Intercultural Communication Between Forensic and Clinical Psychologists

While working in clinical and forensic psychology settings, a communication difficulty between the two professions became apparent. Forensic psychologists often appeared cold and callous from the clinical psychologist’s perspective, while clinical psychologists often appeared naïve or too client centered from the forensic psychologist’s perspective. I wondered if viewing each subfield of psychology as a culture could facilitate better communication through intercultural communication. Guided by Intercultural Communication in Contexts (Martin & Nakayama, 2010) in approaching intercultural communication between the two professions, I explored factors contributing to each profession’s cultural identities. Once this was established, I attempted to explore the different ways each culture could communicate more effectively. By recognizing and utilizing the strengths from each profession and understanding the possible pitfalls of one’s own, we may become competent in intercultural communication

Hibridación entre la codorniz común (Coturnix coturnix) y la codorniz de granja: estado de un problema de conservación

La hibridación entre especies es un fenómeno ampliamente extendido que puede tener consecuencias en la conservación de la biodiversidad. En el presente artículo se hace una revisión del problema de conservación derivado de la suelta de codornices de granja en poblaciones silvestres de codorniz común (Coturnix coturnix). Estas codornices de granja han resultado ser híbridos de codorniz común y codorniz japonesa (Coturnix japonica). Si no existen mecanismos de aislamiento reproductor, estas sueltas favorecerían la introgresión de genes de codorniz japonesa en las poblaciones de codorniz común; ello conllevaría que se produjera un “enjambre de híbridos” y la sedentarización de las poblaciones de codorniz, lo que comportaría muy probablemente su disminución en Europa. Esta amenaza es real, al haberse demostrado que no hay mecanismos de aislamiento reproductor, ni pre-cigóticos, ni post-cigóticos, ni ecológicos. Sin embargo, datos empíricos sugieren que a pesar de ello no se produce el temido “enjambre de híbridos”, sugiriéndose una mortalidad diferencial entre las dos especies como una posible explicación. Finalmente, se sugieren algunas medidas de gestión derivadas de la situación actual, entre las que destacaría un control genético que certifique el origen de los individuos criados en granja y la prohibición de efectuar sueltas de codornices japonesas o híbridos.

Considering Efficacy of an Outdoor Environmental Education Program: Facilitating Elementary Students’ Environmental Knowledge, Attitudes, and Behaviours

Various sources have sought to consider the educational interventions that foster changes in perception of and attitudes toward nature, with the ultimate intent of understanding how education can be used to encourage environmentally responsible behaviours. With these in mind, the current study identified an outdoor environmental education program incorporating these empirically supported interventions, and assessed its ability to influence environmental knowledge, attitudes, and behaviours. Specifically, this study considered the following research questions: 1) To what degree can participation in this outdoor education program foster environmental knowledge and encourage pro-environmental attitudes and self-reported pro-environmental behaviours? 2) How is this effect different among students of different genders, and those who have different prior experiences in nature? Two motivational frameworks guided inquiry in the current study: the Value-Belief-Norm Model of Environmentalism (VBN) and the Theory of Planned Behaviour (TPB). The study employed a quantitative survey methodology, combining contemporary data measuring knowledge, attitudes, and behaviours with archived data collected by program staff, reflecting frequency of environmentally responsible behaviour. Further, a single qualitative item was included for which students provided “the first three words that [came] to mind when [they] think of the word nature.” Terms provided before and after the program were compared for differences in theme to detect subtle or underlying changes. Quantitative results indicated no significant change in student knowledge or attitudes through the outdoor environmental education program. However, a significant change in self-reported behaviour was identified from both the contemporary and archived data. This agreement in positive findings across the two data sets, collected using different measures and different participants, lends evidence of the program’s ability to encourage self-reported pro-environmental behaviour. Further, qualitative results showed some change in students’ perceptions of nature through the program, providing direction for future research. These findings suggest that this particular outdoor education program was successful in encouraging students’ self-reported environmentally responsible behaviour. This change was achieved without significant change in knowledge or environmental attitudes, suggesting that external factors not measured in this study might have played a role in affecting behaviour.

