244 research outputs found

    Multi-fault classification of rotor systems based on phase feature of axis trajectory in noisy environments

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    As it is difficult to distinguish multiple rotor faults with similar dynamic phenomena in noisy environments, a multi-fault classification method is proposed by combining the extracted trajectory phase feature, a parameter-optimized variational mode decomposition (VMD) method and a light gradient boosting machine (LightGBM) model. The trajectory phase feature is extracted from an axis trajectory by fusing the frequency, amplitude, and phase information related to rotor motion and can comprehensively describe the dynamic characteristics induced by different rotor faults. First, the vibration displacement signals in two orthogonal directions are collected to construct the axis trajectories with 12 rotor states including healthy, unbalance, misalignment, single crack, multiple cracks, and a mixture of them. Second, the trajectory phase feature is extracted from the vectorized axis trajectories, and the frequency spectra of trajectory phase angles under different rotor faults are analyzed through Fourier transform. Finally, a parameter-optimized VMD method combined with a LightGBM model is applied to classify multiple faults of rotor systems in different noisy environments based on the extracted trajectory phase feature. The 12 rotor states can be classified into nine categories based on the harmonic information of 1X–7X components (X is the rotating frequency of a rotor system) and other components with smaller amplitudes in the frequency spectra of trajectory phase angles. The average classification accuracy of the 12 rotor states exceeds 93.0%, and the recognition rate for each kind of fault is greater than 77.5% in noisy environments. The simulated and experimental results demonstrate the effectiveness and adaptability of the proposed multi-fault classification method. This work can provide a reference for the condition monitoring and fault diagnosis of rotor systems in engineering. </jats:p

    Rapid Estimation of Binding Activity of Influenza Virus Hemagglutinin to Human and Avian Receptors

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    A critical step for avian influenza viruses to infect human hosts and cause epidemics or pandemics is acquisition of the ability of the viral hemagglutinin (HA) to bind to human receptors. However, current global influenza surveillance does not monitor HA binding specificity due to a lack of rapid and reliable assays. Here we report a computational method that uses an effective scoring function to quantify HA-receptor binding activities with high accuracy and speed. Application of this method reveals receptor specificity changes and its temporal relationship with antigenicity changes during the evolution of human H3N2 viruses. The method predicts that two amino acid differences at 222 and 225 between HAs of A/Fujian/411/02 and A/Panama/2007/99 viruses account for their differences in binding to both avian and human receptors; this prediction was verified experimentally. The new computational method could provide an urgently needed tool for rapid and large-scale analysis of HA receptor specificities for global influenza surveillance.National Key Project (2008ZX10004-013)National Institutes of Health (U.S.) (grant AI07443)Singapore-MIT Alliance for Research and TechnologyMassachusetts Institute of Technology. International Science and Technology Initiatives Global Seed FundNational Basic Research Program (973 Program) (2009CB918503)National Basic Research Program (973 Program) (2006CB911002

    Superconductivity in a new layered cobalt oxychalcogenide Na6_{6}Co3_{3}Se6_{6}O3_{3} with a 3d5d^{5} triangular lattice

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    Unconventional superconductivity in bulk materials under ambient pressure is extremely rare among the 3dd transition-metal compounds outside the layered cuprates and iron-based family. It is predominantly linked to highly anisotropic electronic properties and quasi-two-dimensional (2D) Fermi surfaces. To date, the only known example of the Co-based exotic superconductor was the hydrated layered cobaltate, Nax_{x}CoO2_{2}\cdot yH2_{2}O, and its superconductivity is realized in the vicinity of a spin-1/2 Mott state. However, the nature of the superconductivity in these materials is still an active subject of debate, and therefore, finding new class of superconductors will help unravel the mysteries of their unconventional superconductivity. Here we report the discovery of unconventional superconductivity at \sim 6.3 K in our newly synthesized layered compound Na6_{6}Co3_{3}Se6_{6}O3_{3}, in which the edge-shared CoSe6_{6} octahedra form [CoSe2_{2}] layers with a perfect triangular lattice of Co ions. It is the first 3dd transition-metal oxychalcogenide superconductor with distinct structural and chemical characteristics. Despite its relatively low TcT_{c}, material exhibits extremely high superconducting upper critical fields, μ0Hc2(0)\mu_{0}H_{c2}(0), which far exceeds the Pauli paramagnetic limit by a factor of 3 - 4. First-principles calculations show that Na6_{6}Co3_{3}Se6_{6}O3_{3} is a rare example of negative charge transfer superconductor. This new cobalt oxychalcogenide with a geometrical frustration among Co spins, shows great potential as a highly appealing candidate for the realization of high-TcT_{c} and/or unconventional superconductivity beyond the well-established Cu- and Fe-based superconductor families, and opened a new field in physics and chemistry of low-dimensional superconductors

    Symmetry induced selective excitation of topological states in SSH waveguide arrays

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    The investigation of topological state transition in carefully designed photonic lattices is of high interest for fundamental research, as well as for applied studies such as manipulating light flow in on-chip photonic systems. Here, we report on topological phase transition between symmetric topological zero modes (TZM) and antisymmetric TZMs in Su-Schrieffer-Heeger (SSH) mirror symmetric waveguides. The transition of TZMs is realized by adjusting the coupling ratio between neighboring waveguide pairs, which is enabled by selective modulation of the refractive index in the waveguide gaps. Bi-directional topological transitions between symmetric and antisymmetric TZMs can be achieved with our proposed switching strategy. Selective excitation of topological edge mode is demonstrated owing to the symmetry characteristics of the TZMs. The flexible manipulation of topological states is promising for on-chip light flow control and may spark further investigations on symmetric/antisymmetric TZM transitions in other photonic topological frameworks

    A Drive to Driven Model of Mapping Intraspecific Interaction Networks.

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    Community ecology theory suggests that an individual\u27s phenotype is determined by the phenotypes of its coexisting members to the extent at which this process can shape community evolution. Here, we develop a mapping theory to identify interaction quantitative trait loci (QTL) governing inter-individual dependence. We mathematically formulate the decision-making strategy of interacting individuals. We integrate these mathematical descriptors into a statistical procedure, enabling the joint characterization of how QTL drive the strengths of ecological interactions and how the genetic architecture of QTL is driven by ecological networks. In three fish full-sib mapping experiments, we identify a set of genome-wide QTL that control a range of societal behaviors, including mutualism, altruism, aggression, and antagonism, and find that these intraspecific interactions increase the genetic variation of body mass by about 50%. We showcase how the interaction QTL can be used as editors to reconstruct and engineer new social networks for ecological communities

    Emotion experience and regulation in China and the United States: How do culture and gender shape emotion responding?

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    Culture and gender shape emotion experience and regulation, in part because the value placed on emotions and the manner of their expression is thought to vary across these groups. This study tested the hypothesis that culture and gender would interact to predict people's emotion responding (emotion intensity and regulatory strategies). Chinese (n=220; 52% female) and American undergraduates (n=241; 62% female) viewed photos intended to elicit negative emotions after receiving instructions to either "just feel" any emotions that arose (Just Feel), or to "do something" so that they would not experience any emotion while viewing the photos (Regulate). All participants then rated the intensity of their experienced emotions and described any emotion-regulation strategies that they used while viewing the photos. Consistent with predictions, culture and gender interacted with experimental condition to predict intensity: Chinese men reported relatively low levels of emotion, whereas American women reported relatively high levels of emotion. Disengagement strategies (especially distancing) were related to lower emotional intensity and were reported most often by Chinese men. Taken together, findings suggest that emotion-regulation strategies may contribute to differences in emotional experience across Western and East Asian cultures
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