Integrating demand and traffic simulation modeling to evaluate adaptive evacuation plans

Significant efforts are currently being made by transportation officials to improve the planning and preparation of mass evacuations. The idea of adaptive evacuation plans is an avenue of research that could help improve future evacuation processes. Adaptive evacuation plans stem from the observation that different disaster threat scenarios require different evacuation responses. While adaptive evacuation planning can be generalized to any form of evacuation planning, this project focused on adaptive planning in the context of a hurricane evacuation. This project was the first to adapt the demand models of Fu, et al, and Cheng, et al, into a regional-scale traffic simulation model. The conclusion of this component of research was that the use of household-level evacuation decision models to generate traffic demand in a simulation model can accurately produce cumulative evacuation volumes. The results showed R2 correlations to observed cumulative evacuation volumes with values of at least 0.7. A qualitative and quantitative assessment of the traffic impacts of using adaptive evacuation plans was also performed in the study. Overall, the results showed that the average travel time across the entire simulated region was reduced by 14.8 percent when adaptive evacuation plans were employed. The significance of these results lies in their applicability in effectively moving more people out of danger when faced with a threat. The main argument behind this study was that to effectively transport evacuees, something must be known about how they will react to any given threat. A single, static evacuation plan does not tailor to the broad range of response that could come from evacuees. Evacuation plans that have been adapted to suit a range of likely evacuation responses have been shown in this study to better serve evacuees by reducing travel time and other costs associated with evacuation. The general results should be enormously important to all researchers in the evacuation field as well as emergency managers

Daily Practice1: Ethics In Leadership

The classic question, “Should business schools teach ethics?” is not often asked anymore given the drip, drip, drip of business corruption reported in the news. Even skeptics allow that business ethics education could not hurt and might improve the ethics of business leaders. Furthermore, universities, colleges, and business accrediting agencies prominently represent their ethics for all to see in standards, codes, handbooks, and advertisements. They seem to promote ethical conduct at their institutions. But how do faculty and administrators actually behave? And if not ethically, what are the educational lessons new professionals take to the workplace?&nbsp

Modeling History Dependence in Network-Behavior Coevolution

Spatial interdependence--the dependence of outcomes in some units on those in others--is substantively and theoretically ubiquitous and central across the social sciences. Spatial association is also omnipresent empirically. However, spatial association may arise from three importantly distinct processes: common exposure of actors to exogenous external and internal stimuli, interdependence of outcomes/behaviors across actors (contagion), and/or the putative outcomes may affect the variable along which the clustering occurs (selection). Accurate inference about any of these processes generally requires an empirical strategy that addresses all three well. From a spatial-econometric perspective, this suggests spatiotemporal empirical models with exogenous covariates (common exposure) and spatial lags (contagion), with the spatial weights being endogenous (selection). From a longitudinal network-analytic perspective, we can identify the same three processes as potential sources of network effects and network formation. From that perspective, actors\u27 self-selection into networks (by, e.g., behavioral homophily) and actors\u27 behavior that is contagious through those network connections likewise demands theoretical and empirical models in which networks and behavior coevolve over time. This paper begins building such modeling by, on the theoretical side, extending a Markov type-interaction model to allow endogenous tie-formation, and, on the empirical side, merging a simple spatial-lag logit model of contagious behavior with a simple p-star logit model of network formation, building this synthetic discrete-time empirical model from the theoretical base of the modified Markov type-interaction model. One interesting consequence of network-behavior coevolution--identically: endogenous patterns of spatial interdependence--emphasized here is how it can produce history-dependent political dynamics, including equilibrium phat and path dependence (Page 2006). The paper explores these implications, and then concludes with a preliminary demonstration of the strategy applied to alliance formation and conflict behavior among the great powers in the first half of the twentieth century

