The hidden order of Turing patterns in arid and semi-arid vegetation ecosystems.

Vegetation Turing patterns play a critical role in the ecological functioning of arid and semi-arid ecosystems. However, the long-range spatial features of these patterns have been neglected compared to short-range features like patch shape and spatial wavelength. Drawing inspiration from hyperuniform structures in material science, we find that the arid and semi-arid vegetation Turing pattern exhibits long-range dispersion similar to hyperuniformity. As the degree of hyperuniformity of the vegetation Turing pattern increases, so does the water-use efficiency of the vegetation. This finding supports previous studies that suggest that Turing patterns represent a spatially optimized self-organization of ecosystems for water acquisition. The degree of hyperuniformity of Turing-type ecosystems exhibits significant critical slowing down near the tipping point, indicating that these ecosystems have non-negligible transient dynamical behavior. Reduced rainfall not only decreases the resilience of the steady state of the ecosystem but also slows down the rate of spatial optimization of water-use efficiency in long transient regimes. We propose that the degree of hyperuniformity indicates the spatial resilience of Turing-type ecosystems after strong, short-term disturbances. Spatially heterogeneous disturbances that reduce hyperuniformity lead to longer recovery times than spatially homogeneous disturbances that maintain hyperuniformity.

Single-Camera Multi-View 6DoF pose estimation for robotic grasping.

Accurately estimating the 6DoF pose of objects during robot grasping is a common problem in robotics. However, the accuracy of the estimated pose can be compromised during or after grasping the object when the gripper collides with other parts or occludes the view. Many approaches to improving pose estimation involve using multi-view methods that capture RGB images from multiple cameras and fuse the data. While effective, these methods can be complex and costly to implement. In this paper, we present a Single-Camera Multi-View (SCMV) method that utilizes just one fixed monocular camera and the initiative motion of robotic manipulator to capture multi-view RGB image sequences. Our method achieves more accurate 6DoF pose estimation results. We further create a new T-LESS-GRASP-MV dataset specifically for validating the robustness of our approach. Experiments show that the proposed approach outperforms many other public algorithms by a large margin. Quantitative experiments on a real robot manipulator demonstrate the high pose estimation accuracy of our method. Finally, the robustness of the proposed approach is demonstrated by successfully completing an assembly task on a real robot platform, achieving an assembly success rate of 80%.

Foraging behaviours lead to spatiotemporal self-similar dynamics in grazing ecosystems.

Biological behaviour-driven self-organized patterns have recently been confirmed to play a key role in ecosystem functioning. Here, we develop a theoretical phase-separation model to describe spatiotemporal self-similar dynamics, which is a consequence of behaviour-driven trophic interactions in short-time scales. Our framework integrates scale-dependent feedback and density-dependent movement into grazing ecosystems. This model derives six types of selective foraging behaviours that trigger pattern formation for top-down grazing ecosystems, and one of which is consistent with existing foraging theories. Self-organized patterns nucleate under moderate grazing intensity and are destroyed by overgrazing, which suggests ecosystem degradation. Theoretical results qualitatively agree with observed grazing ecosystems that display spatial heterogeneities under variable grazing intensity. Our findings potentially provide new insights into self-organized patterns as an indicator of ecosystem transitions under a stressful environment.

Ice needles weave patterns of stones in freezing landscapes.

Patterned ground, defined by the segregation of stones in soil according to size, is one of the most strikingly self-organized characteristics of polar and high-alpine landscapes. The presence of such patterns on Mars has been proposed as evidence for the past presence of surface liquid water. Despite their ubiquity, the dearth of quantitative field data on the patterns and their slow dynamics have hindered fundamental understanding of the pattern formation mechanisms. Here, we use laboratory experiments to show that stone transport is strongly dependent on local stone concentration and the height of ice needles, leading effectively to pattern formation driven by needle ice activity. Through numerical simulations, theory, and experiments, we show that the nonlinear amplification of long wavelength instabilities leads to self-similar dynamics that resemble phase separation patterns in binary alloys, characterized by scaling laws and spatial structure formation. Our results illustrate insights to be gained into patterns in landscapes by viewing the pattern formation through the lens of phase separation. Moreover, they may help interpret spatial structures that arise on diverse planetary landscapes, including ground patterns recently examined using the rover Curiosity on Mars.

