Electrochemical CO2 reduction reaction (CO2RR) to formate is considered as one of the most promising routes for value-added fuels and chemical productions. The achievement of excellent activity and ...high Faradaic efficiency in a wide potential range is critical for mature applications. To this regard, we first employed density functional theory simulations to predict activity of Bi nanotubes and Bi nanosheets to CO2RR and selectivity toward formate. The theoretical thermodynamic analysis of the reaction energetics suggests that the limiting potential for CO2 reduction to HCOOH decreases with the increase of the curvature, suggesting a wider potential window of Bi nanotubes for formate formation. Then, Bi nanotubes with highly curved surface were experimentally prepared, showing a large current density (−39.4 mA cm–2 at −1.1 V vs reversible hydrogen electrode (RHE)) for CO2 reduction and a maximum formate selectivity of 97% at −1.0 V vs RHE. More importantly, compared with Bi nanosheets, an appreciable selectivity for formate was achieved on Bi nanotubes in a significantly wider potential window of ∼600 mV (selectivity > 80%). This research provides not only the CO2RR activity–surface structure relationship of metallic Bi but also an efficient strategy for the rational design of electrocatalysts with high activity and selectivity in a wide potential window for CO2RR, which is favorable for compatible application with varied types of photovoltaics and other renewable energy sources.
In visible light communication (VLC), the precise latency evaluation of wireless access networks and the efficient forwarding strategy of core networks are the crux for end-to-end reliability ...provisioning. Leveraging martingale theory, an elegant latency-bounded reliability analysis framework is studied for the VLC network. Considering the characteristic that VLC links are easy to block, the martingale of the service process is constructed. Based on the time shift features, the martingale process related to latency is proposed for the VLC system, which models the influence of entanglement between aggregate arrivals and random service on latency. A stopping time event about latency is defined. Renting the stopping time theory, a tight upper bound of the unreliability with regard to latency is derived. In the core network, a dynamic forward backhaul framework is proposed, which uses the relay selection algorithm based on back-pressure theory to improve data transmission quality. The theoretical latency-bounded reliability matches the simulation results well, which verifies the effectiveness of the proposed analysis framework, and the proposed relay selection algorithm can also improve network performance under data-intensive transmission.
Thermostable cross-β structures are characteristic of pathological amyloid fibrils, but these structures cannot explain the reversible nature of fibrils formed by RNA-binding proteins such as fused ...in sarcoma (FUS), involved in RNA granule assembly. Here, we find that two tandem (S/G)Y(S/G) motifs of the human FUS low-complexity domain (FUS LC) form reversible fibrils in a temperature- and phosphorylation-dependent manner. We named these motifs reversible amyloid cores, or RAC1 and RAC2, and determined their atomic structures in fibrillar forms, using microelectron and X-ray diffraction techniques. The RAC1 structure features an ordered-coil fibril spine rather than the extended β-strand typical of amyloids. Ser42, a phosphorylation site of FUS, is critical in the maintenance of the ordered-coil structure, which explains how phosphorylation controls fibril formation. The RAC2 structure shows a labile fibril spine with a wet interface. These structures illuminate the mechanism of reversible fibril formation and dynamic assembly of RNA granules.
•Both current and legacy community effects influence plant growth.•Aboveground herbivory on focal plants is caused by current neighborhood effects only and not by legacy effects.•Aboveground and ...belowground effects of the current neighborhood explain variance in herbivory equally well.
Current and legacy effects can greatly affect the growth of a focal plant and its interactions with herbivores and such effects can be mediated by above- and belowground effects. However, determining the relative importance of current and legacy above- and belowground effects in natural conditions is a major challenge. In a long-term grassland experiment, we examined the relative importance of the current and legacy above- and belowground effects of plant communities on the growth and aboveground herbivore damage on a focal plant, Leucanthemum vulgare. Focal plants were planted into tubes with soil collected from different plant communities and placed back into the plant communities. Weekly, plant growth and damage were recorded and after 12 weeks plant biomass was measured. We analyzed how well aboveground and belowground characteristics of the current and legacy plots explained plant growth and herbivory. We found both current plant communities and legacy plant communities significantly affected plant growth (shoot biomass and the number of leaves) and herbivory. Root biomass of the focal plants was influenced by current plant communities only. Current and legacy above- and belowground characteristics explained 12% and 11% of the variation in shoot biomass. Root biomass was mainly explained by current above- and belowground characteristics with a total explained variation of 10%, while legacy effects explained 3%. Legacy effects explained most variation in the number of leaves during the first two weeks of measurements, and the effect remained present during the growth season. In contrast, characteristics of the current community explained most of the variation in herbivory throughout the growth period, with on average 6% explained variance aboveground vs. 5% belowground. Our grassland field study highlights that both current and legacy effects influence plant growth, but herbivory on focal plants is caused by current neighborhood effects only and not by legacy effects.
The marine internet of things (MIoT), an increasingly important foundation for ocean development and protection, consists of a variety of marine distributed sensors under water. These sensors of the ...MIoT have always been highly dependent on batteries. To realize in situ power supply, a flexible seaweed-like triboelectric nanogenerator (S-TENG) capable of harvesting wave energy is proposed in this study. The flexible structure, designed with inspiration from the seaweed structure, processes extensive marine application scenarios. The bending and recovering of the S-TENG structure under wave excitations are converted to electricity. As the output performance increases with the number of parallel connected S-TENG units, an S-TENG system with multiple units could serve for floating buoys, coastal power stations, and even submerged devices. Through the demonstration experiments performed in this study, the flexible, low-cost S-TENG could become an effective approach to achieve a battery independent MIoT.
