Effects of light quantity and quality on early seedling development in the red mangrove Rhizophora mangle L

Seedlings of the red mangrove, Rhizophora mangle L., were grown under light conditions differing in both photosynthetic photon flux density (PPFD) and spectral quality (red:far-red ratio, R:FR). During the first 8 mo of development, parameters of stem, leaf, and root growth were affected by PPFD. Significant responses to lowered R:FR, however, were limited to internode extension. The results are moderately indicative of a strategy to persist in shade, but illustrate the complexity of light responses and suggest that precise categorization as shade-tolerant or -intolerant may be unbefitting for this species at this particular stage of development.

Students and Universities: Leading the Future of Development- Lecture by Rajiv Shah, USAID

Lecture held at School of International and Public Affairs Ballroom by college of Arts and Sciences and co-sponsored by Division of Research. Since being sworn in in 2007,Shah had managed US Government's response to 2010 Port-Au-Prince earthquake, co-chaired State Department's first review of American diplomacy, and spearheads Obama's Landmark "Feed the Future" food security initiative. Part of Ruth K. and Shepard Broad Distinguished Lecture Series

Romantic Relationships and Adjustment in Early Adulthood: The Role of Cross-sex Experience in the Context of Social Norms and Support

Attachment and interpersonal theory suggest a sequential pattern of relationships beginning in the earliest stage of development and progressing to social and eventually romantic relationships. Theoretically, cross-sex experiences have an important role in the progression of interpersonal relationships. Despite the prevalence of these theories about the nature of romantic relationship development, the linkage of cross-sex experience (CSE) to romantic relationships has not been established. Indeed, it is an intuitive assumption, especially within Western society and these theories do not consider socio-cultural factors that may influence CSE and relationship satisfaction. This study addresses the varying contextual factors that may contribute to relationship satisfaction and adjustment, aside from CSE, and is divided into two parts. Study 1, addresses CSE, relationship satisfaction, and adjustment in a unique population, ultra-Orthodox Jews. Among this population, social or romantic CSE is limited and sexes are effectively segregated. Study 2, expanded the study to a larger sample of U.S. college students, to assess the linkage of CSE to romantic relationship satisfaction in a more typical Western population. It included social norm and support variables to address the contextual nature of relationship development and satisfaction. Results demonstrated clear differences in the relation between CSE and relationship satisfaction in the two samples. In the first sample CSE was unrelated to relationship satisfaction; nevertheless, relationship satisfaction was associated with adjustment as it is for more typical populations with greater CSE. These results suggested the importance of specifying how social norms and social support relate to CSE, relationship satisfaction and adjustment. The results from the second sample were consistent with the theoretical framework upon which the social/romantic literature is based. CSE was directly connected to relationship satisfaction. As anticipated, CSE, relationship satisfaction, and adjustment also varied as a function of social norms and support. These findings further validate the influence of socio-cultural factors on relationship satisfaction and adjustment. This study contributes to the romantic relationship literature and broadens our understanding of the complex nature of interpersonal and romantic relationships.

Romantic relationships and adjustment in early adulthood: The role of cross-sex experience in the context of social norms and support

Attachment and interpersonal theory suggest a sequential pattern of relationships beginning in the earliest stage of development and progressing to social and eventually romantic relationships. Theoretically, cross-sex experiences have an important role in the progression of interpersonal relationships. Despite the prevalence of these theories about the nature of romantic relationship development, the linkage of cross-sex experience (CSE) to romantic relationships has not been established. Indeed, it is an intuitive assumption, especially within Western society and these theories do not consider socio-cultural factors that may influence CSE and relationship satisfaction. This study addresses the varying contextual factors that may contribute to relationship satisfaction and adjustment, aside from CSE, and is divided into two parts. Study 1, addresses CSE, relationship satisfaction, and adjustment in a unique population, ultra-Orthodox Jews. Among this population, social or romantic CSE is limited and sexes are effectively segregated. Study 2, expanded the study to a larger sample of U.S. college students, to assess the linkage of CSE to romantic relationship satisfaction in a more typical Western population. It included social norm and support variables to address the contextual nature of relationship development and satisfaction. Results demonstrated clear differences in the relation between CSE and relationship satisfaction in the two samples. In the first sample CSE was unrelated to relationship satisfaction; nevertheless, relationship satisfaction was associated with adjustment as it is for more typical populations with greater CSE. These results suggested the importance of specifying how social norms and social support relate to CSE, relationship satisfaction and adjustment. The results from the second sample were consistent with the theoretical framework upon which the social/romantic literature is based. CSE was directly connected to relationship satisfaction. As anticipated, CSE, relationship satisfaction, and adjustment also varied as a function of social norms and support. These findings further validate the influence of socio-cultural factors on relationship satisfaction and adjustment. This study contributes to the romantic relationship literature and broadens our understanding of the complex nature of interpersonal and romantic relationships.^

Design strategies for an artificial neural network based algorithm for automatic incident detection on major arterial streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our nation’s highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

Design Strategies for an Artificial Neural Network Based Algorithm for Automatic Incident Detection on Major Arterial Streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our national highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.