Network Selection and Path-Dependent Coevolution

Scholars have increasingly become aware that actors’ self-selection into networks (e.g., homophily) is an important determinant of network-tie formation. Such self-selection adds methodological complexity to the empirical evaluation of the effects of network ties on individual behavior. Moreover, the endogenous network formation implies that network-tie structures and actors’ behavior “coevolve” over time. Therefore, in longitudinal network studies, it is very crucial for scholars to understand the nature of coevolutionary dynamics in the data, in order to explain the network-formation and the behavioral-decision-making mechanisms accurately. In this project, we claim that one of the most important aspects of the coevolutionary dynamic is its connection with history dependence. By history dependence, we primarily focus on what Page (2006) defines as “phat” and path dependence. We first establish theoretically that systems with coevolution can easily generate multiple equilibria (i.e., the steady states of the system), using a simple Markov type-interaction model that allows for endogenous tie formation. The potential of multiple equilibria posits an important and very difficult empirical question--how sensitive are equilibrium distributions (over types) to the past states? More simply put, to what extent does history matter? What is at stake in this question is not trivial. If history matters for an equilibrium attained in the society, then we can also analyze the potential policy interventions that could change the path of the social process such that it would lead to a socially optimal equilibrium. As for the empirical strategy, we start with developing a discrete-time Markov model, combining a spatial-logit and p-star model to evaluate the empirical significance of coevolutionary dynamics in the data. The strength of this empirical approach is in its direct connection with the theoretical Markov interaction model, and can provide a foundation for developing statistical tests for history dependence generated by coevolution

Scalable Hierarchical Network Management System for Displaying Network Information in Three Dimensions

A network management system has SNMP agents distributed at one or more sites, an input output module at each site, and a server module located at a selected site for communicating with input output modules, each of which is configured for both SNMP and HNMP communications. The server module is configured exclusively for HNMP communications, and it communicates with each input output module according to the HNMP. Non-iconified, informationally complete views are provided of network elements to aid in network management

Investigating Project Success Factors in Post-Disaster Rebuilding Efforts in NYC

On October 29, 2012, Superstorm Sandy caused nearly $19 billion in damages in New York City including damage to 69,000 residential units. A precipitated amount of roughly$4.2 billion in Community Development Block Grant was allocated towards PDR construction. These funds addressed a range of needs, including rebuilding and rehabilitating housing, assisting displaced tenants, and providing aid to businesses. Post-Disaster Rebuilding (PDR) is similar to construction in the modification of an existing facility that involves either renovation, additions, or subtractions to scopes of work to assist the overall performance of the facility. However, PDR goes further in a highly coordinated process involving planning for future disaster events, integrating a temporary facility plan for those displaced, and tackling housing issues for all those affected by natural disasters. PSF (project success factors) consist of activities or elements that are required to ensure the successful completion of the project. Researchers have discussed literature PSF for PDR projects on topics including the importance of shared data modeling for interdisciplinary exchange of information for effective communication and risk reduction, formulating a holistic PDR approach that can be effective and adaptable to future reconstruction efforts (and inclusive of all stakeholders), and assessing the experience levels of all team members. However, existing research into the assessment of the goals for PDR projects is limited, warranting an investigation of construction success factors as it applies to PDR efforts to improve equitable community resettlement and sustainable and resilient structure. A review of the literature was generated to identify accepted project success factors in construction projects, such as the case study of PDR response to Hurricane Sandy in New York City, in helping to identify common themes for success factors. Specifically, three areas will be examined from the case study: 1) Strategy/planning, 2) Resiliency and 3) Communication. Implementing these strategies in PDR projects will assist in the further understanding and success of reconstruction projects in this field of work

PPARδ binding to heme oxygenase 1 promoter prevents angiotensin II-induced adipocyte dysfunction in Goldblatt hypertensive rats

