Upgrading Passenger Vehicle Emission Standard Helps to Reduce China's Air Pollution Risk from Uncertainty in Electrification.

Upgrading to the CHINA 7 standard is crucial for managing air pollution from passenger vehicles in China. Meanwhile, China aims to achieve carbon neutrality by 2060, which necessitates large-scale replacement of gasoline vehicles with electric vehicles in the future. Consequently, the public might view upgrading gasoline vehicles to the CHINA 7 standard as redundant. However, the emission reduction benefits of upgrading standards in the context of uncertain electrification ambitions have not received adequate attention. Here, we show that upgrading standards will compensate for the absence of emissions reductions due to hindered electrification efforts. In the best scenario, China's CO2 emissions can be reduced to 0.047 Gt and NOx to 8.2 × 103 t in 2050. In nonextreme electrification scenarios with CHINA 7 standard, the emission intensity reduction will remain the main driver for emission reductions, outweighing the electrification contribution. In extreme electrification scenarios, upgrading standards will tackle the increased emissions from plug-in hybrid electric vehicles. Our fleet-level results advocate for early standards upgrades to enhance resilience against air pollution risks arising from uncertainties in electrification. Our evidence from China, with one of the most stringent emission standards, can provide a reference point for the world on the upgrading passenger vehicle emission standard issue.

Rethinking industrial land-use in American rust cities towards sustainability based on a block-level model.

Urban land is a fundamental but scarce resource that carries intensive human socio-economic activities. The demographic decline and housing vacancy issues that emerged with de-industrialization have raised concerns regarding the sustainable utilization of urban land resources, particularly in the American Rust Belt region. In this context, a comprehensive analysis of industrial land use can offer valuable insights to support the sustainable planning of shrinking cities. However, existing urban land research exhibits insufficient resolution at the sectoral scale and impedes the evaluation of industrial land use efficiency within the urban context. To address this gap, we established an integrated land use estimation framework for economic sectors based on multi-source data, which enables the assessment of land use efficiency at a finer sectoral scale. The method was then applied to the city of Detroit, Cleveland, and Pittsburgh. The results demonstrate that the current industrial land mix in the three cities is dominated by service-providing industries, but the land usage by goods-producing sectors in these cities presents a relatively high level of efficiency. The Moran's I value indicates a clustered tendency for the main economic sectors. The land use area results reveal that Other Services occupies the most land area in Detroit (2.29 million m2) and Cleveland (2.04 million m2). While in Pittsburgh, Professional Scientific and Technical Services (1.44 million m2) is the largest. In terms of the economic output, Management of Companies and Enterprises is the most efficient sector in Detroit (20.28 thousand $/m2) and Cleveland (29.43 thousand $/m2), while Pittsburgh's Public Administration (11.73 thousand $/m2) is the most efficient. As many other cities in the world are about to enter the era of de-industrialization or low growth, the outcomes can also serve as a reference to guide their sustainable revitalization in line with the SDGs.

Toward Developing a Powered Ankle-Foot Prosthesis With Electromyographic Control to Enhance Functional Performance: A Case Study in a U.S. Service Member.

