Do Marine Protected Areas Affect Human Nutrition and Health? A Comparison between Villages in Roviana,Solomon Islands

The implementation of marine protected areas (MPAs) for fisheries management has increased recently due to the perceived role of MPAs in conserving biodiversity, increasing fish stocks, and enhancing the food security of coastal communities. However, it is unclear whether MPAs may restrict the availability of marine resources and decrease overall food security and the health of the people. In the Roviana Lagoon of the Solomon Islands, we conducted cross-comparisons of villages with MPAs and a village without an MPA to assess whether MPAs influenced local perceptions of governance, environmental change, livelihood strategies, and actual human nutrition and health. Results showed that residents of villages with effective MPAs had higher energy and protein intake than those who had no MPA or an ineffective MPA. We conclude that “no-take” marine reserves do not have adverse effects and that when MPAs are effectively sustained they may enhance local nutrition and health.     

Numerical Investigation of Sloshing Under Roll Excitation at Shallow Liquid Depths and the Effect of Baffles

Sloshing is relevant in several applications like ship tanks, space and automotive industry and seiching in harbours. Due to the relationship between ship and s...     

A hybrid model based method for bus travel time estimation

Providing accurate information about bus arrival time to passengers can make the public transport system more attractive. Such information helps the passengers by reducing the uncertainty on waiting time and the associated frustrations. However, accurate estimation of bus travel time is still a challenging problem, especially under heterogeneous and lane-less traffic conditions. The accuracy of such information provided to passengers depends mainly on the estimation method used, which in turns depends on the input data used. Hence, developing suitable estimation methods and identifying the most significant/appropriate input data are important. The present study focused on these aspects of development of estimation methods that can accurately estimate travel time by using significant inputs. In order to identify significant inputs, a data mining technique, namely the k-NN classifying algorithm, was used. It is based on the similarity in pattern between the input and historic data. These identified inputs were then used in a hybrid model that combined exponential smoothing technique with recursive estimation scheme based on the Kalman Filtering (KF) technique. The optimal values of the smoothing parameter were dynamically estimated and were updated using the latest measurements available from the field. The performance of the proposed algorithm showed a clear improvement in estimation accuracy when compared with existing methods.     

Behavioral modeling of on-demand mobility services: general framework and application to sustainable travel incentives

Transportation - This paper presents a systematic way of understanding and modeling traveler behavior in response to on-demand mobility services. We explicitly consider the sequential and yet...     

Addressing the joint occurrence of self-selection and simultaneity biases in the estimation of program effects based on cross-sectional observational surveys: case study of travel behavior effects in carsharing

Transportation - We estimate the effect of carsharing on travel behavior (specifically, household vehicle holdings, frequency of transit usage, and frequency of biking and walking) using data from...     

A structural equations analysis of commuters' activity and travel patterns

An exploratory analysis of commuters' activity and travel patterns was carried out using activity-based travel survey data collected in the Washington, DC metropolitan area to investigate and estimate relationships among socio-demographics, activity participation, and travel behavior. Structural equations modeling methodology was adopted to determine the structural relationships among commuters' demographics, activity patterns, trip generation, and trip chaining information. Three types of structural equations model systems were estimated: one that models relationships between travel and activity participation, another that captures trade-offs between in-home and out-of-home activity durations, and a third that models the generation of complex work trip chains. The model estimation results show that strong relationships do exist among commuters' socio-demographic characteristics, activity engagement information, and travel behavior. The finding that significant trade-offs exist between in-home and out-of-home activity participation is noteworthy in the context of in-home vs. out-of-home substitution effects. Virtually all of the results obtained in this paper corroborate earlier findings reported in the literature regarding relationships among time use, activity participation, and travel. This revised version was published online in June 2006 with corrections to the Cover Date.     

Non-commitment bias in public opinion on transit usage

Estimation of ridership on a new transit system in an area where no comparable service existed before is a difficult task of transit planning. Traditional modal split models cannot be used in these cases, because no data or basis for developing a new model or adjusting a “borrowed” model are available. One of the techniques which can be used in this type of situation, is to perform a “concept test” based on public opinion. This approach, however, is plagued with the phenomenon of non-commitment bias of interviewees, and tends to overestimate the ridership. A new fixed route and fixed schedule transit service in Johnson City in Tennessee provided a rare opportunity to perform an investigation on the non-commitment bias through “before” and “after” surveys. The analysis of the non-commitment and actual responses of a sample of residents revealed substantial bias. Overall, the non-commitment ridership estimate was about twice (100% greater than) the actual ridership.:It was also observed that the bias was higher for persons owning automobiles, and for work and shopping trips.     

Integrated population synthesis and workplace assignment using an efficient optimization-based person-household matching method

Transportation - Large scale activity-based simulation models inform a variety of transportation and planning policies using models that often rely on fixed or flexible workplace location in a...