Women's Volleyball Team, 2010. UM

Back Row: Karlee Bruck, Jennifer Cross, Courtney Fletcher, Claire McElheny, Amanda Yerke, Lexi Erwin

Middle Row: Lexi Zimmerman, Molly Toon, Alex Hunt, Catherine Yager, Brittany Lee

Front Row: Ally Sabol, Sloane Donhoff, Michelle McMahon, Maggie Busch

Artistes français des XVIIe et XVIIIe siècles (1681-1787)

"Contrats de mariage, actes de notoriété, testaments, inventaires ... etc. Ces actes, centralisés par la Chambre des comptes de Bretagne, établie à Nantes, y ont été conservés, et ils forment aujourd'hui un des fonds les plus riches des Archives départementales de la Loire-Inférieure."--p. 2.

The illuminated calendar and home diary for 1845.

Copied from the Hours of Anne of Brittany in the Bibliotheque Royale.

School of Nursing Class of 2008

Top Row: Therese Adamowski, Anel Adamson, Michelle Ahleman, Brooke Babineau, Jennifer Ballough, Lisa Anne Beckman, Jennifer Bergeren, Tedra Boedigheimer, Mary Bonner, Genevieve Bott, Megan Bouwhuis, Mitchell Bradley, Rachel Brown, Katherine Bulson, Jennifer Calhoun, Carley Cebelak, Sarah Choinard

Row 2: Sarah Clevenger, Elizabeth Anne Conway, Erin Coughlin, Karie Curtis, Stephanie Curtis, Jodi Danhof, Rebecca Debri, Stacie Deleszek, Andrea Dehline, Amanda Devlin, Charlotte Dietrich, Angela Dodge, Elizabeth Dougherty, Ashley Doyle, Lindsay Driver, Nancy Duckworth, Kathy Dunnuck, Jennifer Dziadaio, Ellen English

Row 3: Kelly Esser, Amanda Fender, Lindsey Smith, Andrew Bradburn, Fallon Garfield Turner, Margaret Dembeck, Courtney Van Essen, Jessica paige Smith, Lauren Inouye, Jacqueline Dufek, Emily Klump, Amanda Jones, Tiffany Burrell, Deborah Mitchell, Emily Michel, Michelle Steen, Kirsten Thulin, Emily Hautamaki, Sheila Fender, Keith Ferguson

Row 4: Annie Fields, Jillian Fisher, Erin Flatley, Renee Forma, Aileen Franchi, Lindsey Freysinger, Sarah Fulgenzi, Beth Funnell, Andrea Galaviz, Lacey Garbo, Katherine Garcia, Lynn Garofalo

Row 5: Heather Gehrke, Nicole Genrich, Katie Giordano, Lindsey Glover, Andrea Godfrey, Jocelyn Gossman, Alana Greenberg, Julien Guttman, Sarah Halfmann, Kimberly Hanger, Allison Hanson, Stephanie Hecklin

Row 6: Geri Helminiak, Kristi Hershiser, Erin Hipp, Amanda Hoath, Tracy Hurlbutt, Nadya Indrei, Nisa Joorabchi, Katy Kerrigan, Layne Kiella, Jessica Kim, Samantha Klaiman, Jodi Knight, Laura Kovacic, Alicia Kreger

Row 7: Amanda Kretsch, Kimberly Kurzeja, Julie Lamonoff, Sarah Leirstein, Ashley Labb, Suzanne Loeb, Alessandra Lollini, Heather Loomis, Caroline Luke, Stephanie Maniquis, Elizabeth Mann, LaTasha Marable, Amanda McAdams, Mara McKinley

Row 8: Leah McLaughlin, Erin Migda, Scott Migut, Joane Nwoke, Lazarus Okammor, Brittany Pajewski, Judith Lynch-Sauer, Patricia Coleman-Burns, Bonnie Hagerty, Kathleen Potempa, Carol Loveland-Cherry, Carolyn Sampselle, Joanne Pohl, Sarah Pajtas, Maria Paneda, Jennifer Parker, Carol Peterson, Kimberley Peven, Rachel Poterek, Sarah Poucher

Row 9: Jannet Provost, Jessica Quigley, Nicole Rasmuson, Joanthan Reed, Sharon Reske, John Reves, Amy Riebe, Sara Riegner, Kelly Risicato, Christine Sabado, Stephanie Sargent, Jolene Schaefer, Erin Schroeder, Catherine Scott, Katherine See, Andrea Semaan, Jessica Shantz, Kathryn Sibbold, Kathleen Skendrovic, Aaron Smith, Elizabeth Stanton

Row 10: Mary Stewart, Ashley Strotbaum, Danielle Swartz, Janet Trost, Elizabeth Underwood, Lauren Underwood, Allison Vanhall, Brian Velker, Kristen Wells, Ryan Werblow, Jennifer Werden, David Westrin, Mallory Wiesen, Karen Wingrove, Amy Wright, Carrie Wright, Emily Wright, Minou Xie, Charles Zimmerman

Pictures of the old French court; Jeanne de Bourbon, Isabeau de Bavière, Anne de Bretagne,

Bibliographical foot-notes.

