Accurate Estimation of Gait Altitude Using One Wearable IMU Sensor

We present a novel method of estimating gait altitude by using the acceleration and angular velocity data obtained from a single Inertial Measurement Unit (IMU) sensor. High-precision foot tracking and vertical positioning were achieved by using this method. The inherent drifts of IMU sensors, which may cause cumulative errors for position estimation, were reduced by using our algorithm. Firstly, a multitude-threshold detection method was used to determine the stance phase and swing phase in gait movement. Secondly, a zero-velocity update was performed in the stance phase to minimize the drift error when the single foot is stationary. Finally, in the swing phase, the motion direction was represented by quaternion, and the gait altitude was estimated using a method that combines a Complementary Filter (CF) algorithm and a Target-error Compensation algorithm. Experimental results show that this method can effectively reduce inherent drifts of wearable IMU sensors and ensure accurate estimation of gait altitude

Precipitation reduction alters herbaceous community structure and composition in a savanna

Questions In the changing climate scenario, the decline in precipitation is expected to alter water availability for plants, which in turn affects plant community structure and composition. The responses of community composition and structure to declines in precipitation are well documented in other biomes but remain understudied in water-limited savannas. Location A savanna ecosystem in southwest China. Methods We used a four-year (2014-2017) precipitation manipulation experiment to examine changes in herbaceous community composition and structure across the species, functional group and community levels under precipitation reduction. Results Precipitation reduction significantly decreased the average height and percentage cover of the herbaceous community, while increasing species richness and the Pielou evenness index. Precipitation reduction significantly decreased average height, percentage cover and relative abundance of graminoids and perennials, but increased those of forbs and annuals. Precipitation reduction prompted a shift in the dominant species of the herbaceous community towards Fimbristylis monostachya. Conclusions The results show that precipitation reduction changed the composition and structure of the herbaceous community of this savanna. Furthermore, they provide strong evidence that changes in herbaceous community structure and composition in response to the intensity and duration of precipitation reduction in this savanna exhibited relatively low thresholds, which suggests that the herbaceous community's response to a decline in precipitation was essentially nonlinear. These findings imply that even relatively small declines in precipitation may stimulate shifts in plant community structure and composition and affect the function and stability of savanna ecosystems

Looseness Detection of Rail Fasteners Using MEMS Sensor and Power Spectrum Entropy

Rail fasteners, a key component of a railway track, are used to connect the rail and the sub-rail foundation together with the required degree of elasticity. Severely loose or failed fasteners may lead to serious safety hazards for rail transportation. However, current strategies for determining fastener looseness are mainly implemented manually, which is labor-intensive, inefficient and less-than-objective. In this paper, we propose a system that uses a MEMS acceleration meter and a wireless data transmission technique to detect railway fasteners. Vibration was generated by hitting the rail with a hammer. Then the acceleration data was transmitted to the cloud by the Global System for Mobile Communications (GSM) technique. The fastener looseness was analyzed using power spectrum entropy and frequency domain analysis. Results from the field experiments show that our method can identify the fastener's loosening state accurately and automatically. This wireless, low-cost fastener inspection system is expected to provide an effective approach to improving the efficiency of regular railway maintenance

Patterns and Controls of Light Use Efficiency in Four Contrasting Forest Ecosystems in Yunnan, Southwest China

Ecosystem light use efficiency (LUE) is a critical parameter in estimating CO2 uptake by vegetation from climatological and satellite data. However, the spatiotemporal dynamics and biophysical regulations of ecosystem-level LUE are not well understood, resulting in large uncertainties in the estimation of gross primary productivity (GPP) using LUE-based models. In this study, we used eddy covariance to explore spatiotemporal variations and controls of LUE in four contrasting forest ecosystems (savanna, tropical rainforest, subtropical evergreen forest, and subalpine coniferous forest). Based on 27 site years of data, we found that (1) the multiyear mean LUE was 0.063, 0.251, 0.247, and 0.140g C mol photon(-1) in the four contrasting ecosystems, respectively; (2) the LUE in the wet season (May-October) was higher than that in the dry season in all studied ecosystems; (3) the leaf area index controlled GPP and LUE significantly and explained 74%, 29%, 54%, and 36% of the variation in GPP and 51%, 19%, 41%, and 54% of the variation in LUE in the four contrasting ecosystems, respectively; (4) path analysis revealed the critical roles of GPP and vapor pressure deficit in controlling LUE in these four forest ecosystems; and (5) under warming scenarios, LUE may decrease in savanna but increase in the other three ecosystems, while decreasing precipitation (P) may reduce LUE in the ecosystems studied. This study improves our understanding of the influence of biophysical factors on LUE and demonstrates how LUE changes with variations in temperature, soil moisture, and leaf area index, thereby improving estimations of large-scale carbon exchange/cycling