Physical Activity Promotion in the Evolving Work Landscape

How and where we do our work is changing in the United States across industry, government, and non-profit sectors. This evolving landscape includes downsized office space, the reduction of corporate fitness centers, decreased daily commutes, increased hybrid or remote work environments, and experiments with the length of the work week. While some of these changes may prove transient, others will likely be permanent changes affecting the context of work. Some occupations require in-person work settings, especially in the health care, education, travel and food processing sectors. Many of these employees are experiencing burnout after prolonged overtime work and stressful pandemic-related work conditions. Accordingly, employers are turning their focus to employee health and well-being; productivity, retention, promotion; diversity, equity, and inclusion; re-thinking their corporate wellness programs; and prioritizing financial stability, work-life balance, mental health, and other health-promoting culture, systems and policy changes

Physical Activity Surveillance in the United States for Work and Commuting: Understanding the Impact on Population Health and Well-being

Objective: To summarize and describe the current US surveillance systems that assess physical activity (PA) for work and commuting. Methods: An expert group conducted an environmental scan, generating a list (n = 18) which was ultimately reduced to 12, based on the inclusion of PA and/or sedentary behavior data. Results: The 12 surveys or surveillance systems summarized provide nationally representative data on occupational-level PA or individual-level PA at work, data on active commuting, some are scorecards that summarize workplace health best practices and allow benchmarking, and one is a comprehensive nationally representative survey of employers assessing programs and practices in different worksites. Conclusions: The various surveillance systems and surveys/scorecards are disparate and need to be better analyzed and summarized to understand the impact of occupational-level PA and commuting on population health and well-being, life expectancy, and workforce productivity

The AliveCor KardiaMobile ECG device allows electrocardiogram assessment in awake bonobos (Pan paniscus)

OBJECTIVE To determine the diagnostic utility of a smartphone-based ECG device (Alivecor KardiaMobile) in awake bonobos (Pan paniscus). ANIMALS 7 adult bonobos in human care. PROCEDURES Bonobos were trained with positive reinforcement to hold 1 finger from each hand onto the KardiaMobile sensors for 30 seconds to obtain an ECG reading. Ten ECG tracings were recorded from each bonobo and evaluated by a veterinarian, a veterinary cardiologist, and a human cardiologist for tracing quality, tracing length, heart rate, identification of P-waves, and presence and quantification of premature ventricular or atrial contractions. RESULTS 6 of the 7 bonobos were trained within 21 weeks to allow the collection of 10 diagnostic quality ECG tracings. The average heart rate recorded was 87 bpm (range = 60 to 118 bpm). Potential abnormalities identified by the KardiaMobile included premature ventricular contractions in 2 male bonobos and 1 premature atrial contraction in another male. There was strong agreement by reviewers in all ECG parameters except for the identification of P-waves. CLINICAL RELEVANCE The Alivecor KardiaMobile device has diagnostic utility as a screening tool for use in bonobos in human care. The training was accomplished to yield diagnostic ECG readings of acceptable duration in awake bonobos. Given the prevalence of cardiovascular disease in great apes, this technology may identify a subset of great apes who may benefit from early intervention and treatment in an effort to delay the progression of cardiac disease.This article is published as Olds, June E., Ashley Goldacker, David Huneycutt, Sarah P. Huneycutt, Jared P. Taglialatela, and Jessica L. Ward. "The AliveCor KardiaMobile ECG device allows electrocardiogram assessment in awake bonobos (Pan paniscus)." American Journal of Veterinary Research (2023): 1-7. DOI: 10.2460/ajvr.23.01.0013. Copyright 2023 American Veterinary Medical Association. Attribution-NonCommercial 4.0 International (CC BY-NC 4.0). Posted with permission

Energy Efficient Network Memory for Ubiquitous Devices

This paper explores the energy and delay issues that occur when some or all of the local storage is moved out of the embedded device, and into a remote network server. We demonstrate using the network to access remote storage in lieu of local DRAM results in significant power savings. Mobile applications continually demand additional memory, with traditional designs increasing DRAM to address this problem. Modern devices also incorporate low-power network links to support connected ubiquitous environments. Engineers then attempt to minimize utilization of the network due to its perceived large power consumption. This perception is misleading. For 1KB application "pages", network memory is more power efficient than one 2MB DRAM part when the mean time between page transfers exceeds 0.69s. During each transfer the application delay to the user is only 16ms

SoftCache: A Technique for Power and Area Reduction in Embedded Systems

Explicitly software managed cache systems are postulated as a solution for power considerations in computing devices. The savings expected in a SoftCache lies in the removal of tag storage, associativity logic, comparators, and other hardware dedicated to memory hierarchies. The penalty lies in high cache-miss cost and additional instructions required to effect a cache model. In this paper, we characterize SoftCaches by placing them in the overall computing landscape, analyzing the energy and space trade-offs. We present results that indicate a SoftCache saves power and space over hardware caches. Based on the TSMC 0.25um process from MOSIS, we use schematic and layout representations of hardware and SoftCache models for comparison. Accounting for additional instructions executed and simplification of logic, we examine high SoftCache miss cost in relation to the overall system. For a 256KB "mode" change every 1.45 hours, the SoftCache exhibits 1% application slowdown for energy savings of 30% or more in a low-power device such as the SA-110 microprocessor used in PocketPC platforms