Adaptive Networks Sayed, Ali H.
Proceedings of the IEEE,
04/2014, Letnik:
102, Številka:
4
Journal Article
Recenzirano
This paper surveys recent advances related to adaptation, learning, and optimization over networks. Various distributed strategies are discussed that enable a collection of networked agents to ...interact locally in response to streaming data and to continually learn and adapt to track drifts in the data and models. Under reasonable technical conditions on the data, the adaptive networks are shown to be mean square stable in the slow adaptation regime, and their mean square error performance and convergence rate are characterized in terms of the network topology and data statistical moments. Classical results for single-agent adaptation and learning are recovered as special cases. The performance results presented in this work are useful in comparing network topologies against each other, and in comparing adaptive networks against centralized or batch implementations. The presentation is complemented with various examples linking together results from various domains.
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•Functional metal-organic frameworks are classified and discussed based organic function.•Evidences about the effects of the organic functions are compiled from the published ...papers.•Possible effects of functional groups on structure of metal-organic frameworks are summarized.•Useful strategies are provided about designing functional metal-organic frameworks.
Owing to their three dimensionality and high porosity, metal-organic frameworks (MOFs) have attracted the attention of scientists especially chemists and material engineers. The frameworks of this subclass of hybrid materials are made of inorganic metal ions/clusters and organic bridging ligands. Special connections between these two building blocks of MOFs lead to a theoretically unlimited number of frameworks. Unlike other porous materials, MOFs benefit from characteristics such as high crystallinity and regularity, high porosity and surface area, hybrid organic-inorganic nature, moderate to high chemical and thermal stability, and decorable pores with different functional groups. Decorating MOFs with functions is possible through functionalization of organic linkers, inorganic building blocks, and void cavities of the framework. Tunability of MOFs with organic linkers is of particular importance due to the unlimited possibility to design functional or multi-functional organic linkers as well as distinctive chemical properties of organic functional groups (OFGs). The purpose of this review is to gain deeper insight into the effects of organic functional groups on structure, host-guest chemistry and applications of functional metal-organic frameworks (FMOFs) in order to be able to synthesize functional MOFs for specific purposes through an in depth analysis of the literature.
We propose an adaptive diffusion mechanism to optimize global cost functions in a distributed manner over a network of nodes. The cost function is assumed to consist of a collection of individual ...components. Diffusion adaptation allows the nodes to cooperate and diffuse information in real-time; it also helps alleviate the effects of stochastic gradient noise and measurement noise through a continuous learning process. We analyze the mean-square-error performance of the algorithm in some detail, including its transient and steady-state behavior. We also apply the diffusion algorithm to two problems: distributed estimation with sparse parameters and distributed localization. Compared to well-studied incremental methods, diffusion methods do not require the use of a cyclic path over the nodes and are robust to node and link failure. Diffusion methods also endow networks with adaptation abilities that enable the individual nodes to continue learning even when the cost function changes with time. Examples involving such dynamic cost functions with moving targets are common in the context of biological networks.
In multiuser MIMO downlink communications, it is necessary to design precoding schemes that are able to suppress co-channel interference. This paper proposes designing precoders by maximizing the ...so-called signal-to-leakage-and-noise ratio (SLNR) for all users simultaneously. The presentation considers communications with both single- and multi-stream cases, as well as MIMO systems that employ Alamouti coding. The effect of channel estimation errors on system performance is also studied. Compared with zero-forcing solutions, the proposed method does not impose a condition on the relation between the number of transmit and receive antennas, and it also avoids noise enhancement. Simulations illustrate the performance of the scheme
Higher-Order Weyl Semimetals Ghorashi, Sayed Ali Akbar; Li, Tianhe; Hughes, Taylor L
Physical review letters,
12/2020, Letnik:
125, Številka:
26
Journal Article
Recenzirano
Odprti dostop
We investigate higher-order Weyl semimetals (HOWSMs) having bulk Weyl nodes attached to both surface and hinge Fermi arcs. We identify a new type of Weyl node, which we dub a 2nd-order Weyl node, ...that can be identified as a transition in momentum space in which both the Chern number and a higher order topological invariant change. As a proof of concept we use a model of stacked higher order quadrupole insulators (QI) to identify three types of WSM phases: 1st order, 2nd order, and hybrid order. The model can also realize type-II and hybrid-tilt WSMs with various surface and hinge arcs. After a comprehensive analysis of the topological properties of various HOWSMs, we turn to their physical implications that show the very distinct behavior of 2nd-order Weyl nodes when they are gapped out. We obtain three remarkable results: (i) the coupling of a 2nd-order Weyl phase with a conventional 1st-order one can lead to a hybrid-order topological insulator having coexisting surface cones and flat hinge arcs that are independent and not attached to each other. (ii) A nested 2nd-order inversion-symmetric WSM by a charge-density wave (CDW) order generates an insulating phase having coexisting flatband surface and hinge states all over the Brillouin zone. (iii) A CDW order in a time-reversal symmetric higher-order WSM gaps out a 2nd-order node with a 1st-order node and generates an insulating phase having coexisting surface Dirac cone and hinge arcs. Moreover, we show that a measurement of charge density in the presence of magnetic flux can help to identify some classes of 2nd-order WSMs. Finally, we show that periodic driving can be utilized as a way for generating HOWSMs. Our results are relevant to metamaterials as well as various phases of Cd_{3}As_{2}, KMgBi, and rutile-structure PtO_{2} that have been predicted to realize higher order Dirac semimetals.
