Quantum Robot: Structure, Algorithms and Applications

A kind of brand-new robot, quantum robot, is proposed through fusing quantum theory with robot technology. Quantum robot is essentially a complex quantum system and it is generally composed of three fundamental parts: MQCU (multi quantum computing units), quantum controller/actuator, and information acquisition units. Corresponding to the system structure, several learning control algorithms including quantum searching algorithm and quantum reinforcement learning are presented for quantum robot. The theoretic results show that quantum robot can reduce the complexity of O(N^2) in traditional robot to O(N^(3/2)) using quantum searching algorithm, and the simulation results demonstrate that quantum robot is also superior to traditional robot in efficient learning by novel quantum reinforcement learning algorithm. Considering the advantages of quantum robot, its some potential important applications are also analyzed and prospected.Comment: 19 pages, 4 figures, 2 table

Bis(diethyl­enetriamine-κ3 N,N′,N′′)nickel(II) bis­(1,2-dicyanoethene-1,2-dithiolato-κ2 S,S′)nickel(II)

The title compound, [Ni(C4H13N3)2][Ni(C4N2S2)2], has been synthesized by the reaction of Ni(ClO4)2·6H2O, diethyl­enetriamine (deta) and Na2[Ni(mnt)2] [mnt = maleonitrile­dithiol­ate(2-)] in methanol. The structure is composed of a [Ni(deta)2]2+ cation and a [Ni(mnt)2]2− anion. The coordination geometry of the NiII ion in the cation is slightly distorted octa­hedral, defined by six N atoms from two deta ligands, while the NiII ion in the anion is four-coordinated by four S atoms from two mnt ligands in a slightly distorted square-planar geometry. The cations and anions are connected by N—H⋯N hydrogen bonds

Earthworms Modulate Impacts of Soil Heterogeneity on Plant Growth at Different Spatial Scales

[Abstract] Soil heterogeneity (uneven distribution of soil nutrients and/or other properties) is ubiquitous in nature and can greatly affect plant growth. As earthworm activity can influence nutrient redistribution in the soil, we hypothesize that earthworms may alter the effect of soil heterogeneity on plant growth and this effect may depend on the scale of soil heterogeneity. To test these hypotheses, we grew the clonal grass Leymus chinensis in three soil treatments (heterogeneous large vs. heterogeneous small patch vs. homogeneous soil treatment) with or without earthworms [i.e., Eisenia fetida Savigny (Lumbricidae, epigeic redworm)]. In the heterogeneous treatments, the soil consisted of patches with and without 15N-labeled litter (referred to as high- and low-quality patches, respectively), and in the homogeneous treatment, the soil was an even mixture of the two types of soil patches. Biomass of L. chinensis was significantly higher in the high- than in the low-quality patches, showing the foraging response; this foraging response occurred at both scales and under both earthworm treatments. Compared to the homogeneous treatment, the heterogeneous large patch treatment increased biomass of L. chinensis without earthworms, but decreased it with earthworms. In contrast, biomass of L. chinensis in the heterogeneous small patch treatment did not differ from that in the homogeneous treatment, irrespective of earthworms. Belowground biomass was much greater in the heterogeneous small than in the heterogeneous large patch treatment without earthworms, but it did not differ between these two scale treatments with earthworms. In the heterogeneous treatments, soil 15N was greater in the high- than in the low-quality patches, but this effect became much weaker with than without earthworms, suggesting that earthworm activity homogenized the soil. We conclude that earthworms can change the impact of soil heterogeneity on plant growth via homogenizing the soil, and that this effect of earthworms varies with patch scale. Such scale-dependent interactive effects of soil heterogeneity and earthworms could be a potential mechanism modulating plant community structure and productivity.This study was supported by the National Natural Science Foundation of China (31800341) and the Ten-Thousand-Talent Program of Zhejiang Province (2018R52016)China. National Natural Science Foundation of China; 31800341China. Ten-Thousand-Talent Program of Zhejiang Province; 2018R5201

Control of non-controllable quantum systems: A quantum control algorithm based on Grover iteration

A new notion of controllability, eigenstate controllability, is defined for finite-dimensional bilinear quantum mechanical systems which are neither strongly completely controllably nor completely controllable. And a quantum control algorithm based on Grover iteration is designed to perform a quantum control task of steering a system, which is eigenstate controllable but may not be (strongly) completely controllable, from an arbitrary state to a target state.Comment: 7 pages, no figures, submitte

