VastTrack: Vast Category Visual Object Tracking

In this paper, we introduce a novel benchmark, dubbed VastTrack, towards facilitating the development of more general visual tracking via encompassing abundant classes and videos. VastTrack possesses several attractive properties: (1) Vast Object Category. In particular, it covers target objects from 2,115 classes, largely surpassing object categories of existing popular benchmarks (e.g., GOT-10k with 563 classes and LaSOT with 70 categories). With such vast object classes, we expect to learn more general object tracking. (2) Larger scale. Compared with current benchmarks, VastTrack offers 50,610 sequences with 4.2 million frames, which makes it to date the largest benchmark regarding the number of videos, and thus could benefit training even more powerful visual trackers in the deep learning era. (3) Rich Annotation. Besides conventional bounding box annotations, VastTrack also provides linguistic descriptions for the videos. The rich annotations of VastTrack enables development of both the vision-only and the vision-language tracking. To ensure precise annotation, all videos are manually labeled with multiple rounds of careful inspection and refinement. To understand performance of existing trackers and to provide baselines for future comparison, we extensively assess 25 representative trackers. The results, not surprisingly, show significant drops compared to those on current datasets due to lack of abundant categories and videos from diverse scenarios for training, and more efforts are required to improve general tracking. Our VastTrack and all the evaluation results will be made publicly available https://github.com/HengLan/VastTrack.Comment: Tech. repor

Fast-Response Micro-Phototransistor Based on MoS2/Organic Molecule Heterojunction

Over the past years, molybdenum disulfide (MoS2) has been the most extensively studied two-dimensional (2D) semiconductormaterial. With unique electrical and optical properties, 2DMoS2 is considered to be a promising candidate for future nanoscale electronic and optoelectronic devices. However, charge trapping leads to a persistent photoconductance (PPC), hindering its use for optoelectronic applications. To overcome these drawbacks and improve the optoelectronic performance, organic semiconductors (OSCs) are selected to passivate surface defects, tune the optical characteristics, and modify the doping polarity of 2D MoS2. Here, we demonstrate a fast photoresponse in multilayer (ML) MoS2 by addressing a heterojunction interface with vanadylphthalocyanine (VOPc) molecules. The MoS2/VOPc van der Waals interaction that has been established encourages the PPC effect in MoS2 by rapidly segregating photo-generated holes, which move away from the traps of MoS2 toward the VOPc molecules. The MoS2/VOPc phototransistor exhibits a fast photo response of less than 15 ms for decay and rise, which is enhanced by 3ordersof magnitude in comparison to that of a pristine MoS2-based phototransistor (seconds to tens of seconds). This work offers a means to realize high-performance transition metal dichalcogenide (TMD)-based photodetection with a fast response speed

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

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

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

Unconventional superconductivity in bulk materials under ambient pressure is extremely rare among the 3$d$ 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, Na$_{x}$CoO$_{2}\cdot$ yH$_{2}$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 Na$_{6}$Co$_{3}$Se$_{6}$O$_{3}$, in which the edge-shared CoSe$_{6}$ octahedra form [CoSe$_{2}$] layers with a perfect triangular lattice of Co ions. It is the first 3$d$ transition-metal oxychalcogenide superconductor with distinct structural and chemical characteristics. Despite its relatively low $T_{c}$, material exhibits extremely high superconducting upper critical fields, $\mu_{0}H_{c2}(0)$, which far exceeds the Pauli paramagnetic limit by a factor of 3 - 4. First-principles calculations show that Na$_{6}$Co$_{3}$Se$_{6}$O$_{3}$ 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-$T_{c}$ 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

Perovskite Origami for Programmable Microtube Lasing

Metal halide perovskites are promising materials for optoelectronic and photonic applications ranging from photovoltaics to laser devices. However, current perovskite devices are constrained to simple low-dimensional structures suffering from limited design freedom and holding up performance improvement and functionality upgrades. Here, a micro-origami technique is developed to program 3D perovskite microarchitectures toward a new type of microcavity laser. The design flexibility in 3D supports not only outstanding laser performance such as low threshold, tunable output, and high stability but also yields new functionalities like 3D confined mode lasing and directional emission in, for example, laser “array-in-array” systems. The results represent a significant step forward toward programmable microarchitectures that take perovskite optoelectronics and photonics into the 3D era. © 2021 The Authors. Advanced Functional Materials published by Wiley-VCH GmbH

Symmetry‐Induced Selective Excitation of Topological States in Su–Schrieffer–Heeger Waveguide Arrays

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. Herein, the topological phase transition between symmetric topological zero modes (TZM) and antisymmetric TZMs in Su–Schrieffer–Heeger mirror symmetric waveguides is reported. 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. Bidirectional topological transitions between symmetric and antisymmetric TZMs can be achieved with 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

Symmetry induced selective excitation of topological states in SSH waveguide arrays

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.

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