WISE: Women in Science and Engineering, Spring 2009

Women in Science and Engineering (WISE) Program is to expand and improve educational and professional opportunities for women in all fields of science, technology, engineering and math (STEM) by facilitating individual, institutional, and social change.

WISE: Women in Science and Engineering, Winter 2007

Women in Science and Engineering (WISE) Program is to expand and improve educational and professional opportunities for women in all fields of science, technology, engineering and math (STEM) by facilitating individual, institutional, and social change.

WISE: Women in Science and Engineering, Winter 2007-2008

Women in Science and Engineering (WISE) Program is to expand and improve educational and professional opportunities for women in all fields of science, technology, engineering and math (STEM) by facilitating individual, institutional, and social change.

WISE: Women in Science and Engineering, Winter 2009

Women in Science and Engineering (WISE) Program is to expand and improve educational and professional opportunities for women in all fields of science, technology, engineering and math (STEM) by facilitating individual, institutional, and social change.

WISE: Women in Science and Engineering, Winter 2011-2012

Women in Science and Engineering (WISE) Program is to expand and improve educational and professional opportunities for women in all fields of science, technology, engineering and math (STEM) by facilitating individual, institutional, and social change.

Audit report of Debt Service and Coverage for Iowa State University of Science and Technology as of June 30, 2014

Audit report of Debt Service and Coverage for Iowa State University of Science and Technology as of June 30, 2014

Information sharing and social network dynamics : a coevolutionary approach

The capacity to interact socially and share information underlies the success of many animal species, humans included. Researchers of many fields have emphasized the evo¬lutionary significance of how patterns of connections between individuals, or the social networks, and learning abilities affect the information obtained by animal societies. To date, studies have focused on the dynamics either of social networks, or of the spread of information. The present work aims to study them together. We make use of mathematical and computational models to study the dynamics of networks, where social learning and information sharing affect the structure of the population the individuals belong to. The number and strength of the relationships between individuals, in turn, impact the accessibility and the diffusion of the shared information. Moreover, we inves¬tigate how different strategies in the evaluation and choice of interacting partners impact the processes of knowledge acquisition and social structure rearrangement. First, we look at how different evaluations of social interactions affect the availability of the information and the network topology. We compare a first case, where individuals evaluate social exchanges by the amount of information that can be shared by the partner, with a second case, where they evaluate interactions by considering their partners' social status. We show that, even if both strategies take into account the knowledge endowments of the partners, they have very different effects on the system. In particular, we find that the first case generally enables individuals to accumulate higher amounts of information, thanks to the more efficient patterns of social connections they are able to build. Then, we study the effects that homophily, or the tendency to interact with similar partners, has on knowledge accumulation and social structure. We compare the case where individuals who know the same information are more likely to learn socially from each other, to the opposite case, where individuals who know different information are instead more likely to learn socially from each other. We find that it is not trivial to claim which strategy is better than the other. Depending on the possibility of forgetting information, the way new social partners can be chosen, and the population size, we delineate the conditions for which each strategy allows accumulating more information, or in a faster way For these conditions, we also discuss the topological characteristics of the resulting social structure, relating them to the information dynamics outcome. In conclusion, this work paves the road for modeling the joint dynamics of the spread of information among individuals and their social interactions. It also provides a formal framework to study jointly the effects of different strategies in the choice of partners on social structure, and how they favor the accumulation of knowledge in the population. - La capacité d'interagir socialement et de partager des informations est à la base de la réussite de nombreuses espèces animales, y compris les humains. Les chercheurs de nombreux domaines ont souligné l'importance évolutive de la façon dont les modes de connexions entre individus, ou réseaux sociaux et les capacités d'apprentissage affectent les informations obtenues par les sociétés animales. À ce jour, les études se sont concentrées sur la dynamique soit des réseaux sociaux, soit de la diffusion de l'information. Le présent travail a pour but de les étudier ensemble. Nous utilisons des modèles mathématiques et informatiques pour étudier la dynamique des réseaux, où l'apprentissage social et le partage d'information affectent la structure de la population à laquelle les individus appartiennent. Le nombre et la solidité des relations entre les individus ont à leurs tours un impact sur l'accessibilité et la diffusion de l'informa¬tion partagée. Par ailleurs, nous étudions comment les différentes stratégies d'évaluation et de choix des partenaires d'interaction ont une incidence sur les processus d'acquisition des connaissances ainsi que le réarrangement de la structure sociale. Tout d'abord, nous examinons comment des évaluations différentes des interactions sociales influent sur la disponibilité de l'information ainsi que sur la topologie du réseau. Nous comparons un premier cas, où les individus évaluent les échanges sociaux par la quantité d'information qui peut être partagée par le partenaire, avec un second cas, où ils évaluent les interactions en tenant compte du statut social de leurs partenaires. Nous montrons que, même si les deux stratégies prennent en compte le montant de connaissances des partenaires, elles ont des effets très différents sur le système. En particulier, nous constatons que le premier cas permet généralement aux individus d'accumuler de plus grandes quantités d'information, grâce à des modèles de connexions sociales plus efficaces qu'ils sont capables de construire. Ensuite, nous étudions les effets que l'homophilie, ou la tendance à interagir avec des partenaires similaires, a sur l'accumulation des connaissances et la structure sociale. Nous comparons le cas où des personnes qui connaissent les mêmes informations sont plus sus¬ceptibles d'apprendre socialement l'une de l'autre, au cas où les individus qui connaissent des informations différentes sont au contraire plus susceptibles d'apprendre socialement l'un de l'autre. Nous constatons qu'il n'est pas trivial de déterminer quelle stratégie est meilleure que l'autre. En fonction de la possibilité d'oublier l'information, la façon dont les nouveaux partenaires sociaux peuvent être choisis, et la taille de la population, nous déterminons les conditions pour lesquelles chaque stratégie permet d'accumuler plus d'in¬formations, ou d'une manière plus rapide. Pour ces conditions, nous discutons également les caractéristiques topologiques de la structure sociale qui en résulte, les reliant au résultat de la dynamique de l'information. En conclusion, ce travail ouvre la route pour la modélisation de la dynamique conjointe de la diffusion de l'information entre les individus et leurs interactions sociales. Il fournit également un cadre formel pour étudier conjointement les effets de différentes stratégies de choix des partenaires sur la structure sociale et comment elles favorisent l'accumulation de connaissances dans la population.

