| 1. |
- Kristan, Matej, et al.
(author)
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The first visual object tracking segmentation VOTS2023 challenge results
- 2023
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In: 2023 IEEE/CVF International conference on computer vision workshops (ICCVW). - : Institute of Electrical and Electronics Engineers Inc.. - 9798350307443 - 9798350307450 ; , s. 1788-1810
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Conference paper (peer-reviewed)abstract
- The Visual Object Tracking Segmentation VOTS2023 challenge is the eleventh annual tracker benchmarking activity of the VOT initiative. This challenge is the first to merge short-term and long-term as well as single-target and multiple-target tracking with segmentation masks as the only target location specification. A new dataset was created; the ground truth has been withheld to prevent overfitting. New performance measures and evaluation protocols have been created along with a new toolkit and an evaluation server. Results of the presented 47 trackers indicate that modern tracking frameworks are well-suited to deal with convergence of short-term and long-term tracking and that multiple and single target tracking can be considered a single problem. A leaderboard, with participating trackers details, the source code, the datasets, and the evaluation kit are publicly available at the challenge website1
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| 2. |
- Ying, Qianwen, et al.
(author)
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Highly stable measurement for nanoparticle extinction cross section by analyzing aperture-edge blurriness
- 2021
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In: Optics Express. - : Optical Society of America. - 1094-4087. ; 29:11, s. 16323-16333
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Journal article (peer-reviewed)abstract
- In order to stabilize the extinction cross section measurement of a single nanoparticle, we propose to analyze the blurriness parameter of aperture edge images in real time, which provides a feedback to lock the sample position. Unlike the conventional spatial modulation spectroscopy (SMS) technique, a probe beam experiences both the spatial modulation by a piezo stage and the temporal modulation by a chopper. We experimentally demonstrate that the measurement uncertainty is one order magnitude less than that in the previous report. The proposed method can be readily implemented in conventional SMS systems and can help to achieve high stability for sensing based on light extinction by a single nanoparticle, which alleviate the impact from laboratory environment and increase the experimental sensitivity.
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| 3. |
- Ying, Qianwen, et al.
(author)
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Highly stable measurement for nanoparticle extinction cross section by analyzing aperture-edge blurriness
- 2021
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In: Optics Express. - : Optical Society of America. - 1094-4087. ; 29:11, s. 16323-16323
-
Journal article (peer-reviewed)abstract
- In order to stabilize the extinction cross section measurement of a single nanoparticle, we propose to analyze the blurriness parameter of aperture edge images in real time, which provides a feedback to lock the sample position. Unlike the conventional spatial modulation spectroscopy (SMS) technique, a probe beam experiences both the spatial modulation by a piezo stage and the temporal modulation by a chopper. We experimentally demonstrate that the measurement uncertainty is one order magnitude less than that in the previous report. The proposed method can be readily implemented in conventional SMS systems and can help to achieve high stability for sensing based on light extinction by a single nanoparticle, which alleviate the impact from laboratory environment and increase the experimental sensitivity.
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| 4. |
- Yu, Wenjin, et al.
