Sufficient Control of Complex Networks

In this paper, we propose to study on sufficient control of complex networks which is to control a sufficiently large portion of the network, where only the quantity of controllable nodes matters. To the best of our knowledge, this is the first time that such a problem is investigated. We prove that the sufficient controllability problem can be converted into a minimum cost flow problem, for which an algorithm can be easily devised with polynomial complexity. Further, we study the problem of minimum-cost sufficient control, which is to drive a sufficiently large subset of the network nodes to any predefined state with the minimum cost using a given number of controllers. It is proved that the problem is NP-hard. We propose an ``extended $L_{\mathrm{0}}$-norm-constraint-based Projected Gradient Method" (eLPGM) algorithm which may achieve suboptimal solutions for the problems at small or medium sizes. To tackle the large-scale problems, we propose to convert the control problem into a graph algorithm problem, and devise an efficient low-complexity ``Evenly Divided Control Paths" (EDCP) algorithm to tackle the graph problem. Simulation results on both synthetic and real-life networks are provided, demonstrating the satisfactory performance of the proposed methods

Controlling local thermalization dynamics in a Floquet-engineered dipolar ensemble

Understanding the microscopic mechanisms of thermalization in closed quantum systems is among the key challenges in modern quantum many-body physics. We demonstrate a method to probe local thermalization in a large-scale many-body system by exploiting its inherent disorder, and use this to uncover the thermalization mechanisms in a three-dimensional, dipolar-interacting spin system with tunable interactions. Utilizing advanced Hamiltonian engineering techniques to explore a range of spin Hamiltonians, we observe a striking change in the characteristic shape and timescale of local correlation decay as we vary the engineered exchange anisotropy. We show that these observations originate from the system's intrinsic many-body dynamics and reveal the signatures of conservation laws within localized clusters of spins, which do not readily manifest using global probes. Our method provides an exquisite lens into the tunable nature of local thermalization dynamics, and enables detailed studies of scrambling, thermalization and hydrodynamics in strongly-interacting quantum systems.Comment: 6 pages, 4 figures main tex

Revising the WHO verbal autopsy instrument to facilitate routine cause-of-death monitoring.

OBJECTIVE: Verbal autopsy (VA) is a systematic approach for determining causes of death (CoD) in populations without routine medical certification. It has mainly been used in research contexts and involved relatively lengthy interviews. Our objective here is to describe the process used to shorten, simplify, and standardise the VA process to make it feasible for application on a larger scale such as in routine civil registration and vital statistics (CRVS) systems. METHODS: A literature review of existing VA instruments was undertaken. The World Health Organization (WHO) then facilitated an international consultation process to review experiences with existing VA instruments, including those from WHO, the Demographic Evaluation of Populations and their Health in Developing Countries (INDEPTH) Network, InterVA, and the Population Health Metrics Research Consortium (PHMRC). In an expert meeting, consideration was given to formulating a workable VA CoD list [with mapping to the International Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) CoD] and to the viability and utility of existing VA interview questions, with a view to undertaking systematic simplification. FINDINGS: A revised VA CoD list was compiled enabling mapping of all ICD-10 CoD onto 62 VA cause categories, chosen on the grounds of public health significance as well as potential for ascertainment from VA. A set of 221 indicators for inclusion in the revised VA instrument was developed on the basis of accumulated experience, with appropriate skip patterns for various population sub-groups. The duration of a VA interview was reduced by about 40% with this new approach. CONCLUSIONS: The revised VA instrument resulting from this consultation process is presented here as a means of making it available for widespread use and evaluation. It is envisaged that this will be used in conjunction with automated models for assigning CoD from VA data, rather than involving physicians

Lipophilic aroylhydrazone chelator HNTMB and its multiple effects on ovarian cancer cells

<p>Abstract</p> <p>Background</p> <p>Metal chelators have gained much attention as potential anti-cancer agents. However, the effects of chelators are often linked solely to their capacity to bind iron while the potential complexation of other trace metals has not been fully investigated. In present study, we evaluated the effects of various lipophilic aroylhydrazone chelators (AHC), including novel compound HNTMB, on various ovarian cancer cell lines (SKOV-3, OVCAR-3, NUTU-19).</p> <p>Methods</p> <p>Cell viability was analyzed via MTS cytotoxicity assays and NCI60 cancer cell growth screens. Apoptotic events were monitored via Western Blot analysis, fluorescence microscopy and TUNEL assay. FACS analysis was carried out to study Cell Cycle regulation and detection of intracellular Reactive Oxygen Species (ROS)</p> <p>Results</p> <p>HNTMB displayed high cytotoxicity (IC50 200-400 nM) compared to previously developed AHC (oVtBBH, HNtBBH, StBBH/206, HNTh2H/315, HNI/311; IC50 0.8-6 μM) or cancer drug Deferoxamine, a hexadentate iron-chelator (IC50 12-25 μM). In a NCI60 cancer cell line screen HNTMB exhibited growth inhibitory effects with remarkable differences in specificity depending on the cell line studied (GI50 10 nM-2.4 μM). In SKOV-3 ovarian cancer cells HNTMB treatment led to chromatin fragmentation and activation of the extrinsic and intrinsic pathways of apoptosis with specific down-regulation of Bcl-2. HNTMB caused delayed cell cycle progression of SKOV-3 through G2/M phase arrest. HNTMB can chelate iron and copper of different oxidation states. Complexation with copper lead to high cytotoxicity via generation of reactive oxygen species (ROS) while treatment with iron complexes of the drug caused neither cytotoxicity nor increased ROS levels.</p> <p>Conclusions</p> <p>The present report suggests that both, non-complexed HNTMB as a chelator of intracellular trace-metals as well as a cytotoxic HNTMB/copper complex may be developed as potential therapeutic drugs in the treatment of ovarian and other solid tumors.</p