Underwater communication is a critical and challenging issue, on account of the complex underwater environment. This study introduces an underwater wireless communication approach via Maxwell's ...displacement current generated by a triboelectric nanogenerator. Underwater electric field can be generated through a wire connected to a triboelectric nanogenerator, while current signal can be inducted in an underwater receiver certain distance away. The received current signals are basically immune to disturbances from salinity, turbidity and submerged obstacles. Even after passing through a 100 m long spiral water pipe, the electric signals are not distorted in waveform. By modulating and demodulating the current signals generated by a sound driven triboelectric nanogenerator, texts and images can be transmitted in a water tank at 16 bits/s. An underwater lighting system is operated by the triboelectric nanogenerator-based voice-activated controller wirelessly. This triboelectric nanogenerator-based approach can form the basis for an alternative wireless communication in complex underwater environments.
Non-negative matrix factorization (NMF) has attracted much attention for multi-view clustering due to its good theoretical and practical values. Although existing multi-view NMF methods have achieved ...satisfactory performance to some extent, there still exist the following problems: 1) most existing methods only consider the first-order relationship to construct the similarity matrix, which cannot fully explore the neighborhood information; 2) most existing methods only consider the common information shared by different views, and the complementary information contained in different views is often ignored. To tackle the above-mentioned shortcomings, we present a novel multi-view clustering approach, called robust multi-view NMF (RMNMF). Specifically, in RMNMF, we consider the high-order relationship among features, where the first-order and second-order relationship is utilized to obtain an optimal neighborhood structure. Also, we introduce the Hilbert-Schmidt independence criterion (HSIC) to fully explore the complementary information in different views. Extensive experimental results on several benchmark datasets prove the effectiveness of our proposed approach.
With the large-scale application of the Internet of Things (IoT), security issues have become increasingly prominent. Device identification is an effective way to secure IoT environment by quickly ...identifying the category or model of devices in the network. Currently, the passive fingerprinting method used for IoT device identification based on network traffic flow mostly focuses on protocol features in packet headers but does not consider the direction and length of packet sequences. This paper proposes a device identification method for the IoT based on directional packet length sequences in network flows and a deep convolutional neural network. Each value in a packet length sequence represents the size and transmission direction of the corresponding packet. This method constructs device fingerprints from packet length sequences and uses convolutional layers to extract deep features from the device fingerprints. Experimental results show that this method can effectively recognize device identity with accuracy, recall, precision, and f1-score over 99%. Compared with methods using traditional machine learning and feature extraction techniques, our feature representation is more intuitive, and the classification model is effective.
The remediation of cadmium (Cd) contaminated soil has become a global problem due to its toxicity to living organisms. In this study, earthworm (Eisenia fetida) alone or combined with EDTA or bean ...dregs were used for Cd removal from soils. The total and available Cd in soils, soil physicochemical and biological (soil enzyme) properties, Cd accumulation in the earthworm and its antioxidant responses towards Cd, were determined during the 35 days of soil incubation experiment. Our results showed that earthworms were capable of removing Cd from soils, and the remediation process was accelerated by both EDTA and bean dregs. By translocation of Cd from soils, the content of Cd in earthworm steadily increased with the exposure time to 8.11, 12.80, and 9.26 mg kg−1 on day 35 for T2 (earthworm alone), T3 (EDTA enhancement), and T4 (bean dregs enhancement), respectively. Consequently, a great reduction in the Cd contents in soils was achieved in T3 (36.53%) and T4 (30.8%) compared with T2 (28.95%). The concentrations of water/DTPA extractable Cd were also reduced, indicating the low Cd mobility after amendment. Finally, the soil became more fertile and active after wermi-remediation. The soil pH, EC, NO3−-N, available P, and K contents increased, while soil SOM, DOC, and NH4+-N contents were decreased. There were higher soil enzyme activities (including acid phosphatase activity, β-glucosidase activity, and urease activity) among treatments with earthworms. Additionally, the operational taxonomic units (OTUs) increased by 100–150 units, and the higher chao1 and Shannon indexes indicated the enhanced microbial community after wermi-remediation, especially among treatment with EDTA and bean dregs. Therefore, we concluded that earthworms, alone or combined with EDTA and bean dregs, are feasible for the remediation of Cd-contaminated soil.
Display omitted
•Over 30% Cd was removed after a 35-days remediation practice.•Both EDTA and bean dregs enhanced the soil remediation efficiencies by earthworm.•Soil fertility, bacterial communities, and enzymatic activities were elevated after remediation.•Worm-remediation could be optimal techniques for an accelerated soil remediation.
In this study, to establish the biomechanical characteristics of commercial vehicle drivers’ muscles and bones while operating the three pedals, a driver pedal-operation simulator was built, and the ...real-life situation was reconstructed in OpenSim 3.3 software. We set up three seat heights to investigate the drivers’ lower limbs, and the research proceeded in two parts: experiment and simulation. Chinese adult males in the 95th percentile were selected as the research participants. In the experiment, Delsys wireless surface electromyography (EMG) sensors were used to collect the EMG signals of the four main muscle groups of the lower limbs when the drivers operated the three pedals. Then, we analyzed the muscle activation and the degree of muscle fatigue. The simulation was based on OpenSim software to analyze the driver’s lower limb joint angles and joint torque. The results show that the activation of the hamstrings, gastrocnemius, and rectus femoris muscles were higher in the four muscle groups. In respect of torque, in most cases, hip joint torque > knee joint torque > ankle joint torque. The knee joint angles were the largest, and the ankle joint angles changed the most. The experimental results provide a reference for improving drivers’ handling comfort in commercial vehicles and provide theoretical bases for cab design and layout optimization.