K-Ar and 40Ar/39Ar ages of dikes emplaced in the onshore basement of the Santos Basin, Resende area, SE Brazil: implications for the South Atlantic opening and tertiary reactivation

New K-Ar and Ar-40/Ar-39 data of tholeiitic and alkaline dike swarms from the onshore basement of the Santos Basin (SE Brazil) reveal Mesozoic and Tertiary magmatic pulses. The tholeiitic rocks (basalt, dolerite, and microgabbro) display high TiO2 contents (average 3.65 wt%) and comprise two magmatic groups. The NW-oriented samples of Group A have (La/Yb)N ratios between 15 and 32.3 and range in age from 192.9 +/- 2.2 to 160.9 +/- 1.9 Ma. The NNW-NNE Group B samples, with (La/Yb)(N) ratios between 7 and 16, range from 148.3 +/- 3 to 133.9 +/- 0.5 Ma. The alkaline rocks (syenite, trachyte, phonolite, alkaline basalts, and lamprophyre) display intermediate-K contents and comprise dikes, plugs, and stocks. Ages of approximately 82 Ma were obtained for the lamprophyre dikes, 70 Ma for the syenite plutons, and 64-59 Ma for felsic dikes. Because Jurassic-Early Cretaceous basic dikes have not been reported in SE Brazil, we might speculate that, during the emplacement of Group A dikes, extensional stresses were active in the region before the opening of the south Atlantic Ocean and coeval with the Karoo magmatism described in South Africa. Group B dikes yield ages compatible with those obtained for Serra Geral and Ponta Grossa magmatism in the Parana Basin and are directly related to the breakup of western Gondwana. Alkaline magmatism is associated with several tectonic episodes that postdate the opening of the Atlantic Ocean and related to the upwelling of the Trindade plume and the generation of Tertiary basins southeast of Brazil. In the studied region, alkaline magmatism can be subdivided in two episodes: the first one represented by lamprophyre dykes of approximately 82 Ma and the second comprised of felsic alkaline stocks of approximately 70 Ma and associated dikes ranging from 64 to 59 Ma. (c) 2005 Elsevier Ltd. All rights reserved.

Gnathostome microremains from the lower Devonian Jawf Formation, Saudi Arabia

Calcareotis horizons in the Qasr and Hammamiyat members (Lower Devonian, ?Pragian and lower Emsian) of file Jawf Formation, northwestern Saudi Arabia, yielded a rich assemblage of microremains from acanthodian, placoderm. chondrichthyan, and sarcopterygian vertebrates. The most abundant elements are scales from acanthodians Nostolepis spp., Milesacanthus ancestralis n. sp., Canadatepis? sp., and Gomphonchus? fromensis. scales and dermal bone fragments from acanthothoracid and ?rhenanid placoderms, and teeth from onychodontids. Rarer occurrences include ?chondrichthyan scales of several different morphotypes, and petalichthid and ?ptyctodontid placoderm elements. The Qasr Member assemblage shows a close resemblance to slightly older faunas front the Lochkovian of Brittany and Spain. The Hammamiyat Member microvertebrate fauna shows closest affinity with that of the stratigraphically lower Qasr Member, with similarities also to coeval faunas from southeastern Australia, late Emsian/Eifelian faunas from west-central Europe, and the Givetian Aztec Siltstone fauna from Antarctica.

