from to + 1.4348 + , for any positive . In this paper, we extend the techniques of Caprara and Rizzi and incorporate a balancing argument to further improve the approximation ratio to + 1.4193 + , for any positive . These improvements imply improved approximation results for SORTING BY REVERSALS for almost all random permutations.     

An Edge-Splitting Algorithm in Planar Graphs

For a multigraph G = (V, E), let s V be a designated vertex which has an even degree, and let _G (V – s) denote min{c _G(X) | Ø X V – s}, where c _G(X) denotes the size of cut X. Splitting two adjacent edges (s, u) and (s, v) means deleting these edges and adding a new edge (u, v). For an integer k, splitting two edges e ₁ and e ₂ incident to s is called (k, s)-feasible if _G(V – s) k holds in the resulting graph G. In this paper, we prove that, for a planar graph G and an even k or k = 3 with k _G (V – s), there exists a complete (k, s)-feasible splitting at s such that the resulting graph G is still planar, and present an O(n ³ log n) time algorithm for finding such a splitting, where n = |V|. However, for every odd k 5, there is a planar graph G with a vertex s which has no complete (k, s)-feasible and planarity-preserving splitting. As an application of this result, we show that for an outerplanar graph G and an even integer k the problem of optimally augmenting G to a k-edge-connected planar graph can be solved in O(n ³ log n) time.     

Business student ethical values anew in the 1990s

This paper uses a Rokeach Value Survey methodology to again ask the question, now in the mid 1990s, whether business student ethics are different from non-business student ethics. Additionally, the paper addresses the question of whether a course can alter or change student ethics and values during a semester. Thirdly, this paper attempts to operationalize and empirically test and measure the new ethical concepts of moral management and moral maximization.     

Are g.p.a. and ethics related?

This article reports results of a study of some 200 college-aged students at California State University. Ethical values are measured using a subset of the well-known and frequently used Rokeach Value Survey. Using nonparametric statistical analysis, four value measures, and four different consistent tests of significance and probability, the research data, perhaps disappointedly for many observers including the authors, reveal that there is no relationship between college grade point average and student ethics. Statistical analysis was done on g.p.a. splits of less than 3.0 versus 3.0 or more and also on g.p.a. data for 2.5 or less versus 3.5 or more. In all cases, there are no significant relationships between high or low grade point averages and scores on ethical value rankings.     

Human Resource Management Best Practices and Globalization: The Universality of Common Sense

Popular strategies for reform have come directly from the private sector in what is perhaps the most profound redefinition of public administration since the field first emerged as an identifiable specialty. The purpose of this paper is to examine the context out of which these reforms have grown, the challenges that have arisen as a result, and cases where private sector reform strategies have been successfully (and sometimes unsuccessfully) applied in human resource management (HRM). We discuss the benefits and hazards of many of the reforms and conclude that restoring a measure of confidence in the legitimate role of the civil service is essential for nations dealing with the challenges of globalization.     

An Approximation Algorithm for Alignment of Multiple Sequences using Motif Discovery

Given a set of N sequence, the Multiple Sequence Alignment problem is to align these N sequences, possibly with gaps, that brings out the best commonality of the N sequences. The quality of the alignment is usually measured by penalizing the mis-matches and gaps, and rewarding the matches with appropriate weight functions. However for larger values of N, additional constraints are required to give meaningful alignments. We identify a user-controlled parameter, an alignment number K (2 K N): this additional requirement constrains the alignment to have at least K sequences agree on a character, whenever possible, in the alignment. We identify a natural optimization problem for this approach called the K-MSA problem. We show that the problem is MAX SNP hard. We give a natural extension of this problem that incorporates biological relevance by using motifs (common patterns in the sequences) and give an approximation algorithm for this problem in terms of the motifs in the data. MUSCA is an implementation of this approach and our experimental results indicate that this approach is efficient, particularly on large numbers of long sequences, and gives good alignments when tested on biological data such as DNA and protein sequences.