Report on Iowa State University of Science and Technology, Ames, Iowa for the year ended June 30, 2014

Report on Iowa State University of Science and Technology, Ames, Iowa for the year ended June 30, 2014

Report on a review of selected general and application controls over the Iowa State University of Science and Technology Kuali Financial System for the period April 30, 2014 through May 28, 2014

Report on a review of selected general and application controls over the Iowa State University of Science and Technology Kuali Financial System for the period April 30, 2014 through May 28, 2014

State of the science and the way forward for the ecotoxicological assessment of contaminated land

Over the past two decades, soil ecotoxicologists have made strides in utilizing the basic concepts and advancements in soil zoology and ecology. They have applied the existing tools, and developed new ones to investigate how chemical contamination can affect soil ecosystems, including the degradation or destruction of soil quality and habitats or the diminishment of belowground biodiversity. Soil ecotoxicologists are applying a suite of standard protocols, originally developed as laboratory tests with single chemicals (e.g., pesticides), and further enhancing both the approaches and protocols for the assessment of contaminated lands. However, ecological relevance of some approaches remains unresolved. The authors discuss the main challenges for a coherent ecotoxicological assessment of soil ecosystems amid contaminated lands, and provide recommendations on how to integrate the effects of physical and chemical soil properties, the variations in the diversity of soil invertebrates, and the interactions among organisms of various trophic levels. The review examines new international approaches and test methods using examples from three continents (in particular research conducted in Brazil), and provides recommendations for improving ecological relevance of ecotoxicological investigations of contaminated lands.

Spatial Scale of Clustering of Motor Vehicle Crash Types and Appropriate Countermeasures, 2009

This project analyzes the characteristics and spatial distributions of motor vehicle crash types in order to evaluate the degree and scale of their spatial clustering. Crashes occur as the result of a variety of vehicle, roadway, and human factors and thus vary in their clustering behavior. Clustering can occur at a variety of scales, from the intersection level, to the corridor level, to the area level. Conversely, other crash types are less linked to geographic factors and are more spatially “random.” The degree and scale of clustering have implications for the use of strategies to promote transportation safety. In this project, Iowa's crash database, geographic information systems, and recent advances in spatial statistics methodologies and software tools were used to analyze the degree and spatial scale of clustering for several crash types within the counties of the Iowa Northland Regional Council of Governments. A statistical measure called the K function was used to analyze the clustering behavior of crashes. Several methodological issues, related to the application of this spatial statistical technique in the context of motor vehicle crashes on a road network, were identified and addressed. These methods facilitated the identification of crash clusters at appropriate scales of analysis for each crash type. This clustering information is useful for improving transportation safety through focused countermeasures directly linked to crash causes and the spatial extent of identified problem locations, as well as through the identification of less location-based crash types better suited to non-spatial countermeasures. The results of the K function analysis point to the usefulness of the procedure in identifying the degree and scale at which crashes cluster, or do not cluster, relative to each other. Moreover, for many individual crash types, different patterns and processes and potentially different countermeasures appeared at different scales of analysis. This finding highlights the importance of scale considerations in problem identification and countermeasure formulation.

Audit report of Iowa State University of Science and Technology, Ames, Iowa, (Iowa State University) as of and for the years ended June 30, 2015 and 2014

Audit report of Iowa State University of Science and Technology, Ames, Iowa, (Iowa State University) as of and for the years ended June 30, 2015 and 2014

Audit report of Iowa State University of Science and Technology, Ames, Iowa, (Iowa State University) and its discretely presented component unit as of and for the years ended June 30, 2015 and 2014

Audit report of Iowa State University of Science and Technology, Ames, Iowa, (Iowa State University) and its discretely presented component unit as of and for the years ended June 30, 2015 and 2014