Sviluppo e Applicazione di Metodologie per l'Ottimizzazione di Sistemi Energetici

La riduzione dei consumi di combustibili fossili e lo sviluppo di tecnologie per il risparmio energetico sono una questione di centrale importanza sia per l’industria che per la ricerca, a causa dei drastici effetti che le emissioni di inquinanti antropogenici stanno avendo sull’ambiente. Mentre un crescente numero di normative e regolamenti vengono emessi per far fronte a questi problemi, la necessità di sviluppare tecnologie a basse emissioni sta guidando la ricerca in numerosi settori industriali. Nonostante la realizzazione di fonti energetiche rinnovabili sia vista come la soluzione più promettente nel lungo periodo, un’efficace e completa integrazione di tali tecnologie risulta ad oggi impraticabile, a causa sia di vincoli tecnici che della vastità della quota di energia prodotta, attualmente soddisfatta da fonti fossili, che le tecnologie alternative dovrebbero andare a coprire. L’ottimizzazione della produzione e della gestione energetica d’altra parte, associata allo sviluppo di tecnologie per la riduzione dei consumi energetici, rappresenta una soluzione adeguata al problema, che può al contempo essere integrata all’interno di orizzonti temporali più brevi. L’obiettivo della presente tesi è quello di investigare, sviluppare ed applicare un insieme di strumenti numerici per ottimizzare la progettazione e la gestione di processi energetici che possa essere usato per ottenere una riduzione dei consumi di combustibile ed un’ottimizzazione dell’efficienza energetica. La metodologia sviluppata si appoggia su un approccio basato sulla modellazione numerica dei sistemi, che sfrutta le capacità predittive, derivanti da una rappresentazione matematica dei processi, per sviluppare delle strategie di ottimizzazione degli stessi, a fronte di condizioni di impiego realistiche. Nello sviluppo di queste procedure, particolare enfasi viene data alla necessità di derivare delle corrette strategie di gestione, che tengano conto delle dinamiche degli impianti analizzati, per poter ottenere le migliori prestazioni durante l’effettiva fase operativa. Durante lo sviluppo della tesi il problema dell’ottimizzazione energetica è stato affrontato in riferimento a tre diverse applicazioni tecnologiche. Nella prima di queste è stato considerato un impianto multi-fonte per la soddisfazione della domanda energetica di un edificio ad uso commerciale. Poiché tale sistema utilizza una serie di molteplici tecnologie per la produzione dell’energia termica ed elettrica richiesta dalle utenze, è necessario identificare la corretta strategia di ripartizione dei carichi, in grado di garantire la massima efficienza energetica dell’impianto. Basandosi su un modello semplificato dell’impianto, il problema è stato risolto applicando un algoritmo di Programmazione Dinamica deterministico, e i risultati ottenuti sono stati comparati con quelli derivanti dall’adozione di una più semplice strategia a regole, provando in tal modo i vantaggi connessi all’adozione di una strategia di controllo ottimale. Nella seconda applicazione è stata investigata la progettazione di una soluzione ibrida per il recupero energetico da uno scavatore idraulico. Poiché diversi layout tecnologici per implementare questa soluzione possono essere concepiti e l’introduzione di componenti aggiuntivi necessita di un corretto dimensionamento, è necessario lo sviluppo di una metodologia che permetta di valutare le massime prestazioni ottenibili da ognuna di tali soluzioni alternative. Il confronto fra i diversi layout è stato perciò condotto sulla base delle prestazioni energetiche del macchinario durante un ciclo di scavo standardizzato, stimate grazie all’ausilio di un dettagliato modello dell’impianto. Poiché l’aggiunta di dispositivi per il recupero energetico introduce gradi di libertà addizionali nel sistema, è stato inoltre necessario determinare la strategia di controllo ottimale dei medesimi, al fine di poter valutare le massime prestazioni ottenibili da ciascun layout. Tale problema è stato di nuovo risolto grazie all’ausilio di un algoritmo di Programmazione Dinamica, che sfrutta un modello semplificato del sistema, ideato per lo scopo. Una volta che le prestazioni ottimali per ogni soluzione progettuale sono state determinate, è stato possibile effettuare un equo confronto fra le diverse alternative. Nella terza ed ultima applicazione è stato analizzato un impianto a ciclo Rankine organico (ORC) per il recupero di cascami termici dai gas di scarico di autovetture. Nonostante gli impianti ORC siano potenzialmente in grado di produrre rilevanti incrementi nel risparmio di combustibile di un veicolo, è necessario per il loro corretto funzionamento lo sviluppo di complesse strategie di controllo, che siano in grado di far fronte alla variabilità della fonte di calore per il processo; inoltre, contemporaneamente alla massimizzazione dei risparmi di combustibile, il sistema deve essere mantenuto in condizioni di funzionamento sicure. Per far fronte al problema, un robusto ed efficace modello dell’impianto è stato realizzato, basandosi sulla Moving Boundary Methodology, per la simulazione delle dinamiche di cambio di fase del fluido organico e la stima delle prestazioni dell’impianto. Tale modello è stato in seguito utilizzato per progettare un controllore predittivo (MPC) in grado di stimare i parametri di controllo ottimali per la gestione del sistema durante il funzionamento transitorio. Per la soluzione del corrispondente problema di ottimizzazione dinamica non lineare, un algoritmo basato sulla Particle Swarm Optimization è stato sviluppato. I risultati ottenuti con l’adozione di tale controllore sono stati confrontati con quelli ottenibili da un classico controllore proporzionale integrale (PI), mostrando nuovamente i vantaggi, da un punto di vista energetico, derivanti dall’adozione di una strategia di controllo ottima.