(author)
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Deep Learning-Based Classification of Cancer Cell in Leptomeningeal Metastasis on Cytomorphologic Features of Cerebrospinal Fluid
- 2022
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In: Frontiers in Oncology. - : Frontiers Media SA. - 2234-943X. ; 12, s. 1-11
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Journal article (peer-reviewed)abstract
- Background: It is a critical challenge to diagnose leptomeningeal metastasis (LM), given its technical difficulty and the lack of typical symptoms. The existing gold standard of diagnosing LM is to use positive cerebrospinal fluid (CSF) cytology, which consumes significantly more time to classify cells under a microscope.Objective: This study aims to establish a deep learning model to classify cancer cells in CSF, thus facilitating doctors to achieve an accurate and fast diagnosis of LM in an early stage.Method: The cerebrospinal fluid laboratory of Xijing Hospital provides 53,255 cells from 90 LM patients in the research. We used two deep convolutional neural networks (CNN) models to classify cells in the CSF. A five-way cell classification model (CNN1) consists of lymphocytes, monocytes, neutrophils, erythrocytes, and cancer cells. A four-way cancer cell classification model (CNN2) consists of lung cancer cells, gastric cancer cells, breast cancer cells, and pancreatic cancer cells. Here, the CNN models were constructed by Resnet-inception-V2. We evaluated the performance of the proposed models on two external datasets and compared them with the results from 42 doctors of various levels of experience in the human-machine tests. Furthermore, we develop a computer-aided diagnosis (CAD) software to generate cytology diagnosis reports in the research rapidly.Results: With respect to the validation set, the mean average precision (mAP) of CNN1 is over 95% and that of CNN2 is close to 80%. Hence, the proposed deep learning model effectively classifies cells in CSF to facilitate the screening of cancer cells. In the human-machine tests, the accuracy of CNN1 is similar to the results from experts, with higher accuracy than doctors in other levels. Moreover, the overall accuracy of CNN2 is 10% higher than that of experts, with a time consumption of only one-third of that consumed by an expert. Using the CAD software saves 90% working time of cytologists.Conclusion: A deep learning method has been developed to assist the LM diagnosis with high accuracy and low time consumption effectively. Thanks to labeled data and step-by-step training, our proposed method can successfully classify cancer cells in the CSF to assist LM diagnosis early. In addition, this unique research can predict cancer’s primary source of LM, which relies on cytomorphologic features without immunohistochemistry. Our results show that deep learning can be widely used in medical images to classify cerebrospinal fluid cells. For complex cancer classification tasks, the accuracy of the proposed method is significantly higher than that of specialist doctors, and its performance is better than that of junior doctors and interns. The application of CNNs and CAD software may ultimately aid in expediting the diagnosis and overcoming the shortage of experienced cytologists, thereby facilitating earlier treatment and improving the prognosis of LM.
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| 5. |
- Zhang, Jiahao, et al.
(author)
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Analysis and Compensation of Nonlinear Dynamics in Optical Fiber Transmission with the Optoelectronic Reservoir Computing
- 2023
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In: Photonics Global Conference, PGC 2023. - : Institute of Electrical and Electronics Engineers (IEEE). ; , s. 12-16
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Conference paper (peer-reviewed)abstract
- Optical fiber communication systems play an important role in broadband signal transmissions, where the nonlinear dynamics in the long-haul optical fiber transmissions greatly degrade the transmission performance and limit the fiber capacity and reach. This paper analyzes and compensates for the nonlinear dynamics in the long-haul optical fiber transmission with the delay-based optoelectronic reservoir computing (RC) scheme, which provides benefits like time-adaptive tracking, low-complexity and hardware implementation potentials. The generalization of the analysis and compensation schemes from the traditional amplitude-modulated PAM signal to the amplitude-phase-modulated QAM signal is achieved by signal preprocessing. In the numerical study, the proposed RC-based fiber dynamics compensation scheme, with fiber reach from 1400km to 3000km, shows considerable performance with the digital backpropagation scheme, which is always used as the benchmark for nonlinear compensation of long-haul fiber transmissions. The realization complexity is much reduced with the RC-based schemes, which has provided a new dawn for optics-based nonlinear analysis and compensations.
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| 6. |
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| 7. |
- Fu, Xianbiao, et al.
(author)
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High-Entropy Alloy Nanosheets for Fine-Tuning Hydrogen Evolution
- 2022
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In: ACS Catalysis. - : American Chemical Society (ACS). - 2155-5435. ; 12:19, s. 11955-11959
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Journal article (peer-reviewed)abstract
- The electrolysis of water is promising for hydrogen production. The development of high-performance and low-cost hydrogen evolution reaction (HER) electrocatalysts is particularly important for the wide application of water electrolyzers. Tuning the hydrogen binding energy (HBE) of materials is an effective way to optimize the HER electrocatalysts, particularly for applications in an acidic environment. Here, we report the discovery of a Pt-free combination, PdMoGaInNi, which has the HBE optimum, via computer-facilitated screening. As the exploratory example of the two-dimensional high-entropy alloy (HEA) for HER, the PdMoGaInNi HEA nanosheets were synthesized to realize the predicted Pt-free combination with optimal HBE. The PdMoGaInNi HEA nanosheets exhibit a high HER activity with low overpotentials of 13 mV at 10 mA cm-2, outperforming commercial Pd/C and Pt/C catalysts. Given the high entropy, lattice distortion, and sluggish diffusion effects of HEA, the PdMoGaInNi shows great long-term durability for at least 200 h in a proton exchange membrane water electrolyzer.
