The use of constructive-developmental theory to advance the understanding of leadership

Constructive-developmental theory is a stage theory of adult development that focuses on the growth and elaboration of a person's ways of understanding the self and the world. In this article we review how the constructive-developmental frameworks of Kegan [Kegan, R. (1982). The evolving self: Problem and process in human development. Cambridge, MA: Harvard University Press], Torbert [Torbert, W. R. (1987). Managing the corporate dream: Restructuring for long-term success. Homewood, IL: Dow Jones-Irwin.], and Kohlberg [Kohlberg, L. (1969). Stage and sequence: The cognitive developmental approach to socialization. In D. Goslin (Ed.), Handbook of socialization: Theory and research. New York: Rand McNally] have been applied in the theoretical and empirical literature on leadership and management. Although the literature has produced a number of propositions, the notion that a leader's order of development should impact his or her leadership effectiveness or managerial performance has generated the most research. We found mixed support for this proposition as well as a number of limitations in the research in general. To have a greater impact on the leadership field, constructive-developmental theory needs to generate more robust research, to link more clearly with on-going streams of leadership research, and to explore the contribution of aspects of the theory beyond individual order of development.     

Value of Information in Closed Loop Supply Chains

We explore the value of information (VOI) in the context of a firm that faces uncertainty with respect to demand, product return, and product recovery (yield). The operational decision of interest in matching supply with demand is the quantity of new product to order. Our objective is to evaluate the VOI from reducing one or more types of uncertainties, where value is measured by the reduction in total expected holding and shortage costs. We start with a single period model with normally distributed demands and returns, and restrict the analysis to the value of full information (VOFI) on one or more types of uncertainty. We develop estimators that are predictive of the value and sensitivity of (combinations of) different information types. We find that there is no dominance in value amongst the different types of information, and that there is an additional pay‐off from investing in more than one type. We then extend our analysis to the multi‐period case, where returns in a period are correlated with demands in the previous period, and study the value of partial information (VOPI) as well as full information. We demonstrate that our results from the single period model (adapted for VOPI) carry‐over exactly. Furthermore, a comparison with uniformly distributed demand and return show that these results are robust with respect to distributional assumptions.     

One-dimensional optimal bounded-shape partitions for Schur convex sum objective functions

Consider the problem of partitioning n nonnegative numbers into p parts, where part i can be assigned n_i numbers with n_i lying in a given range. The goal is to maximize a Schur convex function F whose ith argument is the sum of numbers assigned to part i. The shape of a partition is the vector consisting of the sizes of its parts, further, a shape (without referring to a particular partition) is a vector of nonnegative integers (n₁,..., n_p) which sum to n. A partition is called size-consecutive if there is a ranking of the parts which is consistent with their sizes, and all elements in a higher-ranked part exceed all elements in the lower-ranked part. We demonstrate that one can restrict attention to size-consecutive partitions with shapes that are nonmajorized, we study these shapes, bound their numbers and develop algorithms to enumerate them. Our study extends the analysis of a previous paper by Hwang and Rothblum which discussed the above problem assuming the existence of a majorizing shape. This research is partially supported by ROC National Science grant NSC 92-2115-M-009-014.     

Optimal algorithms for uncovering synteny problem

The syntenic distance between two genomes is the minimum number of fusions, fissions, and translocations that can transform one genome to the other, ignoring the gene order within chromosomes. As the problem is NP-hard in general, some particular classes of synteny instances, such as linear synteny, exact synteny and nested synteny, are examined in the literature. In this paper, we propose a new special class of synteny instances, called uncovering synteny. We first present a polynomial time algorithm to solve the connected case of uncovering synteny optimally. By performing only intra-component moves, we then solve the unconnected case of uncovering synteny. We will further calculate the diameters of connected and unconnected uncovering synteny, respectively.     

A Risk and Economic Analysis of Dirty Bomb Attacks on the Ports of Los Angeles and Long Beach

This article analyzes possible terrorist attacks on the ports of Los Angeles and Long Beach using a radiological dispersal device (RDD, also known as a "dirty bomb") to shut down port operations and cause substantial economic and psychological impacts. The analysis is an exploratory investigation of a combination of several risk analysis tools, including scenario generation and pruning, project risk analysis, direct consequence modeling, and indirect economic impact assessment. We examined 36 attack scenarios and reduced them to two plausible or likely scenarios using qualitative judgments. For these two scenarios, we conducted a project risk analysis to understand the tasks terrorists need to perform to carry out the attacks and to determine the likelihood of the project's success. The consequences of a successful attack are described in terms of a radiological plume model and resulting human health and economic impacts. Initial findings suggest that the chances of a successful dirty bomb attack are about 10-40% and that high radiological doses are confined to a relatively small area, limiting health effects to tens or at most hundreds of latent cancers, even with a major release. However, the economic consequences from a shutdown of the harbors due to the contamination could result in significant losses in the tens of billions of dollars, including the decontamination costs and the indirect economic impacts due to the port shutdown. The implications for countering a dirty bomb attack, including the protection of the radiological sources and intercepting an ongoing dirty bomb attack are discussed.     

