A Flexible Capacitive Pressure Sensor with Adjustable Detection Range Based on the Inflatable Dielectric Layer for Human-Computer Interaction.

As an essential component in wearable electronic devices and intelligent robots, flexible pressure sensors have enormous application value in fields such as healthcare, human-computer interaction, and intelligent perception. However, due to the complex and ever-changing pressure loads borne by sensors in different application scenarios, this also puts great demands on the flexible response and adjustment ability of a sensor's detection range. Therefore, developing a flexible pressure sensor with a wide and adjustable detection range, which can be applied flexibly under different pressure loads, is also a major challenge in current research. In this paper, we propose a flexible pressure sensor with a wide and adjustable detection range based on an inflatable adjustable safety airbag as the dielectric layer. This sensor uses inflatable airbags prepared using 3D printing technology and silicone reverse molding technology as the dielectric layer and achieves high sensitivity (0.6 kPa-1 to 1.19 kPa-1), wide detection range (220-1500 kPa), and flexible performance applicability by adjusting the air pressure inside the dielectric layer. At the same time, its simple production process, convenient production, fast response time (100 ms), and good stability provide the possibility for the flexible application of sensors in different pressure detection. The experimental results indicate that the sensor has enormous potential for applications in wearable devices, healthcare, human-computer interaction, and intelligent perception recognition.

Microbial network structure, not plant and microbial community diversity, regulates multifunctionality under increased precipitation in a cold steppe.

It is known that the dynamics of multiple ecosystem functions (i. e., multifunctionality) are positively associated with microbial diversity and/or biodiversity. However, how the relationship between microbial species affects ecosystem multifunctionality remains unclear, especially in the case of changes in precipitation patterns. To explore the contribution of biodiversity and microbial co-occurrence networks to multifunctionality, we used rainfall shelters to simulate precipitation enhancement in a cold steppe in Northeast China over two consecutive growing seasons. We showed that an increased 50% precipitation profoundly reduced bacterial diversity and multidiversity, while inter-annual differences in precipitation did not shift microbial diversity, plant diversity, or multidiversity. Our analyses also revealed that increased annual precipitation significantly increased ecosystem, soil, nitrogen, and phosphorous cycle multifunctionality. Neither increased precipitation nor inter-annual differences in precipitation had a significant effect on carbon cycle multifunctionality, probably due to the relatively short period (2 years) of our experiment. The co-occurrence network of bacterial and fungal communities was the most dominant factor affecting multifunctionality, the numbers of negative interactions but not positive interactions were linked to multifunctionality. In particular, our results provided evidence that microbial network topological features are crucial for maintaining ecosystem functions in grassland ecosystems, which should be considered in related studies to accurately predict the responses of ecosystem multifunctionality to predicted changes in precipitation patterns.

Nitrogen addition regulates the effects of variation in precipitation patterns on plant biomass formation and allocation in a Leymus chinensis grassland of northeast China.

Global warming is predicted to change precipitation amount and reduce precipitation frequency, which may alter grassland primary productivity and biomass allocation, especially when interact with other global change factors, such as nitrogen deposition. The interactive effects of changes in precipitation amount and nitrogen addition on productivity and biomass allocation are extensively studied; however, how these effects may be regulated by the predicted reduction in precipitation frequency remain largely unknown. Using a mesocosm experiment, we investigated responses of primary productivity and biomass allocation to the manipulated changes in precipitation amount (PA: 150 mm, 300 mm, 450 mm), precipitation frequency (PF: medium and low), and nitrogen addition (NA: 0 and 10 g N m-2 yr-1) in a Leymus chinensis grassland. We detected significant effects of the PA, PF and NA treatments on both aboveground biomass (AGB) and belowground biomass (BGB); but the interactive effects were only significant between the PA and NA on AGB. Both AGB and BGB increased with an increment in precipitation amount and nitrogen addition; the reduction in PF decreased AGB, but increased BGB. The reduced PF treatment induced an enhancement in the variation of soil moisture, which subsequently affected photosynthesis and biomass formation. Overall, there were mismatches in the above- and belowground biomass responses to changes in precipitation regime. Our results suggest the predicted changes in precipitation regime, including precipitation amount and frequency, is likely to alter primary productivity and biomass allocation, especially when interact with nitrogen deposition. Therefore, predicting the influence of global changes on grassland structure and functions requires the consideration of interactions among multiple global change factors.

Mowing enhances the positive effects of nitrogen addition on ecosystem carbon fluxes and water use efficiency in a semi-arid meadow steppe.