Pore formation induced by nanoparticles binding to a lipid membrane.

Nanoparticles (NPs) enter a cell primarily via endocytosis, during which they are engulfed by the cell and reside in lipid vesicles named endosomes. Apart from when an endosome is pinched off the plasma membrane, structural integrity of its lipid membrane is usually well maintained. Under certain circumstances, however, such structural integrity can be considerably perturbed by a nanoparticle. For instance, recent experiments [Chu et al., Sci. Rep., 2014, 4, 4495] indicate that nanodiamonds with sharp corners can escape from an endosome by piercing its lipid membrane. Nonetheless, the energetics of this behavior and how it may be controlled by membrane adhesion and NP morphology remain unclear. In this work, we employ continuum modeling to investigate membrane pore formation induced by the spontaneous binding of a sharp nanoparticle. Based on two axial-symmetric NP models, we characterize the indispensable role played by curvature heterogeneity, membrane adhesion, and the sharpness as well as the size of a nanoparticle in 'breaking' a lipid membrane. Apart from revealing a general mechanism of NP binding-induced membrane pore formation, our results provide the reference for improving the endosomal escape of nanoparticles through manipulating their morphology, a direction that can be explored either independently or combined with existing strategies targeting NP surface chemistry.

Influence of Structured Water Layers on Protein Adsorption Process: A Case Study of Cytochrome c and Carbon Nanotube Interactions and Its Implications.

Cytochrome c, an essential protein of the electron transport chain, is known to be capable of amplifying the toxicity of carbon nanomaterials via free-radical generation. To understand their interaction, as well as the more general protein-nanoparticle interaction at molecular levels, we investigate the adsorptions between cytochrome c and carbon nanotubes (CNTs) in dynamic and thermodynamic ways using molecular dynamics simulations. The results reveal a well-defined three-phase process separated by two transition points: the diffusion phase where the protein diffuses in the water box, the lockdown phase I where the protein inserts into the surface-bound water layers and rearranges its conformation to fit to the surface of the CNT, and the lockdown phase II where cytochrome c repels the water molecules standing in its way to the surface of CNT and reaches stable adsorption states. The structured water layers affect the movement of atoms by electrostatic forces. In lockdown phase I, the conformation adjustment of the protein dominates the adsorption process. The most thermally favorable adsorption conformation is determined. It shows that except for the deformation of short ß sheets and some portions of α helixes, most of the secondary structures of cytochrome c remain unchanged, implying that most of the functions of cytochrome c are preserved. During these processes, the energy contributions of the hydrophilic residues of cytochrome c are much larger than those of hydrophobic residues. Interestingly, the structured water layers at the CNT surface allow more hydrophilic residues such as Lys to get into close contact with the CNT, which plays a significant role during the anchoring process of adsorption. Our results demonstrate that the heme group is in close contact with the CNT in some of the adsorbed states, which hence provides a way for electron transfer from cytochrome c to the CNT surface.

Anchored but not internalized: shape dependent endocytosis of nanodiamond.

Nanoparticle-cell interactions begin with the cellular uptake of the nanoparticles, a process that eventually determines their cellular fate. In the present work, we show that the morphological features of nanodiamonds (NDs) affect both the anchoring and internalization stages of their endocytosis. While a prickly ND (with sharp edges/corners) has no trouble of anchoring onto the plasma membrane, it suffers from difficult internalization afterwards. In comparison, the internalization of a round ND (obtained by selective etching of the prickly ND) is not limited by its lower anchoring amount and presents a much higher endocytosis amount. Molecular dynamics simulation and continuum modelling results suggest that the observed difference in the anchoring of round and prickly NDs likely results from the reduced contact surface area with the cell membrane of the former, while the energy penalty associated with membrane curvature generation, which is lower for a round ND, may explain its higher probability of the subsequent internalization.

Estimation of Nanodiamond Surface Charge Density from Zeta Potential and Molecular Dynamics Simulations.

