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Aim: This study aimed to investigate the effect of circadian rhythm stability and amplitude on musculoskeletal disorder prevalence and work–family conflict among nurses. Design: This cross‐sectional study was conducted on 386 nurses working in three hospitals, in Shahroud, Iran. Method: The data were collected using the Circadian Rhythm Inventory, Nordic Musculoskeletal Disorders, and Carlson Work‐Family Conflict questionnaires. Results: The highest prevalence of musculoskeletal disorders was reported in the lower back (68.4%), upper back (65.5%) and shoulders (53.6%), respectively. No significant relation was found between circadian rhythm stability and amplitude, and musculoskeletal disorders prevalence. The nurses who could not overcome drowsiness reported more Work Interference with Family (WIF), Family Interference with Work (FIW) (time‐based) and FIW (strain‐based) compared to the nurses who overcame drowsiness. In addition, the appropriate nurses for shift work experienced less WIF, FIW (behavioural‐based) and WIF (strain‐based) compared to the nurses who could not work overtime or at night. [ABSTRACT FROM AUTHOR]

This article proposes a methodology for critical path selection and delay sensor insertion for aging monitoring in field-programmable gate arrays (FPGAs). The aging information can be used to reconfigure FPGAs to achieve better performance or wear leveling. To filter out the paths aging less aggressively, our methodology decides based on both physical-level parameters [e.g., path delay, process variation, temperature, static stress (duty cycle), and dynamic stress (switching activity) as well as aging-relevant parameters (e.g., fan-out, and endpoint physical location)]. After selection of an optimal set of paths, age sensors, introduced in our earlier work, are placed in a distributed fashion throughout the FPGA area to provide aging information of its various parts as they are being used. Accurate aging models for FPGAs are required to determine the contribution of the above-mentioned parameters in aging. In this article, ASICs’ aging models are adapted for FPGAs through measurement-based fitting approach. The experimental results using various benchmarks reveal that our algorithm selects paths with a minimum error. [ABSTRACT FROM AUTHOR]

In this article, we propose a fine-grained FPGA aging mitigation method. Our method focuses on Look Up Tables (LUTs) on which Boolean functions are mapped. Based on our observations, for any configuration, even if it is carefully selected, a number of LUT transistors experience severe stress rates. Therefore, an algorithm is presented to select several alternative configurations for each LUT. Alternative configurations are obtained by LUT input reordering. These alternative configurations are rotationally loaded into the FPGA. Experimental results shows that our method achieves 263 and 14.1 percent Mean Time To Failure (MTTF) improvement for Hot Carrier Injection (HCI) and Bias Temperature Instability (BTI), respectively. Additionally, due to changing only local routings, our method imposes up to 1 percent performance overhead to the systems. [ABSTRACT FROM AUTHOR]

This paper proposes a highly scalable sensor design for late transition detection in FPGA based platforms. Transition delays occur because of aging mechanisms such as Biased Temperature Instability (BTI) and Hot Carrier Injection (HCI). We propose a sensor clock (SCLK) that is a function of minimum slack time of a set of paths selected for age monitoring. There will be one such clock for many sensors as are needed in an entire FPGA. Our proposed sensor architecture makes it possible for a single SCLK to be shared by all sensors. Additionally, the proposed sensor occupies one slice (basic FPGA logic block), which leads to low area, power, and performance overhead. Using Artix-7-based board, experimental results demonstrate that the proposed aging sensor detects aging earlier than existing sensors and provides less power and performance overheads. [ABSTRACT FROM AUTHOR]