A field investigation on the content of heavy metals in soils and dominant plants was conducted in three sites (A<0.5 km, B<1.0 km, C<1.5 km) with different distances of mine tailings. The spatial ...distribution of heavy metals and the accumulation in plants were compared, and the candidate species for ecosystem restoration were selected. The results indicated that the soil was polluted by chromium (Cr), Cadmium (Cd), copper (Cu), nickel (Ni) in varying degrees, which is 2.07, 2.60, 1.79, and 4.49 times higher than the Class-Ⅱ standard in China. The concentrate of Ni, Cd, and Zinc (Zn) increased, while Cr, Lead (Pb), and Cu decreased with the distance from the mine tailings. 73 species (34 families) were found and mainly herbaceous plants. The concentrate of Cd, Cu, Cr, and Ni in 29 dominant plants were measured and 66.67%, 21.43%, 100%, 47.62% plants exceeded the normal concentration range. Based on the comparative analysis of heavy metal content, bioconcentration factor, and translocation factor in plants, Polygonum capitatum has good phytoextraction ability, Boehmeria nivea, Chrysanthemum indicum, Miscanthus floridulus, Conyza canadensis, Rubus setchuenensis, Senecio scandens, and Arthraxon hispidus showed remarkable phytostabilization abilities of Cr, Cd, Ni, and Cu, which can be used as potential phytoremediation candidate.
•The area is contaminated with Cr, Cd, Ni and Cu to varying degrees.•The migration and accumulation of heavy metals, soil nutrient content and the diversity of vegetation were related to the distance from the mining tailings.•We screened eight plants with good phytoextraction/phytostabilization capabilities for Cr, Cd, Ni and Cu.
Generative Attention Learning (GenerAL) is a framework for high-DOF multi-fingered grasping that is not only robust to dense clutter and novel objects but also effective with a variety of different ...parallel-jaw and multi-fingered robot hands. This framework introduces a novel attention mechanism that substantially improves the grasp success rate in clutter. Its generative nature allows the learning of full-DOF grasps with flexible end-effector positions and orientations, as well as all finger joint angles of the hand. Trained purely in simulation, this framework skillfully closes the sim-to-real gap. To close the visual sim-to-real gap, this framework uses a single depth image as input. To close the dynamics sim-to-real gap, this framework circumvents continuous motor control with a direct mapping from pixel to Cartesian space inferred from the same depth image. Finally, this framework demonstrates inter-robot generality by achieving over
92
%
real-world grasp success rates in cluttered scenes with novel objects using two multi-fingered robotic hand-arm systems with different degrees of freedom.
Learning interpretable and transferable subpolicies and performing task decomposition from a single, complex task is difficult. Such decomposition can lead to immense sample efficiency gains in ...lifelong learning. Some traditional hierarchical reinforcement learning techniques enforce this decomposition in a top-down manner, while meta-learning techniques require a task distribution at hand to learn such decompositions. This article presents a framework for using diverse suboptimal world models to decompose complex task solutions into simpler modular subpolicies. Given these world models, this framework performs decomposition of a single source task in a bottom up manner, concurrently learning the required modular subpolicies as well as a controller to coordinate them. We perform a series of experiments on high dimensional continuous action control tasks to demonstrate the effectiveness of this approach at both complex single-task learning and lifelong learning. Finally, we perform ablation studies to understand the importance and robustness of different elements in the framework and limitations to this approach.
Protection of polymeric materials from the atomic oxygen erosion in low-earth orbit spacecrafts has become one of the most important research topics in aerospace science. In the current research, a ...series of novel organic/inorganic nanocomposite films with excellent atomic oxygen (AO) resistance are prepared from the phosphorous-containing polyimide (FPI) matrix and trisilanolphenyl polyhedral oligomeric silsesquioxane (TSP-POSS) additive. The PI matrix derived from 2,2'-bis(3,4-dicarboxyphenyl)hexafluoropropane dianhydride (6FDA) and 2,5-bis(4-amino- phenoxy)phenyldiphenylphosphine oxide (BADPO) itself possesses the self-healing feature in AO environment. Incorporation of TSP-POSS further enhances the AO resistance of the FPI/TSP composite films via a Si-P synergic effect. Meanwhile, the thermal stability of the pristine film is maintained. The FPI-25 composite film with a 25 wt % loading of TSP-POSS in the FPI matrix exhibits an AO erosion yield of 3.1 × 10
cm
/atom after an AO attack of 4.0 × 10
atoms/cm
, which is only 5.8% and 1.0% that of pristine FPI-0 film (6FDA-BADPO) and PI-ref (PMDA-ODA) film derived from 1,2,4,5-pyromellitic anhydride (PMDA) and 4,4'-oxydianline (ODA), respectively. Inert phosphorous and silicon-containing passivation layers are observed at the surface of films during AO exposure.
