Stochasticity and coherent structures in ultra-long mode-locked lasers

Ultra-long mode-locked lasers are known to be strongly influenced by nonlinear interactions in long cavities that results in noise-like stochastic pulses. Here, by using an advanced technique of real-time measurements of both temporal and spatial (over round-trips) intensity evolution, we reveal an existence of wide range of generation regimes. Different kinds of coherent structures including dark and grey solitons and rogue-like bright coherent structures are observed as well as interaction between them are revealed.

Nonlinear mixing and mode correlations in a short Raman fiber laser

In the present paper we experimentally demonstrate a generation in a short Raman fiber laser having 10 000 different longitudinal modes only. We design the laser using 12 meters of commercially available fiber. Contrary to the recently demonstrated single longitudinal mode DFB Raman laser and short DBR Raman laser, in the laser under study the number of modes is high enough for efficient nonlinear interactions. Experimentally measured time dynamics reveals the presence of mode correlations in the radiation: the measured extreme events lasts for more than 10 round-trips.

Real-time heterodyne-based measurements of fiber laser spectral dynamics

We present a method to measure in real-time the instantaneous generation spectrum of fiber lasers over consecutive cavity round-trips. © 2015 OSA.

Vector solitons with slowly evolving states of polarisation

We demonstrate experimentally and study theoretically new type of stable pulse structures in erbium-doped fibre lasers - slowly polarisation evolving vector solitons. Demonstrated vector solitons precess with characteristic times of 100-1000 round trips and their trajectories form a double semicircle on the Poincaré sphere. © 2012 Optical Society of America.

Radiation build-up in laminar and turbulent regimes in quasi-CW Raman fiber laser

We study the radiation build-up in laminar and turbulent generation regimes in quasi-CW Raman fiber laser. We found the resulted spectral shape and generation type is defined by the total spectral broadening/narrowing balance over laser cavity round-trip, which is substantially different in different regimes starting from first round-trips of the radiation build-up. In turbulent regime, the steady-state is reached only after a few round-trips, while in the laminar regime the laser approaches the equilibrium spectrum shape asymptotically.

A study of the relationship between parental self-efficacy and indicators of school involvement exhibited by Hispanic parents of elementary school children

The purpose of this study was to examine the relationship between Hispanic parents' sense of self-efficacy at various degrees of acculturation to the United States and specific indicators of school involvement in their elementary school children's education. It assessed the effects of acculturation on the level of parental self-efficacy and their degree of school involvement. The theoretical framework guiding this investigation was Bandura's theory of self-efficacy which advocates that the amount of effort a person devotes to the accomplishment of a specific outcome is related to a person's beliefs in their capabilities regardless of actual competencies.^ The research method involved a correlational design measuring levels of parental self-efficacy, acculturation, degree of school involvement and related demographic characteristics. Multiple regression analysis was performed to determine the degree of relationships existing between the predictor variables of self-efficacy and level of acculturation, and level of school involvement. The data was subjected to a path analysis to test the validity of the causal model advanced in this study specifying a positive relationship between the constructs of acculturation, parental self-efficacy and level of school involvement.^ A total of 109 Hispanic parents of students enrolled in five elementary public schools in Dade County, Florida, were selected for participation in the study. Results revealed a significant positive correlation r =.23, p $<$.05 between level of parental self-efficacy and number of hours parents spent helping their children with homework. A statistically significant positive correlation was found between acculturation and level of self-efficacy r =.21, p $<$.05. Statistically significant positive correlations were also found between acculturation and such indicators of parental school involvement as participation in parent-teacher conferences r =.20, p $<$.05, volunteering at school, r =.22, p $<$.05, attendance at school sponsored sports activities r =.26, p $<$.01, and volunteering in field-trips r =.28, p $<$.01.^ The multiple regression analysis equation predicting level of homework assistance provided by parents and self-efficacy was statistically significant, F(2,106) = 3.59, p $<$.03. The beta weights revealed that self-efficacy contributed the most to the prediction of homework assistance by parents, B =.258, p $<$.009. In turn, the variable of acculturation was the most significant predictor of number of school based parent involvement activities, B =.281, p $<$.05 level. The path analysis confirmed the results obtained in the multiple regression analyses, establishing self-efficacy as having a direct effect on the level of homework assistance provided by parents. Conversely, the variable of acculturation had a direct effect on the number of school based parent involvement activities. ^

