PREFERENTIAL TRADE OF AGRICULTURAL COMMODITIES IN THE CARIBBEAN BASIN

Preferential agricultural trade under the Caribbean Basin Initiative has been beneficial to participating countries, particularly for differentiated goods. Goods that have not performed well were either subject to policy changes, eroding preferences and deteriorating market trends or structural changes that diminished CBI exports.International Relations/Trade,

Volunteer Growth in America: A Review of Trends Since 1974

The Corporation has produced a national report that for the first time tracks volunteering over a 30-year period. "Volunteer Growth in America: A Review of Trends Since 1974" illustrates how volunteering has rebounded to a 30-year high today -- rising by more than 32 percent over the past 16 years -- after declining between 1974 and 1989. The report found that older teenagers (ages 16-19) have more than doubled their time spent volunteering since 1989; that far from being a "Me Generation," that Baby Boomers are volunteering at sharply higher rates than did the previous generation at mid-life; and that the volunteer rate for Americans ages 65 years and over has increased 64 percent since 1974; and the proportion of Americans volunteering with an educational or youth service organization has seen a 63 percent increase just since just 1989. "Volunteer Growth in America" is based on statistics from the U.S. Census Bureau and the Bureau of Labor Statistics. The findings are encouraging while demonstrating that more engagement is needed to achieve a national goal of raising the number of volunteers from 65 million in 2005 to 75 million by 2010

Data Mining and Machine Learning to Improve Northern Florida’s Foster Care System

The purpose of this research project is to use statistical analysis, data mining, and machine learning techniques to determine identifiable factors in child welfare service records that could lead to a child entering the foster care system multiple times. This would allow us the capability of accurately predicting a case’s outcome based on these factors. We were provided with eight years of data in the form of multiple spreadsheets from Partnership for Strong Families (PSF), a child welfare services organization based in Gainesville, Florida, who is contracted by the Florida Department for Children and Families (DCF). This data contained a number of different aspects of the clients (“participants”) who were entered into the system as part of PSF’s record keeping. These aspects included dates, ages, removal types, disabilities, demographics, case details, and more of the parents, children, relatives, and caregivers involved. We analyzed and mined through this data using statistical analysis software (mostly R Studio), searching for correlations that could help us predict if a child is to be removed from their home and enter back into the foster care system. This research was overall a success, and we found significant insights into the cases that allowed us to predict their success or failure; we also built multiple machine learning models and prediction schemes that facilitated further understanding of statistically significant insights about the cases

Volunteering in America: 2007 City Trends and Rankings

"Volunteering in America: 2007 City Trends and Rankings" uses volunteer data collected by the U.S. Census Bureau and Bureau of Labor Statistics from 2004-2006. It ranks and includes profiles for 50 of the largest cities including the volunteer rate; the types of organizations through which residents serve; their main volunteering activities, the average hours per year and volunteer rates for age and gender demographic groups, and key trends and highlights. The report also analyzes social and demographic trends affect city volunteer rates and finds that there are four key drivers of volunteering: community attachment; commuting times, high school graduation levels and poverty; and the prevalence of nonprofits and their capacity to retain volunteers from year to year. The information on volunteering at the local level can help local governments, community leaders, service organizations, and volunteers nationwide develop a volunteer growth strategy, set goals to increase the level of individual engagement in volunteer activities, and build the infrastructure of nonprofits and communities to support more volunteer opportunities

A Logic Your Typechecker Can Count On: Unordered Tree Types in Practice

Type systems featuring counting constraints are often stud- ied, but seldom implemented. We describe an efficient im- plementation of a type system for unordered, edge-labeled trees based on Presburger arithmetic constraints. We begin with a type system for unordered trees and give a compilation into counting automata. We then describe an optimized implementation that provides the fundamental operations of membership and emptiness testing. Although each operation has worst-case exponential complexity, we show how to achieve reasonable performance in practice using a combination of techniques, including syntactic translations, lazy automata unfolding, hash-consing, memoization, and incremental tree processing implemented using partial evaluation. These techniques avoid constructing and examining large structures in many cases and amortize the costs of expensive operations across many computations. To demonstrate the effectiveness of these optimizations, we present experimental data from executions on realistically sized examples drawn from the Harmony data synchronizer

Flipping an Agricultural Teaching Methods Course at a Non-Land Grant University

The purpose of this study was to analyze undergraduate students’ perceptions of experiencing a flipped classroom in a teaching methods course at a Non-Land Grant Public Institution. The flipped classroom moves lectures and online videos outside of the classroom and uses class time for learning activities that promote problem-solving and discussion. Basic qualitative methods were used to provide flexibility, rich description, and the emergence of common patterns and themes. Participants reported the online lectures were beneficial and provided order and structure to the learning process. Personal responsibility emerged as a subtheme with mixed responses. Some participants felt it was the responsibility of the students to watch the videos and make sure they understood, while others felt it was too much responsibility on the students. All participants acknowledged that online lectures were a valuable tool for delivering content knowledge. All participants reported the online lectures, combined with the learning activities during class meetings, deepened their knowledge of teaching and learning application and skill development. Overall, participants felt the flipped classroom approach was a confidence booster due to the use of class time to practice their teaching skills. Participants recognized the flipped classroom as an effective teaching approach

Incremental View Maintenance For Collection Programming

In the context of incremental view maintenance (IVM), delta query derivation is an essential technique for speeding up the processing of large, dynamic datasets. The goal is to generate delta queries that, given a small change in the input, can update the materialized view more efficiently than via recomputation. In this work we propose the first solution for the efficient incrementalization of positive nested relational calculus (NRC+) on bags (with integer multiplicities). More precisely, we model the cost of NRC+ operators and classify queries as efficiently incrementalizable if their delta has a strictly lower cost than full re-evaluation. Then, we identify IncNRC+; a large fragment of NRC+ that is efficiently incrementalizable and we provide a semantics-preserving translation that takes any NRC+ query to a collection of IncNRC+ queries. Furthermore, we prove that incremental maintenance for NRC+ is within the complexity class NC0 and we showcase how recursive IVM, a technique that has provided significant speedups over traditional IVM in the case of flat queries [25], can also be applied to IncNRC+.Comment: 24 pages (12 pages plus appendix

Episodic Memory Measures Complement Structural and Functional MRI for Predicting Cognitive Decline in Apolipoprotein E ε4 Carriers

Apolipo-protein E (APOE) ?4 allele carriers demonstrate greater risk for cognitive decline and Alzheimer\u27s disease than non-carriers. However, factors associated with risk of decline among APOE ?4 carriers are not well-known. In this longitudinal study, we investigated whether discrete aspects of baseline episodic memory performance and structural (sMRI) and function (fMRI) magnetic resonance imaging were associated with cognitive decline in older APOE ?4 carriers and non-carriers. Seventy-eight healthy older adults underwent cognitive testing at baseline and after 18 months, baseline serum APOE genotyping, manually-traced hip-pocampal volume measurement from sMRI, and task-activated fMRI. Cognitive decline was defined as a one SD or greater reduction from baseline on at least one of three cognitive measures at follow-up (Rey Auditory Verbal Learning Test [AVLT] Delayed Recall and Trials 1-5 Sum, Mattis Dementia Rating Scale-2 Total Score). Declining APOE ?4 carriers (n=14) exhibited reduced hippocampal volume (