Abstract-Persons with spinal cord injury (SCI) have heightened risk for cardiovascular disease (CVD). Multidisciplinary risk reduction programs using case management models have been effective in reducing CVD risk in nondisabled persons, but little is known regarding the effects of such programs in SCI. Twenty-six persons with SCI underwent a pilot 2 yr risk intervention program including frequent telephone contact by a case manager and in-person visits by a dietitian, physical therapist, and exercise physiologist. At 6 mo intervals, measurements were made of dietary intake, glucose and lipids, physical activity patterns, and exercise capacity. Of the 26 participants, 10 remained in the program for the full 2 yr; medical issues unrelated to the program were the major reasons for dropping out. Significant improvements were observed in weight, plasma insulin, homeostatic model assessment insulin resistance, and total cholesterol/high-density lipoprotein ratio, although these changes were not consistent across visits. No differences in estimates of physical activity patterns were demonstrated, nor were differences in dietary macronutrient intake observed. Thus, modest changes in some CVD risk markers can be achieved by a multidisciplinary risk reduction program in SCI. Such programs present more challenges than in ambulatory persons, and more intensive risk intervention may be required to appreciably reduce CVD risk in SCI.
Remote access of scientific instruments over the Internet (i.e., remote instrumentation) demand high-resolution (2D and 3D) video image transfers with simultaneous real-time mouse and keyboard controls. Consequently, user quality of experience (QoE) is highly sensitive to network bottlenecks. Further, improper user control while reacting to impaired video caused due to network bottlenecks could result in physical damages to the expensive instrument equipment. Hence, it is vital to understand the interplay between (a) user keyboard/mouse actions toward the instrument, and (b) corresponding network reactions for transfer of instrument video images toward the user. In this paper, we first present an analytical model for characterizing user and network interplay during remote instrumentation sessions in terms of demand and supply interplay principles of traditional economics. Next, we describe the trends of the model parameters using subjective and objective measurements obtained from QoE experiments. Thereafter, we describe our Remote Instrumentation Collaboration Environment (RICE) software that leverages our experiences from the user and network interplay studies, and has functionalities that facilitate reliable and efficient remote instrumentation such as (a) network health awareness to detect network bottleneck periods, and (b) collaboration tools for multiple participants to interact during research and training sessions.
A multi‐line addressing technique that is based on diagonal matrices is demonstrated. Number of time intervals to complete a cycle is independent of the number of address lines that are selected simultaneously. Good brightness uniformity is achieved among pixels that are driven to the same state.
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