Dougherty Foundation

Online baccalaureate programs now serve a quarter of American degree-seeking students. As those programs proliferated in the past decade, host institutions tended to “unbundle” academic affairs and student affairs (often neglecting the latter in the design and delivery of online programs). And so, while online programs opened the door for students facing barriers, the programs might not be conveying the full set of social, personal, and professional benefits of a college education. Herein, we describe our initiation of a data-driven effort to enrich online degree programs.

We examined the relationship between comorbid medical conditions and changes in cognition over the course of rehabilitation following acquired brain injury. In particular, we compared outcomes between traumatic brain injury (TBI) and non-TBI using a retrospective inpatient rehabilitation dataset. We hypothesized that differences by diagnosis would be minimized among subgroups of patients with common comorbid medical conditions. We used the Functional Independence Measure (FIM)-cognition subscale to index changes in cognition over rehabilitation. A decision tree classifier determined the top 10 comorbid conditions that maximally differentiated TBI and non-TBI. Ten subsets of patients were identified by matching on these conditions, in rank order. Data from these subsets were submitted to repeated-measures logistic regression to establish the minimum degree of commonality in comorbid conditions that would produce similar cognitive rehabilitation, regardless of etiology. The TBI group demonstrated a greater increase in ordinal scores over time relative to non-TBI, across all subscales of the FIM-cognition. When both groups were matched on the top 3 symptoms, there were no significant group differences in rehabilitation trajectory in problem-solving and memory domains (Cohen's d range: 0.2-0.4). Comorbid medical conditions explain differences in cognitive rehabilitation trajectories following acquired brain injury beyond etiology.

Demand for hardwood from plantation-grown stands for pulp and bio-energy in the southern US is more than 90 million tons per year and is increasing. In the specific case of bio-energy and pulp, demand for biomass from eucalypts could approach 20 million tons/year by the year 2022. Fast growing species and hybrids of Eucalyptus are being evaluated to partially fill this demand gap. Though widely grown in a number of countries for pulp as well as for bio-energy, eucalypts in the southern US have not been extensively researched. Initial growth rates of 18 to 36 green tons/ha/year on rotation lengths of 6 to 8 years are possible. Current estimated costs for energy production from eucalypts in the Southern US are estimated at $3.10 to $3.49 per MBtu, where landowner required return rates on reforestation capital invested range from 6 to 14 percent. Eucalypts as a bio-energy feedstock can be competitive with coal in cost per BTU in the southern US.