Based on the finite element limit analysis method, the stability of the face in case of active failure under three constitutive models, the Mohr-Coulomb model (MC), the modified Cambridge model (MCC) ...and the Drucker-Prager model (DP), were analyzed. The ultimate support pressure of the face and the influence of factors such as different burial depth ratios (
C/D
), cohesion (
c
) and friction angle (
φ
) in the MC model are also discussed. The results show that the safety factor obtained by the MCC model under the same support pressure is always smaller than that of the MC model, and the difference is the largest when there is no support pressure. As the support pressure increases, it will gradually approach the MC model. When the support pressure is small, the safety factor obtained by the DP model is larger than the MC model, but when the support pressure is large, it is smaller than the MC model, and the final difference tends to be stable. It is necessary to select an appropriate constitutive model according to different rock masses in practical engineering. The self-stabilizing performance of the face is not affected by
C/D
, and the ultimate support pressure will increase with the increase of
C/D
, decrease linearly with the increase of cohesion, and decrease with the increase of friction angle. When the friction angle is small, the ultimate support pressure is greatly affected by
C/D
, and when the friction angle is large, it is hardly affected by
C/D
.
To investigate the compression-shear behavior of a new circumferential joint based on the sleeve-straight bolt combination type connection of large-diameter shield tunnels, a series of full-scale ...joint experiments was carried out. In the process of the experiment, more attention was paid to the specimen displacement, bolt stress and joint damage mode. On the basis of these experiment phenomena, this study discussed the compression-shear bearing process of the new connector, analyzed the damage mode of the joint structure, and finally evaluated the performance of the new connector. It is found that the bearing process of the joint can be divided into four stages: the transitional stage for overcoming the friction of the concrete, the sleeve bearing stage for the sleeve bearing shear loads alone, the combined bearing stage for bearing shear loads by the connector system, and the structural damage stage for structural instability and damage. Generally speaking, affected by connector position and hand hole, the positive compression-shear stiffness of the joint is less than the negative compression-shear stiffness, and the positive shear strength of the joint is greater than the negative shear strength. The increase of longitudinal axial force will improve the compression-shear performance of the joint. The relationship between longitudinal axial force and joint stiffness is a logarithmic function. The use of new type of connector can effectively improve the compression-shear stiffness of joints under low shear loads, but the application of straight bolts will lose part of the strength performance.
Human failures occur in nuclear power plants when operators are under acute stress. Therefore, an automatic stressed recognition system should be developed for nuclear power work. Previous studies on ...the prediction of stress are limited because of their reliance on subjective ratings and contact physiological measurement. To solve this problem, we developed a non-intrusive way by using voice features to detect stress. We aim to build a system that can estimate the level of stress from speech which may be applied to nuclear power plants where operators engage in regular verbal communication as part of their duties. In this study, we collected voice recordings from 34 participants during a simulated nuclear plant power task in a time-limited situation that requires high cognitive resources. Mel frequency cepstrum coefficients (MFCCs) were extracted from stressed voice samples and the neural network model was used to assess stress levels continuously. The experimental results showed that voice features can provide satisfactory predictions of the stress state. Mean relative errors of prediction are possible within approximately 5%. We discuss the implications of the use of voice as a minimally intrusive means for monitoring the effects of stress on cognitive performance in practical applications.