Molecular dynamics simulations of nanoparticles (NPs) are increasingly used to study their interactions with various biological macromolecules. Such simulations generally require detailed knowledge of the surface composition of the NP under investigation. Even for some well-characterized nanoparticles, however, this knowledge is not always available. An example is nanodiamond, a nanoscale diamond particle with surface dominated by oxygen-containing functional groups. In this work, we explore using the harmonic restraint method developed by Venable et al., to estimate the surface charge density (σ) of nanodiamonds. Based on the Gouy-Chapman theory, we convert the experimentally determined zeta potential of a nanodiamond to an effective charge density (σeff), and then use the latter to estimate σ via molecular dynamics simulations. Through scanning a series of nanodiamond models, we show that the above method provides a straightforward protocol to determine the surface charge density of relatively large (> ∼100 nm) NPs. Overall, our results suggest that despite certain limitation, the above protocol can be readily employed to guide the model construction for MD simulations, which is particularly useful when only limited experimental information on the NP surface composition is available to a modeler.

Semi-automatic recognition of marine debris on beaches.

An increasing amount of anthropogenic marine debris is pervading the earth's environmental systems, resulting in an enormous threat to living organisms. Additionally, the large amount of marine debris around the world has been investigated mostly through tedious manual methods. Therefore, we propose the use of a new technique, light detection and ranging (LIDAR), for the semi-automatic recognition of marine debris on a beach because of its substantially more efficient role in comparison with other more laborious methods. Our results revealed that LIDAR should be used for the classification of marine debris into plastic, paper, cloth and metal. Additionally, we reconstructed a 3-dimensional model of different types of debris on a beach with a high validity of debris revivification using LIDAR-based individual separation. These findings demonstrate that the availability of this new technique enables detailed observations to be made of debris on a large beach that was previously not possible. It is strongly suggested that LIDAR could be implemented as an appropriate monitoring tool for marine debris by global researchers and governments.

Interface Adsorption Taking the Most Advantageous Conformation for Electron Transfer Between Graphene and Cytochrome c.

Most designed functions in biomedical nanotechnology are directly influenced by interactions of biological molecules with nano surfaces. Here, we explored and detected the most favorable adsorption conformation of cytochrome c on graphene by measuring the adsorption energy, the number of contact atoms, and the minimal distance between protein and surface. From the root mean square deviation of the protein backbone, the radius of gyration, and the proportion of secondary structure, it is revealed that cytochrome c does not deform significantly and the secondary structures are preserved to a large extent. The residues, Lys, Phe and Thr contribute significantly to the adsorption of cytochrome c to graphene. The long hydrophobic and flexible alkyl tail of Lys, the π-π stacking interaction between Phe and graphene, and the presence of abundant Thr constitute the driving force for the stable adsorption of cytochrome c on graphene. Cytochrome c is adsorbed to graphene with the group heme lying almost perpendicular to the graphene, and the distance between Fe atom and the graphene is 10.15 A, which is shorter than that between electron donor and receptor in many other biosystems. All the results suggest that the most favorable adsorption takes the most advantageous conformation for electron transfer, which promotes significantly the electron transfer between graphene and cytochrome c. The findings might provide new and important information for designs of biomedical devices or products with graphene-based nanomaterials.

Free Energy Calculation of Nanodiamond-Membrane Association-The Effect of Shape and Surface Functionalization.

Nanodiamonds (NDs) are nanoscale diamond particles with broad applications in biosensing, drug delivery, and long-term tracking. Their interactions with a membrane dictate both the endocytosis process and subsequent intracellular fate of the nanoparticles. However, details of ND-membrane association and the energetics of this process remain largely unknown. In this work, we use all-atom molecular dynamics (MD) simulations to determine the free energy profile and molecular details of ND-membrane association, with a focus on the impact of shape and surface functionalization. Through altogether 6.5 µs umbrella sampling on six atomistic ND models of different shapes (spherical or pyramidal) and surface functionalization (5%, 35%, and 55%), we show that nanodiamonds associate favorably with the membrane, which is largely driven by ND-lipid interactions. During its membrane association, the shape of a nanodiamond plays a key role in determining the location of the free energy minimum, while its surface functionalization modulates the depth of the minimum. Of the six models studied here, all spherical NDs adhere to the bilayer surface, whereas pyramidal NDs, with the exception of the most functionalized P55, anchor inside the membrane. Shape also dominates the height of the free energy barrier: the sharp pyramidal NDs have much lower barriers against penetrating a POPC bilayer than spherical ones. Our all-atom ND models and their bilayer association strength determined here can be combined with future coarse-grained or continuum models to further explore ND-membrane interactions on larger length scales.