The only commercially available ankle-foot prosthesis with powered propulsion lacks ruggedization and other capabilities for service members seeking to return to duty and/or other physically demanding activities. Here, we evaluated a ruggedized powered ankle-foot prosthesis with electromyographic control ("Warrior Ankle"; WA) in an experienced male user of the predicate (Empower) prosthesis. The participant (age = 56 years, mass = 86.8 kg, stature = 173 cm) completed a 650 m simulated hike with varying terrain at a fixed, self-selected speed in the WA and predicate prosthesis, with and without a 22.8 kg weighted vest ("loaded" and "unloaded," respectively). Peak dorsiflexion and plantarflexion angles were extracted from each gait cycle throughout the simulated hike (∼500 prosthetic-side steps). The participant walked faster with the WA (1.15 m/s) compared to predicate (0.80 m/s) prosthesis. On the prosthetic side, peak dorsiflexion angles were larger for the WA (loaded: 27.9°; unloaded: 26.9°) compared to the predicate (loaded: 19.4°; unloaded: 21.3°); peak plantarflexion angles were similar between prostheses and loading conditions [WA (loaded: 15.5°; unloaded: 14.9°), predicate (loaded: 16.9°; unloaded: 14.8°). The WA better accommodated the varying terrain profile, evidenced by greater peak dorsiflexion angles, as well as dorsiflexion and plantarflexion angles that more closely matched or exceeded those of the innate ankle [dorsiflexion (WA: 31.6°, predicate: 27.5°); plantarflexion (WA: 20.7°, predicate: 20.5°)]. Furthermore, the WA facilitated a faster walking speed, suggesting a greater functional capacity with the WA prosthesis. Although further design enhancements are needed, this case study demonstrated feasibility of a proof-of-concept, ruggedized powered ankle-foot prosthesis with electromyographic control.

Case Study: A Bio-Inspired Control Algorithm for a Robotic Foot-Ankle Prosthesis Provides Adaptive Control of Level Walking and Stair Ascent.

Powered ankle-foot prostheses assist users through plantarflexion during stance and dorsiflexion during swing. Provision of motor power permits faster preferred walking speeds than passive devices, but use of active motor power raises the issue of control. While several commercially available algorithms provide torque control for many intended activities and variations of terrain, control approaches typically exhibit no inherent adaptation. In contrast, muscles adapt instantaneously to changes in load without sensory feedback due to the intrinsic property that their stiffness changes with length and velocity. We previously developed a "winding filament" hypothesis (WFH) for muscle contraction that accounts for intrinsic muscle properties by incorporating the giant titin protein. The goals of this study were to develop a WFH-based control algorithm for a powered prosthesis and to test its robustness during level walking and stair ascent in a case study of two subjects with 4-5 years of experience using a powered prosthesis. In the WFH algorithm, ankle moments produced by virtual muscles are calculated based on muscle length and activation. Net ankle moment determines the current applied to the motor. Using this algorithm implemented in a BiOM T2 prosthesis, we tested subjects during level walking and stair ascent. During level walking at variable speeds, the WFH algorithm produced plantarflexion angles (range = -8 to -19°) and ankle moments (range = 1 to 1.5 Nm/kg) similar to those produced by the BiOM T2 stock controller and to people with no amputation. During stair ascent, the WFH algorithm produced plantarflexion angles (range -15 to -19°) that were similar to persons with no amputation and were ~5 times larger on average at 80 steps/min than those produced by the stock controller. This case study provides proof-of-concept that, by emulating muscle properties, the WFH algorithm provides robust, adaptive control of level walking at variable speed and stair ascent with minimal sensing and no change in parameters.

Computational modeling of peripheral nerve stimulation.

Nerve localization using peripheral nerve stimulation (PNS) is affected by tissue properties, the anatomy surrounding the nerve, and characteristics of the stimulus waveform. A better understanding of the factors influencing PNS should lead to improved nerve localization techniques for use in regional anesthesia. A finite element approach is described here that includes capacitive effects and accounts for frequency-dependent tissue properties in a computationally efficient manner. The modeling approach can be applied to other bioelectric problems where capacitive effects may be important.

F-wave decomposition for time of arrival profile estimation.

F-waves are distally recorded muscle responses that result from "backfiring" of motor neurons following stimulation of peripheral nerves. Each F-wave response is a superposition of several motor unit responses (F-wavelets). Initial deflection of the earliest F-wavelet defines the traditional F-wave latency (FWL) and earlier F-wavelet may mask F-wavelets traveling along slower (and possibly diseased) fibers. Unmasking the time of arrival (TOA) of late F-wavelets could improve the diagnostic value of the F-waves. An algorithm for F-wavelet decomposition is presented, followed by results of experimental data analysis.