Elementary classroom teachers' knowledge of tort liability for negligence

The purpose of this research study was to investigate the legal knowledge of Florida's public elementary classroom teachers in the area of tort liability for negligence. A second purpose of the study was to assess the knowledge of school law in the area of negligence according to specific variables to determine if significant differences in knowledge existed among groups of teachers classified by: years of teaching experience, whether or not teachers took a school law course or inservice, college degree held and whether or not teachers had administrative experience. A validated survey instrument consisting of 22 scenarios based on decided court cases in the United States was utilized. These cases included court decisions ranging from 1938–1994, and represented the categories of duty and standard of care, proper instruction, proper supervision, proper maintenance, field trips, and post-injury treatment. ^ A random sample of 420 elementary classroom teachers were sent the survey instrument to complete, and a total of 309 surveys were returned producing a return rate of 77%. The results of this research study revealed that the overall level of legal knowledge of public elementary classroom teachers in the State of Florida produced a mean percent correct of 53%. The range of scores varied from 18%–82%, with the approximate average of correct answers of 12 out of 22. The category of proper instruction produced the lowest mean percent correct of 35%, and the area of post-injury treatment yielded the highest mean percent correct of 78%. ^ The findings of this study emphasize the necessity of preparing teachers regarding their legal rights, duties and responsibilities. The need for teachers to receive training at the preservice and inservice levels has become clear by this study. ^

An analysis of teachers' perceptions of informal science professional development

Science professional development, which is fundamental to science education improvement, has been described as being weak and fragmentary. The purpose of this study was to investigate teachers' perceptions of informal science professional development to gain an in-depth understanding of the essence of the phenomenon and related science-teaching dispositions. Based on the frameworks of phenomenology, constructivism, and adult learning theory, the focus was on understanding how the phenomenon was experienced within the context of teachers' everyday world. ^ Data were collected from eight middle-school teachers purposefully selected because they had participated in informal programs during Project TRIPS (Teaching Revitalized Through Informal Programs in Science), a collaboration between the Miami-Dade school district, government agencies (including NASA), and non-profit organizations (including Audubon of Florida). In addition, the teachers experienced hands-on labs offered through universities (including the University of Arizona), field sites, and other agencies. ^ The study employed Seidman's (1991) three-interview series to collect the data. Several methods were used to enhance the credibility of the research, including using triangulation of the data. The interviews were transcribed, color-coded and organized into six themes that emerged from the data. The themes included: (a) internalized content knowledge, (b) correlated hands-on activities, (c) enhanced science-teaching disposition, (d) networking/camaraderie, (e) change of context, and (f) acknowledgment as professionals. The teachers identified supportive elements and constraints related to each theme. ^ The results indicated that informal programs offering experiential learning opportunities strengthened understanding of content knowledge. Teachers implemented hands-on activities that were explicitly correlated to their curriculum. Programs that were conducted in a relaxed context enhanced teachers' science-teaching dispositions. However, a lack of financial and administrative support, perceived safety risks, insufficient reflection time, and unclear itineraries impeded program implementation. The results illustrated how informal educators can use this cohesive model as they develop programs that address the supports and constraints to teachers' science instruction needs. This, in turn, can aid teachers as they strive to provide effective science instruction to students; notions embedded in reforms. Ultimately, this can affect how learners develop the ability to make informed science decisions that impact the quality of life on a global scale. ^

Plant biogeography and conservation on a tropical island: Isla del Coco, Costa Rica

Isla del Coco (Cocos Island) is a small volcanic island located in the Pacific 500 km west of Costa Rica. Three collecting trips to Isla del Coco, in addition to herbarium research, were completed in order to assess the floristic diversity of the island. The current flora of Isla del Coco contains 262 plant species of which 37 (19.4%) are endemic. This study reports 58 species as new to the island. Seventy-one species (27.1%) were identified as introduced by humans. In addition, five potentially invasive plant species are identified. Seven vegetation types are identified on the island: bayshore, coastal cliff, riparian, low elevation humid forest, high elevation cloud forest, landslide and islet. ^ The biogeographic affinities of the native and endemic species are with Central America/northern South America and to a lesser extent, the Caribbean. Endemic species in the genus Epidendrum were investigated to determine whether an insular radiation event had produced two species found on Isla del Coco. Phylogenetic analysis of the internal transcribed spacer (ITS) of nuclear ribosomal DNA was not able to disprove that the endemic species in this genus are not sister species. Molecular biogeographic analyses of ITS sequence data determined that the Isla del Coco endemic species in the genera Epidendrum, Pilea and Psychotria are most closely related to Central American/northern South American taxa. No biogeographical links were found between the floras of Isla del Coco and the Galápagos Islands. ^ The native and endemic plant diversity of Isla del Coco is threatened with habitat degradation by introduced pigs and deer, and to a lesser extent, by exotic plant species. The IUCN Red List and RAREplants criteria were used to assess the extinction threat for the 37 endemic plant taxa found on the island. All of the endemic species are considered threatened with extinction at the Critically Endangered (CR) by the IUCN criteria or either CR or Endangered (EN) using RAREplants methodology. ^