Collisions of hyperthermal oxygen atoms, with an average laboratory-frame translational energy of 520 kJ mol−1, on continuously refreshed ionic liquids, 1-ethyl-3-methylimidazolium ...bis(trifluoromethylsulfonyl) imide (emimNTf2) and 1-dodecyl-3-methylimidazolium bis(trifluoromethylsulfonyl) imide (C12mimNTf2), were studied with the use of a beam-surface scattering technique. Time-of-flight and angular distributions of inelastically scattered O and reactively scattered OH and H2O were collected for various angles of incidence with the use of a rotatable mass spectrometer detector. For both O and OH, two distinct scattering processes were identified, which can be empirically categorized as thermal and nonthermal. Nonthermal scattering is more probable for both O and OH products. The observation of OH confirms that at least some reactive sites, presumably alkyl groups, must be exposed at the surface. The ionic liquid with the longer alkyl chain, C12mimNTf2, is substantially more reactive than the liquid with the shorter alkyl chain, emimNTf2, and proportionately much more so than would be predicted simply from stoichiometry based on the number of abstractable hydrogen atoms. Molecular dynamics models of these surfaces shed light on this change in reactivity. The scattering behavior of O is distinctly different from that of OH. However, no such differences between inelastic and reactive scattering dynamics have been seen in previous work on pure hydrocarbon liquids, in particular, the benchmark, partially branched hydrocarbon, squalane (C30H62). The comparison between inelastic and reactive scattering dynamics indicates that inelastic scattering from the ionic liquid surfaces takes place predominantly at nonreactive sites that are effectively stiffer than the reactive alkyl chains, with a higher proportion of collisions sampling such sites for emimNTf2 than for C12mimNTf2.
A mass of tailings left by mineral exploitation have caused serious environmental pollution. Although many studies have shown that soil microorganisms have the potential to remediate environmental ...pollution, the interaction mechanism between microorganisms and the surrounding environment of tailings is still unclear. In this study, 15 samples around pyrite mine tailing were collected to explore the ecological effects of environmental factors on bacterial community. The results showed that most of the samples were acidic and contaminated by multiple metals. Cadmium (Cd), copper (Cu), nickel (Ni) migrated and accumulated to into downstream farmlands while chromium (Cr) was the opposite. Proteobacteria, Chloroflex and Actinobacteria were the dominant phyla. Soil pH, total phosphorus (TP), total nitrogen (TN), available potassium (AK), available phosphorus (AP), the bacteria abundance and diversity all gradually increased with the increase of the distance from the tailing. Invertase, acid phosphatase, total organic carbon (TOC), pH, TP and Cr were the main influencing factors to cause the variation of bacterial community. This work could help us to further understand the changes in soil microbial communities around pollution sources.
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•Investigated the microecosystem with different distance away from the tailing•The soil surrounding tailings were acidic and contaminated by multiple heavy metals.•Microbial communities exhibit spatial variation and metabolic function diversity.•Proteobacteria, Chloroflexi, Actinobacteria dominated in the study region.•Soil enzymes are the key factors affecting bacterial community.
Wireless rechargeable sensor networks (WRSNs) provide a solution to the energy problem in wireless sensor networks by introducing chargers to recharge the sensor nodes with rechargeable batteries. ...Most of the existing studies on WRSN focus on charging static nodes or nodes with certain mobility, while a few works investigate charging non-deterministic mobile nodes, where the movement pattern of nodes is unknown. The main challenge in the study of charging non-deterministic nodes is how to find the energy-hungry nodes, because the movement of the nodes is uncertain. The existing schemes assume that the historical trajectories of each node are known and predict the future locations of the nodes by analyzing the trajectory data. However, these schemes require a large amount of trajectory data to train the prediction model, and it takes a considerable amount of time for the network to run to obtain this trajectory data. If there is a node energy depletion during this time, these schemes cannot perform the energy replenishment to the nodes. To address this problem, we propose a novel charging scheme to provide charging services for non-deterministic nodes by introducing the transfer learning technology to predict the future locations of non-deterministic nodes. In the proposed scheme, a backbone Graph Convolutional Network (GCN) is pre-trained with other trajectory datasets, based on which only a small amount of trajectory data of nodes in the target network is needed to complete the location prediction task. In addition, a new scheduling algorithm is proposed, which considers multiple states of the nodes, including the energy consumption rate, the remaining energy state and the future locations, to select the charging target nodes. Simulation results show that the proposed scheme is able to achieve energy replenishment of non-deterministic mobile nodes when the network is just starting to operate.
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