Low-coordinate first-row transition metal complexes in catalysis and small molecule activation

Enforcing unusually low coordination numbers on transition metals with sterically demanding ligands has long been an area of interest for chemists. Historically, the synthesis of these challenging molecules has helped to elucidate fundamental principles of bonding and reactivity. More recently, there has been a move towards exploiting these highly reactive complexes to achieve a range of transformations using cheap, earth-abundant metals. In this Perspective, we will highlight selected examples of transition metal complexes with low coordination numbers that have been used in catalysis and the activation of small molecules featuring strong bonds (N2, CO2, and CO)

Selective Search Collaborative Representation for Hyperspectral Anomaly Detection

As an important tool in hyperspectral anomaly detection, collaborative representation detection (CRD) has attracted significant attention in recent years. However, the lack of global feature utilization, the contamination of the background dictionary, and the dependence on the sizes of the dual-window lead to instability of anomaly detection performance of CRD, making it difficult to apply in practice. To address these issues, a selective search collaborative representation detector is proposed. The selective search is based on global information and spectral similarity to realize the flexible fusion of adjacent homogeneous pixels. According to the homogeneous segmentation, the pixels with low background probability can be removed from the local background dictionary in CRD to achieve the purification of the local background and the improvement of detection performance, even under inappropriate dual-window sizes. Three real hyperspectral images are introduced to verify the feasibility and effectiveness of the proposed method. The detection performance is depicted by intuitive detection images, receiver operating characteristic curves, and area under curve values, as well as by running time. Comparison with CRD proves that the proposed method can effectively improve the anomaly detection accuracy of CRD and reduce the dependence of anomaly detection performance on the sizes of the dual-window

Selective Search Collaborative Representation for Hyperspectral Anomaly Detection

As an important tool in hyperspectral anomaly detection, collaborative representation detection (CRD) has attracted significant attention in recent years. However, the lack of global feature utilization, the contamination of the background dictionary, and the dependence on the sizes of the dual-window lead to instability of anomaly detection performance of CRD, making it difficult to apply in practice. To address these issues, a selective search collaborative representation detector is proposed. The selective search is based on global information and spectral similarity to realize the flexible fusion of adjacent homogeneous pixels. According to the homogeneous segmentation, the pixels with low background probability can be removed from the local background dictionary in CRD to achieve the purification of the local background and the improvement of detection performance, even under inappropriate dual-window sizes. Three real hyperspectral images are introduced to verify the feasibility and effectiveness of the proposed method. The detection performance is depicted by intuitive detection images, receiver operating characteristic curves, and area under curve values, as well as by running time. Comparison with CRD proves that the proposed method can effectively improve the anomaly detection accuracy of CRD and reduce the dependence of anomaly detection performance on the sizes of the dual-window

Allocating minimum number of leaders for seeking consensus over directed networks with time-varying nonlinear multi-agents

In this paper, we consider how to determine the minimum number of leaders with allocation and how to achieve consensus over directed networks consisting of time-varying nonlinear multi-agents. Firstly, the problem of finding minimum number of leaders is formulated as a minimum spanning forest problem, i.e., finding the minimum population of trees in the network. By introducing a toll station connecting with each agent, this problem is converted to a minimum spanning tree problem. In this way, the minimum number of leaders is determined and these leaders are found locating at the roots of each tree in the obtained spanning forest. Secondly, we describe a virtual leader connected with the allocated leaders, which indicates that the number of edges connected the follower agents with the virtual leader is the least in an arbitrary directed network. This method is different from the existing consensus problem of redundant leaders or edges that connect the follower with one leader in special networks. A distributed consensus protocol is revisited for achieving final global consensus of all agents. It is theoretically shown that such a protocol indeed ensures consensus. Simulation examples in real-life networks are also provided to show the effectiveness of the proposed methodology. Our works enable studying and extending application of consensus problems in various complex networks.The work was supported partially by National Science Foundation of China (No. 61603209, 61876215), and National Basic Research Program of China (973 Program, Grant No. 2015CB057406), and Independent Research Plan of Tsinghua University (20151080467)

Computing non-Newtonian fluid flow with radial basis function networks

This paper is concerned with the application of radial basis function networks (RBFNs) for solving non-Newtonian fluid flow problems. Indirect RBFNs, which are based on an integration process, are employed to represent the solution variables; the governing differential equations are discretized by means of point collocation. To enhance numerical stability, stress-splitting techniques are utilized. The proposed method is verified through the computation of the rectilinear and non-rectilinear flows in a straight duct and the axisymmetric flow in an undulating tube using Newtonian, power-law, Criminale-Ericksen-Filbey (CEF) and Oldroyd-B models. The obtained results are in good agreement with the analytic and benchmark solutions