Estimation and prediction of average vehicle occupancies using traffic accident records

As congestion management strategies begin to put more emphasis on person trips than vehicle trips, the need for vehicle occupancy data has become more critical. The traditional methods of collecting these data include the roadside windshield method and the carousel method. These methods are labor-intensive and expensive. An alternative to these traditional methods is to make use of the vehicle occupancy information in traffic accident records. This method is cost effective and may provide better spatial and temporal coverage than the traditional methods. However, this method is subject to potential biases resulting from under- and over-involvement of certain population sectors and certain types of accidents in traffic accident records. In this dissertation, three such potential biases, i.e., accident severity, driver’s age, and driver’s gender, were investigated and the corresponding bias factors were developed as needed. The results show that although multi-occupant vehicles are involved in higher percentages of severe accidents than are single-occupant vehicles, multi-occupant vehicles in the whole accident vehicle population were not overrepresented in the accident database. On the other hand, a significant difference was found between the distributions of the ages and genders of drivers involved in accidents and those of the general driving population. An information system that incorporates adjustments for the potential biases was developed to estimate the average vehicle occupancies (AVOs) for different types of roadways on the Florida state roadway system. A reasonableness check of the results from the system shows AVO estimates that are highly consistent with expectations. In addition, comparisons of AVOs from accident data with the field estimates show that the two data sources produce relatively consistent results. While accident records can be used to obtain the historical AVO trends and field data can be used to estimate the current AVOs, no known methods have been developed to project future AVOs. Four regression models for the purpose of predicting weekday AVOs on different levels of geographic areas and roadway types were developed as part of this dissertation. The models show that such socioeconomic factors as income, vehicle ownership, and employment have a significant impact on AVOs.

Predicting hurricane evacuation decisions: When, how many, and how far

Traffic from major hurricane evacuations is known to cause severe gridlocks on evacuation routes. Better prediction of the expected amount of evacuation traffic is needed to improve the decision-making process for the required evacuation routes and possible deployment of special traffic operations, such as contraflow. The objective of this dissertation is to develop prediction models to predict the number of daily trips and the evacuation distance during a hurricane evacuation. ^ Two data sets from the surveys of the evacuees from Hurricanes Katrina and Ivan were used in the models' development. The data sets included detailed information on the evacuees, including their evacuation days, evacuation distance, distance to the hurricane location, and their associated socioeconomic characteristics, including gender, age, race, household size, rental status, income, and education level. ^ Three prediction models were developed. The evacuation trip and rate models were developed using logistic regression. Together, they were used to predict the number of daily trips generated before hurricane landfall. These daily predictions allowed for more detailed planning over the traditional models, which predicted the total number of trips generated from an entire evacuation. A third model developed attempted to predict the evacuation distance using Geographically Weighted Regression (GWR), which was able to account for the spatial variations found among the different evacuation areas, in terms of impacts from the model predictors. All three models were developed using the survey data set from Hurricane Katrina and then evaluated using the survey data set from Hurricane Ivan. ^ All of the models developed provided logical results. The logistic models showed that larger households with people under age six were more likely to evacuate than smaller households. The GWR-based evacuation distance model showed that the household with children under age six, income, and proximity of household to hurricane path, all had an impact on the evacuation distances. While the models were found to provide logical results, it was recognized that they were calibrated and evaluated with relatively limited survey data. The models can be refined with additional data from future hurricane surveys, including additional variables, such as the time of day of the evacuation. ^

Improved Annual Average Daily Traffic (AADT) estimation for local roads using parcel-level travel demand modeling

Annual Average Daily Traffic (AADT) is a critical input to many transportation analyses. By definition, AADT is the average 24-hour volume at a highway location over a full year. Traditionally, AADT is estimated using a mix of permanent and temporary traffic counts. Because field collection of traffic counts is expensive, it is usually done for only the major roads, thus leaving most of the local roads without any AADT information. However, AADTs are needed for local roads for many applications. For example, AADTs are used by state Departments of Transportation (DOTs) to calculate the crash rates of all local roads in order to identify the top five percent of hazardous locations for annual reporting to the U.S. DOT. ^ This dissertation develops a new method for estimating AADTs for local roads using travel demand modeling. A major component of the new method involves a parcel-level trip generation model that estimates the trips generated by each parcel. The model uses the tax parcel data together with the trip generation rates and equations provided by the ITE Trip Generation Report. The generated trips are then distributed to existing traffic count sites using a parcel-level trip distribution gravity model. The all-or-nothing assignment method is then used to assign the trips onto the roadway network to estimate the final AADTs. The entire process was implemented in the Cube demand modeling system with extensive spatial data processing using ArcGIS. ^ To evaluate the performance of the new method, data from several study areas in Broward County in Florida were used. The estimated AADTs were compared with those from two existing methods using actual traffic counts as the ground truths. The results show that the new method performs better than both existing methods. One limitation with the new method is that it relies on Cube which limits the number of zones to 32,000. Accordingly, a study area exceeding this limit must be partitioned into smaller areas. Because AADT estimates for roads near the boundary areas were found to be less accurate, further research could examine the best way to partition a study area to minimize the impact.^

Does variation in movement tactics and trophic interactions among American alligators create habitat linkages?

