SDR-GAIN: A High Real-Time Occluded Pedestrian Pose Completion Method for Autonomous Driving

To mitigate the challenges arising from partial occlusion in human pose keypoint based pedestrian detection methods , we present a novel pedestrian pose keypoint completion method called the separation and dimensionality reduction-based generative adversarial imputation networks (SDR-GAIN) . Firstly, we utilize OpenPose to estimate pedestrian poses in images. Then, we isolate the head and torso keypoints of pedestrians with incomplete keypoints due to occlusion or other factors and perform dimensionality reduction to enhance features and further unify feature distribution. Finally, we introduce two generative models based on the generative adversarial networks (GAN) framework, which incorporate Huber loss, residual structure, and L1 regularization to generate missing parts of the incomplete head and torso pose keypoints of partially occluded pedestrians, resulting in pose completion. Our experiments on MS COCO and JAAD datasets demonstrate that SDR-GAIN outperforms basic GAIN framework, interpolation methods PCHIP and MAkima, machine learning methods k-NN and MissForest in terms of pose completion task. In addition, the runtime of SDR-GAIN is approximately 0.4ms, displaying high real-time performance and significant application value in the field of autonomous driving

Quantum state purification

Quantum state purification is a process in which decoherence is partially reversed by using multiple copies of the input states that have been subject to the same decoherence effect. This thesis focuses on purifying the decoherence caused by the depolarizing channel. In the first half of the thesis, the purification problem is formally introduced and one efficient purification procedure featuring the swap-test is presented and analyzed. The rest of the thesis formulates the optimal purification problem as an optimization problem and applies it to qubit and qutrit purification

Parallel Self-Testing of EPR Pairs Under Computational Assumptions

Self-testing is a fundamental feature of quantum mechanics that allows a classical verifier to force untrusted quantum devices to prepare certain states and perform certain measurements on them. The standard approach assumes at least two spatially separated devices. Recently, Metger and Vidick [Metger and Vidick, 2021] showed that a single EPR pair of a single quantum device can be self-tested under computational assumptions. In this work, we generalize their results to give the first parallel self-test of N EPR pairs and measurements on them in the single-device setting under the same computational assumptions. We show that our protocol can be passed with probability negligibly close to 1 by an honest quantum device using poly(N) resources. Moreover, we show that any quantum device that fails our protocol with probability at most ? must be poly(N,?)-close to being honest in the appropriate sense. In particular, our protocol can test any distribution over tensor products of computational or Hadamard basis measurements, making it suitable for applications such as device-independent quantum key distribution [Metger et al., 2021] under computational assumptions. Moreover, a simplified version of our protocol is the first that can efficiently certify an arbitrary number of qubits of a single cloud quantum computer using only classical communication

Quantum Probability Estimation for Randomness with Quantum Side Information

We develop a quantum version of the probability estimation framework [arXiv:1709.06159] for randomness generation with quantum side information. We show that most of the properties of probability estimation hold for quantum probability estimation (QPE). This includes asymptotic optimality at constant error and randomness expansion with logarithmic input entropy. QPE is implemented by constructing model-dependent quantum estimation factors (QEFs), which yield statistical confidence upper bounds on data-conditional normalized R\'enyi powers. This leads to conditional min-entropy estimates for randomness generation. The bounds are valid for relevant models of sequences of experimental trials without requiring independent and identical or stationary behavior. QEFs may be adapted to changing conditions during the sequence and trials can be stopped any time, such as when the results so far are satisfactory. QEFs can be constructed from entropy estimators to improve the bounds for conditional min-entropy of classical-quantum states from the entropy accumulation framework [Dupuis, Fawzi and Renner, arXiv:1607.01796]. QEFs are applicable to a larger class of models, including models permitting measurement devices with super-quantum but non-signaling behaviors and semi-device dependent models. The improved bounds are relevant for finite data or error bounds of the form $e^{-\kappa s}$, where $s$ is the number of random bits produced. We give a general construction of entropy estimators based on maximum probability estimators, which exist for many configurations. For the class of $(k,2,2)$ Bell-test configurations we provide schemas for directly optimizing QEFs to overcome the limitations of entropy-estimator-based constructions. We obtain and apply QEFs for examples involving the $(2,2,2)$ Bell-test configuration to demonstrate substantial improvements in finite-data efficiency.Comment: v2: Clarified soundness discussion and other edits, see the explanation after the references. v3: Clarified discussion of examples and comparisons. Parts of this paper have been published as Physical Review Research, 2, 013016, 2020, https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.2.01301

Streaming quantum state purification

Quantum state purification is the task of recovering a nearly pure copy of an unknown pure quantum state using multiple noisy copies of the state. This basic task has applications to quantum communication over noisy channels and quantum computation with imperfect devices, but has only been studied previously for the case of qubits. We derive an efficient purification procedure based on the swap test for qudits of any dimension, starting with any initial error parameter. Treating the initial error parameter and the dimension as constants, we show that our procedure has sample complexity asymptotically optimal in the final error parameter. Our protocol has a simple recursive structure that can be applied when the states are provided one at a time in a streaming fashion, requiring only a small quantum memory to implement

Baicalin-aluminum alleviates necrotic enteritis in broiler chickens by inhibiting virulence factors expression of Clostridium perfringens

Clostridium perfringens type A is the main cause of necrotic enteritis (NE) in chickens. Since the use of antibiotics in feed is withdrawn, it is imperative to find out suitable alternatives to control NE. Baicalin-aluminum complex is synthesized from baicalin, a flavonoid isolated from Scutellaria baicalensis Georgi. The present study investigated the effects of baicalin-aluminum on the virulence-associated traits and virulence genes expression of C. perfringens CVCC2030, it also evaluated the in vivo therapeutic effect on NE. The results showed that baicalin-aluminum inhibited bacterial hemolytic activity, diminished biofilm formation, attenuated cytotoxicity to Caco-2 cells, downregulated the expression of genes encoding for clostridial toxins and extracellular enzymes such as alpha toxin (CPA), perfringolysin O (PFO), collagenase (ColA), and sialidases (NanI, NanJ). Additionally, baicalin-aluminum was found to negatively regulate the expression of genes involved in quorum sensing (QS) communication, including genes of Agr QS system (agrB, agrD) and genes of VirS/R two-component regulatory system (virS, virR). In vivo experiments, baicalin-aluminum lightened the intestinal lesions and histological damage, it inhibited pro-inflammatory cytokines (TNF-α, IL-1β, IL-6) expression in the jejunal and ileal tissues. Besides, baicalin-aluminum alleviated the upregulation of C. perfringens and Escherichia coli and raised the relative abundance of Lactobacillus in the ileal digesta. This study suggests that baicalin-aluminum may be a potential candidate against C. perfringens infection by inhibiting the virulence-associated traits and virulence genes expression