Information-technology approach to quantum feedback control

Quantum control theory is profitably reexamined from the perspective of quantum information, two results on the role of quantum information technology in quantum feedback control are presented and two quantum feedback control schemes, teleportation-based distant quantum feedback control and quantum feedback control with quantum cloning, are proposed. In the first feedback scheme, the output from the quantum system to be controlled is fed back into the distant actuator via teleportation to alter the dynamics of system. The result theoretically shows that it can accomplish some tasks such as distant feedback quantum control that Markovian or Bayesian quantum feedback can't complete. In the second feedback strategy, the design of quantum feedback control algorithms is separated into a state recognition step, which gives "on-off" signal to the actuator through recognizing some copies from the cloning machine, and a feedback (control) step using another copies of cloning machine. A compromise between information acquisition and measurement disturbance is established, and this strategy can perform some quantum control tasks with coherent feedback.Comment: 10 pages,submitte

Quantum mechanics helps in learning for more intelligent robot

A learning algorithm based on state superposition principle is presented. The physical implementation analysis and simulated experiment results show that quantum mechanics can give helps in learning for more intelligent robot.Comment: 9 pages, 2 figure

Comparison of Asian Aquaculture Products by Use of Statistically Supported Life Cycle Assessment

We investigated aquaculture production of Asian tiger shrimp, whiteleg shrimp, giant river prawn, tilapia, and pangasius catfish in Bangladesh, China, Thailand, and Vietnam by using life cycle assessments (LCAs), with the purpose of evaluating the comparative eco-efficiency of producing different aquatic food products. Our starting hypothesis was that different production systems are associated with significantly different environmental impacts, as the production of these aquatic species differs in intensity and management practices. In order to test this hypothesis, we estimated each system's global warming, eutrophication, and freshwater ecotoxicity impacts. The contribution to these impacts and the overall dispersions relative to results were propagated by Monte Carlo simulations and dependent sampling. Paired testing showed significant (p < 0.05) differences between the median impacts of most production systems in the intraspecies comparisons, even after a Bonferroni correction. For the full distributions instead of only the median, only for Asian tiger shrimp did more than 95% of the propagated Monte Carlo results favor certain farming systems. The major environmental hot-spots driving the differences in environmental performance among systems were fishmeal from mixed fisheries for global warming, pond runoff and sediment discards for eutrophication, and agricultural pesticides, metals, benzalkonium chloride, and other chlorine-releasing compounds for freshwater ecotoxicity. The Asian aquaculture industry should therefore strive toward farming systems relying upon pelleted species-specific feeds, where the fishmeal inclusion is limited and sourced sustainably. Also, excessive nutrients should be recycled in integrated organic agriculture together with efficient aeration solutions powered by renewable energy sources. © 2015 American Chemical Society.Additional coauthors: M. Mahfujul Haque Froukje Kruijssen, Geert R. de Snoo, Reinout Heijungs, Peter M. van Bodegom, and Jeroen B. Guiné

A Refined Study of FCRL Genes from a Genome-Wide Association Study for Graves’ Disease

To pinpoint the exact location of the etiological variant/s present at 1q21.1 harboring FCRL1-5 and CD5L genes, we carried out a refined association study in the entire FCRL region in 1,536 patients with Graves’ disease (GD) and 1,516 sex-matched controls by imputation analysis, logistic regression, and cis-eQTL analysis. Among 516 SNPs with P<0.05 in the initial GWAS scan, the strongest signals associated with GD and correlated to FCRL3 expression were located at a cluster of SNPs including rs7528684 and rs3761959. And the allele-specific effects for rs3761959 and rs7528684 on FCRL3 expression level revealed that the risk alleles A of rs3761959 and C of rs7528684 were correlated with the elevated expression level of FCRL3 whether in PBMCs or its subsets, especially in $CD19^+$ B cells and $CD8^+$ T subsets. Next, the combined analysis with 5,300 GD cases and 4,916 control individuals confirmed FCRL3 was a susceptibility gene of GD in Chinese Han populations, and rs3761959 and rs7528684 met the genome-wide association significance level ($P_{combined}$ = 2.27×$10^{−12}$ and 7.11×$10^{−13}$, respectively). Moreover, the haplotypes with the risk allele A of rs3761959 and risk allele C of rs7528684 were associated with GD risk. Finally, our epigenetic analysis suggested the disease-associated C allele of rs7528684 increased affinity for NF-KB transcription factor. Above data indicated that FCRL3 gene and its proxy SNP rs7528684 may be involved in the pathogenesis of GD by excessive inhibiting B cell receptor signaling and the impairment of suppressing function of Tregs