Grasslands are now facing a continuously increasing supply of nitrogen (N) fertilizers, resulting in alterations in ecosystem functioning, including changes in carbon (C) and water cycling. Mowing, one of the most widely used grassland management techniques, has been shown to mitigate the negative impacts of increased N availability on species richness. However, knowledge of how N addition and mowing, alone and/or in combination, affect ecosystem-level C fluxes and water use efficiency (WN) is still limited. We experimentally manipulated N fertilization (0 and 10 g N m-2 yr-1) and mowing (once per year at the end of the growing season) following a randomized block design in a meadow steppe characterized by salinization and alkalinization in northeastern China. We found that, compared to the control plots, N addition, mowing, and their interaction increased net ecosystem CO2 exchange by 65.1%, 14.7%, and 133%, and WN by 40.7%, 18.5%, and 96.1%, respectively. Nitrogen enrichment also decreased soil pH, which resulted in greater aboveground biomass (AGB). Moreover, N addition indirectly increased AGB by inducing changes in species richness. Our results indicate that mowing enhances the positive effects of N addition on ecosystem C fluxes and WN. Therefore, appropriate grassland management practices are essential to improve ecosystem C sequestration, WN, and mitigate future species diversity declines due to ecosystem eutrophication.

Different drivers of soil C accumulation in aggregates in response to altered precipitation in a semiarid grassland.

Soil carbon (C) stabilization partially depends on its distribution within soil structural aggregates, and on the physicochemical processes of C within these aggregates. Changes in precipitation can alter the size distribution of aggregate classes within soils, and C input and output processes within these aggregates, which have potential consequences for soil C storage. However, the mechanisms underlying C accumulation within different aggregates under various precipitation regimes remain unclear. In this study, we conducted a 3-year field manipulation experiment to test the effects of a gradient of altered precipitation (-70%, -50%, -30%, 0%, +30%, and +50% amounts compared with ambient rainfall) on soil aggregate distribution and C accumulation in aggregates (53-250 µm, microaggregates; < 53 µm, silt and clay fractions) in a meadow steppe of northeastern China. Our results revealed that the distribution of soil microaggregates decreased along the precipitation gradient, with no detectable discrepant responses with respect to soil C accumulation within the microaggregates to precipitation treatments. In contrast, higher precipitation amounts coupled with a greater proportion of silt and clay fractions enhanced the accumulation of soil C. Importantly, structural equation models revealed that the pathways by which changes in precipitation control the accumulation of soil C varied across aggregate size fractions. Plant biomass was the main direct factor controlling the accumulation of C within soil microaggregates, whereas soil aggregate distribution and enzyme activities strongly interacted with soil C accumulation in the silt and clay fractions. Our findings imply that identifying how plant and soil aggregate properties respond to precipitation changes and drive C accumulation among soil particles will enhance the ability to predict responses of ecosystem processes to future global change.

The Preparation of FeCo/ZnO Composites and Enhancement of Microwave Absorbing Property by Two-Step Method.

In this paper, the flower-like FeCo/ZnO composites were successfully firstly prepared by a two-step method, and their microstructures and microwave absorbing properties were characterized. The results show that with an increase of temperature, the content of ZnO loaded on a FeCo/ZnO composite surface was increased. The optimal reflection loss (RL) value can be reached around -53.81 dB at 9.8 GHz, which is obviously superior to results of previous studies and reports, and its effective bandwidth (RL < -10 dB) is 3.8 GHz in the frequency range of 8.7-11.8 GHz with a matching thickness of 1.9 mm. We considered that a large number of lamellar and rod-like ZnO loaded on nano-FeCo single-phase solid solution by two-step method can significantly improve the electromagnetic wave absorption properties.

Arbuscular Mycorrhizal Fungi Alleviate Drought Stress in C3 (Leymus chinensis) and C4 (Hemarthria altissima) Grasses via Altering Antioxidant Enzyme Activities and Photosynthesis.

As one of the most important limiting factors of grassland productivity, drought is predicted to increase in intensity and frequency. Greenhouse studies suggest that arbuscular mycorrhizal fungi (AMF) can improve plant drought resistance. However, whether AMF can improve plant drought resistance in field conditions and whether the effects of AMF on drought resistance differ among plants with different photosynthetic pathways remain unclear. To evaluate the effect of indigenous AMF on plant drought resistance, an in situ rainfall exclusion experiment was conducted in a temperate meadow in northeast China. The results showed that AMF significantly reduced the negative effects of drought on plant growth. On average, AMF enhanced plant biomass, photosynthetic rate (A), stomatal conductance (g s), intrinsic water use efficiency (iWUE), and superoxide dismutase (SOD) activity of the C3 species Leymus chinensis by 58, 63, 38, 15, and 45%, respectively, and reduced levels of malondialdehyde (MDA) by 32% under light and moderate drought (rainfall exclusion of 30 and 50%, respectively). However, under extreme drought (rainfall exclusion of 70%), AMF elevated only aboveground biomass and catalase (CAT) activities. Averagely, AMF increased the aboveground biomass, A, and CAT activity of Hemarthria altissima (C4) by 37, 28, and 30%, respectively, under light and moderate droughts. The contribution of AMF to plant drought resistance was higher for the C3 species than that for the C4 species under both light and moderate drought conditions. The results highlight potential photosynthetic type differences in the magnitude of AMF-associated enhancement in plant drought resistance. Therefore, AMF may determine plant community structure under future climate change scenarios by affecting the drought resistance of different plant functional groups.