Abstract: OBJECTIVE: Renin–angiotensin system (RAS) regulates adipogenic response with adipocyte hypertrophy by increasing oxidative stress. Recent studies have shown the role of peroxisome proliferator-activated receptor-d (PPARδ) agonist in attenuation of angiotensin II-induced oxidative stress. The aim of this study was to explore a potential mechanistic link between PPARδ and the cytoprotective enzyme heme oxygenase-1 (HO-1) and to elucidate the contribution of HO-1 to the adipocyte regulatory effects of PPARδ agonism in an animal model of enhanced RAS, the Goldblatt 2 kidney 1 clip (2K1C) model. METHOD: We first established a direct stimulatory effect of the PPARδ agonist (GW 501516) on the HO-1 gene by demonstrating increased luciferase activity in COS-7 cells transfected with a luciferase-HO-1 promoter construct. Sprague-Dawley rats were divided into four groups: sham-operated animals, 2K1C rats and 2K1C rats treated with GW 501516, in the absence or presence of the HO activity inhibitor, stannous mesoporphyrin (SnMP). RESULTS: 2K1C animals had increased visceral adiposity, adipocyte hypertrophy, increased inflammatory cytokines, increased circulatory and adipose tisssue levels of renin and Ang II along with increased adipose tissue gp91 phox expression (Po0.05) when compared with sham-operated animals. Treatment with GW 501516 increased adipose tissue HO-1 and adiponectin levels (Po0.01) along with enhancement of Wnt10b and b-catenin expression. HO-1 induction was accompanied by the decreased expression of Wnt5b, mesoderm specific transcript (mest) and C/EBPa levels and an increased number of small adipocytes (Po0.05). These effects of GW501516 were reversed in 2K1C animals exposed to SnMP (Po0.05). CONCLUSION: Taken together, our study demonstrates, for the first time, that increased levels of Ang II contribute towards adipose tissue dysregulation, which is abated by PPARδ-mediated upregulation of the heme-HO system. These findings highlight the pivotal role and symbiotic relationship of HO-1, adiponectin and PPARδ in the regulation of metabolic homeostasis in adipose tissues

A 21-year record of vertically migrating subepilimnetic populations of Cryptomonas spp.

The vertical distribution and diel migration of Cryptomonas spp. were monitored continuously for 21 years in mesotrophic Cross Reservoir, northeast Kansas, USA. The movements of these motile algae were tracked on multiple dates during July–October of each year using in situ fluorometry and optical microscopy of Lugol’s iodine-preserved samples. Episodes of subepilimnetic diel vertical migration by Cryptomonas were detected and recorded on 221 different days between 1994 and 2014, with just 2 of these years (1998 and 2013) lacking any sampling events with deep peaks sufficiently large enough to track. Whenever a subepilimnetic layer of Cryptomonas was detectable, it was generally observed to ascend toward the bottom of the epilimnion beginning approximately at sunrise; to descend toward the lake bottom during the late afternoon and evening; and to remain as a deep-dwelling population until dawn of the following day. Moreover, there was high day-to-day consistency in the absolute water column depths at which the migrating algal cells would cease their ascending or descending movement. We believe this unique and remarkable dataset comprises the most detailed record of diel migratory behavior for any planktonic freshwater alga reported for a single freshwater lake

Multi-transcriptome analysis following an acute skeletal muscle growth stimulus yields tools for discerning global and MYC regulatory networks

Myc is a powerful transcription factor implicated in epigenetic reprogramming, cellular plasticity, and rapid growth as well as tumorigenesis. Cancer in skeletal muscle is extremely rare despite marked and sustained Myc induction during loading-induced hypertrophy. Here, we investigated global, actively transcribed, stable, and myonucleus-specific transcriptomes following an acute hypertrophic stimulus in mouse plantaris. With these datasets, we define global and Myc-specific dynamics at the onset of mechanical overload-induced muscle fiber growth. Data collation across analyses reveals an under-appreciated role for the muscle fiber in extracellular matrix remodeling during adaptation, along with the contribution of mRNA stability to epigenetic-related transcript levels in muscle. We also identify Runx1 and Ankrd1 (Marp1) as abundant myonucleus-enriched loading-induced genes. We observed that a strong induction of cell cycle regulators including Myc occurs with mechanical overload in myonuclei. Additionally, in vivo Myc-controlled gene expression in the plantaris was defined using a genetic muscle fiber-specific doxycycline-inducible Myc-overexpression model. We determined Myc is implicated in numerous aspects of gene expression during early-phase muscle fiber growth. Specifically, brief induction of Myc protein in muscle represses Reverbα, Reverbβ, and Myh2 while increasing Rpl3, recapitulating gene expression in myonuclei during acute overload. Experimental, comparative, and in silico analyses place Myc at the center of a stable and actively transcribed, loading-responsive, muscle fiber–localized regulatory hub. Collectively, our experiments are a roadmap for understanding global and Myc-mediated transcriptional networks that regulate rapid remodeling in postmitotic cells. We provide open webtools for exploring the five RNA-seq datasets as a resource to the field