This paper develops a distributed optimization strategy with guaranteed exact convergence for a broad class of left-stochastic combination policies. The resulting exact diffusion strategy is shown in ...Part II of this paper to have a wider stability range and superior convergence performance than the EXTRA strategy. The exact diffusion method is applicable to locally balanced left-stochastic combination matrices which, compared to the conventional doubly stochastic matrix, are more general and able to endow the algorithm with faster convergence rates, more flexible step-size choices, and improved privacy-preserving properties. The derivation of the exact diffusion strategy relies on reformulating the aggregate optimization problem as a penalized problem and resorting to a diagonally weighted incremental construction. Detailed stability and convergence analyses are pursued in Part II of this paper and are facilitated by examining the evolution of the error dynamics in a transformed domain. Numerical simulations illustrate the theoretical conclusions.
The diffusion strategy for distributed learning from streaming data employs local stochastic gradient updates along with exchange of iterates over neighborhoods. In Part I <xref ref-type="bibr" ...rid="ref3">3 of this work we established that agents cluster around a network centroid and proceeded to study the dynamics of this point. We established expected descent in non-convex environments in the large-gradient regime and introduced a short-term model to examine the dynamics over finite-time horizons. Using this model, we establish in this work that the diffusion strategy is able to escape from strict saddle-points in <inline-formula><tex-math notation="LaTeX">O(1/\mu)</tex-math></inline-formula> iterations, where <inline-formula><tex-math notation="LaTeX">\mu</tex-math></inline-formula> denotes the step-size; it is also able to return approximately second-order stationary points in a polynomial number of iterations. Relative to prior works on the polynomial escape from saddle-points, most of which focus on centralized perturbed or stochastic gradient descent, our approach requires less restrictive conditions on the gradient noise process.
Background The 2019 coronavirus disease (COVID-19) epidemic is a global health emergency which has been shown to pose a great challenge to mental health, well-being and resilience of healthcare ...workers, especially nurses. Little is known on the impact of COVID-19 among nurses in sub-Saharan Africa. Methods A cross sectional study was carried out between August and November 2020 among nurses recruited from the Aga Khan University Hospital, Nairobi. The survey questionnaire consisted of six components- demographic and work title characteristics, information regarding care of COVID-19 patients, symptoms of depression, anxiety, insomnia, distress and burnout, measured using standardized questionnaires. Multivariable logistic regression analysis was performed to identify factors associated with mental health disorders. Results Of 255 nurses, 171 (67.1%) consented to complete the survey. The median age of the participants was 33.47 years, 70.2% were females and 60.8% were married. More than half, 64.9% were frontline workers directly engaged in COVID-19 care. Only 1.8% reported a prior history or diagnosis of any mental health disorder. Depression, anxiety, insomnia, distress, and burnout were reported in 45.9%, 48.2%, 37.0%, 28.8% and 47.9% of all nurses. Frontline nurses reported experiencing more moderate to severe symptoms of depression, distress and burnout. Furthermore, females reported more burnout as compared to males. Multivariate logistic regression analysis showed that after adjustment, working in the frontlines was an independent risk variable for depression and burnout. Conclusion This is one of the few studies looking at mental health outcomes among nurses during the COVID-19 pandemic in Kenya. Similar to other studies from around the world, nurses directly involved with COVID-19 patients reported higher rates of mental health symptoms. Burnout threatens to exacerbate the pre-existing severe nursing workforce shortage in low-resource settings. Cost-effective and feasible mitigating strategies, geared to low-middle income countries, are urgently needed to help cope with mental health symptoms during such a pandemic.
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