Agent Based Models of Competition and Collaboration

Swarm intelligence is a popular paradigm for algorithm design. Frequently drawing inspiration from natural systems, it assigns simple rules to a set of agents with the aim that, through local interactions, they collectively solve some global problem. Current variants of a popular swarm based optimization algorithm, particle swarm optimization (PSO), are investigated with a focus on premature convergence. A novel variant, dispersive PSO, is proposed to address this problem and is shown to lead to increased robustness and performance compared to current PSO algorithms. A nature inspired decentralised multi-agent algorithm is proposed to solve a constrained problem of distributed task allocation. Agents must collect and process the mail batches, without global knowledge of their environment or communication between agents. New rules for specialisation are proposed and are shown to exhibit improved eciency and exibility compared to existing ones. These new rules are compared with a market based approach to agent control. The eciency (average number of tasks performed), the exibility (ability to react to changes in the environment), and the sensitivity to load (ability to cope with differing demands) are investigated in both static and dynamic environments. A hybrid algorithm combining both approaches, is shown to exhibit improved eciency and robustness. Evolutionary algorithms are employed, both to optimize parameters and to allow the various rules to evolve and compete. We also observe extinction and speciation. In order to interpret algorithm performance we analyse the causes of eciency loss, derive theoretical upper bounds for the eciency, as well as a complete theoretical description of a non-trivial case, and compare these with the experimental results. Motivated by this work we introduce agent "memory" (the possibility for agents to develop preferences for certain cities) and show that not only does it lead to emergent cooperation between agents, but also to a signicant increase in efficiency.

The effect of load on agent-based algorithms for distributed task allocation

Multi-agent algorithms inspired by the division of labour in social insects and by markets, are applied to a constrained problem of distributed task allocation. The efficiency (average number of tasks performed), the flexibility (ability to react to changes in the environment), and the sensitivity to load (ability to cope with differing demands) are investigated in both static and dynamic environments. A hybrid algorithm combining both approaches, is shown to exhibit improved efficiency and robustness. We employ nature inspired particle swarm optimisation to obtain optimised parameters for all algorithms in a range of representative environments. Although results are obtained for large population sizes to avoid finite size effects, the influence of population size on the performance is also analysed. From a theoretical point of view, we analyse the causes of efficiency loss, derive theoretical upper bounds for the efficiency, and compare these with the experimental results.

Exploring ant-based algorithms for gene expression data analysis

Objective: Recently, much research has been proposed using nature inspired algorithms to perform complex machine learning tasks. Ant colony optimization (ACO) is one such algorithm based on swarm intelligence and is derived from a model inspired by the collective foraging behavior of ants. Taking advantage of the ACO in traits such as self-organization and robustness, this paper investigates ant-based algorithms for gene expression data clustering and associative classification. Methods and material: An ant-based clustering (Ant-C) and an ant-based association rule mining (Ant-ARM) algorithms are proposed for gene expression data analysis. The proposed algorithms make use of the natural behavior of ants such as cooperation and adaptation to allow for a flexible robust search for a good candidate solution. Results: Ant-C has been tested on the three datasets selected from the Stanford Genomic Resource Database and achieved relatively high accuracy compared to other classical clustering methods. Ant-ARM has been tested on the acute lymphoblastic leukemia (ALL)/acute myeloid leukemia (AML) dataset and generated about 30 classification rules with high accuracy. Conclusions: Ant-C can generate optimal number of clusters without incorporating any other algorithms such as K-means or agglomerative hierarchical clustering. For associative classification, while a few of the well-known algorithms such as Apriori, FP-growth and Magnum Opus are unable to mine any association rules from the ALL/AML dataset within a reasonable period of time, Ant-ARM is able to extract associative classification rules.