1. Highly mobile top predators are hypothesized to spatially and/or temporally link disparate habitats through the combination of their movement and feeding patterns, but recent studies suggest that individual specialization in habitat use and feeding could keep habitats compartmentalized. 2.  We used passive acoustic telemetry and stable isotope analysis to investigate whether specialization in movement and feeding patterns of American alligators (Alligator mississippiensis) in an oligotrophic subtropical estuary created habitat linkages between marine and estuarine/freshwater food webs. 3.  Individual alligators adopted one of the three relatively distinct movement tactics that were linked to variation in diets. Fifty-six per cent of alligators regularly travelled from the upstream (freshwater/mid-estuary) areas into the downstream (marine-influenced) areas where salinities exceed those typically tolerated by alligators. Thirty-one per cent of the alligators made regular trips from the mid-estuarine habitat into the upstream habitat; 13% remained in the mid-estuary zone year-round. 4.  Stable isotopic analysis indicated that, unlike individuals remaining in the mid-estuary and upstream zones, alligators that used the downstream zone fed at least partially from marine food webs and likely moved to access higher prey abundance at the expense of salt stress. Therefore, ‘commuting’ alligators may link marine food webs with those of the estuary and marshes in the coastal Everglades and create an upstream vector for allochthonous nutrient inputs into the estuary. 5.  This study lends further support to the hypothesis that large-bodied highly mobile predators faced with trade-offs are likely to exhibit individual specialization leading to habitat linkages, rather than compartmentalization. However, the conditions under which this scenario occurs require further investigation.

Social Capital and International Migration from Latin America

We combine data from the Latin American Migration Project and the Mexican Migration Project to estimate models predicting the likelihood of taking of first and later trips to the United States from five nations: Mexico, the Dominican Republic, Costa Rica, Nicaragua, and Peru. The models test specific hypotheses about the effects of social capital on international migration and how these effects vary with respect to contextual factors. Our findings confirm the ubiquity of migrant networks and the universality of social capital effects throughout Latin America. They also reveal how the sizes of these effects are not uniform across settings. Social capital operates more powerfully on first as opposed to later trips and interacts with the cost of migration. In addition, effects are somewhat different when considering individual social capital (measuring strong ties) and community social capital (measuring weak ties). On first trips, the effect of strong ties in promoting migration increases with distance whereas the effect of weak ties decreases with distance. On later trips, the direction of effects for both individual and community social capital is negative for long distances but positive for short distances.

Advanced methodologies in dynamic traffic assignment modeling of managed lanes

Managed lane strategies are innovative road operation schemes for addressing congestion problems. These strategies operate a lane (lanes) adjacent to a freeway that provides congestion-free trips to eligible users, such as transit or toll-payers. To ensure the successful implementation of managed lanes, the demand on these lanes need to be accurately estimated. Among different approaches for predicting this demand, the four-step demand forecasting process is most common. Managed lane demand is usually estimated at the assignment step. Therefore, the key to reliably estimating the demand is the utilization of effective assignment modeling processes. ^ Managed lanes are particularly effective when the road is functioning at near-capacity. Therefore, capturing variations in demand and network attributes and performance is crucial for their modeling, monitoring and operation. As a result, traditional modeling approaches, such as those used in static traffic assignment of demand forecasting models, fail to correctly predict the managed lane demand and the associated system performance. The present study demonstrates the power of the more advanced modeling approach of dynamic traffic assignment (DTA), as well as the shortcomings of conventional approaches, when used to model managed lanes in congested environments. In addition, the study develops processes to support an effective utilization of DTA to model managed lane operations. ^ Static and dynamic traffic assignments consist of demand, network, and route choice model components that need to be calibrated. These components interact with each other, and an iterative method for calibrating them is needed. In this study, an effective standalone framework that combines static demand estimation and dynamic traffic assignment has been developed to replicate real-world traffic conditions. ^ With advances in traffic surveillance technologies collecting, archiving, and analyzing traffic data is becoming more accessible and affordable. The present study shows how data from multiple sources can be integrated, validated, and best used in different stages of modeling and calibration of managed lanes. Extensive and careful processing of demand, traffic, and toll data, as well as proper definition of performance measures, result in a calibrated and stable model, which closely replicates real-world congestion patterns, and can reasonably respond to perturbations in network and demand properties.^