A Smart, Textile-Driven, Soft Exosuit for Spinal Assistance.

Work-related musculoskeletal disorders (WMSDs) are often caused by repetitive lifting, making them a significant concern in occupational health. Although wearable assist devices have become the norm for mitigating the risk of back pain, most spinal assist devices still possess a partially rigid structure that impacts the user's comfort and flexibility. This paper addresses this issue by presenting a smart textile-actuated spine assistance robotic exosuit (SARE), which can conform to the back seamlessly without impeding the user's movement and is incredibly lightweight. To detect strain on the spine and to control the smart textile automatically, a soft knitting sensor that utilizes fluid pressure as a sensing element is used. Based on the soft knitting hydraulic sensor, the robotic exosuit can also feature the ability of monitoring and rectifying human posture. The SARE is validated experimentally with human subjects (N = 4). Through wearing the SARE in stoop lifting, the peak electromyography (EMG) signals of the lumbar erector spinae are reduced by 22.8% ± 12 for lifting 5 kg weights and 27.1% ± 14 in empty-handed conditions. Moreover, the integrated EMG decreased by 34.7% ± 11.8 for lifting 5 kg weights and 36% ± 13.3 in empty-handed conditions. In summary, the artificial muscle wearable device represents an anatomical solution to reduce the risk of muscle strain, metabolic energy cost and back pain associated with repetitive lifting tasks.

Carbon resource reallocation with emission quota in carbon emission trading system.

In this study, a two-stage data envelopment analysis approach is developed to examine resource allocation in a real-world carbon emissions trading system. First, this study focuses on the actual participation process of incorporated units in the trading system, where incorporated units will be allocated with a carbon emission quota. Second, we propose a research structure for the carbon trading process with two stages. The first stage is to identify congestion, and the second stage is to trade among the units. We make a sensitivity analysis by considering restrictive parameters on the initial carbon emission quota. Then, we expand the research with a target-setting model that retains production technology from the previous year to set the target output for the following year. The congestion and the trading amount for each unit could be determined in advance. Furthermore, these results are able to anticipate the trading situation and provide valuable recommendations for the production and trading of the analyzed units. Finally, the proposed approach is applied to analyze 13 cities in Hubei Province to investigate their congestion and trading conditions.