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| 8. |
- Hu, Chang-Kang, et al.
(author)
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Native Conditional iSWAP Operation with Superconducting Artificial Atoms
- 2023
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In: Physical Review Applied. - 2331-7019. ; 20:3
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Journal article (peer-reviewed)abstract
- Controlling the flow of quantum information is a fundamental task for quantum computers, which is unfeasible to realize on classical devices. Coherent devices, which can process quantum states are thus required to route the quantum states that encode information. In this paper we demonstrate experimentally the smallest quantum transistor with a superconducting quantum processor, which is composed of a collector qubit, an emitter qubit, and a coupler (transistor gate). The interaction strength between the collector and emitter qubits is controlled by the frequency and state of the coupler, effectively implementing a quantum switch. Through the coupler-state-dependent Heisenberg (inherent) interaction between the qubits, a single-step (native) conditional iSWAP operation can be applied. To this end, we find that it is useful to take into consideration the higher-energy level for achieving a native and high-fidelity transistor operation. By reconstructing the quantum process tomography, we obtain an operation fidelity of 92.36% when the transistor gate is open (iSWAP implementation) and 95.23% in the case of closed gate (identity gate implementation). The architecture has strong potential in quantum information processing applications with superconducting qubits.
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| 9. |
- Hu, Chang-Kang, et al.
(author)
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Optimal charging of a superconducting quantum battery
- 2022
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In: Quantum Science and Technology. - : IOP Publishing. - 2058-9565. ; 7:4
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Journal article (peer-reviewed)abstract
- Quantum batteries are miniature energy storage devices and play a very important role in quantum thermodynamics. In recent years, quantum batteries have been extensively studied, but limited in theoretical level. Here we report the experimental realization of a quantum battery based on superconducting qutrit. Our model explores dark and bright states to achieve stable and powerful charging processes, respectively. Our scheme makes use of the quantum adiabatic brachistochrone, which allows us to speed up the battery ergotropy injection. Due to the inherent interaction of the system with its surrounding, the battery exhibits a self-discharge, which is shown to be described by a supercapacitor-like self-discharging mechanism. Our results paves the way for proposals of new superconducting circuits able to store extractable work for further usage.
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| 10. |
- Lamichhaney, Sangeet, 1984-, et al.
(author)
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Structural genomic changes underlie alternative reproductive strategies in the ruff (Philomachus pugnax)
- 2016
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In: Nature Genetics. - : Springer Nature. - 1061-4036 .- 1546-1718. ; 48:1, s. 84-88
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Journal article (peer-reviewed)abstract
- The ruff is a Palearctic wader with a spectacular lekking behavior where highly ornamented males compete for females1,2,3,4. This bird has one of the most remarkable mating systems in the animal kingdom, comprising three different male morphs (independents, satellites and faeders) that differ in behavior, plumage color and body size. Remarkably, the satellite and faeder morphs are controlled by dominant alleles5,6. Here we have used whole-genome sequencing and resolved the enigma of how such complex phenotypic differences can have a simple genetic basis. The Satellite and Faeder alleles are both associated with a 4.5-Mb inversion that occurred about 3.8 million years ago. We propose an evolutionary scenario where the Satellite chromosome arose by a rare recombination event about 500,000 years ago. The ruff mating system is the result of an evolutionary process in which multiple genetic changes contributing to phenotypic differences between morphs have accumulated within the inverted region.
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