Detrended fluctuation analysis on the correlations of complex networks under attack and repair strategy

We analyze the correlation properties of the Erdos-Renyi random graph (RG) and the Barabasi-Albert scale-free network (SF) under the attack and repair strategy with detrended fluctuation analysis (DFA). The maximum degree k_max, representing the local property of the system, shows similar scaling behaviors for random graphs and scale-free networks. The fluctuations are quite random at short time scales but display strong anticorrelation at longer time scales under the same system size N and different repair probability p_re. The average degree , revealing the statistical property of the system, exhibits completely different scaling behaviors for random graphs and scale-free networks. Random graphs display long-range power-law correlations. Scale-free networks are uncorrelated at short time scales; while anticorrelated at longer time scales and the anticorrelation becoming stronger with the increase of p_re.Comment: 5 pages, 4 figure

Normalization of large-scale behavioural data collected from zebrafish

Many contemporary neuroscience experiments utilize high-throughput approaches to simultaneously collect behavioural data from many animals. The resulting data are often complex in structure and are subjected to systematic biases, which require new approaches for analysis and normalization. This study addressed the normalization need by establishing an approach based on linear-regression modeling. The model was established using a dataset of visual motor response (VMR) obtained from several strains of wild-type (WT) zebrafish collected at multiple stages of development. The VMR is a locomotor response triggered by drastic light change, and is commonly measured repeatedly from multiple larvae arrayed in 96-well plates. This assay is subjected to several systematic variations. For example, the light emitted by the machine varies slightly from well to well. In addition to the light-intensity variation, biological replication also created batch-batch variation. These systematic variations may result in differences in the VMR and must be normalized. Our normalization approach explicitly modeled the effect of these systematic variations on VMR. It also normalized the activity profiles of different conditions to a common baseline. Our approach is versatile, as it can incorporate different normalization needs as separate factors. The versatility was demonstrated by an integrated normalization of three factors: light-intensity variation, batch-batch variation and baseline. After normalization, new biological insights were revealed from the data. For example, we found larvae of TL strain at 6 days post-fertilization (dpf) responded to light onset much stronger than the 9-dpf larvae, whereas previous analysis without normalization shows that their responses were relatively comparable. By removing systematic variations, our model-based normalization can facilitate downstream statistical comparisons and aid detecting true biological differences in high-throughput studies of neurobehaviour

Effects of Noise, Correlations and errors in the preparation of initial states in Quantum Simulations

In principle a quantum system could be used to simulate another quantum system. The purpose of such a simulation would be to obtain information about problems which cannot be simulated with a classical computer due to the exponential increase of the Hilbert space with the size of the system and which cannot be measured or controlled in an actual experiment. The system will interact with the surrounding environment, with the other particles in the system and be implemented using imperfect controls making it subject to noise. It has been suggested that noise does not need to be controlled to the same extent as it must be for general quantum computing. However the effects of noise in quantum simulations and how to treat them are not completely understood. In this paper we study an existing quantum algorithm for the one-dimensional Fano-Anderson model to be simulated using a liquid-state NMR device. We calculate the evolution of different initial states in the original model, and then we add interacting spins to simulate a more realistic situation. We find that states which are entangled with their environment, and sometimes correlated but not necessarily entangled have an evolution which is described by maps which are not completely positive. We discuss the conditions for this to occur and also the implications.Comment: Revtex 4-1, 14 pages, 21 figures, version 2 has typos corrected and acknowledgement adde

Learning high-level robotic manipulation actions with visual predictive model

Learning visual predictive models has great potential for real-world robot manipulations. Visual predictive models serve as a model of real-world dynamics to comprehend the interactions between the robot and objects. However, prior works in the literature have focused mainly on low-level elementary robot actions, which typically result in lengthy, inefficient, and highly complex robot manipulation. In contrast, humans usually employ top–down thinking of high-level actions rather than bottom–up stacking of low-level ones. To address this limitation, we present a novel formulation for robot manipulation that can be accomplished by pick-and-place, a commonly applied high-level robot action, through grasping. We propose a novel visual predictive model that combines an action decomposer and a video prediction network to learn the intrinsic semantic information of high-level actions. Experiments show that our model can accurately predict the object dynamics (i.e., the object movements under robot manipulation) while trained directly on observations of high-level pick-and-place actions. We also demonstrate that, together with a sampling-based planner, our model achieves a higher success rate using high-level actions on a variety of real robot manipulation tasks

Discovery of Rubinite, Ca_3Ti^(3+)_2Si_3O_(12), a new Garnet Mineral in Refractory Inclusions from Carbonaceous Chondrites

During a nanomineralogy investigation of carbonaceous chondrites, a new Ti^(3+)-dominant garnet, named “rubinite,” Ca_3Ti^(3+)_2Si_3O_(12) with the Ia^3d garnet structure, was identified in five Ca-Al-rich inclusions (CAIs) from the CV3 chondrites Vigarano, Allende, and Efremovka. Field-emission scanning electron microscope, electron back-scatter diffraction, electron microprobe and ion microprobe techniques were used to characterize the chemistry, oxygen-isotope compositions, and structure of rubinite and associated phases. Synthetic Ca_3Ti^(3+)_2Si_3O_(12) garnet was reported by [1]. Here, we describe the first natural occurrences of rubinite as a refractory mineral in primitive meteorites. The mineral has been approved by the Commission on New Minerals, Nomenclature and Classification of the International Mineralogical Association (IMA 2016-110) [2]. The name honors Alan E. Rubin, a cosmochemist at University of California, Los Angeles (UCLA), USA, for his many contributions to cosmochemistry and meteorite research

Evidence for fault lubrication during the 1999 Chi-Chi, Taiwan, earthquake (Mw7.6)

The ground motion data of the 1999 Chi-Chi, Taiwan, earthquake exhibit a striking difference in frequency content between the north and south portions of the rupture zone. In the north, the ground motion is dominated by large low-frequency displacements with relatively small high-frequency accelerations. The pattern is opposite in the south, with smaller displacements and larger accelerations. We analyze the fault dynamics in light of a fault lubrication mechanism using near-field seismograms and a detailed rupture model. The fault zone contains viscous material (e.g., gouge), in which pressure increases following the Reynolds lubrication equation. When the displacement exceeds a threshold, lubrication pressure becomes high enough to widen the gap, thereby reducing the area of asperity contact. With less asperity contact, the fault slips more smoothly, suppressing high-frequency radiation