Development of a Screening Approach to Interpret Human Biomonitoring Data on Volatile Organic Compounds: Reverse Dosimetry on Biomonitoring Data for Trichloroethylene

A screening approach is developed for volatile organic compounds (VOCs) to estimate exposures that correspond to levels measured in fluids and/or tissues in human biomonitoring studies. The approach makes use of a generic physiologically-based pharmacokinetic (PBPK) model coupled with exposure pattern characterization, Monte Carlo analysis, and quantitative structure property relationships (QSPRs). QSPRs are used for VOCs with minimal data to develop chemical-specific parameters needed for the PBPK model. The PBPK model is capable of simulating VOC kinetics following multiple routes of exposure, such as oral exposure via water ingestion and inhalation exposure during shower events. Using published human biomonitoring data of trichloroethylene (TCE), the generic model is evaluated to determine how well it estimates TCE concentrations in blood based on the known drinking water concentrations. In addition, Monte Carlo analysis is conducted to characterize the impact of the following factors: (1) uncertainties in the QSPR-estimated chemical-specific parameters; (2) variability in physiological parameters; and (3) variability in exposure patterns. The results indicate that uncertainty in chemical-specific parameters makes only a minor contribution to the overall variability and uncertainty in the predicted TCE concentrations in blood. The model is used in a reverse dosimetry approach to derive estimates of TCE concentrations in drinking water based on given measurements of TCE in blood, for comparison to the U.S. EPA's Maximum Contaminant Level in drinking water. This example demonstrates how a reverse dosimetry approach can be used to facilitate interpretation of human biomonitoring data in a health risk context by deriving external exposures that are consistent with a biomonitoring data set, thereby permitting comparison with health-based exposure guidelines.     

交通信息条件下道路和停车选择SUE模型及算法

考虑交通信息系统(advanced traveler information system,ATIS)对出行者道路和停车选择行为的影响,并将出行者分成两类:一类出行者使用ATIS,另一类不使用ATIS.在此基础上,构造了一个基于概率的随机用户均衡模型来描述ATIS条件下的道路和停车选择问题,并给出了相应的求解算法.最后,通过一个算例分析了模型及算法的使用效果.     

一类CRM模型的构建及其销售策略分析

从分析现有CRM(客户关系管理)系统的缺失入手,强调了销售以客户“人”为分析基点的重要性,在此基础上给出了一类销售过程的简化状态指标.应用该思路、指标、借助于Pfeifer和Carraway的思路、利用Markov链建立商家与客户关系模型,就有限次销售的一次交易、多次交易及无限次销售的情况分别给出相应分析结果.并考虑企业实际运作,进一步讨论了该模型下不同销售策略模型的响应.结果表明,减少成功率小的销售活动,企业期望获利会更大些.     

Risk of Legionellosis in residential areas around farms irrigating with municipal wastewater

The conservation of freshwater is of both global and national importance, and in the United States, agriculture is one of the largest consumers of this resource. Reduction of the strain farming puts on local surface or groundwater is vital for ensuring resilience in the face of climate change, and one possible option is to irrigate with a combination of freshwater and reclaimed water from municipal wastewater treatment facilities. However, this wastewater can contain pathogens that are harmful to human health, such as Legionella pneumophila, which is a bacterium that can survive aerosolization and airborne transportation and cause severe pneumonia when inhaled. To assess an individual adult's risk of infection with L. pneumophila from a single exposure to agricultural spray irrigation, a quantitative microbial risk assessment was conducted for a scenario of spray irrigation in central Illinois, for the growing seasons in 2017, 2018, and 2019. The assessment found that the mean risk of infection for a single exposure exceeded the safety threshold of 10^–6 infections/exposure up to 1 km from a low-pressure irrigator and up to 2 km from a high-pressure irrigator, although no median risk exceeded the threshold for any distance or irrigator pressure. These findings suggest that spray irrigation with treated municipal wastewater could be a viable option for reducing freshwater consumption in Midwest farming, as long as irrigation on windy days is avoided and close proximity to the active irrigator is limited.